bluuebunny/crossref_metadata_2025_split huggingface dataset:
EVALUASI PROGRAM KARTU JAKARTA PINTAR (KJP) DI SMAN 22 JAKARTA TIMUR DENGAN PENDEKATAN CIPP
Authors: Anwar Chaerul 
Published: April 2023

To increase student learning opportunities up to high school level, the DKI Jakarta government provides the Jakarta Smart Card (KJP) program for people who are classified as poor. Evaluation on the implementation of this program needs to be done to see the extent of program success. This study aims to look at the evaluation of the KJP program at SMA Negeri 22 Jakarta using the CIPP (Context, Input, Process, Output) method. The results showed that SMAN 22 had run the KJP program very well. The results of the evaluation on context aspect shows a very good result with 85% of implementation. The input aspects have been carried out 80% with good categories. The process aspect is running well with a percentage of 80% of the plan, and the product evaluation (output) aspect also reaches 80% of the specified criteria. The study also recommends that there should be an officer from provincial government officials to conduct home visit program to maintain the quality of KJP implementation.
Evaluasi Program Pembelajaran E-learning di Badan Pendidikan dan Pelatihan Keuangan Tahun 2020
Authors: Anggraeni Sayekti Dewi 
Published: April 2023

Evaluasi Pelatihan ini bertujuan untuk menganalisis tingkat kepuasan peserta (evaluasi level reaction) terhadap Penyelenggara pelatihan e-learning, menganalisis tingkat pemahaman peserta (evaluasi level learning), menganalisis perubahan perilaku peserta (evaluasi level behavior), dan menganalisis dampak perubahan perilaku peserta (evaluasi level result). Metode yang digunakan dalam penelitian ini adalah Metode Evaluasi Kirkpatrik empat level. Hasil dari penelitian ini dari keempat level evaluasi telah memenuhi kriteria berhasil tetapi masih ada perbaikan yang harus ditindaklanjuti oleh BPPK.
qEEGViz — An Open Source Web Application to Visualize the Reliability of Quantitative EEG Features
Authors: Jain Akarshi , Ramaswami Vydianathan 
Published: April 2023

Abstract
Background: Reliability and validity of features are important statistical concepts used by researchers to evaluate the quality of a research and draw meaningful conclusions from a study. One of the most popular ways of evaluating the reliability is by quantifying using intra-class correlation coefficient (ICC). We aim to develop a user-friendly, interactive web application that enables scholars and researchers to visualize the reliability of quantitative EEG (qEEG) features across various subjects. To our knowledge, currently there are no applications that provide a platform to visualize the reliability of features.
Results: We designed a web application qEEGViz — a freely accessible, easy-to-use, open source web-application that can be used by researchers and scholars to interactively visualize the reliability of quantitative EEG (qEEG) features in the form of topographic maps across various subjects, electrode references and epochs lengths. It is a democratic platform which gives the user flexibility to upload raw EEG signals and adjust parameters like power features, electrode reference and epoch lengths according to their requirements. Finally, the web application outputs the visualization of reliability of the qEEG features in the form of topographic map.
Conclusion: This tool is an academic contribution created solely for scholars and researchers to enhance the statistical power of the EEG experiment to detect a true treatment effect. It is a non-profitable open source web-application, independent of any operating system and can easily run on the local server. The source code and step by step instructions are provided on: https://github.com/akarshijain/qeegviz.
RPL protocol enhancement using K-Nearest Neighbor machine learning approach for IoT application
Authors: Kuwelkar Sonia , Virani Hassanali G 
Published: April 2023

