bluuebunny/crossref_metadata_2025 huggingface dataset:
UNEXPLAINED UNILATERAL LOWER LIMB NEUROLOGICAL DEFICITS AFTER POSTERIOR SPINAL DECOMPRESSION AND FUSION FOR DEGENERATIVE LUMBAR SPONDYLOLISTHESIS
Authors: Alzakri A.
Published: December 2023

The observational data from the Spine Patient Outcomes Research Trial (SPORT) confirm the superiority of surgical over conservative management of symptomatic degenerative spondylolisthesis. The most common reported neurologic complications after lumbar posterior decompression and fusion are implant malposition, contralateral foraminal stenosis, hematoma/seroma, arachnoiditis, and nerve root oedema or vascular underlying causes.

The current study reported that the patient developed unexpected left side neurological deficit after conventional lumbar posterior spinal decompression surgery for degenerative spondylolisthesis. No intraoperative dural insult. The computer topography (CT) scan and magnetic resonance imaging (MRI) of the spine after index surgery show adequate canal and foraminal decompression. No hardware-related complications or compressive hematoma could explain the patient’s symptoms. The patient recovered completely after removing the redundant posterolateral bone graft. The theory behind that is aggressive posterolateral dissection over the transverse process and abundant application of the bone graft might compress or injure the lumbar plexus. So, we suggested a delicate dissection posterolaterally and only a reasonable amount of bone graft could be applied to prevent such a devastating neurological complication.
Understanding the behaviour of seismically derived Poisson's ratio in near-surface characterization
Authors: Alam Md. Iftekhar , Katumwehe Andrew B. , Abbasi Salman
Published: December 2023

Near-surface characterization is often challenging using a single geophysical technique. We show that seismic refraction is an effective tool by combining P- and S-wave velocity models in the form of
V
P
/
V
S
and Poisson's ratio (

σ

) to detect buried targets along with electrical resistivity imaging (ERI). We acquired vertical and horizontal component seismic data along a 2D profile over two known targets. The first is a water pipe of
c
. 0.8 m diameter located
c
. 1.5 m below the surface and the second is a storm drainage pipe (SDP) of
c
. 1 m diameter at
c
. 2 m depth. The first arrival times of vertical and horizontal component data were picked and inverted using grid-based tomography. The resulting velocity models have smoothly varying structures and could not identify any of the target features. However, when combined as
V
P
/
V
S
and Poisson's ratio models, the features clearly appeared as anomalous zones. A collocated 2D electrical resistivity model shows the presence of anomalies around the same locations. Our study suggests that anomalous
V
P
/
V
S
and Poisson's ratio values derived from seismic velocities are indicative of the relative changes owing to the disturbances in the soil because of construction with respect to the background instead of the anomaly.
Distributional Learning for Network Alignment with Global Constraints
Authors: Xu Hui , Xiang Liyao , Gan Xiaoying , Fu Luoyi , Wang Xinbing , Zhou Chenghu
Published: December 2023

Network alignment, pairing corresponding nodes across the source and target networks, plays an important role in many data mining tasks. Extensive studies focus on learning node embeddings across different networks in a unified space. However, these methods have not taken the large structural discrepancy between aligned nodes into account and, thus, are largely confined by the deterministic representations of nodes. In this work, we propose a novel network alignment framework highlighted by distributional learning and globally optimal alignment. By modeling the uncertainty of each node by Gaussian distribution, our framework builds similarity matrices on the Wasserstein distance between distributions and applies Sinkhorn operation, which learns the globally optimal mapping in an end-to-end fashion. We show that each integrated part of the framework contributes to the overall performance. Under a variety of experimental settings, our alignment framework shows superior accuracy and efficiency to the state-of-the-art.
Swarm Self-supervised Hypergraph Embedding for Recommendation
Authors: Jian Meng , Bai Yulong , Guo Jingjing , Wu Lifang
Published: December 2023

The information era brings both opportunities and challenges to information services. Confronting information overload, recommendation technology is dedicated to filtering personalized content to meet users’ requirements. The extremely sparse interaction records and their imbalanced distribution become a big obstacle to building a high-quality recommendation model. In this article, we propose a swarm self-supervised hypergraph embedding (SHE) model to predict users’ interests by hypergraph convolution and self-supervised discrimination. SHE builds a hypergraph with multiple interest clues to alleviate the interaction sparsity issue and performs interest propagation to embed CF signals in hybrid learning on the hypergraph. It follows an auxiliary local view by similar hypergraph construction and interest propagation to restrain unnecessary propagation between user swarms. Besides, interest contrast further inserts self-discrimination to deal with long-tail bias issue and enhance interest modeling, which aid recommendation by a multi-task learning optimization. Experiments on public datasets show that the proposed SHE outperforms the state-of-the-art models demonstrating the effectiveness of hypergraph-based interest propagation and swarm-aware interest contrast to enhance embedding for recommendation.
Two classes of action-stabilizing synergies reflecting spinal and supraspinal circuitry
Authors: De Sayan Deep , Ricotta Joseph M. , Benamati Anna , Latash Mark L.
Published: December 2023

