bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Interoperable Web-based Application for 3D City Modelling and Analysis
Authors: Usta Ziya , Cömert Çetin , Akın Alper Tunga 
Published: September 2023

Abstract
This study presents a web-based application developed for the efficient management of large 3D city models (3DCMs). The application offers functionalities such as 3D tiling, web-based visualization, 3DCM generation from 2D data, and 3D spatial analysis. It complies with international standards and utilizes open-source software components. The application includes a 3D tiling tool that implements the OGC 3D Tiles Standard, allowing users to partition their 3DCMs into optimized tiles for storage, transmission, and rendering. A web-based procedural modeling tool enables users to generate 3DCMs from 2D building footprint data without the need for complex modeling languages. A 3D spatial analysis component empowers users to perform comprehensive spatial analyses within the web-based environment. Leveraging modern web technologies facilitates precise and efficient spatial computations. To provide standardized visualization, the application features a viewer and client application built using HTML5 and WebGL technologies. This viewer adheres closely to the 3D Tiles Standard , enabling immersive navigation and interaction with 3DCMs. By combining these components, this web-based application intuitiveize the management of large 3DCMs, offering enhanced visualization, analysis, and model generation capabilities. It represents a milestone in web-based 3D city model management, prioritizing international standards and open-source principles.
The Effect of Quiet Eye Training on Golf Putting Performance in Pressure Situation
Authors: He Qiao , Liu Yunzhou 
Published: September 2023

Abstract
Purpose
This study discussed the effect and mechanism of quiet eye training on the accuracy of golfers´ putts in pressure situations. This study provides methods and basis for targeted attention training and regulation.
Method
22 young golfers in China golf team aged from 13–18 were randomly assigned to the experimental group (quiet eye training group) and the control group (technical guidance group) according to gender. Both groups of participants underwent two consecutive weeks of push training (3 groups per day, 20 times golf putter training each group) separately in accordance with the guidance of a professional psychological research group and an expert coach. Eye tracking technology, biofeedback technology, and subjective evaluation methods were used to test and analyze the push process of the two groups of participants before and after training under pressure situations (Eye movement behaviors and the heart rate were recorded by ASL Mobile Eye-XG and NeXus-2 biofeedback, pressure and state anxiety were evaluated by self-rating pressure scale and S-AI. Golf putting performance was recorded by a research graduate assistant).
Results
A higher hit ratio as well as lower pressure and SAI level was founded in quiet eye training group in the pressure situation, the stationary eye movement time and total fixation time was longer than technical group. The quiet eye training group has a better putting performance.
Conclusions
Quiet eye training can improve the golf putting performance in pressure situations.
Estimation of Water Quality Index using modern-day machine learning algorithms
Authors: Gupta Piyush , Samui Pijush , Quaff A. R. 
Published: September 2023

Abstract
Many human-made activities currently pollute groundwater supplies, with mining operations playing a substantial role in this degradation. Water quality index (WQI) was calculated and forecasted for groundwater in gold mining sites of Kolar Gold Fields (KGF), Karnataka, using several water quality criteria. Aside from the difficulties in obtaining water quality monitoring for a specific location, artificial intelligence (AI) approaches have shown beneficial in consistently calculating target WQI based on optimum combination proportions. In the absence of available data, the most critical input parameters were discovered using three sophisticated deep learning models: convolution neural network (CNN), deep neural network (DNN), and recurrent neural network (RNN). The models were created utilizing the findings of seasonal monitoring experiments using various water quality metrics 80% of the experimental data was used to train the models, with the remainder used to validate the models. The best hyper-parameters for each model were trial-and-error selected; for CNN, DNN, and RNN, variable numbers of hidden layers, neurons, and training algorithms were used. Using parametric analyses on a simulated dataset, the trained models were validated. Mean absolute error (MAE), root mean square error (RMSE), determination coefficient (R2), Nash Sutcliffe efficiency (NSE), variance account factor (VAF), performance index (PI), Willmott's index of agreement (WI), mean bias error (MBE), and Root Relative Squared Error (RRSE) were used to assess the predictive abilities of proposed models. Furthermore, each model's strengths and weaknesses are examined. The researchers discovered that using CNN to do systematic calculations between water parameters and time series might be a useful tool for rapid water quality monitoring.
On-site calibration procedure and uncertainty contributions on air temperature sensors
Authors: Aranda Natali Giselle , Merlone Andrea 
Published: September 2023

