bluuebunny/crossref_metadata_2025 huggingface dataset:
Extending the Breast Cancer Surveillance Consortium Model of Invasive Breast Cancer
Authors: Gard Charlotte C. , Tice Jeffrey A. , Miglioretti Diana L. , Sprague Brian L. , Bissell Michael C.S. , Henderson Louise M. , Kerlikowske Karla
Published: November 2023

PURPOSE

We extended the Breast Cancer Surveillance Consortium (BCSC) version 2 (v2) model of invasive breast cancer risk to include BMI, extended family history of breast cancer, and age at first live birth (version 3 [v3]) to better inform appropriate breast cancer prevention therapies and risk-based screening.

METHODS

We used Cox proportional hazards regression to estimate the age- and race- and ethnicity-specific relative hazards for family history of breast cancer, breast density, history of benign breast biopsy, BMI, and age at first live birth for invasive breast cancer in the BCSC cohort. We evaluated calibration using the ratio of expected-to-observed (E/O) invasive breast cancers in the cohort and discrimination using the area under the receiver operating characteristic curve (AUROC).

RESULTS

We analyzed data from 1,455,493 women age 35-79 years without a history of breast cancer. During a mean follow-up of 7.3 years, 30,266 women were diagnosed with invasive breast cancer. The BCSC v3 model had an E/O of 1.03 (95% CI, 1.01 to 1.04) and an AUROC of 0.646 for 5-year risk. Compared with the v2 model, discrimination of the v3 model improved most in Asian, White, and Black women. Among women with a BMI of 30.0-34.9 kg/m
2
, the true-positive rate in women with an estimated 5-year risk of 3% or higher increased from 10.0% (v2) to 19.8% (v3) and the improvement was greater among women with a BMI of ≥35 kg/m
2
(7.6%-19.8%).

CONCLUSION

The BCSC v3 model updates an already well-calibrated and validated breast cancer risk assessment tool to include additional important risk factors. The inclusion of BMI was associated with the largest improvement in estimated risk for individual women.
Fertility Preservation in Adolescents and Young Adults With Cancer: A Case-Based Review
Authors: Burns Karen , Loren Alison W.
Published: November 2023

Adolescent and young adult (AYA) oncology patients are unique in many aspects of their care; fertility preservation (FP) is one of the most complex to address. In addition to the newly diagnosed AYA patient, there are growing numbers of AYA survivors of childhood cancer who present with concerns about their fertility. Emerging independence, emotional and intellectual growth, and development of an adult mindset are hallmarks of the AYA population; these transitions heighten the intrinsic medical, social, and financial challenges of a cancer diagnosis. FP is extraordinarily important in AYA oncology and can be addressed in many ways: experimental options as well as standard of care, with key differences on the basis of pubertal development, cancer diagnosis, and urgency of cancer-directed therapy. Options exist both at diagnosis and throughout the survivorship journey. It is imperative that oncologists recognize the challenges in this age group, as well as opportunities to pursue FP. The field has evolved significantly in the past 25 years and will continue to evolve as we incorporate more immune-based and targeted therapies into our treatment regimens. This case-based review will explore opportunities to preserve fertility in this unique patient population.
Association of Endocrine Disrupting Chemicals With the Metabolic Syndrome Among Women in the Multiethnic Cohort Study
Authors: Ihenacho Ugonna , Guillermo Cherie , Wilkens Lynne R , Franke Adrian A , Tseng Chiuchen , Li Yuqing , Sangaramoorthy Meera , Derouen Mindy C , Haiman Christopher A , Stram Daniel O , Le Marchand Loïc , Cheng Iona , Wu Anna H
Published: November 2023

Metabolic syndrome (MetS) is associated with a high risk of cardiovascular disease, a leading cause of death among women. MetS is a diagnosis of at least 3 of the following: high blood pressure, high fasting glucose, high triglycerides, high waist circumference, and low high-density lipoprotein cholesterol. Epidemiological studies suggest that endocrine disrupting chemical (EDC) exposure is positively associated with individual components of MetS, but evidence of an association between EDCs and MetS remains inconsistent. In a cross-sectional analysis within the Multiethnic Cohort Study, we evaluated the association between 4 classes of urinary EDCs (bisphenol A [BPA], triclosan, parabens, and phthalates) and MetS among 1728 women. Multivariable logistic regression was used to estimate odds ratios and 95% CI for the association between tertiles of each EDC and MetS adjusting for age, body mass index (BMI), racial and ethnic group, and breast cancer status. Stratified analyses by race and ethnicity and BMI were conducted. MetS was identified in 519 (30.0%) women. We did not detect statistically significant associations of MetS with BPA, triclosan, or phthalate metabolite excretion. MetS was inversely associated with total parabens (Ptrend = .002). Although there were suggestive inverse associations between EDCs and MetS among Latino and African American women, and women with BMI < 30 kg/m2, there was no statistically significant heterogeneity in associations by race and ethnicity or BMI. These findings suggest an inverse association between parabens and MetS in larger multiethnic studies. Prospective analyses to investigate suggested differences in associations by race, ethnicity, and BMI are warranted.
In vitro analysis of quercetin-like compounds from mistletoe Dendrophthoe pentandra (L.) Miq as a potential antiviral agent for Newcastle disease
Authors: Mochamad Lazuardi , Malarvili Selvaraja , Jasmine Khairat , Lim Vuanghao
Published: November 2023

