bluuebunny/crossref_metadata_2025 huggingface dataset:
Big Data Analysis and Digital Sharing Research on Innovation and Entrepreneurship Education in the Digital Economy Era
Authors: Yin Li , Zhang Weidong , Wang Zicheng , Zhou Mingxing
Published: October 2024

Within the rapidly evolving panorama of the virtual financial system, the function of training in fostering innovation and entrepreneurship has become more and more vital. This study aims to explore how big records analysis and digital sharing techniques can be leveraged to complement innovation and entrepreneurship schooling. The observation is grounded within the context of the virtual economy generation, characterised with the aid of the proliferation of virtual technologies and the exponential boom of facts. The middle objective is to research how instructional techniques can be more desirable thru the utility of large records analytics and digital sharing, thereby preparing college students extra effectively for entrepreneurial roles inside the digital age. The studies employ a deep learning technique, combining quantitative information evaluation with qualitative insights. Primary statistics could be accumulated through surveys and interviews with educators and marketers, even as secondary statistics will be sourced from existing educational literature and case research. The observe will awareness on key regions which includes the effect of huge facts on expertise marketplace developments and client conduct, the function of virtual sharing in fostering collaborative learning and innovation, and the integration of these technologies into curriculum design and pedagogical practices. Anticipated results include a set of recommendations for academic institutions on integrating large statistics and digital sharing tools into entrepreneurship training. The study targets to offer insights into how this technology can enhance college students’ analytical and innovative skills, put together them for the challenges of the digital economic system, and foster a tradition of innovation and entrepreneurial attitude.
A Big Data Intelligent Evaluation System for Sports Knowledge
Authors: Peng Gao
Published: October 2024

The rapid evolution of computer technology has significantly impacted the field of medicine, particularly in the utilization of information and image evidence. In the realm of sports medicine, this technological advancement plays a crucial role in ensuring sports safety, especially in the context of injury recovery following sports-related activities. The necessity to interpret and utilize a vast amount of sports medical data effectively has emerged as a pivotal research avenue. This paper delves into the challenges associated with extracting, studying, and the accuracy training of complex algorithms essential for analyzing critical sporting medical data.Central to this discussion is introducing an Optimized Convolutional Neural Network (OCNN) model, which is based on deep learning principles. This model is designed to enhance the detection and risk assessment of diseases related to sport medicine. It incorporates a novel Self-Adjustment Resizing algorithm (SAR), augmented by a self-coding method of convolution (SCM). The proposed OCNN model comprises two convolutional layers, two pooling layers, a fully connected layer, and a SoftMax structure. This architecture is tailored for the classification and analysis of sport-related medical data.
Algorithm Identification and Integrated with Push Service for Telemedicine System
Authors: Cai Yan-Ling , Li Xin-Yu , Kumar Kannan
Published: October 2024

Telemedicine systems, while overcoming physical space constraints, often lack personalized interactions. By incorporating a push service and leveraging prediction-oriented algorithms, these systems can offer an improved user experience. Such enhancements enable timely treatment options and reduce unnecessary resource usage in on-site outpatient clinics. This research work starts by creating a robust algorithm using data mining techniques. Next, it establishes the foundation for a telemedicine push service. The service includes essential modules for disease differentiation, doctor recommendations, and diagnosis predictions. To optimize these modules, a merged algorithm combining k-nearest neighbor classification, nearest neighbor recommendation, and FP-growth is needed. This work aims to enhance treatment options for patients and streamline resource usage in on-site outpatient clinics. Moreover, this work has carried out empirical research for identification of algorithm by using available data at a public Chinese telemedicine system. The results of data analysis show the follows: 1. For disease diagnosis, the KNN model (k=1) is more accurate but less efficient, SVM and LibSVM are more efficient but less accurate than the KNN model; 2. In terms of doctor recommendation, nearest neighbor recommendation performs better but is not as efficient as matrix factorization; 3. in diagnostic prediction, the combination of introducing association mining and data segmentation can play a better role. The developed algorithm and its conclusions from this study could make easier and more efficient to provide treatment options for undecided-condition patients.
A Human Resource Evaluation and Recommendation System based on Big Data Mining
Authors: Xing Xueli , Wen Qiushi
Published: October 2024

