bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data analysis accuracy of Urban and rural economic forecast based on neural network algorithm
Authors: Zhang Yan , Yanjie Pan , Zepeng Lv 
Published: February 2023

Abstract
Economic forecasting is affected by many factors. The analysis of economic data needs an intuitive and operable algorithm model. Therefore, based on this, this paper designs an urban and rural economic forecasting system based on neural network algorithm, and conducts a system test. First of all, in the data processing module, this paper adopts an efficient BP neural network algorithm based on error back propagation. This algorithm can effectively improve the accuracy of data recognition. At the same time, in order to solve the identification error caused by the complexity of urban and rural economic data during data input, the data processing layer of the system can preprocess the input data and normalize the multiple linear regression algorithm. Finally, in order to further prove the availability of the neural network algorithm used in this paper, by comparing the results of the original data and the predicted data, it is concluded that the data prediction results obtained by using the model algorithm in this paper have high accuracy and are basically consistent with the target value. Finally, through the analysis of the urban and rural economic development data, the degree of coordination of urban and rural economic development is analyzed, and the urban and rural development model is constructed. This paper also further analyzes the factors that restrict the coordinated development of urban and rural economy through indicators such as population structure, economic development, residents' life, social services and ecological construction, so as to achieve a more comprehensive urban and rural economic forecast, and provide a basis for improving the development of urban and rural economy in the regional economy.
A Look at the Measurement of the Quantum Wave function
Authors: McKeown Daniel 
Published: February 2023

Abstract
In Non-Relativistic Quantum Mechanics, the Schr¨odinger equation describes the evolution of a
quantum system as a superposition of different states, but cannot explain why the system is only
ever measured to be in one of these states. Here we show a new dynamical wave equation for
the evolution of the wave function, and then apply this equation to a variety of different physical
cases, showing how the wave function changes when we move from one potential to another. We
then show how a measurement in quantum mechanics is an example of a potential changing the
possible eigenvalues associated with a quantum system. The dynamical process of a measurement
that evolves the wave function not only returns a single eigenvalue for the basis it is measuring,
but also returns a new Hamiltonian with corresponding eigenvalues. This shows, contrary to some
interpretations, that the wave function is continuous after measurement.
Root-Analogue Implants compared to Forced Orthodontic Extrusion: A retrospective analysis of clinical, radiological and esthetic outcomes after restoration.
Authors: Böse Mats Wernfried Heinrich , Beuer Florian , Naumann Michael , Spies Benedikt Christopher , Neumeyer Stefan , Hildebrand Detlef , Bruhnke Maria 
Published: February 2023

Abstract
Objectives
To assess clinical, radiological and esthetic outcomes of prosthodontic rehabilitations supported by root-analogue implants (RAIs) or roots of severely damaged teeth after forced orthodontic extrusion (FOE).
Materials and Methods
Clinical data regarding RAIs and FOE were recorded and retrospectively evaluated for 40 patients by two independent investigators. Functional and esthetic outcomes were assessed for n = 20 pre-molars and n = 20 anterior teeth via comparison of radiographic and digital images applying the novel Functional Implant Prosthodontic Score (FIPS). Krippendorff’s alpha coefficient was calculated to assess inter-rater reliability. Mann-Whitney-U-Test was used to compare the assessed parameters. Level of significance was set to p < 0.05.
Results
Mean observation period for restorations supported by RAIs was 18.4 ± 5.7 months and 43.9 ± 16.4 months for restorations after FOE. Krippendorff’s alpha coefficients did not reveal unacceptable inter-rater reliabilities regarding the investigators and applicability of FIPS. Significant differences were documented when comparing restorations after FOE or supported by RAIs regarding “bone” (p < 0.01), “interproximal” (p < 0.05) and “mucosa” (p < 0.02) in favor of FOE.
Conclusions
Within the limitations of the present retrospective investigation both concepts seem to provide clinically acceptable results. However, bone- and tissue-preserving characteristics of FOE appear to be more promising.
Clinical Relevance:
Especially bone- and tissue-preserving characteristics regarding the concept of FOE are promising. It could be applicable for socket preservation and subsequent conventional implant placements in an adapted workflow.
Neurofunctional Differences Between the Processing of Short and Long Auditory Time Intervals
Authors: Thibault Nicola , Albouy Philippe , Grondin Simon 
Published: February 2023