Abstract
Due to the increasing demand of climate change studies, traceability of measurements according to the International System of Units (SI) becomes fundamental to establish data quality and comparability in time. With the aim of guaranteeing the traceability, in October 2022, an on-site calibration of three thermometers operated by the Osservatorio meteorologico di Moncalieri was assessed. The calibration by comparison against traceable travelling standards was performed in a transportable thermal chamber manufactured by the Istituto Nazionale di Ricerca Metrologica (INRIM). Results showed that the main uncertainty contributions to the expanded uncertainty were the interpolation method, the chamber inhomogeneity and the repeatability of the sensors under calibration. This current calibration was compared with previous calibration in 2012 (on-site calibration) and in 2016 (laboratory calibration). The comparison analysis evidenced the drift effect on the thermometers and the importance of having an active calibration program to reduce this effect. Regarding the expanded uncertainty, both on-site calibrations presented the same order of magnitude and smaller than the correction values. This paper points out the advantage of performing an on-site calibration: since the calibration involves the same dataloggers and cables in thesame environmental conditions, the calculated calibration curve represents more convincingly the real measurement conditions.
Coordinated Self-Assembly and Feedback Control of Distributed Magnetic Cuboid Robots
Authors: Rogowski Louis William , Kararsiz Gokhan , Bhattacharjee Anuruddha , Lu Yitong , Wang Zhengguang , Zhang Xiao , Becker Aaron T. , Kim Min Jun 
Published: September 2023

Abstract
Small-scale magnetic robots that can assemble, disassemble, and propel under globally applied magnetic fields can be versatile modular subunits for manufacturing and in vivo operations. This paper presents a magnetic cuboid robot that contains assembled cubes with encapsulated freely rotating permanent magnets. This minimalistic, scalable design enables the magnetic cubes to assemble under magnetic fields into a cube chain that can propel using pivot-walking locomotion. A vision-based closed-loop controller that modulates the cuboid robot's position and orientation during pivot walking is presented. The controller is simulated to navigate cuboid robots to user-selected goal locations. A BFS (Breadth-First Search) path-planning algorithm for obstacle avoidance is used to generate optimal paths for closed-loop pivot walking.Two physical workspaces are tested, one with a large free space and the other with a maze.Experiments and simulations demonstrate that magnetic cuboid robots can navigate in complex mazes and selectively self-assemble into cube chains while following the optimal path generated by the motion planner with visual feedback control.
Extra O2 evolution reveals an O2-independent alternative electron sink in photosynthesis of marine diatoms
Authors: Shimakawa Ginga , Matsuda Yusuke 
Published: September 2023