Two types of synergies, in the space of commands to individual fingers and in the space of motor unit groups, show qualitatively different behaviors during accurate multifinger force-production tasks. After removing visual feedback, finger force synergies disappear, whereas motor unit-based synergies persist. These results point at different neural circuitry involved in these two basic classes of synergies: supraspinal for multieffector synergies, and spinal for motor unit-based synergies.
Airborne Pollutant Removal Effectiveness and Hidden Pollutant Source Identification of Bionic Ventilation Systems: Direct and Inverse CFD Demonstrations
Authors: Zhang Hong-Liang , Li Bin , Shang Jin , Wang Wei-Wei , Zhao Fu-Yun
Published: December 2023

A healthy and efficient ventilation system is essential for establishing a comfortable indoor environment and significantly reducing a building’s energy demand simultaneously. This paper proposed a novel ventilation system and applied it to the IEA Annex 20 mixing ventilation enclosure to verify its feasibility through mathematical modeling and CFD simulations. First, two bionic ventilation systems, single-side and dual-side ventilations, were compared to a conventional constant-volume supply system using CFD simulations, with the results demonstrating that the bionic ventilation system could provide higher ventilation efficiency and more effective pollutant removal from stagnant regions. Furthermore, the present work exercised these two bionic ventilation systems with different temporal periods of sine and rectangular wave functions, identifying a turning point at a period of 0.06

τ

n

, which could contribute to further enhancement of these bionic ventilation systems. Finally, a methodology depending on the Bayesian inference algorithm was developed for identifying pollution sources in the bionic ventilation system with unstable flow fields, and factors influencing source identification accuracy were discussed. The results show that the peaks of the KDE distributions and the sampling average values of both the source location and intensity are all consistent with the actual source parameters. The potential of the proposed bionic ventilation systems has been well demonstrated by direct and inverse CFD models, paving the way for further engineering applications.
Enhancing Understanding of Hydrologic Processes in the Shafe Watershed, Ethiopia
Authors: Mada Zerihun Makayno , Nannawo Abera Shigute
Published: December 2023

Research on the combined impact of watershed attributes on streamflow is crucial in water resources planning and management, particularly due to the strong link between landscape modification and watershed attributes. However, identifying critical watershed attributes remains a challenge. This study focuses on investigating the impact of watershed attributes on streamflow in the Hare catchment of Ethiopia’s rift valley lakes basin. The Soil and Water Assessment Tool (SWAT) rainfall–runoff model was used, calibrated, and validated against observed discharge data to identify remedial measures for streamflow generation. The model’s performance was evaluated using criteria such as R2, NSE, PBIAS, and RSR, which yielded satisfactory values. The study found significant changes in land cover, with forest and shrub land declining and agricultural land expanding. Comparing mean annual streamflow between 1998, 2009, and 2021, streamflow at 2021 land use and land cover increased by 13.03% compared to 2009, which had already increased by 16.05% compared to 1998. The study also examined the impact of climate variations by manipulating meteorological data length and average slope. Overall, this study provides valuable insights into the relationship between watershed attributes and streamflow, emphasizing the importance of considering land cover changes and climate variations for effective water resource management in the Hare catchment.
Endovascular versus Surgical Lower Extremity Revascularization among Patients with Chronic Kidney Disease
Authors: Chen Qingzheng , Han Jialin , Parvathinathan Gomathy , Ross Elsie , Stedman Margaret R. , Chang Tara I.
Published: December 2023

Introduction. Patients with chronic kidney disease (CKD) have a high prevalence of peripheral artery disease. How best to manage lower extremity peripheral artery disease remains unclear in this patient population. We therefore sought to compare the outcomes after endovascular versus surgical lower extremity revascularization among patients with CKD. Methods. We used data from Optum’s de-identifed Clinformatics® Data Mart Database, a nationwide database of commercially insured persons in the United States to study patients with CKD who underwent lower extremity endovascular or surgical revascularization. We used inverse probability of treatment weighting to balance covariates. We employed proportional hazard regression to study the primary outcome of major adverse limb events (MALE), defined as a repeat revascularization or amputation. We also studied each of these events separately and death from any cause. Results. In our cohort, 60,057 patients underwent endovascular revascularization and 9,338 patients underwent surgical revascularization. Endovascular revascularization compared with surgical revascularization was associated with a higher adjusted hazard of MALE (hazard ratio (HR) 1.52; 95% confidence interval (CI) 1.46–1.59). Endovascular revascularization was also associated with a higher adjusted hazard of repeat revascularization (HR 1.65; 95% CI 1.57–1.72) but a lower adjusted risk of amputation (HR 0.71; CI 0.73–0.89). Patients undergoing endovascular revascularization also had a lower adjusted hazard for death from any cause (0.85; CI 0.82–0.88). Conclusions. In this analysis of patients with CKD undergoing lower extremity revascularization, an endovascular approach was associated with a higher rate of repeated revascularization but a lower risk of subsequent amputation and death compared with surgical revascularization. Multiple factors must be considered when counseling patients with CKD, who have a high burden of comorbid conditions. Clinical trials should include more patients with kidney disease, who are often otherwise excluded from participation, to better understand the most effective treatment strategies for this vulnerable patient population.
Effective Utilization of Data for Predicting COVID-19 Dynamics: An Exploration through Machine Learning Models
Authors: Chumachenko Dmytro , Dudkina Tetiana , Yakovlev Sergiy , Chumachenko Tetyana
Published: December 2023

