bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Innovation and Economic Freedom on Female Economic Inclusion
Authors: Ofori Pamela E. , Ofori Isaac K. , Castelnovo Paolo 
Published: June 2024

Abstract

The Sustainable Development Goal 5 emphasises the need to achieve gender parity in economic participation. Perusing the extant scholarship on female economic inclusion in Africa, we identify two pressing gaps. First, we find that previous studies have not explored how innovation affects female economic inclusion (FEI). Second, we note that prior studies have not examined the interactive effect of innovation and economic freedom on FEI. This study addresses these gaps by using macro data from 1995-2022 for a sample of 51 African countries. Findings from the two-step system GMM estimator reveal the following: (1) innovation reduces FEI, whereas economic freedom increases it, and (2) economic freedom moderates innovation to promote FEI. Further, we find that this positive total effect of innovation on FEI is remarkable at higher thresholds of economic freedom. We conclude that for innovation to promote FEI in Africa, investments in promoting economic freedom are critical.
JEL Code: 031; 055; E24; J16; J21
Heterogeneous Effects of Frontier Technology Readiness on Economic Growth in Africa
Authors: Ofori Isaac K. , Gbolonyo Emmanuel Y. , Vezzulli Andrea 
Published: June 2024

Abstract

Despite the remarkable growth in frontier technology adoption (FTR) in the Global South, empirical evidence concerning their socioeconomic impacts in the context of Africa is hard to find. This study, therefore, employs macro data for a sample of 39 African countries to bridge three pressing gaps in the growth literature. First, we examine the impact of FTR on economic growth. Second, the study assesses whether FTR and egalitarian democracy synergistically enhance economic growth. Third, this study examines the heterogeneous effects of FTR across growth quantiles. Robust evidence, based on the dynamic system-GMM and the method of moments quantile regression, reveals the following: first, FTR promotes economic growth, but the effect is modest; second, egalitarian democracy amplifies the growth-enhancing impact of FTR, but only at higher thresholds of egalitarianism. Third, although FTR is growth-enhancing across all growth quantiles, the effect diminishes from the 1st to the 9th quantile. However, in the presence of egalitarian democracy, FTR significantly enhances growth across all growth quantiles from the 1st to the 9th. We conclude that progress in egalitarian democracy and investments for enhancing FTR are crucial for economic growth in Africa.
JEL Code: O31; O38; O55; Q01; P48
Cutting-Edge AI Technology to Recognize Signs of Suicidal Thoughts in Social Media Posts
Authors: R Anjit Raja , B Nagarajan 
Published: June 2024

Abstract

Detecting signs of suicidal thoughts from social media poses significant challenges for researchers. Many individuals who may be at risk of suicide express their emotions and thoughts openly on these platforms, offering valuable clues for identification. However, comprehending the intricate risk factors and warning signs associated with suicide prevention remains a formidable endeavour. Automating the recognition of abrupt changes in user behavior is crucial in this context. This task leverages natural language processing techniques to scrutinize social media interactions for behavioral patterns and textual content. These insights are then processed using specialized frameworks designed to pinpoint unusual behaviors indicative of potential suicidal intentions. Cutting-edge deep learning and machine learning methodologies play a pivotal role in swiftly identifying suicidal ideation. For instance, combining RNN (Recurrent Neural Network) models with LSTM proves effective in capturing emotional nuances from user posts. Strategies such as expanding the training dataset and incorporating attention mechanisms are utilized to enhance the accuracy and efficiency of these models. This study introduces an innovative LSTM-Attention-RNN model specifically crafted for analyzing social media content to detect potential suicidal tendencies. Evaluation of this model yielded promising outcomes, achieving an accuracy of 93.7% and an F1-score of 95.8%, representing notable improvements compared to baseline models. These findings underscore the model's potential for practical implementation in suicide prevention initiatives.
Enhancing the Accuracy of Reference-Guided Genomic Assemblies: Implementing Ragtag Correction for Reference-Guided Scaffolds
Authors: Liu Kai , Xie Nan 
Published: June 2024