Background Recent evidence suggests that some flavonoid compounds obtained from crude methanol extract of mistletoe leaves (Dendrophthoe pentandra L. Miq), also known as Benalu Duku (BD), have antimicrobial effects. Thus, the plant has the potential to eliminate viruses that may cause outbreaks in chicken farms. This study aimed to prove the in vitro ability of flavonoid compounds, namely quercetin-like compounds (QLCs), to eliminate field viruses, specifically the Newcastle disease virus (NDV). Methods This research was performed in two stages. An in vitro test was used with a post-test of the control groups designed at a significance of 0.05. BD leaves (5 kg) were extracted using a maceration method with methanol and then separated into hexane, chloroform, ethyl acetate, and methanol fractions. The final extracted products were separated using semi-preparative high-performance liquid chromatography (HPLC) to obtain QLCs. The QLCs were identified and compared with quercetin using HPLC, proton and carbon nuclear magnetic resonance spectrometry, Fourier transform infrared spectrophotometry, and ultra-performance liquid chromatography–mass spectrometry. The activity of QLCs was tested in vitro against the NDV at a virulence titer of 10−5 Tissue Culture Infectious Dose 50% (TCID50) in chicken kidney cell culture. Results Solutions of 0.05% (w/v) QLCs were discovered to have antiviral activity against NDVs, with an average cytopathogenic effect antigenicity at a 10−5 dilution (p<0.05). Conclusions QLCs from flavonoids from the leaves of BD have in vitro antiviral bioactivity against NDV at a virulence titer of 10-5 Tissue Culture Infectious Dose 50% (TCID50) in chicken kidney cell culture. QLCs may have the potential to be developed as medicinal compounds for the treatment of other human or animal viral infections.
Effect of breather device on respiratory muscle strength and quality of life in coronary artery bypass grafting patients: A randomised control trial protocol
Authors: Nikhade Dhanashri N. , Vardhan Vishnu
Published: November 2023

Coronary artery bypass surgery is widely spread and done for multiple vessel disease, and still a well-established therapy option for coronary artery disease. Reduced respiratory muscle strength has been linked to decreased functional capacity in heart surgery, which has been linked to a prolonged recovery period for lung functions and onset of physical deconditioning, which can last for more than a week. Other common postoperative complications include urinary tract infections, renal failure, limb ischemia, pleural effusion, and hematologic abnormalities. Alterations in lung capacity and size, malfunction of the alveoli, decrease in the central respiratory stimulus, and mechanical issues with thoracic function are all brought on by respiratory consequences. Therefore, to prevent or reduce postoperative pulmonary complications, it is typically advised that patients who have had heart surgery engage in breathing exercises and chest physical therapy. The Breather is a breathing apparatus that uses resistance breathing through various-sized orifices to strengthen respiratory muscles. In addition to healthy people and athletes, breather devices can be used for training, therapy, prevention, or rehabilitation of a variety of pulmonary and other disorders. As there is limited literature showing the efficacy of a breather device in coronary artery bypass grafting (CABG) patients, therefore a need for a study to find the efficacy of a breather device in assessing strength of respiratory muscle and quality of life in CABG patients.

Treatment will be given for three weeks with five sessions per week twice a day. Pre- and post-treatment outcomes will be noted. In this study, results are expected to prove the Breather device is as effective or more effective than conventional chest physiotherapy for refining respiratory muscle strength and quality of life.

CTRI registration: CTRI/2023/05/053052
Data Mining Analysis for Improving Decision-Making in Computer Management Information Systems
Authors: Dong Xiaohong , Xiang Bing
Published: November 2023