This study is centered around the COVID-19 pandemic which has posed a global health concern for over three years. It emphasizes the importance of effectively utilizing epidemic simulation models for informed decision-making concerning epidemic control. The challenge lies in appropriately choosing, adapting, and interpreting these models. The research constructs three statistical machine learning models to predict the spread of COVID-19 in specific regions and evaluates their performance using real COVID-19 incidence data. The paper presents short-term (3, 7, 14, 21, and 30 days) forecasts of COVID-19 morbidity and mortality for Germany, Japan, South Korea, and Ukraine. The precision of each model was scrutinized based on the type of input data used. Recommendations are provided on how various data sources can enhance the interpretation quality of machine learning models predicting infectious disease dynamics. The initial findings suggest the need for the comprehensive utilization of all available data, favoring cumulative data during holiday-rich periods and daily data otherwise. To minimize the absolute error, databases should be compiled using daily morbidity and mortality rates.
DON of Hope: Starving Pancreatic Cancer by Glutamine Antagonism
Authors: Pillai Ray , Papagiannakopoulous Thales
Published: December 2023

A promising approach to treat solid tumors involves disrupting their reliance on glutamine, a key component for various metabolic processes. Traditional attempts using glutamine inhibitors like 6-diazo-5-oxo-L-norleucine (DON) and CB-839 were unsuccessful, but new hope arises with DRP-104, a prodrug of DON. This compound effectively targets tumor metabolism while minimizing side effects. In a recent study published in Nature Cancer, Encarnación-Rosado and colleagues demonstrated in preclinical models that pancreatic ductal adenocarcinoma (PDAC) responds well to DRP-104, although tumors adapt through the MEK/ERK signaling pathway, which can be countered by the MEK inhibitor trametinib. In a related study, Recouvreux and colleagues found that DON is effective against pancreatic tumors, revealing that PDAC tumors upregulate asparagine synthesis in response to DON, making them susceptible to asparaginase treatment. Both studies underscore the potential of inhibiting glutamine metabolism and adaptive pathways as a promising strategy against PDAC. These findings pave the way for upcoming clinical trials utilizing DRP-104 and similar glutamine antagonists in the battle against solid tumors.
Final Results from RIBBIT: A Randomized Phase III Study to Evaluate Efficacy and Quality of Life in Patients with Metastatic Hormone Receptor-Positive, HER2-Negative Breast Cancer Receiving Ribociclib in Combination with Endocrine Therapy or Chemotherapy with or without Bevacizumab in the First-Line Setting
Authors: Decker Thomas , Zaiss Matthias , Klein Dunja , Hahn Antje , Hagen Volker , La Rosée Paul , Liersch Rüdiger , Wolff Thomas , Niemeier Beate , Hillebrand Larissa E. , Lennartz Carolin , Chiabudini Marco , Bengsch Fee , Indorf Martin , Marschner Norbert
Published: December 2023

Background: We investigated the efficacy and health-related quality of life (HRQoL) in patients receiving either ribociclib plus endocrine therapy (ET) or chemotherapy with/without bevacizumab as first-line treatment of metastatic hormone receptor (HR)-positive, HER2-negative breast cancer (BC). Patients and Methods: In this randomized, phase III study (RIBBIT), 38 patients diagnosed with metastatic HR-positive, HER2-negative BC with presence of visceral metastases recruited between May 2018 and December 2020 were randomly assigned in a 1:1 ratio to either arm A (ribociclib + ET) or arm B (chemotherapy with/without bevacizumab) at 12 sites in Germany. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall response rate (ORR), overall survival (OS), patient-reported HRQoL, and frequency and type of adverse events. During study conduction, the recruitment rate was persistently and considerably lower than originally expected. Therefore, the recruitment was ended prematurely. The study was initially designed to enroll and randomize 158 patients. Results: Median [95% CI] PFS was 27.3 months [19.1 – NA, parameter not estimable] in arm A and 15.8 months [8.2 – NA] in arm B. Complete responses were achieved only in arm A (n = 2, 10.5%). The ORR [95% CI] between arm A (57.9% [33.5–79.7]) and arm B (52.6% [28.9–75.6]) was comparable. Median OS [95% CI] was not reached in arm A, while in arm B median OS was 28.4 months [25.0 – NA]. Patients in arm A reported less burden by side-effects. No new safety signals emerged. Conclusion: Treatment of patients with visceral metastatic HR-positive, HER2-negative BC with ribociclib in combination with ET showed a tendency toward a more favorable clinical outcome. Despite small numbers of patients and sites, this head-to-head comparison with chemotherapy supports the use of ribociclib with ET in patients with visceral metastasis at risk of fast disease progression.
3–4 Cycles versus 6 Cycles Neoadjuvant Chemotherapy in Advanced-Stage Epithelial Ovarian Cancer: Survival Is Not Determined by the Number of Neoadjuvant Chemotherapy Cycles
Authors: Bese Tugan , Bicer Elifnur , Kayan Basak Ozge , Cebi Sait Sukru , Acikgoz Abdullah Serdar , Turna Hande , Demirkiran Fuat
Published: December 2023