This investigation presents a paradigm-shifting Human Resource (HR) Assessment and Recommendation Framework, leveraging progressed huge information mining procedures. Drawing bits of knowledge from cybersecurity, healthcare, education, and further detecting spaces, our framework utilizes a different cluster of calculations, counting Arbitrary Forests, Support Vector Machines, K-Means Clustering, and a Feedforward Neural Organize. The comparative investigation uncovers the Feedforward Neural Network as the standout entertainer, emphasizing its various levels including learning for complicated design acknowledgement inside HR measurements. Uniquely, this framework draws on methodologies and insights from varied domains such as cybersecurity, healthcare, and education, applying these rich, interdisciplinary perspectives to HR analytics. This cross-pollination of ideas enables the framework to adopt sophisticated data mining and pattern recognition techniques that are not traditionally utilized within HR, offering new avenues for detecting and interpreting complex employee data patterns. Result values illustrate the system’s adequacy, with a precision of 88%, an accuracy of 90%, a review of 87%, and an F1 score of 88%. These measurements emphasize the system’s capacity to comprehensively assess worker execution, giving exact suggestions for key HR decision-making. Ethical contemplations, innovation acknowledgement, and custom-fitted proposal frameworks, propelled by related works, are coordinates to guarantee the system’s reasonability over assorted organizational settings. This research contributes to the advancing scene of HR administration, offering a spearheading arrangement for organizations looking for data-driven, comprehensive, and morally sound approaches to workforce optimization.
Film and Television Animation Production Technology Based on Expression Transfer and Virtual Digital Human
Authors: Zhang Ning , Pu Belei
Published: October 2024

The world of film and TV animation has witnessed a revolutionary transformation with the combination of Expression transfer and digital virtual Human technology. This paper delves into the superior methodologies and technological improvements in the discipline of animation production, especially specializing in how those technology are redefining the requirements and practices of animation in film and television. Expression transfer technology, a groundbreaking approach in animation, entails the transfer of facial expressions from real actors to lively characters. This technique not most effective enhances the realism of lively characters but additionally lets in for a extra nuanced and emotive performance, bridging the space among conventional animation and stay-action performances. Digital Human era, however, entails creating extraordinarily practical virtual representations of people. Those digital humans aren’t mere caricatures or stylized variations however are reasonable in appearance and movement, way to advancements in motion seize, 3-D modeling, and synthetic intelligence. The mixture of those technologies is main to a new technology in animation where characters aren’t only visually stunning however also exhibit a depth of emotion and realism previously unimaginable. This paper explores diverse case research and applications of these technology in current animation, highlighting their effect on storytelling, person improvement, and viewer engagement. It also addresses the demanding situations and moral considerations in employing these technologies, which includes retaining artistic integrity and the capacity for misuse. The research concludes with a forward-searching attitude on how Expression transfer and digital digital Human technologies are set to redefine the future of movie and television animation, presenting new opportunities for creative expression and narrative intensity.
Character-Level Embedding using FastText and LSTM for Biomedical Named Entity Recognition
Authors: Ahmed AL-Jumaili Ahmed Sabah , Tayyeh Huda Kadhim
Published: October 2024

Extracting biomedical entities has caught many researchers’ attention in which the recent technique of word embedding is employed for such a task. Yet, the traditional word embedding architectures of Word2vec or Glove are still suffering from the ‘out-of-vocabulary’ (OOV) problem. This problem occurs when an unseen term might be encountered during the testing which leads to absence of embedding vector. Hence, this study aims to propose a character-level embedding through FastText architecture. In fact, handling the character-level seems a promising solution for the OOV problem. To this end, the proposed FastText architecture has been used to generate embedding vectors for the possible N-gram combinations of each word. Consequentially, these vectors have been fed to a Long Short Term Memory (LSTM) architecture for classifying the words into its biomedical classes. Using two benchmark datasets of BioCreative-II and NCBI, the proposed method was able to produce an f-measure of 0.912 and 0.918 respectively. Comparing these results with the baseline studies demonstrates the superiority of the proposed character-level embedding of FastText in terms of Biomedical Named Entity Recognition (BNER) task.
Developing Model-Agnostic Meta-Learning Enabled Lightbgm Model Asthma Level Prediction in Smart Healthcare Modeling
Authors: Yadav Sudha , Sehrawat Harkesh , Jaglan Vivek , Singh Yudhvir , Dalal Surjeet , Le Dac-Nhuong
Published: October 2024