Abstract
Previous psychophysical studies have suggested that time intervals above and below 1.2 second are processed differently in the human brain. However, the neural underpinnings of this dissociation are still unclear. In the present study, we investigate whether distinct or common brain networks and dynamics support the passive perception of short (below 1.2s) and long (above 1.2s) empty time intervals. Twenty participants underwent an EEG recording during an auditory oddball paradigm with .8- and 1.6-s standard time intervals and deviants. We computed the auditory event-related potentials for each condition at the sensor and source levels. Then we performed cluster-based permutation statistics around N1 and P2 time periods, testing deviants against standards. At the sensor level, fronto-central components were elicited by deviance detection during N1 for long intervals, and during P2 for short intervals. Source reconstructions revealed that for short intervals, deviance detection was associated with activity in the left auditory cortex, bilateral supplementary motor areas and bilateral cingulate cortices. For long intervals, deviance detection was associated with activity in the left inferior parietal sulcus (IPS), bilateral cingulate cortices, and the right motor cortex. These results suggest that distinct brain dynamics and networks support the perception of short and long time intervals. Main Text
Geographic and Enhanced Opportunistic Routing for Underwater Sensor Networks
Authors: ahmad Zaheer , Ilyas Naveed , Ashraf Nouman , Aslam Sheraz 
Published: February 2023

Abstract
Underwater acoustic communication is a suitable method that facilitates underwater applications. However, the dynamic underwater acoustic environment poses many challenges, such as the three-dimensional expensive energy constraint deployment of nodes, the limited bandwidth, and the movement of nodes due to water currents. This leads to a void hole in the under aquatic region and affects the network performance in terms of packet ratio and energy consumption. To address these issues, we propose two routing protocols named Pro-GEDAR and GEEDAR for under acoustic communication that route data packets from sensor nodes to sonobuoys via opportunistic geographic routing. When a communication void hole occurs, both methods switch to recovery mode instead of using control messages to analyze and discover routing paths along the communication void hole region. The recovery mode procedure relies on the topology control information through improved depth adjustment of the void nodes with a proactive approach. The method significantly improves network performance in sparse and dense distributed networks with maximum traffic load. Our experimental results prove that the performance of our routing protocols is better in terms of fraction of void node, depth adjustment and packet delivery ratio compared to other schemes.
Lead poisoning epidemiology, challenges and opportunities: First systematic review and expert consensus of the MENA region
Authors: Sukaiti Waleed Al , Shuhoumi Mohammed Abdullah Al , Balushi Hassan Al , Faifi Musa Al , Kazzi Ziad 
Published: February 2023

Abstract
Lead is the most ubiquitous heavy metal in the Earth's crust. Since prehistoric times, lead has widely propagated and mobilized in the environment, increasing its non-essential uptake and exposure. The amount of lead entering the atmosphere has reduced substantially in the majority of wealthy nations. Acute exposure becomes relatively low, but chronic exposure to low levels of lead remains a significant public health issue. However, disadvantaged groups are developing and industrializing countries in the Middle East and North Africa (MENA). Our current study comprises various sources of lead pollutant from 48 studies. Of these, 34 studies entered systematic review synthesis after quality assessment and evaluation using the Mixed Method Appraisal Tool (MMAT). The study sought to identify lead pollution sources, epidemiology and distribution and analyse lead poisoning clinical manifestations, management, challenges and opportunities throughout the MENA countries.
Reliability Analysis of Intelligent Manufacturing Systems Based on Improved FMEA Combined with Machine Learning
Authors: Duan Chunyan , Zhu Mengshan , Wang Kangfan 
Published: February 2023

Abstract
Along with the booming of intelligent manufacturing, the reliability management of intelligent manufacturing systems appears increasingly important. Failure mode and effects analysis (FMEA) is a prospective reliability management instrument extensively utilized to manage failure modes of systems, products, processes, and services in various industries. However, the conventional FMEA method has been criticized for its inherent limitations. Therefore, this paper devises a method based on an improved FMEA model combined with machine learning for complex systems and applies it to the reliability management of intelligent manufacturing systems. The structured network of failure modes is constructed based on the knowledge graph for intelligent manufacturing systems. The grey relation analysis (GRA) is applied to determine the risk prioritization of failure modes, hereafter the clustering analysis is employed to extract the features of failure modes. The results show that the proposed method can more accurately reflect the coupling relationship between the failure modes compared with the conventional FMEA method. This research provides significant support for the reliability and risk management of complex systems such as intelligent manufacturing systems.
Hybrid Approach for Certificate Verification using Blockchain in Cloud Environment
Authors: Prabhu D. , Bose S , Naveena R 
Published: February 2023