Abstract
It is predicted that the coming decade will witness an upsurge of devices, mobile phones, sensors and actuators communicating over the Internet to enrich human lifestyle. The network design will have to ensure energy efficiency, speed and reliability for Internet of Things to be sustainable in long run. Routing of data, is one aspect which largely governs the quality of service in wireless networks. The IETF ROLL working group proposed the IPv6 Routing protocol for Low power Lossy Networks (RPL) as de-facto routing standard keeping in mind the sustainability of constrained IoT networks. The standard RPL is designed to select best route based on single parameter like hop count. The standard was kept open for researchers to experiment and augment it further. The main aim of this work is to improve the performance of RPL protocol by considering multiple metrics during selection of best route. Four routing parameters namely, hop count, delay, residual energy and link quality are chosen as criteria for deciding the best route. The K-Nearest Neighbor machine learning technique is proposed for multi criteria decision making. The K-NN computes the quality score for each candidate neighbor node and the one with highest score is selected as the most suitable parent in route towards the sink node This novel version, RPL-ML is tested in the COOJA simulator of Contiki OS. Deep dive analysis of RPL-ML by varying data rates and network density reveals that it lowers energy consumption by 18%, improves PDR by 3%, lowers delay by 20% and reduces the control overhead by 48% as compared to standard RPL implementations.
An Improved Rolling Bearing Fault Diagnosis Method using DenseNet-BLSTM
Authors: ZHAO Kaihui , Wu Sicheng , Liu Wenchang , Jia Lin 
Published: April 2023

Abstract

To solve the problems of the conventional rolling bearing fault diagnosis method requiring a large amount of prior knowledge and easy to introduce error artificially, this paper presents a DenseNet-BLSTM method for rolling bearing fault diagnosis. The method combines the superiority of the multi-scale deep feature extraction ability of the densely connected convolutional network (DenseNet) and the advantage of bidirectional long short-term memory (BLSTM) in sequence modeling. First, multiscale abstract features are extracted from the vibration signal of a rolling bearing using one-dimensional convolution kernels. Then, the BLSTM was used to learn the time-dependence of features. Finally, the feature information is mapped to corresponding fault modes by the fully connected layers. The experimental results show that the accuracy of the proposed method is 99.5\% in multi-load scenarios, and the method has good load adaptability and anti-disturbance ability.
Scleral sutured aniridia intraocular lens (Morcher): indications and long-term outcomes
Authors: Vakros Georgios , Bourkiza Rabia , Tarafdar Sonali , Yang Elizabeth , Charteris David 
Published: April 2023

Abstract
Background/Objective: To evaluate the outcomes of trans-scleral sutured posterior chamber black diaphragm intraocular lens (BDIOL) (Morcher®) implantations over 11 years.
Subjects/Methods: Retrospective case-series of patients, who underwent BDIOL implantation, identified from electronic patient records system from 2006 to 2016, Moorfields Eye Hospital. Demographics, pre/post-operative, final best-corrected visual acuity (BCVA), diagnosis, symptomatic improvement, intraoperative and postoperative complications immediate or late were collected and analysed to relate outcomes to surgical indication.
Results: Forty eyes of 38 patients (F:M 1:2.8) underwent BDIOL implantation with a mean surgical age of 46.6 years and follow-up of 44.5 months (range of 8 to 132 months). Indications included 23(57%) ocular trauma, 7(17%) congenital aniridia, 7(17%) iatrogenic lens and/or iris loss, and 3(7%) infectious keratitis. Mean preoperative BCVA was 1.64 logMAR and mean final postoperative BCVA was 0.94 logMAR with an average improvement in BCVA of 0.23 logMAR, equivalent to 1.5 lines of Snellen visual acuity. Visual results varied according to indications. Infectious cause patients had the greatest vision improvement (-0.7 logMAR), followed by trauma (-0.3 logMAR), and 25% of these achieved vision of 0.3 logMAR (6/12 in Snellen acuity) or better. Conversely, the aniridia group had the least improvement (worsened vision of 0.01 logMAR), 17 patients (42%) reported subjective improvement.
Conclusion: BDIOLs achieve reasonably good visual outcomes in eyes with complex vision threatening pathology. No significant intra-operative complications are documented and most post-operative complications are related to the pre-existing pathology. Post – trauma and iatrogenic aniridia have better outcomes compared to congenital aniridia.
Causal Association of Folic Acid Supplementary Therapy and Gastric Ulcer: A Mendelian Randomization Study
Authors: Li Fuhao , Huang Fengming , Lu Yifan , Wang Xi , Li Meng , Zhang Fan , Jiang Hao , Chen Jun , Lv Bin 
Published: April 2023