In this paper a decision tree-based data mining procedure for information systems is proposed to enhance the accuracy and efficiency of data mining. An enhanced C4.5 decision tree method based on cosine similarity is suggested to evaluate the information gain rate of characteristics and the information entropy of their values. When the information entropy variance among any two values for attributes is within the threshold range, the cosine similarity of the merging attribute values is determined, and the information gain rate of the attributes is recalculated. Large-scale data sets that conventional data processing methods are unable to handle successfully have given rise to the area of data mining. The prime objective is to look into how data mining technology is used in computer management information systems. The benefits of data mining technologies in computer management information systems are examined from a variety of angles in this study. In order to analyze and comprehend huge data sets and to derive knowledge that can be utilized to enhance the decision-making process in computer management information systems, the suggested solution makes use of a number of data mining techniques, including Clustering, Classification, and Association Rule Mining. The experimental analysis indicates that the time required by the proposed method to construct a decision tree is less than the time required by the GBDT, P-GBDT method and the C5.0 decision tree Hyperion image forest type fine classification method. The minimum time is not more than 15 seconds when compared with the minimum time saving of the other two methods. The time required by the C5.0 decision tree Hyperion image forest type fine classification method is always the greatest in comparison with the minimum time saving of the C5.0 decision tree. The classification accuracy of the proposed method for various datasets exceeds 95 percent, and the data mining efficacy is high. This method enhances the precision and efficacy of data mining in order to uncover valuable information concealed behind a large volume of data and maximize its value.
Computer Hardware Fault Detection based on Machine Learning
Authors: Xu Chunxue
Published: November 2023

In order to solve the computer fault detection problem of machine learning, the author proposes a computer hardware fault detection problem based on machine learning. The method combines mutual information and class separability to analyze their relationship, which improves classification accuracy. This study presents an adaptive machine learning technique for the adaptive fusion of data from multiple sources. In addition, the mCRC algorithm seeks for the optimal feature subset using the enhanced forward floating search method, thereby overcoming the limitation that the mRMR algorithm does not specify how to determine the final feature subset. The classification accuracy of the mCRC algorithm is approximately 1% better than that of the mRMR algorithm, and the size of the final feature subset of the mCRC algorithm is 22% smaller than that of the final subset of the mRMR algorithm. Conclusion: the ReMAE algorithm has a higher rate of accurate failure prediction.
IoT and Cloud Based Automated Pothole Detection Model Using Extreme Gradient Boosting with Texture Descriptors
Authors: Ghafoor Kayhan
Published: November 2023

One of crucial activity related to road monitoring and maintenance is the occurrence of potholes. These potholes are also be major reason of road accidents, damaging of vehicles, discomfort of passenger journey and extensive in terms of time and cost. But, identification of potholes can significantly alleviate the aforementioned issues. Other side, the Internet of Things (IoT) plays a crucial role in different applications, and provides viable and state of art solutions for variety of problems. Hence, the aim of this work is to develop a real time automated pothole detection model to detect the potholes in asphalt roads based on IoT devices.The proposed model comprises of three main components such as collection of pothole data and labeling, image pre-processing and texture feature extraction, and extreme gradient boosting (XGBoost) algorithm. The potholes data on asphalt road is collected by three IoT sensors such as accelerometer, ultrasonic sensor, and GPS and further, the collected data is transmitted on cloud via Wi-Fi module. The texture features are extracted using Gaussian steerable and median filters. The extreme gradient boosting (XGBoost) classifier is adopted for prediction task. The simulation results showed that proposed XGBoost model obtains higher accuracy, recall, precision and F1-score rates as 94.56, 97.41, 96.40, and 96.90 respectively using 10-cross fold validation method.
Emotionally Wrapped Social Media Text: Approaches, Opportunities, and Challenges
Authors: Rawat Tara , Jain Shikha
Published: November 2023

With the evolution of several online platforms for information sharing such as social media, blogs, product review sites, and discussion forums, people have become more proactive in sharing their expectations, views, feelings, and experiences. This large amount of emotionally wrapped data motivates many researchers to perform data mining and present the crux of hidden emotions or mental states in a more presentable and comprehensible manner. It has several applications in different domains such as business, education, psychology, politics, and many more. This paper presents a detailed literature review projected to rigorously analyze the existing approaches to identify the mental or emotional state of a person from unstructured textual data. We include the most relevant papers which were published during 2001-2022. The selected papers are classified into three categories: granularity level, contextual level, and cognition level. Each category is carefully analyzed followed by a detailed and critical discussion. Finally, open challenges, opportunities, applications, and future directives are presented in-depth to facilitate the researchers working in the domain of emotion mining.
Real-time Sentiment Analysis on Social Networks using Meta-model and Machine Learning Techniques
Authors: ShiXiao Xiao , Muwafak Alobaedy Mustafa , Goyal S. B. , Singla Sanjay , Kang Sandeep , Chadha Raman
Published: November 2023

Sentiment analysis is a critical task in social media analysis, enabling the understanding of user attitudes and opinions towards various topics. This paper proposes a real- time sentiment analysis system for social networks that utilizes a meta-model and machine learning techniques to accurately classify user sentiment. The proposed system integrates textual and visual data from social media posts to improve sentiment classification accuracy. The methodology includes data collection and preprocessing, feature extraction and selection, and the proposed meta-model for sentiment analysis. The system utilizes several machine learning techniques, including SVM, CNN, and LSTM networks. We evaluated the proposed system on a large-scale dataset and compared its performance with several state- of-the-art methods. The evaluation metrics, including accuracy, precision, recall, and F1-score, showed that our proposed system outperforms existing methods. The proposed system’s ability to handle multimodal data and achieve high accuracy in real- time makes it suitable for various applications, including social media monitoring and marketing analysis. The proposed system’s limitations provide opportunities for further research, such as developing more efficient algorithms and models that require less training data, and improving techniques for handling noisy and ambiguous data, such as sarcasm and irony. In conclusion, the proposed real-time sentiment analysis system using a meta-model and machine learning techniques provides a robust and efficient solution for sentiment analysis on social networks. The proposed system's performance and potential applications demonstrate its importance in the field of social media analysis.
Intelligent Vehicle Inspection Tool Design Based on Freeman Chain Code for Automatic Annotation of 3D Models
Authors: Cheng Shan , Tan Guoqiang
Published: November 2023