Abstract

Recent advancements in long-read sequencing technologies are renowned for providing extended read lengths and lower error rates, which enhance the assembly of complex genomes. However, high costs and stringent sample quality requirements limit their widespread adoption, especially for degraded DNA samples. In contrast, short-read technologies require shorter DNA fragments but produce reads challenging genome assembly continuity. Reference-guided assembly offers a practical solution by aligning contigs with a reference genome, thereby improving scaffold continuity. However, the reference-guided assembly can introduce more misassemblies. To address this limitation, this study explores using Ragtag's Correct function integrated with in silico libraries to correct misassemblies in reference-guided assemblies. Using three draft genomes from two fish species, we demonstrate that this hybrid strategy significantly improves scaffold assembly accuracy. Specifically, in Megalobrama amblycephala, misassemblies were reduced from 8298 to 4920, and cross-links between different chromosomes decreased from 192 to zero in the corrected assemblies. In two Culter alburnus draft genomes, misassemblies were reduced from 5689 and 6582 to 4728 and 5861, respectively, while cross-links between different chromosomes were significantly reduced from 132 and 13 to five and ten in the corrected assemblies. This approach allowed precise correction of scaffold assembly errors, showcasing its potential to enhance the accuracy of genomic assemblies. Our findings underscore the importance of integrating additional genomic data to achieve reliable genome assemblies, especially for species with significant structural variations. This research provides valuable insights into optimizing genome assembly processes, contributing to advancements in genomic studies.
Implementing Automated Safety Circuit Breakers of Large Language Models for Prompt Integrity
Authors: Han Gaoshan , Zhang Qingchun , Deng Baisen , Lei Mengzhu 
Published: June 2024

Abstract

The proliferation of natural language processing applications has brought to light the critical need for robust mechanisms to safeguard against malicious prompts that can lead to harmful or misleading outputs. The novel concept of automated safety circuit breakers significantly enhances the reliability and integrity of large language models by integrating advanced machine learning algorithms with dynamic rule-based systems, providing a scalable and efficient solution for real-time threat mitigation. Comprehensive evaluation of the implemented system revealed high precision, recall, and F1-score, demonstrating its effectiveness in accurately filtering out malicious content and reducing the incidence of misleading responses. Comparative analysis with existing methods highlights the superiority of the automated approach, which offers significant advantages in terms of adaptability and operational efficiency. The research underscores the importance of continuous innovation in the field of natural language processing to ensure the safe and trustworthy deployment of language models across various applications. The findings reinforce the necessity of developing sophisticated automated tools to maintain the security and dependability of generated outputs, addressing both current vulnerabilities and potential future threats.
The effect of using different needle size on patient comfort and pain during the sonographically guided fine needle biopsy of thyroid nodules
Authors: Mehmet  
Published: June 2024

Abstract

Backround
Fine needle biopsy has been used for many decades, but afew studies showed the relationship between pain and needle diameter.
Object
This study aimed to compare patients’ pain and satisfaction levels between 22 and 27-gauge (G) needles used for fine-needle biopsy of thyroid nodules.
Materials and methods
In our study, one hundred sixty-nine patients with thyroid nodule biopsies (159 nodules) were included. Patients with nodules were separated into two independent groups depending on which needle were used. The questionnaire was applied to all the patients after the thyroid biopsy. The main study method was the pain scale measuring a patient’s pain intensity, based on a self-report regarding Visual Analog Scale. The numeric variables between two groups used the Student t test, more than two independent groups used a one-way ANOVA test, and between two categorical variables used a Chi-square test.
Results
There was no statistically significant difference between 22 G and 27 G needles in terms of pain sensations. (P > 0.05). And also there was no statistical differences between gender, pattern of nodule and diameter of nodules. But the women is more prone to feel sensation than men. (P<0,05)
Conclusion
Thyroid fine needle aspiration biopsy is one of the invasive methods that could cause unsatisfactory and pain in patients. The use of different gauges of biopsy can affect the biopsy pain and satisfaction. The results of our study showed that fine needle biopsy with 22-G needles had no difference when we compared it to 27- G needle biopsy
Mortality review of Intensive Care Units (ICUs) in Addis Ababa Public Hospitals: Case Series.
Authors: Boru Yared , Belay Ermiyas , Sultan Menbeu , Gebreyesus Alegnta , Melaku Agazhe , Kassahun Mihret , Kifle Fitsum 
Published: June 2024