Abstract
Background.
The incidence of gastric ulcer (GU) remains high worldwide with limited prevention. While promising animal experiments have suggested a potential preventive role of folic acid (FA) in the development of gastric ulcers, the lack of robust clinical evidence has hindered its widespread implementation as a preventative measure. Therefore, this research aims to determine the relationship between FA supplementation and GU genetically by Mendelian randomization (MR) approach, in order to establish a foundation for developing more effective preventative strategies for this condition.
Methods.
Genome-wide association studies (GWAS) investigating the association between folic acid or folate supplementation and gastric ulcers were sourced from the UK Biobank. The primary methods for Mendelian randomization analysis were the inverse variance-weighted (IVW) methods, including fixed-effect and random-effect IVW models. Other methods used to test the robustness of the results included simple model and median, weighted model and median, as well as penalized weighted median.
Results.
MR analysis was performed to investigate the causal effect of FA adjuvant therapy on GU. Seven single nucleotide polymorphisms (SNPs) of genetic loci associated with FA adjuvant therapy were identified. The random-effect and fixed-effect IVW models revealed that genetically predicted FA complementary therapy was significantly related to the reduction of GU risk (OR, 0.870; 95% CI, 0.826–0.917, p < 0.001; OR, 0.870; 95% CI, 0.825–0.918, p < 0.001). Similar results were also observed using simple mode (OR, 0.826; 95% CI, 0.724–0.943, p = 0.030), Weighted mode (OR, 0.828; 95% CI, 0.728–0.941, p = 0.028), simple median method (OR, 0.835; 95% CI, 0.773–0.901, p < 0.001), weighted median (OR, 0.854; 95% CI, 0.794–0.919, p < 0.001) and penalised weighted median (OR, 0.849; 95% CI, 0.789–0.914, p < 0.001). The association between FA supplementary therapy and GU was not considerably driven by any individual SNP according to the leave-one-out sensitivity analysis.
Conclusions.
This MR study provides evidence from a genetic perspective that FA supplementation may decrease the risk of gastric ulcer. Clinicians should prioritize the role of FA in preventing gastric ulcers among patients.
Building Smart Surveillance Solutions for Livestock Farms
Authors: Gao Jerry , Bambrah Charanjit Kaur , Parihar Nidhi , Kshirsagar Sharvaree , Mallarapu Sruthi , Yu Hailong , Wu Jane , Yang Yunyun 
Published: April 2023

Abstract
Farming is an important industry in the world. With the development of artificial intelligence, the intelligence of agriculture has become a trend. Intelligent monitoring of agricultural activities is an important part of it. However, due to difficulties in achieving a balance between quality and cost, the goal of improving the economic benefits of agricultural activities has not reached the expected level. Farm supervision requires intensive human effort and may not produce strong results. In order to achieve intelligent monitoring of agricultural activities to improve economic benefits, this paper combines UAV with Deep learning model, through the combination of UAV in the agricultural industry to detect and classify objects, to achieve independent agriculture without human intervention. In this paper, a highly reliable target detection and tracking system using UAV is developed, which will be proved to be cost-effective. The system uses Deep learning method to solve the target problem. The model uses the data collected from DJI Mirage 4 UAV to detect, track and classify different types of targets. The average map accuracy of this method for target detection and tracking is 90.98\%, the average accuracy is 89.76\%, and the average recall rate is 88.78\%. In addition, this paper also compares the performance of different Deep learning models, such as YOLOv7, FASTER-RCNN, SSD, MASK-RCNN, and compares them with key evaluation indicators, and finally determines a method through the development of YOLOv7-DeepSort model.
Dental restoration operative time and analysis of the internal gap caused by the microfiltration of conventional resins (incremental technique) vs. bulk fill (single-increment technique): In vitro study
Authors: Medina-Sotomayor Priscilla , Ortega Gabriela , Aguilar José , Ordóñez Paola , Rojas Michelle , Vásquez Roxana 
Published: April 2023