Introduction: The aim of this study was to compare the disease-free survival (DFS) and overall survival (OS) of patients who underwent interval cytoreductive surgery after 3–4 cycles or 6 cycles of neoadjuvant chemotherapy (NACT) in advanced epithelial ovarian cancer patients. Methods: Out of 219 patients with advanced epithelial ovarian cancer, 123 patients received 3–4 cycles and 96 patients received 6 cycles of platinum-based NACT. Afterward, laparotomy was performed for interval cytoreductive surgery. Results: No statistically significant difference was found for DFS and OS of the patients who received 3–4 cycles and those who received 6 cycles of NACT (HR: 1.047, 95.0% CI [0.779–1.407]; p: 0.746 for DFS, and HR: 1.181, 95.0% CI [0.818–1.707]; p: 0.368 for OS). Evaluating 123 patients who received 3–4 cycles of NACT, 87 patients (70.7%) without macroscopic residual tumor after interval cytoreductive surgery had significantly longer DFS and OS compared to 36 patients (29.3%) with any residual tumor (HR: 1.830, 95.0% CI [1.194–2.806]; p: 0.003 for DFS, and HR: 1.946, 95.0% CI [1.166–3.250]; p: 0.009 for OS). 96 patients who received 6 courses of NACT were evaluated; 63 patients (65.6%) without macroscopic residual tumor after interval cytoreductive surgery had significantly longer DFS and OS than 33 patients (34.4%) with any residual tumor (HR: 1.716, 9 5.0% CI [1.092–2.697]; p: 0.010 for DFS, and HR: 1.921, 95.0% CI [1.125–3.282]; p: 0.013 for OS). Conclusion: In patients with advanced ovarian cancer, there is no significant difference in DFS and OS between 3 and 4 cycles or 6 cycles of NACT. The most important factor determining survival is whether macroscopic residual tumor tissue remains after interval cytoreductive surgery following NACT.
A Deep Learning Model for Detecting Rhegmatogenous Retinal Detachment Using Ophthalmologic Ultrasound Images
Authors: Wang Huihang , Chen Xuling , Miao Xiaocui , Tang Shumin , Lin Yijun , Zhang Xiaojuan , Chen Yingying , Zhu Yihua
Published: December 2023

Introduction: Rhegmatogenous retinal detachment (RRD) is one of the most common fundus diseases. Many rural areas of China have few ophthalmologists, and ophthalmologic ultrasound examination is of great significance for remote diagnosis of RRD. Therefore, this study aimed to develop and evaluate a deep learning (DL) model, to be used for automated RRD diagnosis based on ophthalmologic ultrasound images, in order to support timely diagnosis of RRD in rural and remote areas. Methods: A total of 6,000 ophthalmologic ultrasound images from 1,645 participants were used to train and verify the DL model. A total of 5,000 images were used for training and validating DL models, and an independent testing set of 1,000 images was used to test the performance of eight DL models trained using four different DL model architectures (fully connected neural network, LeNet5, AlexNet, and VGG16) and two preprocessing techniques (original, original image augmented). Receiver operating characteristic (ROC) curves were used to analyze their performance. Heatmaps were generated to visualize the process of the best DL model in the identification of RRD. Finally, five ophthalmologists were invited to diagnose RRD independently on the same test set of 1,000 images for performance comparison with the best DL model. Results: The best DL model for identifying RRD achieved an area under the ROC curve (AUC) of 0.998 with a sensitivity and specificity of 99.2% and 99.8%, respectively. The best preprocessing method in each model architecture was the application of original image augmentation (average AUC = 0.982). The best model architecture in each preprocessing method was VGG16 (average AUC = 0.998). Conclusion: The best DL model determined in this study has higher accuracy, sensitivity, and specificity than the ophthalmologists’ diagnosis in identifying RRD based on ophthalmologic ultrasound images. This model may provide support for timely diagnosis in locations without access to ophthalmologic care.
Inequidad y violencia de género: percepciones de universitarios del sur de Chile
Authors: Flores-Aguilar Paula , Cárdenas-Neira Camila Cárdenas-Neira
Published: December 2023

(analytical)The ways in which young people who are students at the Austral University of Chile interpret inequality and gender violence and the positions they adopt towards these phenomena. A qualitative methodology was used to analyze oral and written testimonies from 12 pre and postgraduate students at the university in accordance with constructivist grounded theory. The results show that the students' interpretations and positions are influenced by their direct and indirect experiences of violence, as well as their access to different sources of knowledge. As a result, young people demonstrate different stages of understanding, awareness and critical reflection of this phenomenon, as well as expressing either critical/active or uncritical/passive positions. Finally, the university students proposed strategies to eradicate gender violence, including the creation of coeducational spaces, making heteronormativepractices more flexible and integrating dissenting opinions.
Keywords: Youth; university; gender violence; gender inequality; interpretation; social attitudes; gender equality; non-violence.
A Civil Aviation Customer Service Ontology and Its Applications
Authors: Lv Meixiang , Cao Xudong , Wu Tianxing , Li Yuehua
Published: December 2023