Autonomous vehicle are more and more widely used in daily life, and the requirements for their safety performance are higher and higher. As a tool for testing auto parts, intelligent inspection tools are crucial to the guarantee of automobile quality. However, traditional fixture design relies on manual drawing, which is inefficient and prone to errors. To solve this problem, this research uses Freeman chain code to determine the annotation object, uses case clustering method to annotate, and uses error back propagation algorithm to realize case knowledge classification learning, and designs intelligent vehicle inspection tool design technology based on Freeman chain code 3D automatic annotation method. The experimental results show that the geometric feature matching results are correct, and the difference in feature comparison results is significant, with a high accuracy rate. Meanwhile, the geometric similarity annotation method has a high accuracy rate, taking only 3 minutes to complete the annotation, which is 7 minutes longer than traditional manual annotation. The error backpropagation algorithm can accurately achieve feature classification, and the design time of size chain inspection tool deformation design is reduced by 214 minutes compared to manual reverse deformation design, significantly improving design efficiency. In summary, the proposed design method for automotive inspection tools can achieve automatic model annotation, improve design efficiency, and reduce design time.
Impact of Photovoltaic Systems on Distribution Networks with Advances of Cloud, Grid and Cluster Computing
Authors: Song Zhuoran , Li Jianfeng , Jiang Tao , Lu Sichen
Published: November 2023

The impact of photovoltaic (PV) systems on distribution networks in advances of cloud, grid, and cluster computing was annoying in the study. Additional PV systems are explained with their working principles. Furthermore, A clustering-based model was developed to reduce the error in the calculation. The weather conditions were classified into different synoptic types. Prediction-based models were introduced after classifying the weather conditions in different optic types. For the movie, it was noted that conditions play a Vital role in predicting the output produced by a PV system. Moreover, a coherent discussion about the key elements regarding the impact of PV systems on Distribution Networks for Cloud, Grid, and Cluster Computing is done. Thus, through the discussion, an empirical knowledge-based analysis was presented.
Modeling Financial Products and Their Supply Chains
Authors: Bjarnadóttir Margrét Vilborg , Raschid Louiqa
Published: November 2023

The objective of this paper is to explore how novel financial datasets and machine learning methods can be applied to model and understand financial products. We focus on residential mortgage backed securities, resMBS, which were at the heart of the 2008 US financial crisis. These securities are contained within a prospectus and have a complex waterfall payoff structure. Multiple financial institutions form a supply chain to create the prospectuses. To model this supply chain, we use unsupervised probabilistic methods, particularly dynamic topics models (DTM), to extract a set of features reflecting community (topic) formation and temporal evolution along the chain. We then provide insight into the performance of the resMBS securities and the impact of the supply chain communities through a series of increasingly comprehensive models. First, models at the security level directly identify salient features of resMBS securities that impact their performance. We then extend the model to include prospectus level features and demonstrate that the composition of the prospectus is significant. Our model also shows that communities along the supply chain that are associated with the generation of the prospectuses and securities have an impact on performance. We are the first to show that toxic communities that are closely linked to financial institutions that played a key role in the subprime crisis can increase the risk of failure of resMBS securities.

History: Olivia Sheng served as the senior editor for this article.

Funding: This research was partially supported by National Science Foundation [Grant CNS1305368] and National Institute of Standards and Technology [Grant 70NANB15H194].

Data Ethics & Reproducibility Note: No data ethics considerations are foreseen related to this article. The code capsule is available on Code Ocean at https://doi.org/10.24433/CO.8845455.v1 and in the e-Companion to this article (available at https://doi.org/10.1287/ijds.2020.0006 ).
Stoma care accessory products: an overview
Authors: Harris Gemma
Published: November 2023

Stoma care is complex and challenging and can result in complications that can cause psychological distress and negatively impact ostomates’ quality of life. These include appliance leakage, contact dermatitis, mucocutaneous separation and parastomal herniation. Flange extenders, adhesive removers, barrier films, support garments, discharge solidifying agents, powders, seals, protective and adhesive pastes and deodorants aim to prevent or reduce these. By drawing on assessment tools and guidelines and patient preferences in combination with patient education, stoma care nurses can help patients identify and correctly use the most appropriate accessories for them. Incorrect use of a product can worsen or result in further complications.
Shell extremal eigenvalues of tridiagonal Toeplitz Matrices
Authors: Chorianopoulos Christos
Published: November 2023