Abstract
Background: An incremental technique used in restorations with conventional composite resin promises reduced shrinkage and increased working time; the preparation process consists of applying small increments of resin within a cavity while performing light curing in intervals, which can generate gaps between increments. Bulk fill resin allows the use of single-increment technique, improving operative time and facilitating the restoration. The objective of the present work was to determine the operative time and the internal restoration gap in the restoration–tooth interface in the cavity floor using an incremental technique for conventional resins and the single-increment technique for the bulk fill resin.
Methods: In this in vitro experimental study, the internal gaps of the restoration–tooth interfaces in the cavity floors of two conventional resins and two bulk fill resins were microscopically analyzed, and the restoration times of the single-increment technique and the incremental technique were determined.
Results: Bulk fill resins had smaller internal gap (63.31 µm) than conventional resins (333.14µm).Regarding the restoration time, the single-increment technique obtained the best results in operative time (3.52 minutes), with significant differences relative to the incremental technique.
Conclusions:The Tetric N-Ceram bulk fill resin presented better performance than conventional resins relative to the internal gap of the restoration–tooth interface in the cavity floor. In addition, the single-increment technique presented a short clinical restoration time.
Comparison of two different fixation methods in treating fractures of Type 42A2 through finite element analysis
Authors: Fang Shitao , Zhang Ling , Yang Yunqi , Wang Yun , Guo Jinkun , Mi Lei 
Published: April 2023

Abstract
Background At present, not all open fractures of Type 42A2 can be treated by external fixation stents, and it is inconvenient to use clinically, and external locking steel plates can be used as an alternative treatment for such patients, and the use is light and convenient. And there are few reports of finite element biomechanical analysis of external locking steel plates and external fixation brackets placed on the medial side of tibial fractures. In this study, the biomechanical properties of external locking steel plate and traditional external fixation bracket were compared by finite element method when fixing fracture of Type 42A2, which provided data support for clinical application of external locking steel plate fixation.
Methods We established a fracture of Type 42A2 model using CT data of a volunteer, and constructed two external fixation models: external locking steel plate fixation and external fixation bracket. The fracture of Type 42A2 model and two external fixation models were assembled according to the common clinical fixation methods. Finally, the axial compression, four-point bending and clockwise torsion force of the maximum load were directly loaded into the mechanical software, and the stress distribution, stress peak and overall tibial displacement in the two sets of different external fixation models were observed and compared.
Results Under the maximum load of four different experimental conditions (four-point bending, axial compression, clockwise torsion, counterclockwise torsion), the two sets of external fixation models mainly had obvious Von Mises stress concentrations in the junction between screw and tibia, screw and locking plate, self-tapping self-drilling needle and tibia, self-tapping self-drilling needle and external fixation frame, near the fracture end and near the cortical bone at the upper and lower ends of the tibia. The stress peak is about 26.67 MPa~558.77 MPa, all within the yield stress strength of titanium alloy. The peak displacement of the tibia in the external locking steel plate fixation model was smaller than that of the external fixation bracket model. In terms of structural stability, the external fixation effect of locking steel plate is better than that of single-sided external fixation.
Conclusions When the external locking steel plate fixes the fracture of Type 42A2, it is not only lightweight and convenient, but also reduces the complications in the fracture healing process, and performs better in axial compression force, bending force and torsion resistance. From the finite element biomechanical analysis, the performance of the external locking steel plate is better than that of the traditional external fixation bracket in the treatment of fractures of Type 42A2, which can meet the needs of clinical external fixation applications.
An exploration of the Roles of Lay Mental Health Workers (Cadres) in Community Mental Health Services in Indonesia: A Qualitative Study
Authors: Susanti Herni , Brooks Helen , Yulia Ice , Windarwati Heni D. , Yuliastuti Estin , Hasniah Hasniah , Keliat Budi A. 
Published: April 2023