Abstract
The current analog system for managing educational certificates was unreliable and slow. Students have to request their official transcripts from their university registrar and pay their fees for each copy of the transcript requested. The person who has acquired the credentials should be in charge of them, but most of the time the students have to rely on third parties, such as universities or employers to store, verify and validate the credentials. Employers and universities still at times need to call the issuing authority of the certificate if they want to be sure that the transcript was not faked. It’s complicated and tedious, which is one of the major factors for fraud. Making certificates easily verifiable and transferable is one advantage of digital systems. There are several advantages of creating a digital infrastructure for certificates, but the stakes are high as such systems will grow forward to represent our professional reputations. When proposing a digital method of processing certificates, the elimination of counterfeit certificates from the system should be given top priority. Using a hash-based storage method to assure the authenticity and security of digital content kept on the platform, colleges can submit student certificates and authenticate certificates from other member universities. A permissioned blockchain-based system is employed in the proposed system for the safe verification of academic degrees. The Raft ordering service is used to handle numerous distributed orderers. Universities can upload their student's credentials and validate the certifications of other member universities. A hash-based storage system is used to store the digital contents of the certificate in order to guarantee its authenticity and security. The certificate will be hashed using the SHA-256 technique, then stored in a blockchain. The student can use this hash value to further verify their certificate. The university's reputation is determined using the Beta Reputation Algorithm. This is done in order to avoid or remove the network organization that helps phoney certificates or fake validation. The system can be accessed from any location in the globe if it is set up in a cloud environment.
NumBee versus Traditional Injection: A Comparison of Pain Perception and Efficiency (A Randomized, Split- Mouth Clinical Trail)
Authors: Ameri Duaa Kamal Naji , Jafar Zainab Juma Jafar , Yas Bayda’a Ahmed 
Published: February 2023

AbstractObjectives:Thisstudy compares the anesthetic efficiency of the intraligmentary needless device (NumBee) and traditional dental syringe utilized to anesthetize mandibular 1stpermanent molar, in addition to assessing the pain perception experienced by the subject during anesthesia injection and cavity preparation.Materials and Methods: Non fearful 30 children aged 6-8 years without a history of exposure to dental anesthesia were chosen to participate in the study using a randomized split-mouth design. All of them were indicated for simple class I dental restoration for both of their mandibular 1stpermanent molars. In two randomized sequential dental treatment sessions, they were administered local anesthesia using NumBee for one of their treated teeth and a conventional dental syringe for the other tooth. The pain perception for both devices during the local anesthetic injection and during cavity preparation was evaluated by using Wong Baker Faces pain scale while the efficiency was recorded according to the reported symptoms during cavity preparation.Results:Most of girls who injected by NumBee, experienced significantly less pain during the injection than during cavity preparation (p< 0.05). However, when the children were anesthetized with NumBee, the pain experience during cavity preparation was significantly higher than those anesthetized with inferior alveolar nerve block (p<0.05).Conclusion:NumBee provided a more comfortable and less painful injection as compared to Inferior dental nerve block. However, NumBee gives less anesthetic depth than the inferior alveolar nerve block.Clinical relevance:The features of the NumBee device, such as the absence of a needle, an appearance that is less likely to provoke anxiety, a reasonable duration of action, and the non-necessity of anesthetizing the entire dental nerve branch, could provide a more comfortable injection, and children might indeed favor it to the traditional syringe.Trial registration. : No. 576322 Date: 2.6.2022
Multimodal modeling of human emotions using sound, image and text fusion
Authors: Hosseini Seyed Sadegh , Yamaghani Mohammad Reza , Arabani Soodabeh Poorzaker 
Published: February 2023

Abstract
Multimodal emotion recognition and analysis is considered a developing research field. Improving the multimodal fusion mechanism plays a key role in the more detailed recognition of the recognized emotion. The present study aimed to optimize the performance of the emotion recognition system and presented a model for multimodal emotion recognition from audio, text, and video data. First, the data were fused as a combination of video and audio, then as a combination of audio and text as binary, and finally the results were fused together. The final output included audio, text, and video data taking common features into account. Then, the convolutional neural network, as well as long-term and short-term memory (CNN-LSTM), were used to extract audio. Next, the Inception-Res Net-v2 network was applied for extracting the facial expression in the video. The output fused data were utilized by LSTM as the input of the softmax classifier to recognize the emotion of audio and video features fusion. In addition, the CNN-LSTM was combined in the form of a binary channel for learning audio emotion features. Meanwhile, a Bi-LSTM network was used to extract the text features and softmax was used for classifying the fused features. Finally, the generated results were fused together for the final classification, and the logistic regression model was used for fusion and classification. The results indicated that the recognition accuracy of the proposed method in the IEMOCAP data set was 82.9.
Comparison of Semi and Fully Automated Artificial Intelligence Driven Softwares and Manual System for Cephalometric Analysis
Authors: Zaheer Rumeesha , Shafique Hafiza Zobia , Khalid Zahra , Shahid Rooma , Jan Abdullah , Zahoor Tooba , Nawaz Ramsha , Hassan Mehak ul 
Published: February 2023