Abstract
Following the principle of oxygenic photosynthesis, electron transport in the thylakoid membranes (i.e., light reaction) generates ATP and NADPH from light energy, which is subsequently utilized for CO2 fixation in the Calvin-Benson-Bassham cycle (i.e., dark reaction). These two processes generally maintain a strict equal stoichiometry between O2 evolution and CO2 consumption. The tight coupling of photosynthetic light and dark reactions breaks only where an alternative electron flow functions with a large capacity comparable to that of CO2 fixation. Here, we quantitatively monitored O2 and total dissolved inorganic carbon (DIC) during photosynthesis in the pennate diatom Phaeodactylum tricornutum, and found that evolved O2 was larger than the consumption of DIC, which was consistent with 14CO2 measurements in literature. In our measurements, the stoichiometry of O2 evolution to DIC consumption was always around 1.5 during photosynthesis at different DIC concentrations. The same stoichiometry was observed in the cells grown under different CO2 concentrations and nitrogen sources except for the nitrogen-starved cells showing O2 evolution 4 times larger than DIC consumption. An inhibitor to nitrogen assimilation did not affect the extra O2 evolution. Further, the same physiological phenomenon was observed in the centric diatom Thalassiosira pseudonana. Based on the present dataset, we propose that the marine diatoms possess the metabolic pathway(s) functioning as the O2-independent electron sink under steady state photosynthesis that reaches nearly half of electron flux of the Calvin-Benson-Bassham cycle.
Spatial varying and co-occurring future climate changes over a heterogeneous river basin: a multivariate approach
Authors: Gehlot Lalit Kumar , Patel P. L. , Timbadiya P. V. 
Published: September 2023

Abstract

This study explored co-occurring climate-scale changes across the physioclimatically heterogeneous Tapi River basin (TRB) for baseline (1991–2020) and future periods (2021–2100). We used a novel multivariate framework comprising multi-model ensembles of bias-corrected rainfall and temperature from five global climate models (CMIP-5), 12 climate indices (six for each variable), and principal component analysis (PCA). The univariate assessment showed statistically significant warming of 1.1–1.8 °C (1.5–4.0 °C) under RCP-4.5 (RCP-8.5) scenarios. The Middle Tapi basin showed a substantial shift towards a wetter climate regime in the future. The multivariate assessment of spatially varying climate indices resulted in four significant principal components (PCs). The relative evaluation of these PCs showed that nearly 41.6% (47.0%) of the TRB is vulnerable to the transition of the current climatic patterns to the dry–warm (wet–warm) regime under RCP-8.5 (RCP-4.5) in the near (distant) future. On the optimistic side, under RCP-4.5 and RCP-8.5, 53.0% and 69.8% of the TRB displayed signs of uniform temporal distribution with wet rainfall regimes and profound warming towards the end of the 21st century, respectively. The study outcomes would help to devise policies for regional sustainability and adopt mitigation measures to enhance resiliency in a changing climate.
Waterborne transmission of protozoan parasites: a review of worldwide outbreaks – an update 2017–2022
Authors: Bourli Pavlina , Eslahi Aida Vafae , Tzoraki Ourania , Karanis Panagiotis 
Published: September 2023

Abstract

The current study presents a comprehensive review of worldwide waterborne parasitic protozoan outbreaks reported between 2017 and 2022. In total, 416 outbreaks were attributed to the waterborne transmission of parasitic protozoa. Cryptosporidium accounted for 77.4% (322) of outbreaks, while Giardia was identified as the etiological agent in 17.1% (71). Toxoplasma gondii and Naegleria fowleri were the primary causes in 1.4% (6) and 1% (4) of outbreaks, respectively. Blastocystis hominis, Cyclospora cayetanensis, and Dientamoeba fragilis were independently identified in 0.72% (3) of outbreaks. Moreover, Acanthamoeba spp., Entamoeba histolytica, Vittaforma corneae, and Enterocytozoon bieneusi were independently the causal agents in 0.24% (1) of the total outbreaks. The majority of the outbreaks (195, 47%) were reported in North America. The suspected sources for 313 (75.2%) waterborne parasitic outbreaks were recreational water and/or swimming pools, accounting for 92% of the total Cryptosporidium outbreaks. Furthermore, 25.3% of the outbreaks caused by Giardia were associated with recreational water and/or swimming pools. Developing countries are most likely to be impacted by such outbreaks due to the lack of reliable monitoring strategies and water treatment processes. There is still a need for international surveillance and reporting systems concerning both waterborne diseases and water contamination with parasitic protozoa.
Assessing groundwater quality: a case study in Ghana Talensi district
Authors: Iddrisu Umar Farouk , Armah Edward Kwaku , Tetteh Emmanuel K. , Amedorme Bright Selorm 
Published: September 2023