Abstract
Background: Volunteers trained to support community mental health programs in Indonesia are known as ‘mental health cadres.’ These are lay people trained to provide basic support for people with mental health problems in their local communities. Their contribution has the potential to address the challenges health services currently face in remote, rural, and resource-limited settings. However, little is currently known about the implementation of this form of the lay workforce and the experiences of mental health cadres in Indonesia in particular. This study aimed to explore the role of volunteer cadres in community mental health services in Indonesia from the cadres' perspective.
Methods: The study employed a descriptive qualitative design. Purposive sampling was employed to recruit cadres with at least one year of experience across four geographical areas in Java and Sumatra, Indonesia. Data were collected utilising focus groups undertaken between July and November 2020. Due to Covid-19 restrictions, eight focus group sessions for people with mental disorders and families were carried out virtually via zoom and non-virtual, facilitated by local moderators. Data were analysed using thematic analysis.
Results: The study involved 71 cadres in four regions: Aceh, Jakarta, West Java and East Java. The majority of participants were looking after their families with a minimum of high school-level qualifications. Four themes were interpreted from the data: (1) Motivation for volunteering, (2) The role of cadres in supporting mental health services, (3) Training and support needs, and (4) Barriers and facilitators to the implementation of cadre roles in local communities.
Conclusions:Cadres reported a motivation to help people to improve their mental health and reduce the stigma associated with mental illness. Cadres also contributed to secondary and primary prevention of mental illness with some limitations. This study's results are relevant to those wishing to understand and optimise the implementation of lay workforces in resource-limited settings.
A combined integer-valued autoregressive process with actuarial applications
Authors: Hu Xiang , YAO JING 
Published: April 2023

Abstract
This paper proposes a modification of a combined integer-valued autoregressive (CINAR) process based on binomial thinning, which is instrumental in modelling higher-order dependence between the number of claims in an insurance portfolio. The modified CINAR process is more general and enjoys stationarity and flexibility in higher-order serial dependence modelling. Two actuarial applications of the proposed process in risk theory and credibility model are explored. As an application to risk theory, we derive the distribution of aggregate claims under a discrete-time collective risk model and examine the effect of high-order dependence on the tail-related risk measures of the aggregate claims. Next, we apply the modified CINAR process to account for the unobserved gamma heterogeneity in determining the dynamics of the predictive credibility premium. A real data analysis shows that our approach provides a superior pattern to the predictive premium calculation when compared to the outcomes of several alternative models.
Association between Sjögren’s syndrome and neuromyelitis optica spectrum disorders:a systematic review and meta-analysis
Authors: Wu Zhihong , Wang Dong , Chen Lirong , Yang Huiqing , Xianyu Kaipu 
Published: April 2023

Abstract
Objectives: This meta-analysis was performed to determine the association between Sjögren’s syndrome(SS) and neuromyelitis optica spectrum disorders(NMOSD).
Methods: A systematic review of all published English-language observational studies was performed. This included cross-sectional, prospective, retrospective cohort and case-control studies. Three databases (EMBASE, PubMed and Cochrane Library) up to June 2022 were searched for data collection. The study protocol was registered in PROSPERO (ID: CRD42022346810).
Results: From a total of 471 retrieved articles, 4 studies with 806 patients were eligible for this meta-analysis. 83 patients had SS with NMOSD,52 had NMOSD without SS,and 671 had SS without NMOSD. NMOSD patients with SS had a significantly higher percentage of positive ANA (OR = 19.27, 95% CI: 4.66-79.66, p<0.0001, I2 = 0%), anti-SSA (OR = 131.84, 95% CI: 19.66-884.13, p<0.00001, I2 = 0%) and anti-SSB antibodies (OR = 34.92, 95% CI: 4.09-297.91, p = 0.001, I2 = 0%) than NMOSD patients without SS. Significant differences were found for dry eyes (OR =0.52, 95% CI: 0.28-0.94, p = 0.03, I2 = 0%) and dry mouth (OR =0.31, 95% CI: 0.17-0.59, p = 0.0003, I2 = 4%) when SS patients with NMOSD were compared to those without NMOSD.
Conclusion: NMOSD patients with SS had a significantly higher percentage of positive results for ANA, anti-SSA and anti-SSB antibodies than those without SS. SS patients with NMOSD had less dry mouth and eyes than those without NMOSD,which may pose a significant diagnostic and therapeutic challenge in clinical practice.