Abstract

Background:
Cephalometric analysis has been used as one of the main diagnostic tools for orthodontic diagnosis and treatment planning. The analysis can be performed manually on acetate tracing sheets, digitally by manual selection of landmarks or by recently introduced Artificial Intelligence (AI)-driven tools or softwares that automatically detect landmarks and analyze them. The use of AI-driven tools is expected to avoid errors and make it less time consuming with effective evaluation and high reproducibility.
Objective:
To conduct intra- and inter-group comparisons of the accuracy and reliability of cephalometric tracing and evaluation done manually and with AI-driven tools including WebCeph and CephX softwares.
Methods:
Digital and manual tracing for cephalometric analyses was conducted for 54 patients. 18 cephalometric parameters were assessed on each radiograph by manual method and by using 2 softwares (Webceph and Ceph X). Each parameter was assessed by two investigators using these three methods. SPSS software was then used to assess the differences in values of cephalometric variables between investigators, between softwares, between human investigator means and software means. ICC and paired T test were used for intra-group comparisons while ANOVA and post-hoc were used for inter-group comparisons.
Results:
· Twelve out of eighteen variables had high intra-group correlation and significant ICC p-values, 5 variables had relatively lower values and only one variable (SNO) had significantly low ICC value.
· Fifteen out of eighteen variables had minimal detection error using fully-automatic method of cephalometric analysis. Only three variables had lowest detection error using semi-automatic method of cephalometric analysis.
· Inter-group comparison revealed significant difference between three methods for eight variables; Witts, NLA, SNGoGn, Y-Axis, Jaraback, SNO, MMA and McNamara to Point A.
Conclusion:
There is a lack of significant difference in the majority of variables among the manual, semi automatic and fully automatic methods of cephalometric tracing and analysis. The mean detection errors were the highest for manual analysis and lowest for fully automatic method. Hence the fully automatic AI software has the most reproducible and accurate results.
The development and validation of a Global Advanced Development Framework for the pharmacy workforce: A four-stage multi-methods approach
Authors: Meilianti Sherly , Galbraith Kirsten , Bader Lina , Udoh Arit , Ernawati Desak , Bates Ian 
Published: February 2023

Abstract
Background

Studies have indicated that a generalisable and translatable global framework is a useful tool for supporting career progression and recognising advanced practice.

Aim

To develop and validate a global advanced competency development framework as a tool to advance the pharmacy profession globally.

Methods

A four-stage multi-methods approach was adopted. In sequence, this comprised an assessment of initial content and a cultural validation of the advanced level framework. Following this, we conducted a transnational modified Delphi followed by an online survey sampling the global pharmacy leadership community. Finally, a series of case studies were constructed exemplifying the framework implementation.

Results

Initial validation resulted in a modified draft competency framework comprising 34 developmental competencies across six clusters. Each competency has three phases of advancement to support practitioner progression. The modified Delphi stage provided feedback on framework modifications related to cultural issues, including missing competencies and framework comprehensiveness. External engagement and case study stages provided further validity on the framework implementation and dissemination.

Conclusion

The four-staged approach demonstrated transnational validation of a global advanced competency framework as a mapping and development tool for the pharmacy professions. Further study is needed to develop a global glossary of terminologies on advanced and specialist practice. Also, developing an accompanying professional recognition system and education and training programmes to support framework implementation is recommended.
Simulation and Implementation of an Induction Heating System for Heating Brittle Thin Metal Sheets by Various Excitation Current Frequencies
Authors: HATEM Sude 
Published: February 2023

Abstract
The induction heating process is a highly nonlinear problem since it is associated with so many different variables. The mathematical analysis of this problem is very challenging and needs to be simplified. In most cases, calculating these parameters based on spatial geometry is also non-trivial. This paper deals with a simulation model of induction heating problem. The induction heating properties of brittle metal sheets under various currents and frequencies of an Archimedean spiral coil are simulated in this work using the finite element method of COMSOL Multiphysics, a solution to complicated constructions. In order to distinguish between partial influences, the coil model is adjusted to closely resemble the geometry of the actual coil. The simulation process includes two phases. The former case is obtained by evaluating the heating process and temperature change by gradually increasing the excitation current frequency flowing through induction coil in frequency domain analysis and the latter case is obtained by applying a constant frequency current in a frequency transient condition and evaluating the heating process in model. Hence, the simulation model provides essential information about the nonlinear electromagnetic and thermal properties of the workpiece material in both cases. To verify the simulation model results, a laboratory model is developed and experimental measurements of temperature are compared with simulation results.