bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spectroscopic and an active site analysis of 2,2-diphenyl-1,3- propanediol as antitumor and inflammatory potential
Authors: Bayrakdar Alpaslan , Magudeeswaran Sivanandam , Manivannan Prasath , Bangaru Sathya 
Published: October 2023

Abstract
The compound 2,2-Diphenyl-1,3-Propanediol (22D13P) is very useful in the development of biological-based plastic materials. The FT-IR, 13C and 1H-NMR spectra of 22D13P molecule was recorded theoretically as well as compared with experimental results. The fundamental vibrational modes were assigned based on potential energy distribution% (PED%) analysis. The stabilization energy and charge distributions of 22D13P molecule were obtained with the help of natural bond orbital (NBO) analysis. In addition, the electronic properties of 22D13P molecule were analyzed via highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). The drug-likeness properties of 22D13P molecule were studied. Furthermore, molecular docking was used to examine the interactions between the 22D13P molecule and 6I65 receptor from estrogen-related receptor (ER) family. The molecular dynamics simulation analysis showed that 22D13P molecule can be a potential inhibitor for breast cancer treatment.
Inferring Mental Representational Structure of the Self in Time, Space, and Social Domains via a Modified Redundancy Gain Paradigm
Authors: Kim Hyunji , Florack Arnd 
Published: October 2023

Abstract

The ability to project oneself into an alternative situation is an essential human capacity. While research showing that such abilities base human decision making is abundant, the cognitive organization of the self across social, temporal, and spatial domains constituting the basic materials for self-projection is not clear. The current study introduces a new paradigm to gauge the representational overlaps among social (me myself), temporal (me now) and spatial (me here) selves by utilizing a shape-label matching task in a modified redundancy gain paradigm. Based on the level of redundancy gain effects, we infer a representational overlap among social, temporal, and spatial selves in a systematic way. Our results showed that the spatial self resides at the core of the self-representation which conceptually extends to the temporal and ultimately, to the social self, echoing the human developmental stages of self-representation. This novel finding advances the understanding and theorizing of the self-concept as an orderly structured mental construct.
The nadir platelet count in the first 48 hours after ICU admission is a potential predictor of acute kidney injury in hemorrhagic shock patients
Authors: Liang yufan , Liang Silin , Wu Quanzhong , Huang Jianyang , Hu Linhui , Li Ziyun , Pan Chixing , He Yuemei , Zhou Xinjuan , Chen Chunbo 
Published: October 2023

Abstract
Background
Whether the nadir platelet count in the first 48 hours after intensive care unit (ICU) admission could be a potential predictor of acute kidney injury (AKI) in hemorrhagic shock patients has not been determined. The purpose of this study was to investigate the relationship between the nadir platelet count in the first 48 hours after ICU admission and the occurrence of AKI caused by hemorrhagic shock.
Methods
This dual-center, observational retrospective study included hemorrhagic shock patients hospitalized in Maoming People's Hospital and Guangdong Medical University Affiliated Hospital from January 2019 to May 2022. The nadir platelet count was defined as the lowest value in the first 48 hours after ICU admission. Multivariate logistic regression was used to assess the independent risk factors for AKI. The area under the receiver operating characteristic curve (AUC) was analyzed to compare the diagnostic accuracy of the studied markers. The primary outcome was the occurrence of AKI within the first 7 days of ICU stay diagnosed according to the Kidney Disease Improving Global Outcomes (KDIGO) criteria. In addition, serum cystatin C (sCysC) date were collected to explore the relationship with the nadir platelet count.
Results
A total of 124 patients were included for analysis, including 72 patients with AKI. Compared with patients without AKI, patients with AKI caused by hemorrhagic shock had a significantly the lower nadir platelet count, with the odds ratio (OR) of 0.980 (95% confidence interval [95% CI]: 0.973–0.987, p < 0.001). Multivariate logistic analysis showed that the nadir platelet count was an independent risk factor for AKI (OR = 0.988, 95% CI: 0.978–0.999, p = 0.035). The sensitivity and specificity for the nadir platelet count predicting AKI were 83% and 79%, respectively (AUC = 0.862, 95% CI: 0.795–0.929). Moreover, combining the nadir platelet count with sCysC increased the receiver operating characteristic (ROC) curve to 0.922 (95% CI: 0.870–0.973), and this performance was statistically significantly better than either the individual the nadir platelet count (p = 0.018) or sCysC (p < 0.001).
Conclusions
The nadir platelet count in the first 48 hours after ICU admission was independently associated with the incidence of AKI in hemorrhagic shock patients and could be a potential predictor of AKI in this patient population.
Automation of systematic reviews of biomedical literature: a systematic review of studies indexed in PubMed
Authors: Tóth Barbara , Berek László , Gulácsi László , Péntek Márta , Zrubka Zsombor 
Published: October 2023