The shell of a complex tridiagonal Toeplitz matrix is studied. Closed formulas for all quantities involved in its equation are presented. Necessary and sufficient conditions for a Toeplitz tridiagonal matrix to have shell extremal eigenvalues are given. Several, recently introduced, geometric quantities related to the shell are studied as measures of non-normality of these extremal eigenvalues of such matrices. These quantities are also proposed as measures of non-normality for the matrix itself.
PERIPROSTHETIC HIP FRACTURES MANAGED BY REVISION ARTHROPLASTY
Authors: Mahajan Uday , Mehta Sonu , Kotecha Amit
Published: November 2023

Introduction

In general the life expectancy of population is improving. This is causing to increase case load of peri-prosthesis fractures after joint replacements. We present our results of peri-prosthesis fracture around hip managed by revision arthroplasty.

Methods

A retrospective analysis of 24 consecutive patients of periprosthetic hip fracture treated with a revision arthroplasty at Major Trauma Centre between February 2021 and January 2022.

Results

12 male and 12 female patients, average age 78 years. 3 fractures around BHR prosthesis, 2 type A, 15 type B and 3 of type C (Vancouver). The surgery was done in an average 6 days after injury (range 1–14). 6 patients died in follow up, 1 patient contracted infection, 2 developed LLD and 1 patient had multiple dislocations. 6 patients had revision using endo-prosthesis. Advanced age with peri-prosthesis fracture has increased risk of mortality (average age 84.5 years).

Conclusion

Endo-prosthesis replacement had higher risk of dislocation, infection and mortality. Overall patients do well after a revision arthroplasty for periprosthetic hip fracture.

Declaration of Interest

(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.
PREVALENCE OF RAMP LESION IN ANTERIOR CRUCIATE LIGAMENT INJURIES INCREASES WITH DELAYS
Authors: Alieldin Ehab , Samir Mohamed
Published: November 2023

Introduction

The medial meniscus is crescent shaped and it is wider posteriorly than anteriorly. It covers up to 60 % of the articular surface of medial tibial condyle and helps with the loading distribution in the medial compartment. Meniscal lesions occur in association with ACL tears in 60 % of the time. The posterior aspect of the menisco-capsular junction is known as the meniscal rampzone. If not addressed during surgery, it could lead to unfavourable results.

Objective

Incidence of ramp lesion following ACL injuries.

Methods

Observational study of 100 patients at EL Hadara Main University Hospital who underwent anterior cruciate ligament reconstruction. MRI and arthroscopic diagnosis was done to detect Ramp lesions associated with ACL ruptures in November 2017 till November 2019.

Results

Incidence was 9%. Duration of injury and increased medial meniscal slope were associated with increased incidence of ramp lesion. MRI signs were present in 79% of cases without Ramp lesion, 100% in Cases with ramp lesion. Mode of Injury and presence of locking or giving way symptoms were not associated with increased incidence.

Conclusion

The ramp lesion at the posterior aspect of the meniscus is difficult to visualize from standard anterior portals and is, therefore, frequently missed and can be underestimated. Also, there are no specific MRI signs of this lesion. The overall incidence of ramp lesions in 100 cases that had undergone ACL reconstruction in our study was 9 %. It was found also that the longer the duration from injury, the more likely ramp lesion would occur.

Declaration of Interest

(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.
ORTHOPOD: PREDICTING INJURY PROPORTIONALITY FROM NECK OF FEMUR FRACTURES
Authors: Morris Timoth , Fouweather Maisie , Walshaw Thomas , Wei Nicholas , Baldock Thomas , Eardley William
Published: November 2023

Objectives

The need to accurately forecast the injury burden has never been higher. With an aging, ever expanding trauma population and less than half of the beds available compared to 1990, the National Health Service (NHS) is stretched to breaking point1,2. Resultantly, we aimed to determine whether it is possible to predict the proportionality of injuries treated operatively within orthopaedic departments based on their number of Neck of Femur fracture (NOF) patients reported both in our study and the National Hip Fracture Database (NHFD).

Methods

We utilised the ORthopaedic trauma hospital outcomes - Patient operative delays (ORTHOPOD) dataset of 22,585 trauma patients across the four countries of the United Kingdom (UK) admitted to 83 hospitals between 22/08/22 – 16/10/22. This dataset had two arms: arm one was assessing the caseload and theatre capacity, arm two assessed the patient, injury and management demographics.