Abstract

Because most life processes are directly or indirectly related to water, people are investigating on the various sources of drinking water supply. Surface water and groundwater are the most common sources of water for domestic and other uses. The availability of safe and sufficient drinking water in developing countries’ rural and many urban areas is critical. Groundwater has become the primary source of drinking water supply in northern Ghana, particularly in rural areas. Tongo, in northern Ghana, is entirely dependent on groundwater for its drinking water supply. The quality of groundwater from 15 boreholes and open well samples was assessed in this study. The primary goals of the research are to assess the quality of groundwater for drinking and to determine the distribution of major ions in groundwater and the factors that control them. Groundwater physicochemical parameters were within the WHO guidelines limit. However, coliform bacteria were found in some groundwater sources. Anthropogenic, natural, and ion exchange processes were also identified as controlling groundwater major ion distribution. Insanitary conditions were identified as potential sources of contamination during field observations. As a result, the regular monitoring of groundwater resources could reveal more about the area's groundwater quality status.
Driving factors for decoupling water resources ecological footprint and economic growth in water-deficient cities dominated by agriculture
Authors: Zhang Wenqi , Liu Defu , Chen Xianming , Zhou Xiaoguo , Ding Yifan , Zhang Jialei 
Published: September 2023

Abstract

To explore the key factors and specific thresholds of water resources limiting economic development, and to provide technical support for water resources management in cities dominated by agriculture similar to Zhangjiakou. We used the Tapio elastic decoupling method to quantitatively evaluate the decoupling relationship between the water resources ecological footprint (WEF) and economic growth. Then the logarithmic mean Divisia index (LMDI) and mathematical statistics are used to identify the key factors and threshold effects. The results show a significant decreasing trend in the WEF and obvious spatial differences in Zhangjiakou between 2006 and 2015, with agricultural ecological footprint dominating all districts and counties (77.54 ± 14.35%). The changes in technological effect are a contributing factor to the decoupling between the WEF and the economy in Zhangjiakou, while the economic effect is the main restricting factor. In particular, there is a high correlation between the WEF and the number of water-saving irrigation machines and the total power of agricultural machinery. According to the findings, for water-scarce cities such as Zhangjiakou, where agriculture is the primary focus, it is suggested that increasing the number of agricultural machinery can effectively alleviate the problem of water scarcity constraining economic development.
A Review of Stem Cell Therapy in Ischemic Heart Disease, Where are We Now?
Authors: Kiwan Yahya , Shehab Abdulla , Shehab Omer Abdulla , Elnour Asim Ahmed 
Published: September 2023

Background:
Regenerative therapies to rejuvenate the heart have a significant appeal for researchers. Preliminary findings from pre-clinical studies suggest that bone marrow cells may have reparative and regenerative effects on heart muscles, creating a ripe area for research. Many generations of stem cells used in pre-clinical and early clinical studies have shown promising but variable results.

Objective:
The current review article discusses the dilemmas in applying stem cell therapy to cardiovascular diseases and possible strategies to make it feasible.

Methods:
The field of regenerative therapies continued to progress with second-generation cells, third-generation cells, combination cell therapy, and the use of cell products alone. Research showed promising positive results in multiple randomized phases 1, 2, and 3 clinical trials in addition to numerous meta-analyses. The gaps in knowledge included stem-cell sources, their delivery routes, dosing, types of cells, and the indicated cardiac conditions.