In the process of developing the C919 large aircraft customer service intelligence system, we find that heterogeneous and incomplete data cause the inefficient and inaccurate decision making. Thus, to solve this problem, we propose to introduce the idea of ontology modeling and reasoning into competitive intelligence system building in this paper. We first present the building principles and methods of the civil aviation customer service ontology. We then define the classes and properties to contribute a real-world civil aviation customer service ontology, which is published on the Web (http://www.openkg.cn/dataset/cacso). We finally design SWRL rules corresponding to different intelligence analysis targets to support reasoning in our designed competitive intelligence system.
AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR
Authors: Olatunji Tobi , Afonja Tejumade , Yadavalli Aditya , Emezue Chris Chinenye , Singh Sahib , Dossou Bonaventure F. P. , Osuchukwu Joanne , Osei Salomey , Tonja Atnafu Lambebo , Etori Naome , Mbataku Clinton
Published: December 2023

Africa has a very poor doctor-to-patient ratio. At very busy clinics, doctors could see 30+ patients per day—a heavy patient burden compared with developed countries—but productivity tools such as clinical automatic speech recognition (ASR) are lacking for these overworked clinicians. However, clinical ASR is mature, even ubiquitous, in developed nations, and clinician-reported performance of commercial clinical ASR systems is generally satisfactory. Furthermore, the recent performance of general domain ASR is approaching human accuracy. However, several gaps exist. Several publications have highlighted racial bias with speech-to-text algorithms and performance on minority accents lags significantly. To our knowledge, there is no publicly available research or benchmark on accented African clinical ASR, and speech data is non-existent for the majority of African accents. We release AfriSpeech, 200hrs of Pan-African English speech, 67,577 clips from 2,463 unique speakers across 120 indigenous accents from 13 countries for clinical and general domain ASR, a benchmark test set, with publicly available pre-trained models with SOTA performance on the AfriSpeech benchmark.
The Future of Secular Law in Spain: A Model Based on the Evolution of Religiosity and Religious Influence on Law
Authors: Garciandía Igal David
Published: December 2023

This article analyzes how the evolution of religiosity will affect the secularity of Spanish law. In a liberal constitutional system such as that of Spain, the influence of religion on law is inevitable. The article proposes a model based on two variables: the increase or decrease of the religious population and the capacity and willingness of religions to influence secular law. The four possible resulting scenarios are religious aggrandizement (a growing religious population seeking to shape the law); religious secularization (a growing religious population with a worldview compatible with secularity); religious backlash (some religious minorities undermining the secularity of the law); and religious diminishment (a declining religious population losing its capacity or willingness to influence the law). The model demonstrates theoretically that inclusion policies do not necessarily lead to the Islamization of Spain. Ignoring religious issues can lead to the marginalization of a religious minority, which favors radicalization and non-acceptance of secularity.
Japanese Climate Litigation and the Development of Personal Rights
Authors: Nishikawa Yumeno Grace
Published: December 2023

Since climate change was recognised as a global concern, there has been a growing number of climate-related cases around the world. While the development of climate litigation in Japan is often overlooked in the academic literature, Japanese citizens in fact have instituted four lawsuits that all aim to stop the construction and operation of coal-fired power plants, as the use of coal in the power generation sector is primarily responsible for the total emissions of greenhouse gases in Japan. Accordingly, this article aims to introduce the recent climate-related cases and to show how human rights-based concepts are utilized with the intention of incorporating environmental claims. More specifically, the development of the concept of personal rights (Jinkaku-ken, 人格権) is discussed, primarily by examining the arguments made in the tort law-based climate cases.
Rights-Based Climate Litigation in South Africa and the Netherlands
Authors: Wadiwala Zunaida Moosa
Published: December 2023

Academic research into international climate change litigation has shown that the courts yield significant power in bringing about an awareness of climate impacts as well as firmly entrenching rights and responsibilities for claimants and defendants. In April 2022, the IPCC’s Sixth Assessment Report noted in some detail how climate litigation is shaping climate governance. This article considers these statements within the framework of how courts have drawn on fundamental constitutional rights even without an exclusive reliance on the right to a healthy environment within the jurisdiction of South African climate litigation. The objective of this study is to investigate this claim by analysing the available legal mechanisms in South Africa and what legal strategies have been used in climate litigation to determine how South African climate litigation has shaped climate governance in comparison to climate litigation from the Netherlands. The core analysis examines firstly what the litigation is seeking to achieve, secondly which legal mechanisms and avenues were relied upon and thirdly, how this resonates between different jurisdictions. The key results will contribute to an understanding of the contribution that South African and Dutch climate litigation lends to global climate governance, the extent to which litigation relies on entrenched fundamental rights; it further tracks how, if at all, transnational climate governance litigation has developed in this respect.
Teaching Constructive Replications in the Behavioral and Social Sciences Using Quantitative Data
Authors: Bauer Gerrit , Breznau Nate , Gereke Johanna , Höffler Jan H. , Janz Nicole , Rahal Rima-Maria , Rennstich Joachim K. , Soiné Hannah
Published: December 2023

Introduction

The replication crisis in the behavioral and social sciences spawned a credibility revolution, calling for new open science research practices that ensure greater transparency, including preregistrations, open data and code, and open access.

Statement of the Problem

Replications of published research are an important element in this revolution as part of the self-correcting process of scientific knowledge production; however, the teaching value of replications is still underutilized thus far.

Literature Review

Pedagogical knowledge points to the value of replication as critical to the scientific method of test and retest. Psychology has already begun mass efforts to reproduce previous experiments. Yet, we have very few examples of how analytical and reanalysis replications, after the data come in, contribute to the reproducibility crisis and can be integrated into undergraduate and graduate courses.