Results

Our results complied with the data reported to the NHFD in over 80% of cases for both the 2022 and five-year average reported numbers. More operations were performed for elderly hip fractures alone than for the combined totals of the next four most common fractures: ankle, distal radius, tibial shaft and forearm (6387 vs 5922). Conversely, 10 out of the 13 fracture types were not encountered by at least one hospital and 93% of hospitals encountered less than 2 fractures of a certain type.60% of trauma is treated within Trauma Units (TUs) however, per unit, Major Trauma Centres (MTCs) treat approximately 43% more patients. Similarly, 11 out of the 14 fracture types examined presented more frequently to a MTC however 3 of the most common fractures had a preponderance for TUs (elderly hip, distal radius and forearm fractures). After excluding NOF, lower limb fractures accounted for approximately 57% of fractures in all countries and ankle and distal radius fracture combined comprised more than 50% in 74% of regions. There were few outliers across the study regarding number of fractures treated by a hospital with tibial shaft fractures demonstrating the highest number of outliers with 4.

Conclusions

The number of hip fractures seen on average by an individual unit remains relatively consistent as does the regional variation of any given fracture; resultantly, it is possible to predict injury proportionality based off a unit's hip fracture numbers. This powerful tool could transform both resource allocation and recruitment.

Declaration of Interest

(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.
PATELLA FRACTURES IN THE FRAIL HOST: A SYSTEMATIC REVIEW
Authors: Morris Timothy , Dixon Jan , Baldock Thomas , Eardley William
Published: November 2023

Objectives

The outcomes from patella fracture have remained dissatisfactory despite advances in treatment, especially from operative fixation1. Frequently, reoperation is required following open reduction and internal fixation (ORIF) of the patella due to prominent hardware since the standard technique for patella ORIF is tension band wiring (TBW) which inevitably leaves a bulky knot and irritates soft tissue given the patella's superficial position2. We performed a systematic review to determine the optimal treatment of patella fractures in the poor host.

Methods

Three databases (EMBASE/Medline, ProQuest and PubMed) and one register (Cochrane CENTRAL) were searched. 476 records were identified and duplicates removed. 88 records progressed to abstract screening and 73 were excluded. Following review of complete references, 8 studies were deemed eligible

Results

Complication rates were shown to be high in our systematic review. Over one-fifth of patients require re-operation, predominantly for removal of symptomatic for failed hardware. Average infection rate was 11.95% which is higher than rates reported in the literature for better hosts. Nevertheless, reported mortality was low at 0.8% and thromboembolic events only occurred in 2% of patients. Average range of movement achieved following operative fixation was approximately 124 degrees. Upon further literature review, novel non-operative treatment options have shown acceptable results in low-demand patients, including abandoning weight-bearing restrictions altogether and non-operatively treating patients with fracture gaps greater than 1cm. Regarding operative management, suture/cable TBW has been investigated as a viable option with good results in recent years since the materials used show comparable biomechanics to stainless steel. Additionally, ORIF with locking plates have shown favourable results and have enabled aggressive post-operative rehabilitation protocols. TBW with metallic implants has shown higher complication rates, especially for anterior knee pain, reoperation and poor functional outcomes.

Conclusion

There is sparse literature regarding patella fracture in the poor host. Nevertheless, it is clear that ORIF produces better outcomes than conservative treatment but the optimal technique for patella ORIF remains unclear. TBW with metallic implants should not remain the standard technique for ORIF; low-profile plates of suture TBW are more attractive solutions. Non-operative treatment may be considered for low-demand individuals however any form of patellectomy should be avoided if possible.

Declaration of Interest

(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.
ACCURACY OF MEASURING IN VIVO SYNDESMOSIS JOINT KINEMATICS DURING LEVEL GAIT
Authors: Williams David , Swain Lauren , Brockett Claire
Published: November 2023

Objectives

The syndesmosis joint, located between the tibia and fibula, is critical to maintaining the stability and function of the ankle joint. Damage to the ligaments that support this joint can lead to ankle instability, chronic pain, and a range of other debilitating conditions. Understanding the kinematics of a healthy joint is critical to better quantify the effects of instability and pathology. However, measuring this movement is challenging due to the anatomical structure of the syndesmosis joint. Biplane Video Xray (BVX) combined with Magnetic Resonance Imaging (MRI) allows direct measurement of the bones but the accuracy of this technique is unknown. The primary objective is to quantify this accuracy for measuring tibia and fibula bone poses by comparing with a gold standard implanted bead method.

Methods

Written informed consent was given by one participant who had five tantalum beads implanted into their distal tibia and three into their distal fibula from a previous study. Three-dimensional (3D) models of the tibia and fibula were segmented (Simpleware Scan IP, Synopsis) from an MRI scan (Magnetom 3T Prisma, Siemens). The beads were segmented from a previous CT and co-registered with the MRI bone models to calculate their positions. BVX (125 FPS, 1.25ms pulse width) was recorded whilst the participant performed level gait across a raised platform. The beads were tracked, and the bone position of the tibia and fibula were calculated at each frame (DSX Suite, C-Motion Inc.). The beads were digitally removed from the X-rays (MATLAB, MathWorks) allowing for blinded image-registration of the MRI models to the radiographs. The mean difference and standard deviation (STD) between bead-generated and image-registered bone poses were calculated for all degrees of freedom (DOF) for both bones.