Abstract

Background
The demand for high quality systematic literature reviews (SLRs) is growing for evidence-based medical decision making. SLRs are costly and require the scarce resource of highly skilled reviewers. Automation technology has been proposed to save workload and expedite the SLR workflow.
Objectives
We aimed to provide a comprehensive overview of SLR automation studies indexed in PubMed, focusing on the applicability of these technologies in real world practice.
Methods
In November 2022, we ran a combined search syntax of four published SLRs on SLR automation. Full-text English peer-reviewed articles were included if they reported Studies on SLR Automation Methods (SSAM), or Automated SLRs (ASLR). Bibliographic analyses and knowledge-discovery studies were excluded. Record screening was performed by single reviewers, the selection of full text papers was performed in duplicate. We summarized the publication details, automated review stages, automation goals, applied tools, data sources, methods, results and Google Scholar citations of SLR automation studies.
Results
From 5321 records screened by title and abstract, we included 123 full text articles, out of which 108 were SSAMs and 15 ASLRs. Automation was applied for search, record screening, full-text selection, data extraction, risk of bias assessment, evidence synthesis, assessment of evidence quality and reporting in 19 (15.4%), 89 (72.4%), 6 (4.9%), 13 (10.6%), 9 (7.3%), 2 (1.6%), 2 (1.6%), and 2 (1.6%) studies, respectively. Multiple SLR stages were automated by 11 (8.9%) studies. The performance of automated record screening varied largely across SLR topics. In published ASLRs we found examples of automated search, record screening, full-text selection and data extraction. In some ASLRs automation complemented fully manual reviews to increase sensitivity rather than to save workload. Reporting of automation details were often incomplete in ASLRs.
Conclusions
Automation techniques are being developed for all SLRs stages, but with limited real-world adoption. Most SLR automation tools target single SLR stages, with modest time savings for the entire SLR process and varying sensitivity and specificity across studies. Therefore, the real-world benefits of SLR automation remain uncertain. Standardizing the terminology, reporting, and metrics of study reports could enhance the adoption of SLR automation techniques in real-world practice.
Impact of climate change on droughts: a case study of the Zard River Basin in Iran
Authors: Mahdavi Pedram , Ghorbanizadeh Kharazi Hossein 
Published: October 2023

Abstract

In this research a SWAT model was assembled and used to evaluate the effects of climate change on runoff and drought in a semi-arid basin in Iran. The SWAT model showed good performance in the simulation of runoff. Eleven General Circulation Models (GCMs) under Representative Concentration Pathway 4.5 and Representative concentration Pathway 8.5 (RCP45 and RCP85) scenarios, and the period 2022-2041 was selected to investigate future projections. It was predicted that under all of the scenarios, runoff will decrease significantly. Annual rates showed that runoff will fall to 7.73 m3/s (11.6% decreased) and 6.78 m3/s (22.5% decreased) under RCP45 and RCP85 from 8.75 m3/s during next 20 years in this basin, respectively. In this research, the meteorological and hydrological droughts were estimated using SPI and SDI indices, respectively. By coupling of climate change scenarios and SWAT models it was found that the severity of droughts in the future will be far greater than has ever happened before. Key words: climate change, hydrological drought, SDI, semi-arid basin, SPI, SWAT.
Tertiary treatment using ultrafiltration in an existing sewage treatment plant for industrial reuse: a modelling approach using artificial neural network with uncertainty estimation
Authors: Ramkumar D. , Jothiprakash V. 
Published: October 2023