Results:
The results from the latest randomized clinical trials, namely the Dream-HF, showed improved left ventricle function, symptoms, and overall survival. Studied patient populations include post-myocardial infarction (MI), ischemic/non-ischemic cardiomyopathy, intractable/microvascular angina, and cardiac surgery for congenital and valvular heart disease. The phase 3 DREAM-HF trial did not meet the primary heart failure endpoint of reducing hospital admission. Still, it showed a clinically significant reduction in major adverse cardiovascular events (MACE), including recurrent MI and stroke, by 60%. A 60% reduction in cardiovascular mortality and a 79% reduction in cardiovascular mortality in patients with evidence of inflammation (high CRP). The latter finding suggests a more anti-inflammatory effect. This effect was much higher than that observed in the PARADIGM-HF trial, which showed a 20% relative risk reduction in cardiovascular mortality. By combining the results of the DREAM-HF trial with MSC-HF, ixCELL-DCM, CONCERT-HF, and REGENERATE-DCM, the potential for clinical applications of cell therapy is promising.

Conclusion:
There is a promising role for cell therapy in the management of cardiovascular diseases. Results of trials in the setting of heart failure are more encouraging in both ischemic and non-ischemic cardiomyopathy. This is in contrast with acute myocardial infarction, where the results have been variable. Amongst all the various cell types tested MSCs show the most significant promise for treating HF.
An Early Detection and Classification of Alzheimer's Disease Framework Based
on ResNet-50
Authors: Nithya V P , Mohanasundaram N , Santhosh R. 
Published: September 2023

Objective:
The objective of this study is to develop a more effective early detection system for Alzheimer's disease (AD) using a Deep Residual Network (ResNet) model by addressing the issue of convolutional layers in conventional Convolutional Neural Networks (CNN) and applying image preprocessing techniques.

Methods:
The proposed method involves using Contrast Limited Adaptive Histogram Equalizer (CLAHE) and Boosted Anisotropic Diffusion Filters (BADF) for equalization and noise removal and K-means clustering for segmentation. A ResNet-50 model with shortcut links between three residual layers is proposed to extract features more efficiently. ResNet-50 is preferred over other ResNet types due to its intermediate depth, striking a balance between computational efficiency and improved performance, making it a widely adopted and effective architecture for various computer vision tasks. While other ResNet variations may offer higher depths, they are more prone to overfitting and computational complexity, which can hinder their practical application. The proposed method is evaluated on a dataset of MRI scans of AD patients.

Results:
The proposed method achieved high accuracy and minimum losses of 95% and 0.12, respectively. While some models showed better accuracy, they were prone to overfitting. In contrast, the suggested framework, based on the ResNet-50 model, demonstrated superior performance in terms of various performance metrics, providing a robust and reliable approach to Alzheimer's disease categorization.

Conclusion:
The proposed ResNet-50 model with shortcut links between three residual layers, combined with image preprocessing techniques, provides an effective early detection system for AD. The study demonstrates the potential of deep learning and image processing techniques in developing accurate and efficient diagnostic tools for AD. The proposed method improves the existing approaches to AD classification and provides a promising framework for future research in this area.
An Updated Review on the Chemistry, Biological Characteristics and Analytical
Techniques of Dapagliflozin
Authors: Chaudhari Ujwal , Sahu Jagdish K. , Dande Payal R. 
Published: September 2023

Background:
Globally, type 2 diabetes mellitus (T2DM) prevalence is increasing. A patient must have lifetime therapy for diabetes to manage it and prevent any complications. There are many different medications that can be used to treat Type 2 diabetes. Still, almost all of them concentrate on the declining insulin sensitivity and secretion that are associated with the onset of the illness.

Methods:
There is growing interest in the development of innovative anti-diabetic medications that are not insulin-reliant because treatments with such insulin-dependent mechanisms of action usually lose their effectiveness over time. One such technique is the inhibition of renal glucose reuptake.

Results:
Dapagliflozin, the first line of selective sodium-glucose cotransporter 2 inhibitors that re-duce renal glucose reabsorption, is currently being developed as a therapy for Type 2 diabetes. Numerous analytical techniques have been developed for its detection, measurement, and regular quality control procedures.

Conclusion:
This review deliberates a thorough discussion on the chemistry of Dapagliflozin, all of its pharmacological actions with analytical and bioanalytical analyses, and more information on the clinical trials.