Results

The absolute mean tibia and fibula bone position differences (Table 1) between the bead and BVX poses were found to be less than 0.5 mm for both bones. The bone rotation differences were found to be less than 1° for all axes except for the fibula Z axis rotation which was found to be 1.46°. One study1 has reported the kinematics of the syndesmosis joint and reported maximum ranges of motion of 9.3°and translations of 3.3mm for the fibula. The results show that the accuracy of the methodology is sufficient to quantify these small movements.

Conclusions

BVX combined with MRI can be used to accurately measure the syndesmosis joint. Future work will look at quantifying the accuracy of the talus to provide further understanding of normal ankle kinematics and to quantify the kinematics across a healthy population to act as a comparator for future patient studies.

Declaration of Interest

(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.
Has the threat posed by China to international security been overstated?
Authors: Tench Owen
Published: November 2023

This article evaluates whether the threat posed to international security by a rising China has been overstated. The literature analyzed during the research reveals that China’s rise does most definitely pose a threat to international security, a threat widely interpreted as being of an economic, military, and ideological nature. The article argues that claims of a China threat have not been overstated, but they have been misguided. There has been an overfocus upon China’s military build-up, as well as focusing upon the events of the economic development of China, as opposed to concentrating on the consequences of this economic development. It is fundamental that the appropriate factors of the threat are focused upon and considered, in order for the international community to adapt and respond in a manner that minimizes the impact upon international security, as the threat is likely to grow in significance over future decades, as China’s phenomenal rise continues.
COVID-19 pandemic exposes deep fault lines in global health governance
Authors: Imade Lucky
Published: November 2023

A specter is hunting the world – the specter of a deadly infectious disease – novel coronavirus (COVID-19), which has resulted in 758,390,564 and 6,859,093 confirmed cases and deaths, respectfully, worldwide as of 11 March 2023 (World Health Organization 2023). The lethality and adverse effects of the COVID-19 pandemic have generated increased awareness and interest in reforming the global health system. This study seeks to explain the major conceptual fault lines in global health governance (GHG) that hindered infectious disease-control efforts during the COVID-19 outbreak. This will enable the WHO to reform or consider alternative models of GHG in preparation for the next pandemic. The study finds that a global coordinated response has been conspicuously absent in an attempt to combat the COVID-19 pandemic due largely to stumbling blocks such as state sovereignty, gaps in international legal frameworks, and inadequate institutional coordination and collaboration. The article concludes with some novel, innovative, and prescriptive policy approaches toward filling a lacuna in global health architecture.
The UK counter-terrorism strategy and international justice
Authors: Somal Manpreet Kaur
Published: November 2023

This article critically assesses the UK counter-terrorism strategy and determines the extent to which there is international justice within the War on Terror. It investigates why war crimes are investigated and prosecuted differently, as well as how understandings of what terrorism is varied, according to who the perpetrators are. It argues that new legal mechanisms and institutions need to hold all perpetrators of war crimes accountable, both state and non-state actors.
Assessing the inferential strength of epistemic must
Authors: Ricciardi Giuseppe , Ryskin Rachel , Gibson Edward
Published: November 2023

This article presents four experiments that investigate the meaning of English and Italian statements containing the epistemic necessity auxiliary verb must/dovere , a topic of long-standing debate in the philosophical and linguistics literature. Our findings show that the endorsement of such statements in a given scenario depends on the participants’ subjective assessment about whether they are convinced that the conclusion suggested by the scenario is true, independently from their objective assessment of the conclusion’s likelihood. We interpret these findings as suggesting that English and Italian speakers use epistemic necessity verbs to communicate neither conclusions judged to be necessary (contrary to the prediction of the standard modal logical view) nor conclusions judged to be highly probable (contrary to the prediction of recent analyses using probabilistic models) but conclusions whose truth they believe in (as predicted by the analysis of epistemic must as an inferential evidential). We suggest that this evidential meaning of epistemic must/dovere might have arisen in everyday conversation from a reiterated hyperbolic use of the words with their original meaning as epistemic necessity verbs.
IRS-assisted vehicular visible light communications systems: channel modeling and performance analysis
Authors: Rabiepoor Arash , Nezamalhosseini S. Alireza , Chen Lawrence R.
Published: November 2023