Abstract

Navi Mumbai Municipal Corporation of Maharashtra state, India, unified a tertiary treatment plant (TTP) of 20 × 103 m3/day capacity with ultrafiltration technology in an existing Koparkhairane sewage treatment plant (STP) for producing effluent quality usable for industrial purposes. As prior art, an artificial neural network-genetic algorithm (ANN-GA) along with uncertainty estimation using prediction interval is employed to model secondary treated effluent (STE) flow rate (QT) and other quality parameters such as biochemical oxygen demand, chemical oxygen demand, and total suspended solids (TSS) to conclude the reliability of the range in which the input available to TTP. ANN-GA model provides a coefficient of determination above 0.90 for all STE parameters modelled other than TSS. Inferring that a good quantity and quality of 20 × 103 m3/day STP treated water is currently available, where a decreasing trend of QT is also noticed and highlighted. Further, the Wilcoxon signed-rank test on the quality parameter of effluent TTP for industrial reuse standard infers TSS shows infringement during the initial period but started adhering to standards over time. The research delineates at the outset of exploring water reuse policy in India, emphasizing Maharashtra state, modelling STE using ANN-GA and performance evaluation of TTP.
Analysis of The Itsg-Grace Daily Models in The Determination of Polar Motion Excitation Function
Authors: Partyka Aleksander , Nastula Jolanta , Śliwińska Justyna , Kur Tomasz , Wińska Malgorzata 
Published: October 2023

ABSTRACT
The main aim of this study is to evaluate the usefulness of Institute of Geodesy at Graz University of Technology (ITSG) daily gravity field models in the determination of hydrological angular momentum (HAM) at nonseasonal time scales. We compared the equatorial components (χ1 and χ2) of HAM calculated with the ITSG daily gravity field models (ITSG-Gravity Recovery and Climate Experiment [ITSG-GRACE] 2016 and ITSG-GRACE 2018) with HAM and sea-level angular momentum (SLAM) from hydrological land surface discharge model (LSDM) and the hydrological signal in the polar motion excitation (known as geodetic residuals [GAO]). Data from ITSG have a daily temporal resolution and allow us to determine oscillations with higher frequencies than the more commonly used monthly data. We limited our study to the period between 2004 and 2011 because of the gaps in GRACE observations before and after this period. We evaluated HAM obtained from ITSG GRACE models in spectral and time domains and determined the amplitude spectra of the analyzed series in the spectral range from 2 to 120 days. Our analyses confirm the existence of a sub-monthly signal in the HAM series determined from ITSG daily data. We observed a similar signal in LSDM-based HAM, but with notably weaker amplitudes. We also observed common peaks around 14 days in the amplitude spectra for the GAO- and ITSG-based series, which may be related to the Earth’s tides. ITSG daily gravity field models can be useful to determine the equatorial components of HAM at nonseasonal time scales.
Neural network modelling of non-prosperity of Slovak companies
Authors: Durica Marek , Mazanec Jaroslav , Frnda Jaroslav 
Published: October 2023

Abstract
Early identification of potential financial problems is among important companies’ risk management tasks. This paper aims to propose individual and ensemble models based on various types of neural networks. The created models are evaluated based on several quantitative metrics, and the best-proposed models predict the impending financial problems of Slovak companies a year in advance. The precise analysis and cleaning of real data from the financial statements of real Slovak companies result in a data set consisting of the values of nine potential predictors of almost 19 thousand companies. Individual and ensemble models based on MLP and RBF-type neural networks and the Kohonen map are created on the training sample. On the other hand, several metrics quantify the predictive ability of the created models on the test sample. Ensemble models achieved better predictive ability compared to individual models. MLP networks achieved the highest overall accuracy of almost 89 %. However, the non-prosperity of Slovak companies was best identified by RBF networks created by the boosting and bagging technique. The sensitivity of these models is about 87 %. The study found that models based on neural networks can be successfully designed and used to predict financial distress in the Slovak economy.
Multi-skilled workforce scheduling with training and welfare considerations
Authors: Peña Diana A. , Osorio Andrés F. , Orejuela Juan P. , Idarraga Juan C. 
Published: October 2023