Abstract

Background
Intensive care units (ICUs) play a crucial role in healthcare but face challenges in terms of resource availability and allocation. This is especially evident in low-resource regions such as Ethiopia, where ICUs are scarce and often lack the necessary resources for proper data recording. Although progress has been made in improving healthcare infrastructure in Ethiopia, significant gaps remain in meeting national and global healthcare goals, especially in tertiary care services. This study conducted a retrospective review of ICU records at public tertiary-level facilities in Addis Ababa between January 15 and March 17, 2022. This study aimed to gain insight into disease conditions, identify strategies to reduce preventable deaths, and develop programs to improve patient outcomes.
Results
The study reviewed 65 patient records from varying age groups, from 11 months to 97 years, with a mean age of 48 years. Most patients (35%) were older than 60 years. Nonoperative patients (71%) were the most common reason for admission, with the remainder being operative patients. The primary systems leading to ICU admission were the respiratory (19%), neurological (18%), and cardiovascular (12%) systems. Most patients required mechanical ventilation, and endotracheal intubation (ETI) was the most common method used (58.5%). Among the 65 patients, the cause of death was recorded in 46 of the records. The most frequently documented causes of death were septic shock (23.9%), and cardiorespiratory arrest (17.4%).
Conclusion
This mortality review of ICU-admitted patients in Addis Ababa offers valuable insights into the primary causes of ICU admission and the comorbidities that contribute to ICU mortality. This study emphasizes the necessity of evidence-based protocols to improve patient outcomes in the ICU and the importance of understanding the underlying factors that contribute to ICU mortality. Further research could focus on identifying risk factors for septic shock and cardiorespiratory arrest in ICU patients to develop targeted interventions for prevention and treatment
The Impact of Including Diverse Historical Narratives in Science Education on Student Engagement and Learning Outcomes: A Mixed-Methods Study
Authors: M Poornesh 
Published: June 2024

Abstract

This study examines how incorporating diverse historical narratives into science education affects student engagement and perceptions. The research used a mixed-methods approach, including a pre-test/post-test survey on student engagement (n = 50) and interviews/focus groups with students. The quantitative data showed a significant increase in student interest in the science topic after exposure to the narratives. Qualitative analysis revealed two main themes: (1) a newfound interest in specific scientific fields due to the historical context, and (2) an appreciation for the diverse perspectives that contribute to scientific progress. To illustrate these themes, student quotes from interviews/focus groups were strategically included. These findings emphasize the potential of diverse historical narratives to ignite student interest, enhance understanding of scientific discovery as a global endeavor, and foster a more inclusive learning environment. The research provides valuable insights for science curriculum development, teacher training, and promoting social justice in science classrooms.
Predictors of deep brain stimulation (DBS) response
in patients with obsessive compulsive disorder (OCD):
a systematic review and meta-analysis
Authors: Thavarajasingam Santhosh G. , Zand Amir Puyan Divanbeighi , Ramsay Daniele S. C. , K Sajeenth Vishnu , Thakker Roma D. , Nagi Jasleen , Eraifej John , Amirthalingam Guru , Shaked Zoe , Sivov Hugo , Jankovic Dragan , Kramer Andreas , Linsmayer Denise , Nowacki Andreas , Groppa Sergiu , Glaser Martin B. , Ringel Florian , Green Alexander L. 
Published: June 2024