Visible light communications (VLC) is a promising solution as an alternative for the fully occupied radio frequency bands in the near future. The rear (tail) and front of vehicles have lamps that can be used for vehicular visible light communications (VVLC) systems. However, one of the main challenges of VLC systems is the line-of-sight (LoS) blockage issue. In this paper, we propose the installation of intelligent reflecting surfaces (IRSs) (i.e., smart mirrors) on the back of vehicles to overcome the issue in VVLC systems. We assume three different patterns of angular distribution for the radiation intensity: a commercially available LED with an asymmetrical pattern (Philips Luxeon Rebel), a symmetrical Lambertian pattern, and an asymmetrical Gaussian pattern. In the first section of this paper, we obtain the channel model for the IRS-assisted VVLC systems, then we investigate the path loss results versus link distance under different conditions such as weather type (clear, rainy, moderate fog, and thick fog) and radiation patterns. Moreover, the impact of system parameters such as the aperture size of the photodetector (PD), side-to-side and front-to-front distances, the number of IRS elements, and the IRS area are studied. In the second part, we derive a closed-form expression for the maximum achievable link distance versus the probability of error for the IRS-assisted VVLC systems. In addition, in this section we analyze the impact of the parameters in a single-photon avalanche diode (SPAD), background noise, and the system parameters for the path loss.
Carrier-frequency estimation for digital holograms of phase objects
Authors: Goyal Nishant , Khare Kedar
Published: November 2023

Accurate estimation of carrier fringe frequency is essential for the demodulation of off-axis digital holograms. The fringe frequency is often associated with the amplitude peak of the cross-term in the two-dimensional Fourier transform of a digital hologram. We point out that this definition of carrier frequency is not valid in general for holograms associated with phase objects. We examine the carrier-envelope representation for digital holograms from the viewpoint of Mandel’s criterion [J. Opt. Soc. Am. 57, 613 (1967)10.1364/JOSA.57.000613]. An appropriate definition of carrier frequency is observed to be the centroid of the power spectrum associated with the cross term. This definition is shown to apply uniformly to holograms associated with phase objects, is robust to noise, and leads to the smoothest (or least fluctuating) envelope representation for the demodulated object wave. The proposed definition is illustrated with simulated as well as experimentally recorded off-axis holograms.
Information-theoretic analyses of neural data to minimize the effect of researchers’ assumptions in predictive coding studies
Authors: Wollstadt Patricia , Rathbun Daniel L. , Usrey W. Martin , Bastos André Moraes , Lindner Michael , Priesemann Viola , Wibral Michael
Published: November 2023

Studies investigating neural information processing often implicitly ask both, which processing strategy out of several alternatives is used and how this strategy is implemented in neural dynamics. A prime example are studies on predictive coding. These often ask whether confirmed predictions about inputs or prediction errors between internal predictions and inputs are passed on in a hierarchical neural system—while at the same time looking for the neural correlates of coding for errors and predictions. If we do not know exactly what a neural system predicts at any given moment, this results in a circular analysis—as has been criticized correctly. To circumvent such circular analysis, we propose to express information processing strategies (such as predictive coding) by local information-theoretic quantities, such that they can be estimated directly from neural data. We demonstrate our approach by investigating two opposing accounts of predictive coding-like processing strategies, where we quantify the building blocks of predictive coding, namely predictability of inputs and transfer of information, by local active information storage and local transfer entropy. We define testable hypotheses on the relationship of both quantities, allowing us to identify which of the assumed strategies was used. We demonstrate our approach on spiking data collected from the retinogeniculate synapse of the cat (N = 16). Applying our local information dynamics framework, we are able to show that the synapse codes for predictable rather than surprising input. To support our findings, we estimate quantities applied in the partial information decomposition framework, which allow to differentiate whether the transferred information is primarily bottom-up sensory input or information transferred conditionally on the current state of the synapse. Supporting our local information-theoretic results, we find that the synapse preferentially transfers bottom-up information.
Improving the acceptability of social robots: Make them look different from humans
Authors: Nazir Tatjana A. , Lebrun Benjamin , Li Bing
Published: November 2023

The social robots market will grow considerably in the coming years. What the arrival of these new kind of social agents means for society, however, is largely unknown. Existing cases of robot abuse point to risks of introducing such artificial social agents (ASAs) without considerations about consequences (risks for the robots and the human witnesses to the abuse). We believe that humans react aggressively towards ASAs when they are enticed into establishing dominance hierarchies. This happens when there is a basis for skill comparison. We therefore presented pairs of robots on which we varied similarity and the degree of stimulatability of their mechanisms/functions with the human body (walking, jumping = simulatable; rolling, floating = non-simulatable). We asked which robot (i) resembled more a human, (ii) possessed more “essentialized human qualities” (e.g. creativity). To estimate social acceptability, participants had also (iii) to predict the outcome of a situation where a robot approached a group of humans. For robots with simulatable functions, rating of essentialized human qualities decreased as human resemblance decreased (jumper < walker). For robots with non-simulable functions, the reversed relation was seen: robots that least resembled humans (floater) scored highest in qualities. Critically, robot’s acceptability followed ratings of essentialized human qualities. Humans respond socially to certain morphological (physical aspects) and behavioral cues. Therefore, unless ASAs perfectly mimic humans, it is safer to provide them with mechanisms/functions that cannot be simulated with the human body.