Millions of people across the world suffer from the chronic respiratory condition known as asthma. Predicting the severity of asthma based on a variety of personal and environmental characteristics might yield useful information for preventative measures. LightGBM model is a gradient-boosted model with the potential for great accuracy, but it requires careful hyperparameter adjustment to reach its full potential. Common tuning techniques have a hard time generalizing to new data distributions. The dataset was used, and its many subsets were used to represent various demographics and geographic areas. LightGBM was configured with hyperparameters, trained on a sample dataset, and then verified for each job. To quickly adjust to new tasks, the MAML method sought to find the optimal values for its hyperparameters. After the meta-training step was complete, the generalizability of the hyperparameters was tested on new data. After including MAML for hyperparameter adjustment, the Light- GBM model showed a gain of 7% in accuracy, coming in at 98.5%. Predictions of severe asthma had a crucially high 97.8 percent degree of accuracy. The model’s recall rate for severe asthma levels was 97.4%, demonstrating its capacity to reliably detect and anticipate important instances. An F1-score of 97.1%, a metric that averages the accuracy and recall of a model, is indicative of good overall performance.. For gradient-boosted model applications like asthma level prediction, MAML provides a viable path for hyperparameter adjustment. Although there are obstacles to be overcome, this method has the potential to greatly improve the flexibility and precision of predictive healthcare models. More effective implementations and a wider range of applications can be explored in future studies.
An Internet of Things Task Scheduling Framework Based on Agile Virtual Network on Demand Service Model
Authors: Liu Qiqun
Published: October 2024

In order to improve the efficiency of cloud computing resource utilization and avoid the problem of computing resource allocation and scheduling lagging behind load changes, the author proposes a cloud computing resource on-demand allocation and elastic scheduling method based on network load prediction. Firstly, the author takes the network load data of Wikimedia as the research object and proposes an adaptive two-stage multi network model load prediction method based on LSTM, i.e. ATSMNN-LSTM load prediction method). This method can classify the network load data into climbing and descending types based on the trend and characteristics of the input network load data, And adaptively schedule the input network load data to the LSTM load prediction model that matches its type for prediction based on the classification results. The author proposes a maximum cloud service revenue computing resource quantity search algorithm based on network load prediction (i.e. MaxCSPRNWP algorithm), which aims to improve cloud service revenue as the optimization objective. Under the premise of ensuring task service quality and system stability, the algorithm allocates cloud computing resources on demand and flexibly schedules them in advance based on the predicted network load results. The experimental results show that the ATSMNNLSTM load prediction method proposed by the author can obtain more accurate network load prediction results compared to other load prediction methods, and the MaxCSPR-NWP algorithm, which is based on network load prediction and is capable of effectively converting the network load prediction results into the required number of cloud servers, is the maximum cloud service revenue computing resource quantity search algorithm proposed by the author, not only does it achieve the early allocation and scheduling of cloud computing resources, thereby avoiding the impact of lagging behind in computing resource allocation and scheduling due to load changes on the quality of cloud computing task services and resource utilization efficiency, at the same time, it has also achieved on-demand allocation and flexible scheduling of cloud computing resources with the goal of improving cloud service revenue.
An Efficient Cryptographic Scheme based on Optimized Watermarking Scheme for Securing Internet of Things
Authors: Vidwans Abhinav , Ramiya Manoj
Published: October 2024

In this work, a new efficient cryptographic scheme based on the concept of chaotic map and optimized watermarking scheme is proposed. In the optimized watermarking scheme, a combination of discrete wave transformation (DWT), hessenberg decomposition (HD), and singular value decomposition (SVD) are used. In this, the host image is first broken down into several sub-bands using multi-level DWT, and the resulting coefficients are then fed into HD during the embedding phase. Simultaneous watermark operation is performed on SVD. Finally, the scale factor embeds the watermark into the host image. The Differential evolution method is used to find the best scaling factor for the optimized watermarking scheme. The resulting watermarked image is then encrypted by the session key based scheme. In this scheme for each image encryption, a new random session key will be produced. The presented approach uses 64-bit plaintext and a variable size key that will be decided at the time of encryption for encrypting an image. Since session keys change with each transmission, this approach does not involve extracting and remembering session keys in order to produce subsequent session keys. IoT devices are used to test the developed method for security. The experiment’s findings shows that the suggested method works better than the current scheme in several aspects.
A Student Education Data Mining Method based on Student Sequential Behaviors and Hybrid Recurrent Neural Network
Authors: Luo Wei , Wang Qi
Published: October 2024

This research aims to propose a student education data mining method based on a hybrid recurrent neural network and improved support vector machine-decision tree algorithm through in-depth analysis of student behavior sequences. The method combines the feature extraction capability of a hybrid recurrent neural network and the nonlinear mining efficiency of support vector machine-decision tree algorithm to achieve efficient prediction of students’ learning behavior and performance. Experimental results have shown that the designed method completed an APA of 91.3% and 89.2% for the HR-SDT model on the Student_1 and Student_2 datasets, respectively. The F1 score average values of the HR-SDT model reached 86.7% and 81.9%, respectively. The results indicate that the student behavior data mining method based on hybrid recurrent neural networks can accurately predict the learning behavior and performance of students, providing valuable insights and decision support for educators.
Feature Enhancement Based Joint Extraction of Web Novel Entity Relationships
Authors: Li Ailin , Wei Bin , Liu Weihua
Published: October 2024