Teaching Implications

Replications with quantitative data can be a pedagogical tool for improving student research method skills and introducing them to best research practices via learning-by-doing.

Conclusion

This article aims to start filling this gap by offering guidance to instructors in designing and teaching replications for students at various levels and disciplines in the social and behavioral sciences, including a supplementary teaching companion.
Radiomics from multisite MRI and clinical data to predict clinically significant prostate cancer
Authors: Krauss Wolfgang , Frey Janusz , Heydorn Lagerlöf Jakob , Lidén Mats , Thunberg Per
Published: December 2023

Background

Magnetic resonance imaging (MRI) is useful in the diagnosis of clinically significant prostate cancer (csPCa). MRI-derived radiomics may support the diagnosis of csPCa.

Purpose

To investigate whether adding radiomics from biparametric MRI to predictive models based on clinical and MRI parameters improves the prediction of csPCa in a multisite-multivendor setting.

Material and Methods

Clinical information (PSA, PSA density, prostate volume, and age), MRI reviews (PI-RADS 2.1), and radiomics (histogram and texture features) were retrieved from prospectively included patients examined at different radiology departments and with different MRI systems, followed by MRI-ultrasound fusion guided biopsies of lesions PI-RADS 3–5. Predictive logistic regression models of csPCa (Gleason score ≥7) for the peripheral (PZ) and transition zone (TZ), including clinical data and PI-RADS only, and combined with radiomics, were built and compared using receiver operating characteristic (ROC) curves.

Results

In total, 456 lesions in 350 patients were analyzed. In PZ and TZ, PI-RADS 4-5 and PSA density, and age in PZ, were independent predictors of csPCa in models without radiomics. In models including radiomics, PI-RADS 4-5, PSA density, age, and ADC energy were independent predictors in PZ, and PI-RADS 5, PSA density and ADC mean in TZ. Comparison of areas under the ROC curve (AUC) for the models without radiomics (PZ: AUC = 0.82, TZ: AUC = 0.80) versus with radiomics (PZ: AUC = 0.82, TZ: AUC = 0.82) showed no significant differences (PZ: P = 0.366; TZ: P = 0.171).

Conclusion

PSA density and PI-RADS are potent predictors of csPCa. Radiomics do not add significant information to our multisite-multivendor dataset.
The Need for Training Resources for Volunteer Youth Leaders on Teaching Preparation and Delivery
Authors: Cabaniss Laura
Published: December 2023

In recent decades, pragmatic youth ministry has produced resources on engaging programs, relational equity, practical organization, or family ministry. While all of these are helpful and necessary, they have left a gap in teaching formation resources for volunteer youth leaders. This article surveys the trends in recent literature, reviews current resources, and seeks to show the importance of teaching resources for youth volunteers that address both preparation for teaching and flexibility and adaptability when teaching.
Relationship Between Corticosteroid Administration and Survival Period in Terminal Cancer Patients
Authors: Katayama Hideki , Tabata Masahiro , Kamei Haruhito , Mimura Yusuke , Maeda Yoshinobu
Published: December 2023

Objective: Corticosteroids are commonly used for symptom relief in patients with terminal cancer, but their use may have an impact on patient survival. We compared the survival of patients with terminal cancer who did and did not receive corticosteroid treatment for symptom relief, stratified by their predicted prognosis. Methods: We retrospectively reviewed consecutive patients with cancer who received corticosteroid treatment for symptom relief in a single palliative care unit. We stratified the patients according to their predicted prognosis using the palliative prognostic (PaP) score either before starting the corticosteroid treatment or at admission for control patients who did not receive a corticosteroid treatment. The 2 groups were compared for survival based on the PaP Scores. Results: We analyzed 204 patients treated with a corticosteroid during the study period and 139 control patients who did not receive corticosteroids during their treatment. No difference was observed in the survival between the treatment and control groups. Conclusion: Corticosteroid treatment for symptom relief in patients with terminal cancer did not affect survival time.
Impact of a Parent Education Program Delivered by Nurses and Health Care Providers in Reducing Infant Physical Abuse Hospitalization Rates in British Columbia, Canada
Authors: Sadler Karen , Rajabali Fahra , Zheng Alex , Jain Nita , Pike Ian
Published: December 2023

Background

The Period of PURPLE Crying Program® ( PURPLE) is a universal parent education program that is delivered by nurses and health care providers to all parents/caregivers of newborns in British Columbia (B.C.). The aim of the program is to reduce the incidence of Traumatic Head Injury -Child Maltreatment (THI-CM), a form of child physical abuse.

Objective

To determine if the PURPLE program had an impact on the rate of physical abuse hospitalizations for children less than or equal to 24 months of age in B.C. since implementation in 2009.

Methods

The analysis measured physical abuse hospitalization rates for the period January 1, 1999 to December 31, 2019 and excluded any cases of confirmed Traumatic Head Injury-Child Maltreatment. Data were divided into pre-implementation period January, 1999 to December, 2008, and post-implementation period January, 2009 to December, 2019. Data were obtained from the Discharge Abstract Database and B.C. THI-CM Surveillance System to capture information on infant child abuse. Poisson regression and ANCOVA was applied to model the change in rates pre and post program implementation.