Abstract

Background: Obsessive-compulsive disorder (OCD) is a chronic and debilitating condition, often resistant to conventional treatments. Deep brain stimulation (DBS) emerges as a promising intervention, but its efficacy varies among patients, underscoring the need to understand the predictive factors influencing its outcomes.
Objective: To evaluate and compare disease and patient characteristics in their ability to predict response to DBS in OCD patients.
Methods: All major databases were searched for original studies. This study differentiated responders, partial responders, and non-responders based on relative post-treatment Y-BOCS score changes and pre-defined Y-BOCS cut-off scores. Clinical predictors were assessed using qualitative synthesis, univariate analysis, stepwise and regularisation-tuned multivariate linear and logistic regression analyses.
Results: The meta-analysis, with an overall pooled sample size of 289 patients from 28 studies found that higher baseline Y-BOCS scores and elevated mood /hypomania significantly predicted favourable long-term DBS response (p = 0.00129 and p =0.04637, respectively). Conversely, aggression/intrusive thoughts symptomology was found to be a significant negative predictor in the short-term (p = 0.0499) and long-term (p = 0.04765). Antidepressant use was found to be a negative predictor for long-term DBS response (p = 0.00468). Symmetry/hoarding/perfectionism baseline significantly predicted non-response in the short-term (p = 0.0017) and long-term (p = 0.00185). Disease duration, gender, anatomical target location and age did not predict DBS response (p>0.05).
Conclusion: This study found that a heightened baseline severity of OCD symptoms and specific OCD mood dispositions significantly enhances the efficacy of DBS therapy, while the presence of specific compulsive behaviours and concurrent antidepressant treatment hinders long-term response. Further research with homogenous methodology and outcome reporting, as well as randomised control trials, are required to further elucidate these phenotypes, and allow for more personalised and, and thus likely more effective, DBS treatment strategies for all OCD patients.
Digital and Hybrid Pediatric and Youth Mental Health Program Implementation Challenges During the Pandemic: Literature Review With a Knowledge Translation and Theoretical Lens Analysis
Authors: Lyzwinski Lynnette , Mcdonald Sheila , Zwicker Jennifer , Tough Suzanne 
Published: June 2024

Background
The pandemic brought unprecedented challenges for child and youth mental health. There was a rise in depression, anxiety, and symptoms of suicidal ideation.

Objective
The aims of this knowledge synthesis were to gain a deeper understanding of what types of mental health knowledge translation (KT) programs, mental health first aid training, and positive psychology interventions were developed and evaluated for youth mental health.

Methods
We undertook a literature review of PubMed and MEDLINE for relevant studies on youth mental health including digital and hybrid programs undertaken during the pandemic (2020-2022).

Results
A total of 60 studies were included in this review. A few KT programs were identified that engaged with a wide range of stakeholders during the pandemic, and a few were informed by KT theories. Key challenges during the implementation of mental health programs for youth included lack of access to technology and privacy concerns. Hybrid web-based and face-to-face KT and mental health care were recommended. Providers required adequate training in using telehealth and space.

Conclusions
There is an opportunity to reduce the barriers to implementing tele–mental health in youth by providing adequate technological access, Wi-Fi and stationary internet connectivity, and privacy protection. Staff gained new knowledge and training from the pandemic experience of using telehealth, which will serve as a useful foundation for the future. Future research should aim to maximize the benefits of hybrid models of tele–mental health and face-to-face sessions while working on minimizing the potential barriers that were identified. In addition, future programs could consider combining mental health first aid training with hybrid digital and face-to-face mental health program delivery along with mindfulness and resilience building in a unified model of care, knowledge dissemination, and implementation.
Convolutional neural networks models for visual classification of pressure ulcer stages (Preprint)
Authors: Lei Changbin , Jiang Yan , Xu Ke , Liu Shanshan , Cao Hua , Wang Cong 
Published: June 2024

BACKGROUND

Pressure ulcers (PUs), also called pressure injuries (PIs) bring a negative health impact on patients and pose a substantial economic burden on society. Accurate staging is the key to the treatment of PUs. The deep learning (DL) algorithm using convolutional neural networks(CNNs) of images have achieved good classification performance in complicated of skin diseases, which also has the potential to improve diagnostic accuracy in staging PUs.

OBJECTIVE

We explored the potential of applying different CNNs algorithms, namely AlexNet, VGGNet16, GoogLeNet, ResNet 18, to PUs staging aiming to provide an effective tool to assist in evaluation.