In an era characterized by constant advancements in computer science, web novels represent an extensive and intricate form of text that presents unique challenges for automated processing. This investigation aims to address the issues associated with the time-intensive, laborious, and error-prone nature of text processing within web novels. It presents a novel joint entity-relationship extraction model that is enhanced by various features. By leveraging a combination of computer vision and natural language processing techniques, the extraction of named entities and relationships is modeled in a unified framework to optimize text feature mining. The employment of bidirectional long-short term memory networks and multi-layer perceptron equips the model with the capability to effectively extract entity relationships from web novels comprehensively. Experimental outcomes indicate that the model achieves an F1 score of 72.4%, marking a notable enhancement over traditional pipelined models. This study offers robust tools and methodologies for computers to process extensive and complex textual data, further integrates computer vision with natural language processing, and broadens the potential applications within the domain of information processing.
Information Technology Support for Athlete Health Monitoring and Medical Diagnosis
Authors: Su Jing
Published: October 2024

The paper uses WSN to monitor athletes’ medical diagnosis information remotely. The aim is to strengthen the monitoring and management of athletes’ medical diagnosis data. The method of wireless sensor node and IPv6 routing based on IPv6 is proposed. The terminal-to-terminal network structure based on IP can carry long-distance transmission and share athlete medical diagnosis information. The monitoring system’s bottom structure design is realized using Contiki technology. At the same time, it also realizes the data acquisition and management in the monitoring system. The component interface is designed based on TinyOS. The design of the wireless client based on GPSR is completed based on GPSR. This paper uses the VanetMobiSim platform to complete a remote monitoring system’s software development and simulation test based on wireless medical diagnosis information. The results show that this system’s medical diagnosis information covers a wide range, and the information search efficiency is high.
Risks and Opportunities of Digitalization of Accounting and Control Processes in Small Businesses
Authors: Kalpakchi N.
Published: October 2024

The article presents the identification of risks of digitalization of accounting and control processes in small business entities. The study of the consequences of the occurrence of data security risks when using digital tools, as well as a comparative analysis of the risks of digitalization of accounting and control processes in small and large enterprises allowed us to develop proposals to minimize the risks of data security in small businesses when digitalizing their accounting and control processes.
Information technologies in professional activity: data mining and business analytics
Authors: Nazarov Dmitriy , Kopnin Anton
Published: October 2024

The textbook offers a comprehensive look covering a wide range of topics related to the role of information technology in the modern world. Starting with an overview of the history of information technology and its evolution, the book introduces the reader to professions in the field of information and digital technologies, emphasizing them in various professional fields. The content of the textbook includes a detailed analysis of key concepts such as Data Science, Data Mining and Machine Learning, and their role in healthcare, law, education, science and business. The textbook provides a detailed overview of Data Science methods and algorithms, including teaching methods with and without a teacher, as well as specific methods such as Dematel. In the section on business intelligence tools, special attention is paid to Yandex Cloud DataLens, its data analysis functionality, and practical recommendations on registration, the use of intelligent detection of patterns in data, visualization and the development of analytical panels are provided. The section of the textbook devoted to the R and Python programming languages contains recommendations on the use of the R and Python programming languages for statistical data analysis, a description of the main data types, operations, and specific algorithms used for analytical purposes. This section provides a quick guide on how to use the RStudio and PyCharm tools. The final section is devoted to the application of data analysis tools in real projects, providing the reader with the opportunity to immerse themselves in the world of data processing using advanced technologies and techniques. The presentation of the material of each chapter is accompanied by control questions and tests to consolidate the theoretical material, located at the end of the chapter. This textbook will be an indispensable resource for students, professionals and researchers who want to deeply understand and apply information and digital technologies in their professional activities.
The Development of the Life Insurance Market in Central and Eastern European Countries
Authors: Laskowska Iwona
Published: October 2024

Motivation: The need to implement the process of economic transformation in the recent past is what significantly differentiates the countries of Central and Eastern Europe from other members of the European Union. Integration into the financial system of the European Union has been an important factor influencing the process of transformation of the life insurance sector and the establishment of the level of competition, as well as the quality and scope of insurance services offered. In addition, the improvement in the macroeconomic situation and the increase in household income have had a significant impact on the growth in demand for insurance products from the life insurance segment. Despite positive changes, the insurance market of Central and Eastern European countries remains a relatively underdeveloped market, and its structure, unlike that of Western European countries, is dominated by property insurance. This points towards a need for further research into the determinants of life insurance market growth in this region of Europe.
Aim: The aim of this paper is twofold. The first  part presents an assessment of the level of development of the life insurance market in ten countries of Central and Eastern Europe over the period 2011-2021 using the method of multivariate comparative analysis in dynamic terms. The second  part of the paper is devoted to an attempt to identify the determinants of the development of this market using econometric models for panel data. 
Results: The life insurance market varies widely among the group of countries considered. The trends of change during the period under consideration were also different. The most severe downturn in the life insurance market was recorded in Poland and the Czech Republic. Significant development was observed in Lithuania and Latvia, countries with an underdeveloped market in the past. The econometric models used confirmed the impact of economic development on the life insurance market.
Wartime Management of the Government of National Defense Headed by Wincenty Witos during the Polish-Bolshevik War of 1920
Authors: Podgajna Ewelina
Published: October 2024