Results

Physical abuse hospitalization rates decreased by 30% post-implementation period (95% CI: −14%, 57%, p  =  0.1561). The decreasing linear trend in the post-implementation period was significantly different than the increasing linear trend in the pre-implementation period (F1,17  =  4.832, p  =  0.042).

Conclusions

Nurses’ role in engaging parents in conversations about PURPLE messages over multiple timepoints within a structured universal program model resulted in a decrease in physical abuse hospitalization rates since the implementation of PURPLE.
The effect of gas and oil prices on economic confidence: An empirical analysis for euro area
Authors: Arzova Sabri Burak , Ertuğrul Hasan Murat , Şahin Bertaç Şakir
Published: December 2023

Energy prices are determinants of economic confidence by directly affecting production, consumption, and transportation costs. Nevertheless, countries’ energy policies and macroeconomic and geopolitical developments may moderate the impact of energy prices on economic confidence. This study analyzes the effects of oil and gas prices on business and confidence in the Euro Area over the period 1994–2023. We employ non-linear correlation and regression models to investigate the spillover relationship between the variables. For this purpose, the Markov Switching Regression (MSR) model is employed to analyze the spillover effect of oil and gas prices on both consumer and business confidence. The empirical results show that oil and gas prices harm consumer confidence in all regimes. Oil prices have a positive effect on business confidence in a volatility regime. However, oil prices negatively affect business confidence in low volatility, but this effect is insignificant. The effect of gas prices on the business confidence index is negative and statistically significant during periods of high volatility. Besides, gas prices positively affect business confidence for low volatility.
Artificial intelligence for triaging of breast cancer screening mammograms and workload reduction: A meta-analysis of a deep learning software
Authors: Xavier Debora , Miyawaki Isabele , Campello Jorge Carlos Alberto , Freitas Silva Gabriela Batalini , Lloyd Maxwell , Moraes Fabio , Patel Bhavika , Batalini Felipe
Published: December 2023

Objective

Deep learning (DL) has shown promising results for improving mammographic breast cancer diagnosis. However, the impact of artificial intelligence (AI) on the breast cancer screening process has not yet been fully elucidated in terms of potential workload reduction. We aim to assess if AI-based triaging of breast cancer screening mammograms could reduce the radiologist's workload with non-inferior sensitivity.

Methods

PubMed, EMBASE, Cochrane Central, and Web of Science databases were systematically searched for studies that evaluated AI algorithms on computer-aided triage of breast cancer screening mammograms. We extracted data from homogenous studies and performed a proportion meta-analysis with a random-effects model to examine the radiologist's workload reduction (proportion of low-risk mammograms that could be theoretically ruled out from human's assessment) and the software's sensitivity to breast cancer detection.

Results

Thirteen studies were selected for full review, and three studies that used the same commercially available DL algorithm were included in the meta-analysis. In the 156,852 examinations included, the threshold of 7 was identified as optimal. With these parameters, radiologist workload decreased by 68.3% (95%CI 0.655–0.711, I² = 98.76%, p < 0.001), while achieving a sensitivity of 93.1% (95%CI 0.882–0.979, I² = 83.86%, p = 0.002) and a specificity of 68.7% (95% CI 0.684–0.723, I² = 97.5%, p < 0.01).

Conclusions

The deployment of DL computer-aided triage of breast cancer screening mammograms reduces the radiology workload while maintaining high sensitivity. Although the implementation of AI remains complex and heterogeneous, it is a promising tool to optimize healthcare resources.
Moral distress among critical care nurses before and during the COVID-19 pandemic: A systematic review
Authors: Beheshtaeen Fatemeh , Torabizadeh Camellia , Khaki Sahar , abshorshori Narjes , Vizeshfar Fatemeh
Published: December 2023

Moral distress has emerged as a significant concern for critical care nurses, particularly due to the complex and demanding care provided to critically ill patients in critical care units. The ongoing COVID-19 pandemic has introduced new ethical challenges and changes in clinical practice, further exacerbating the experience of moral distress among these nurses. This systematic review compares the factors influencing moral distress among critical care nurses before and during the COVID-19 pandemic to gain a comprehensive understanding of the impact of the pandemic on moral distress. For this systematic review, PubMed, Scopus, ProQuest, Web of Science, medRxiv, bioRxiv, Embase, and Google Scholar were all utilized in the search. The search covered articles published from 2012 to December 2022, encompassing a 10-year timeframe to capture relevant research on moral distress among critical care nurses. In total, 52 articles were included in this systematic review. The findings indicate that personal, caring-related, and organizational factors can influence nurses' moral distress. Before the pandemic, factors including futile and end-of-life care, conflicts with physicians, nurse performance and authority, poor teamwork, decision-making regarding treatment processes and patient care, limited human resources and equipment, medical errors, patient restraints, and nurses' age and work experience affect critical care nurses' moral distress. Similarly, during the COVID-19 pandemic, factors contributing to moral distress include futile and end-of-life care, fear of contracting and spreading COVID-19, decision-making about treatment processes, poor teamwork, and being female. This study revealed that the factors contributing to moral distress were approximately similar in both periods. Futile care and end-of-life issues were critical care nurses' primary causes of moral distress. Implementing prevention strategies and reducing these underlying factors could decrease this major issue and improve the quality of care.
Effect of different HA/β-TCP coated 3D printed bioceramic scaffolds on repairing large bone defects in rabbits
Authors: Wen Jian , Song Meiling , Zeng Yu , Dong Xieping
Published: December 2023

Background

Treatment of large segmental bone defects is still a major clinical challenge, and bone grafting is the main method. The development of novel bone graft substitutes will help solve this problem.