Abstract
Flexibility in workforce scheduling in services is necessary to reduce the impact of demand uncertainty, absenteeism, and desertion while maintaining high service levels. This paper studies the workforce scheduling problem, including multiple skill accumulation, training, and welfare, as well as flexibility for employees and the company. All these elements are modelled and included in a mixed-integer linear programming (MILP) model that maximises their accumulated skill level. A real case study based on the scheduling of lab assistants to laboratory practices at a university in Colombia is used to generate numerical experiments. Different experiments were conducted, and the results show that the level of skill achieved is highly sensitive to the number of assistants and the number of allocations. The experiments also showed that, while keeping the same number of lab assistants, it is possible to include flexibility and welfare constraints. Finally, the proposed model can generate schedules that achieve high levels of skills and meet the different constraints of the model, including balance, accumulation, demand and welfare.
Industry 4.0 technologies and managers’ decision-making across value chain. Evidence from the manufacturing industry
Authors: Młody Michał , Ratajczak-Mrozek Milena , Sajdak Maja 
Published: October 2023

Abstract
The paper aims to identify how Industry 4.0 technologies affect the quality and speed of the managers’ decision-making process across the different stages of the value chain, based on the example of the manufacturing sector. The paper adopts qualitative research, based on nine in-depth interviews with key informants, to capture senior executives’ experiences with implementing Industry 4.0 technologies in their organisations. The research is focused on three manufacturing industries: the automotive, food and furniture industries. The research shows that depending on the stage of the value chain, different Industry 4.0 technologies are more suitable for the support of managers’ decisions. Various Industry 4.0 technologies support decision-making at different stages of the manufacturing value chain. In the Design stage, 3D printing and scanning technologies play a crucial role. In the case of Inbound Logistics, robotisation, automation, Big Data analysis, and Business Intelligence are most useful. During the Manufacturing stage, robotisation, automation, 3D printing, scanning, Business Intelligence, cloud computing, and machine-to-machine (M2M) integration enable quick decision-making and speed up production. Sensors and the Internet of Things (IoT) optimise distribution in the Outbound Logistics stage. And finally, Business Intelligence supports decisions within the Sales and Marketing stage. It is also the most versatile technology among all particular stages. The paper provides empirical evidence on the Industry 4.0 technology support in decision-making at different stages of the manufacturing value chain, which leads to more effective value chain management, ensuring faster and more accurate decisions at each value-chain stage. When using properly selected Industry 4.0 technologies, managers can optimise their production processes, reduce costs, avoid errors and improve customer satisfaction. Simultaneously, Industry 4.0 technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks. This knowledge allows organisations to make better decisions and take proactive actions to prevent problems.
Methodology of an interpretive structural map construction for social commerce success
Authors: Pijo Hazel , Aguilar Aethyl , Catarongan Mitzie Ann , Orioque Janet , Atibing Nadine May , Wenceslao Charldy , Evangelista Samantha Shane , Aro Joerabell Lourdes , Maturan Fatima , Yamagishi Kafferine , Ocampo Lanndon 
Published: October 2023

Abstract
The factors influencing consumer purchase decisions in electronic commerce platforms and the interrelationships of each element are prevalent in the domain literature. However, a comprehensive analysis of the complex interrelationships among the success factors remains unexplored, especially in a social commerce context. To address the gap, this work evaluates the relationship structure and determines the critical factors using interpretive structural modelling (ISM). On the other hand, the Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) is introduced to analyse the interaction of the factors and recognise the most relevant among them. In demonstrating the ISM-MICMAC analysis, this work performed a case study evaluating 13 factors of social commerce success for food products derived from a previous study. The findings of this work suggest that timeliness, data privacy policy, and Internet connectivity drive most other factors. Thus, focusing the resources on augmenting these factors consequently improves other factors. These findings suggest that sellers must streamline their overall service chain to maintain timeliness in their transactions, safeguard consumers’ data privacy, and uphold consumer communication efficiency to maximise Internet connectivity. These insights provide useful information to help decision-makers in the food industry allocate resources and encourage more consumers for social commerce. Several managerial insights were discussed.
La construcción del discurso de seguridad en América latina
Authors: Ospina Diana Sofía , Ávila Karen Viviana , Vargas-López María Alejandra 
Published: October 2023