Wincenty Witos is one of the undisputed Fathers of Independence of Poland, reborn in November 1918 after 123 years of partition. An outstanding statesman, leader of the people’s movement. Three-time Prime Minister of the Polish government in 1920–1921, 1923, 1926. During the Polish-Soviet War, Witos headed the Government of National Defense, which lasted 433 days, including 254 during the war. When analyzing his management as Prime Minister, two stages should be distinguished. In the first one, he was absorbed in matters of war. He was in favor of concluding peace as soon as possible, which he expressed in his exposé in 1920. In his second exposé, he worked on the reconstruction of the country after the war and the further development of the Republic of Poland as a democratic state. During the war, Witos’s role in mobilizing peasants to participate in the defense of threatened borders, as well as defending independence in the war with Bolshevik Russia in 1920, was particularly important. The article discusses the decisions made regarding management during the war: mobilizing society to rally around the authorities of the reborn Poland and defend the country’s independence, to reject Bolshevik propaganda and fight for the future of the Polish nation and state. The practice of war management was manifested in frequent field trips, organizing support and supplies for the population. Witos paid particular attention to the Borderlands. He emphasized that the presence of the head of the government and this direct contact made it possible to learn about many difficult problems of the reborn state, and at the same time, direct contact with the authorities was an element that bound the population to this state, and the people did not feel alone in solving these problems.
(Dossier Colin Rowe) Notas para una biografía intelectual de Colin Rowe (1938-78).
Authors: Grahame Shane David
Published: October 2024

This article draws on Colin Rowe’s experience as a paratrooper during the war as a metaphor for his ability to cope with diverse and complex circumstances. It highlights different periods of his life, from his peripatetic trajectory (1938-78) to his time at various institutions and the culmination of his 40-year career. Rowe navigated professional changes thanks to three stabilizing codes: a neoclassical classicism influenced by Wittkower, a modernism with utopian ideals influenced by Le Corbusier, and a third imaginary space that allowed for new cultural interpretations. These codes were reflected in his urban projects in Texas, Cornell, and Cambridge. Throughout his career, Rowe adopted and adapted these codes, reflecting his initial rejection of the Georgian city, his commitment to modern utopia, and his eventual rediscovery of the neoclassical city. Rowe’s work, including his meta-city Roma Interrotta, illustrates his ability to integrate the modern and the classical in an urban context, using a metahistorical approach that anticipates the transformation of cities into spaces of recombinant information and memory. The exhibition of Roma Interrotta at the Trajan Market in 1978 and its recreation at the MAXXI Museum in 2014 underscore his vision of the city as a museum and a space of memory. This perspective translates into an architecture that not only responds to contemporary needs but also dialogues with history, showcasing Rowe’s ability to create urban spaces rich in meaning and potential, a timeless hybrid that connects the personal and the collective.
Obstruction, Denialism, and Criticism of Climate Change in Brazil
Authors: Losekann Cristiana
Published: October 2024

Brazil’s non-state debate on climate change is complex. The entry of the climate frame is relatively recent and comes into contexts in which there were already strong actors discussing environmental issues from other frames. In this sense, not all consolidated actors in the environmental movement fully adhere to this agenda. On the other hand, the strengthening of right-wing movements strongly linked to anti-scientific and anti-environmentalist perspectives constitute fronts that oppose the climate change agenda and the idea of global warming as a real environmental problem. In addition, there are traditional political forces linked to specific economic interests that, although not located in right-wing movements, create concrete obstacles to advancing environmental agendas. These different forces put tension in the debate about climate change in Brazil today and constitute significant obstacles for those who seek to produce a severe critical debate regarding which climate policies would be necessary because of the regional context.Therefore, we present three tendencies of antagonism to the climate debate: climate obstruction, climate denialism, and environmental criticism. The objective is to understand how the first two movements harm the construction of environmentalist criticism.
Análise da Velocidade Operacional dos Ônibus durante os Jogos Olímpicos e Paraolímpicos Rio 2016 baseados em dados de GPS
Authors: Rojas Alexandre , Lanzilloti Regina Serrão
Published: October 2024