Methods

Porous bioceramics hydroxyapatite (HA) scaffolds coated with different ratios of HA/β-tricalcium phosphate (β-TCP) were prepared by 3D printing. The scaffolds were sampled and tested in large segmental bone defect rabbit models. X-ray, micro-computed tomography (CT), hematoxylin and eosin (HE) staining, Van-Gieson staining, and type I collagen staining were performed to find the best scaffolds for large segmental bone defect treatment.

Results

The average length, diameter, compressive strength, and porosity of the bioceramics scaffolds were 15.05 ± 0.10 mm, 4.98 ± 0.06 mm, 11.11 ± 0.77 MPa, and 54.26 ± 5.38%, respectively. Postoperative lateral radiographs suggested the scaffold group got better bone healing and stability than the blank group. Micro-CT showed new bones grew into the scaffold from the two ends of the fracture along the scaffold and finally achieved bony union. The new bone volume around the scaffolds suggested the 3:7 HA/β-TCP-coated bioceramic scaffolds were more favorable for the healing of large segmental bone defects. The results of HE, Van-Gieson, and type I collagen staining also suggested more new bone formation in 3:7 HA/β-TCP-coated bioceramic scaffolds.

Conclusion

3:7 HA/β-TCP-coated porous bioceramics scaffolds are more conducive to the repair of large bone defects in rabbits. The results of this study can provide some reference and theoretical support in this area.
Unpeeling the onion: Digital triage and monitoring of general practice, private psychiatry, and psychology
Authors: Allison Stephen , Bastiampillai Tarun , Kisely Stephen , Looi Jeffrey CL
Published: December 2023

Objective

The Australian federal government is considering a ‘digital front door’ to mental healthcare. The Brain and Mind Centre at the University of Sydney has published a discussion paper advocating that the government should adopt a comprehensive model of digital triage and monitoring (DTM) based on a government-funded initiative Project Synergy ($30 million). We critically examine the final report on Project Synergy, which is now available under a Freedom of Information request.

Conclusion

The DTM model is disruptive. Non-government organisations would replace general practitioners as care coordinators. Patients, private psychiatrists, and psychologists would be subjected to additional layers of administration, assessment, and digital compliance, which may decrease efficiency, and lengthen the duration of untreated illness. Only one patient was deemed eligible for DTM, however, during the 8-month regional trial of Project Synergy (recruitment rate = 1/500,000 across the region). Instead of an unproven DTM model, the proposed ‘digital front door’ to Australian mental healthcare should emphasise technology-enabled shared care (general practitioners and mental health professionals) for the treatment of moderate-to-severe illness.
Machine Learning Models for Predicting Early Neurological Deterioration and Risk Classification of Acute Ischemic Stroke
Authors: Yang Huan , Lv Zhe , Wang Wenxi , Wang Yaohui , Chen Jie , Wang Zhanqiu
Published: December 2023

This study aimed to create machine learning models for predicting early neurological deterioration and risk classification in acute ischemic stroke (AIS) before intravenous thrombolysis (IVT). The study included 704 AIS patients categorized into END and non-END groups. The least absolute shrinkage and selection operator (LASSO) regression was employed to select the best predictors from clinical indicators, leading to the creation of Model 1. Univariate and multivariate logistic regression analyses identified independent predictive factors for END from inflammatory cell ratios. These factors were combined with clinical indicators, forming Model 2. Receiver operating characteristic (ROC) curves assessed the models’ predictive performance. Key variables for Model 1 included the NIHSS score, systolic blood pressure, and lymphocyte percentage. Neutrophil-to-Lymphocyte ratio, Platelet-to-Neutrophil ratio, and Platelet-to-Lymphocyte ratio independently predicted END. Model 1 exhibited moderate predictive ability (AUC 0.721 in training, AUC 0.635 in test). Model 2, which integrated clinical indicators and inflammatory cell ratios, demonstrated strong performance in both training (AUC 0.862) and test (AUC 0.816). Machine learning models, combining clinical indicators and inflammatory cell ratios before IVT, accurately predict END and associated risk in AIS.
Mapping the Evolution of Media Management and Industry Studies in Journalism & Mass Communication Quarterly: 100-Year Retrospective and Future Directions
Authors: Chan-Olmsted Sylvia M. , Jung Jaemin
Published: December 2023

To draw a picture of the evolution of media management research in the context of published scholarly work, this invited piece reviews works related to media management and industry studies published in JMCQ for the past 100 years. Initially, attention was paid to understanding the basics of newspaper as an economic entity. Since then, the status of chain ownership and consolidation, impacts of consolidation on newspaper content, intermedia competition, human resource management, business strategy, adoption/consumption, engagement, and recently, AI in the media industry were the major topics in the media management studies chronologically. Future directions for media management and industry studies were discussed.