METHODS

PU images from patients, including stageⅠ, stageⅡ, stage Ⅲ, stage Ⅳ, unstageable, and suspected deep tissue injury (SDTI), were collected at a tertiary hospital in China. To ensure sample balance, we randomly selected an equal number of images in each stage to form image dataset. Additionally, we augmented the sample size through data enhancement. The collected images were then divided into training, validation, and test sets in a ratio of 6:2:2. Subsequently, we trained them using AlexNet, GoogLeNet, VGGNet16, and ResNet 18 to develop staging models.

RESULTS

We collected 821 raw PU images and with the following distribution across stages: stage Ⅰ (113), stage Ⅱ (113), stage Ⅲ (186), stage Ⅳ (108), unstageable (118), and suspected deep tissue injury (SDTI) (113). In addition, 100 images for each stage were selected and a total of 3000 images were obtained after augmentation. The training, validation, and test sets were didvided in a ratio of 6:2:2. Among all the CNN models, ResNet 18 demonstrated the highest accuracy (0.9333), precision (0.987), recall (0.933), and F1 score (0.959). The classification performance of AlexNet, GoogLeNet, and VGGNet16 exhibited accuracies of 0.896, 0.75, and 0.625, respectively. The precision values were 0.97, 0.95, and 0.953, while the recall values were 0.896, 0.75, and 0.953, and the F1 scores were 0.935, 0.83, and 0.953, respectively.

CONCLUSIONS

The CNNs-based models demonstrated a strong classification ability of images of PUs, which might promote high efficient, low-cost PU diagnosis and staging.
Clinical and epidemiological features of enteroviral meningitis in children during the seasonal increase in incidence in 2023
Authors: Martynova G. P. , Zlobin D. V. , Stroganova M. A. , Andreeva A. A. , Мунасипов С. Е. , Laletina S. S. 
Published: June 2024

Objective: to identify the clinical and epidemiological features of enteroviral meningitis (EVM) in children during the seasonal rise in incidence in 2023.Materials and methods: a retrospective analysis of 171 medical histories of children aged 1 month to 17 years, hospitalized in the infectious diseases hospital of the RSBHI «KICCH № 1» from June to October 2023, is presented.Results. The bulk of patients, 77.9 ± 3.2% (133/171), were hospitalized between August and October, which indicates the persistence of the summer-autumn seasonality of incidence. The clinical picture of EVM is characterized by acute development, persistent fever, intoxication, against which headache and repeated vomiting appear, indicating the development of hypertensive-hydrocephalic syndrome. Dissociation of meningeal signs requires liquorological studies to confirm the diagnosis of enteroviral meningitis. Clinical recovery at the time of discharge occurred only in 64.3 ± 3.7% of convalescents; in the remaining children, 35.7 ± ± 3.7% (61/171) residual effects persisted, which required continued observation.
A case of infectious mononucleosis caused by Epstein-Barr virus complicated by autoimmune hemolytic anemia
Authors: Sayfullin R. F. , Abdieva K. E. , Razumeykina A. V. , Zolotareva A. P. , Ivanova O. A. 
Published: June 2024

We represent a rare clinical case of infectious mononucleosis with hepatitis, caused by Epstein-Barr virus, complicated by rare secondary autoimmune hemolytic anemia associated with warm agglutinins in a 16-year-old patient. The disease was long-lasting, with a two-wave course of febrile fever. Signs of hepatitis with the development of anemia of moderate severity appeared during the second wave of febrile fever. The etiology of the disease was confirmed by the detection of Epstein-Barr virus DNA in blood and the detection of anti-VCA IgM antibodies to Epstein-Barr virus in the absence of anti-EBNA IgG antibodies. Hemolytic anemia was verified using markers of hemolysis (increased lactate dehydrogenase activity, decreased haptoglobin concentration), and positive results of a direct Coombs test. After successful initiation of prednisone therapy and clinical improvement, the patient was discharged from the hospital on the 24th day of disease to continue treatment on an outpatient basis (prednisone was replaced by methylprednisolone).This case demonstrates the development of a rare autoimmune complication in infectious mononucleosis caused by the Epstein-Barr virus.