A velocidade operacional dos ônibus urbanos é fator chave na mobilidade urbana. A monitoração desta foi realizada a partir dos dados gerados pelo GPS. Objetiva-se analisar o padrão da velocidade operacional na cidade do Rio de janeiro em quatro vias antes e durante a realização dos Jogos Olímpicos Rio-2016. O tratamento estatístico foi realizado para verificar se há diversidade nos corredores, tanto na via expressa quanto na via convencional. Os registros correspondem a tres periodos: quandoparte das obras viárias estavam em andamento (06/2015), durante a Pré-olimpíada(06/2016) e Olimpíada e Encerramento(08/2016). O resultado mostrou que o legado dos Jogos Olímpicos propiciou a facilitação do ir e vir, sobretudo nos horários de prováveis picos de tráfego e retenções.
Algo+naEscola, Ambiente para Apoio ao Ensino de Programação
Authors: Gouvea Natalia do V. , Castro Maria Clicia Stelling de , Werneck Vera M. B.
Published: October 2024

Este artigo define o ambiente Algo+naEscola que fornece ao professor, um auxílio ao uso da lógica computacional através de jogos na sala de aula. Os requisitos desse ambiente foram propostos através de um experimento do ensino de Matemática utilizando algoritmos e jogos. A ideia do trabalho de campo foi, de maneira interdisciplinar, desenvolver o ensino de ângulos através do uso de algoritmos e programação de computadores. Esse experimento foi desenvolvido durante aulas de Matemática com alunos do ensino Fundamental II, sendo a base para construção do ambiente Algo+naEscola.
Staged revision of the infected knee arthroplasty and endoprosthesis
Authors: Lodge Christopher J. , Adlan Amirul , Nandra Rajpal S. , Kaur Jasprit , Jeys Lee , Stevenson Jonathan D.
Published: October 2024

Aims

Periprosthetic joint infection (PJI) is a challenging complication of any arthroplasty procedure. We reviewed our use of static antibiotic-loaded cement spacers (ABLCSs) for staged management of PJI where segmental bone loss, ligamentous instability, or soft-tissue defects necessitate a static construct. We reviewed factors contributing to their failure and techniques to avoid these complications when using ABLCSs in this context.

Methods

A retrospective analysis was conducted of 94 patients undergoing first-stage revision of an infected knee prosthesis between September 2007 and January 2020 at a single institution. Radiographs and clinical records were used to assess and classify the incidence and causes of static spacer failure. Of the 94 cases, there were 19 primary total knee arthroplasties (TKAs), ten revision TKAs (varus-valgus constraint), 20 hinged TKAs, one arthrodesis (nail), one failed spacer (performed elsewhere), 21 distal femoral endoprosthetic arthroplasties, and 22 proximal tibial arthroplasties.

Results

A total of 35/94 patients (37.2%) had spacer-related complications, of which 26/35 complications (74.3%) were because of mechanical failure of the spacer construct, while 9/35 (25.7%) were due to recurrence of infection. Risk factors for internal failure were a construct where the total intramedullary spacer length was less than twice the length of the central osseous defect (p = 0.009), where proximal or distal intraosseous spacer contact was < 10%, and after tibial tubercle osteotomy (p = 0.005). The incidence of spacer complications significantly increased the time to second stage: mean 157 days (42 to 458) in those without complications versus 227 days (11 to 528) with complications (p = 0.014).

Conclusion

The failure rate of static antibiotic-loaded cement spacers is much higher than anticipated. Complications of the spacer significantly increased the time to second-stage revision. The risk of mechanical failure is significantly increased if the spacer is less than double the size of the segmental defect, or if inadequate reinforcement is inserted into the residual bone. These findings serve as a guide for surgeons to avoid mechanical complications with static spacers.

Cite this article: Bone Joint J 2024;106-B(10):1067–1073.
Estimation of two-year hospital costs of hip and knee periprosthetic joint infection treatments using activity-based costing
Authors: Hammat Aaron S. , Nelson Renjy , Davis Joshua S. , Manning Laurens , Campbell David , Solomon Lucian B. , Gnanamanickam Emmanuel S. , Callary Stuart A.
Published: October 2024

Aims

Our aim was to estimate the total costs of all hospitalizations for treating periprosthetic joint infection (PJI) by main management strategy within 24 months post-diagnosis using activity-based costing. Additionally, we investigated the influence of individual PJI treatment pathways on hospital costs within the first 24 months.