En este documento se ha desplegado un ejercicio de seguimiento y caracterización respecto a las principales preocupaciones en materia de seguridad y defensa presentes en el continente para el segundo semestre del año 2021 y primer trimestre del 2022. En este sentido la observación se concentró en tres intereses: la presencia de Crimen Organizado, el fenómeno migratorio y la participación de Hezbolá en los territorios americanos. A partir de la catalogación de fuentes primarias y secundarias de información sobre seguridad y defensa nacionales, presentes en distintos escenarios de divulgación de los países del hemisferio, fue seleccionada una base de datos que facilita el análisis cualitativo y la expresión cuantitativa de los fenómenos mencionados.
Escarabajos degradadores de la madera (Coleoptera: Passalidae) de la isla Gorgona, Cauca, Colombia.
Authors: Pardo Locarno Luis Carlos , Editorial Asistente 
Published: October 2023

Por tratarse de la única formación insular, selvática, del Chocó biogeográfico, en el pacífico colombiano, los atributos biofísicos y naturaleza del Parque Nacional Natural Gorgona (PNNG), Cauca, han despertado mucho interés en los últimos 20 años conducentes a múltiples estudios de su fauna, en especial de insectos. Sin embargo, llama la atención la ausencia de estudios sobre insectos degradadores y ninguna publicación sobre los escarabajos de la madera (Coleoptera: Passalidae) en esta localidad. Por lo tanto, este artículo registra las especies de estos escarabajos en el Parque Nacional Natural Isla Gorgona (PNNG). El muestreo se llevó a cabo del 28 al 31 de mayo de 1993 en los alrededores del campamento, en los senderos turísticos de la isla (Yundigua, La Chonta y Playa Palmeras). Se examinaron aproximadamente 17 troncos descompuestos, con diámetros desde 8-25 cm. Los ejemplares fueron preservados en alcohol al 95%, posteriormente montados y depositados en la colección familia Pardo-Locarno (CFPL-COL, Palmira, Valle); parte del material fue comparado en el INECOL (Xalapa de Enríquez Veracruz, México) y en el Museo de Historia Natural (Paris, Francia); se registraron cuatro especies: Passalus emberaorum Jimenez-Ferbans et al. (2018) (n=18; 60%), Veturius sinuatocollis Kuwert (1890) (registro bibliográfico), Veturius aspina Kuwert 1898 (n=10; 33,33%) y Petrejoides caldasi Reyes-Castillo y Pardo-Locarno (1995) (n=2; 6,66%). P. emberaorum y Pe. caldasi se consideran nuevos registros para el PNNG. El artículo proporciona una clave taxonómica e ilustraciones de la especie. Además, enfatiza la necesidad de una mayor investigación sobre la estricta naturaleza saproxilófaga del grupo y su importancia en términos del valor de conservación de este ecosistema único de la selva insular.
AD-RED: A new variant of random early detection AQM algorithm
Authors: Hassan Samuel O. 
Published: October 2023

Intensive continuing research has been noticed among scholars in the literature with a particular appreciable interest in developing new enhanced variants for the long-standing Random Early Detection (RED) algorithm. Contemporary trends shows that researchers continue to follow a research line thereby exchanging the linear curve needed in RED with nonlinear curves. Several reports have shown that RED’s sole linear function is insufficiently powered for managing rising degrees of traffic congestion in the network. In this paper, Amended Dropping – Random Early Detection (AD-RED), a revised version of RED is presented. AD-RED algorithm consists in combining two nonlinear packet dropping functions: quadratic plus exponential. What’s more, results from ns-3 simulator shows that AD-RED reasonably stabilized and minified the (average) queue size; and obtained a whittled down end-to-end delay when compared with RED itself and another variant of RED. Hence, AD-RED is offered as a fully sufficient replacement for RED’s algorithm implementation in routers.