Methods

Using admission and procedure data from a prospective observational cohort in Australia and New Zealand, Australian Refined Diagnosis Related Groups were assigned to each admitted patient episode of care for activity-based costing estimates of 273 hip PJI patients and 377 knee PJI patients. Costs were aggregated at 24 months post-diagnosis, and are presented in Australian dollars.

Results

The mean cost per hip and knee PJI patient was $64,585 (SD $53,550). Single-stage revision mean costs were $67,029 (SD $47,116) and $80,063 (SD $42,438) for hip and knee, respectively. Two-stage revision costs were $113,226 (SD $66,724) and $122,425 (SD $60,874) for hip and knee, respectively. Debridement, antibiotics, and implant retention in hips and knees mean costs were $53,537 (SD$ 39,342) and $48,463 (SD $33,179), respectively. Suppressive antibiotic therapy without surgical management mean costs were $20,296 (SD $8,875) for hip patients and $16,481 (SD $6,712) for knee patients. Hip patients had 16 different treatment pathways and knee patients had 18 treatment pathways. Additional treatment, episodes of care, and length of stay contributed to substantially increased costs up to a maximum of $369,948.

Conclusion

Treating PJI incurs a substantial cost burden, which is substantially influenced by management strategy. With an annual PJI incidence of 3,900, the cost burden would be in excess of $250 million to the Australian healthcare system. Treatment pathways with additional surgery, more episodes of care, and a longer length of stay substantially increase the associated hospital costs. Prospectively monitoring individual patient treatment pathways beyond initial management is important when quantifying PJI treatment cost. Our study highlights the importance of optimizing initial surgical treatment, and informs treating hospitals of the resources required to provide care for PJI patients.

Cite this article: Bone Joint J 2024;106-B(10):1084–1092.
Ultrasound-guided infiltration with hyaluronic acid compared with corticosteroid for the treatment of Morton’s neuroma
Authors: Ferreira Gabriel F. , Lewis Thomas L. , Fernandes Tifani D. , Pedroso João P. , Arliani Gustavo G. , Ray Robbie , Patriarcha Vitor A. , Filho Miguel V.
Published: October 2024

Aims

A local injection may be used as an early option in the treatment of Morton’s neuroma, and can be performed using various medications. The aim of this study was to compare the effects of injections of hyaluronic acid compared with corticosteroid in the treatment of this condition.

Methods

A total of 91 patients were assessed for this trial, of whom 45 were subsequently included and randomized into two groups. One patient was lost to follow-up, leaving 22 patients (24 feet) in each group. The patients in the hyaluronic acid group were treated with three ultrasound-guided injections (one per week) of hyaluronic acid (Osteonil Plus). Those in the corticosteroid group were treated with three ultrasound-guided injections (also one per week) of triamcinolone (Triancil). The patients were evaluated before treatment and at one, three, six, and 12 months after treatment. The primary outcome measure was the visual analogue scale for pain (VAS). Secondary outcome measures included the American Orthopaedic Foot and Ankle Society (AOFAS) score, and complications.

Results

Both groups showed significant improvement in VAS and AOFAS scores (p < 0.05) after 12 months. The corticosteroid group had a significantly greater reduction in VAS and increase in AOFAS scores compared with the hyaluronic acid group, at one, three, and six months, but with no significant difference at 12 months. There were no complications in the hyaluronic acid group. There were minor local complications in six patients (six feet) (25.0%) in the corticosteroid group, all with discolouration of the skin at the site of the injection. These minor complications might have been due to the three weekly injections of a relatively high dose of corticosteroid. No patient subsequently underwent excision of the neuroma.

Conclusion

An ultrasound-guided corticosteroid injection showed statistically significantly better functional and pain outcomes than an ultrasound-guided injection of hyaluronic acid for the treatment of a Morton’s neuroma at many timepoints. Thus, a corticosteroid injection should be regarded as a primary option in the treatment of these patients, and the only indication for an injection of hyaluronic acid might be in patients in whom corticosteroid is contraindicated.

Cite this article: Bone Joint J 2024;106-B(10):1093–1099.
Factors associated with the choice of treatment for coronoid fractures
Authors: de Klerk Huub H. , Verweij Lukas P. E. , Doornberg Job N. , Jaarsma Ruurd L. , Murase Tsuyoshi , Chen Neal C. , van den Bekerom Michel P. J.
Published: October 2024

Aims

This study aimed to gather insights from elbow experts using the Delphi method to evaluate the influence of patient characteristics and fracture morphology on the choice between operative and nonoperative treatment for coronoid fractures.

Methods

A three-round electronic (e-)modified Delphi survey study was performed between March and December 2023. A total of 55 elbow surgeons from Asia, Australia, Europe, and North America participated, with 48 completing all questionnaires (87%). The panellists evaluated the factors identified as important in literature for treatment decision-making, using a Likert scale ranging from "strongly influences me to recommend nonoperative treatment" (1) to "strongly influences me to recommend operative treatment" (5). Factors achieving Likert scores ≤ 2.0 or ≥ 4.0 were deemed influential for treatment recommendation. Stable consensus is defined as an agreement of ≥ 80% in the second and third rounds.

Results

Of 68 factors considered important in the literature for treatment choice for coronoid fractures, 18 achieved a stable consensus to be influential. Influential factors with stable consensus that advocate for operative treatment were being a professional athlete, playing overhead sports, a history of subjective dislocation or subluxation during trauma, open fracture, crepitation with range of movement, > 2 mm opening during varus stress on radiological imaging, and having an anteromedial facet or basal coronoid fracture (O’Driscoll type 2 or 3). An anterolateral coronoid tip fracture ≤ 2 mm was the only influential factor with a stable consensus that advocates for nonoperative treatment. Most disagreement existed regarding the treatment for the terrible triad injury with an anterolateral coronoid tip fracture fragment ≤ 2 mm (O’Driscoll type 1 subtype 1).

Conclusion

This study gives insights into areas of consensus among surveyed elbow surgeons in choosing between operative and nonoperative management of coronoid fractures. These findings should be used in conjunction with previous patient cohort studies when discussing treatment options with patients.

Cite this article: Bone Joint J 2024;106-B(10):1150–1157.
The impact of closed suction wound drainage on chronic pain and health-related quality of life after posterior spinal fusion in patients with adolescent idiopathic scoliosis
Authors: Helenius Linda , Gerdhem Paul , Ahonen Matti , Syvänen Johanna , Jalkanen Jenni , Nietosvaara Yrjänä , Helenius Ilkka
Published: October 2024

Aims

Closed suction subfascial drainage is widely used after instrumented posterior spinal fusion in patients with a spinal deformity. The aim of this study was to determine the effect of this wound drainage on the outcomes in patients with adolescent idiopathic scoliosis (AIS). This was a further analysis of a randomized, multicentre clinical trial reporting on patients after posterior spinal fusion using segmental pedicle screw instrumentation. In this study the incidence of deep surgical site infection (SSI) and chronic postoperative pain at two years’ follow-up are reported.

Methods

We conducted a randomized, multicentre clinical trial on adolescents undergoing posterior spinal fusion for AIS using segmental pedicle screw instrumentation. A total of 90 consecutive patients were randomized into a ‘drain’ or ‘no drain’ group at the time of wound closure, using the sealed envelope technique (1:1). The primary outcomes in the initial study were the change in the level of haemoglobin in the blood postoperatively and total blood loss. A secondary outcome was the opioid consumption immediately after surgery. The aim of this further study was to report the rate of deep SSI and persistent postoperative pain, at two years' follow-up.

Results

As previously reported, the mean 48-hour opioid consumption was significantly higher in the no drain group (2.0 mg/kg (SD 0.8) vs 1.4 mg/kg (SD 0.7); p = 0.005). There were no delayed deep SSIs. At two years’ follow-up, the mean Scoliosis Research Society 24-item questionnaire (SRS-24) total score did not differ between the groups (4.11 (SD 0.47) vs 4.16 (SD 0.33); p = 0.910). The mean SRS-24 pain score was 4.28 (SD 0.48) in the no drain group compared with 4.33 (SD 0.66) in the drain group (p = 0.245). Seven patients (19%) in the no drain group and six in the drain group (14%) reported moderate to severe pain (numerical rating scale ≥ 4) at two years’ follow-up (p = 0.484). The general self-image domain score was significantly higher in the no drain group compared with the drain group (4.02 (SD 0.74) vs 4.59 (SD 0.54); p < 0.001).

Conclusion

The main finding in this study was that more severe pain immediately after surgery did not result in a higher incidence of chronic pain in the no drain group compared with the drain group. Back pain and health-related quality of life at two years’ follow-up did not differ between the groups. The patient-reported self-image domain was significantly better in the no drain group compared with the drain group.

Cite this article: Bone Joint J 2024;106-B(10):1176–1181.
The management of idiopathic toe walking
Authors: Gelfer Yael , McNee Anne E. , Harris Jennifer D. , Mavrotas Jason , Deriu Laura , Cashman John , Wright Jonathan , Kothari Alpesh
Published: October 2024

Aims

The aim of this study was to gain a consensus for best practice of the assessment and management of children with idiopathic toe walking (ITW) in order to provide a benchmark for practitioners and guide the best consistent care.

Methods

An established Delphi approach with predetermined steps and degree of agreement based on a standardized protocol was used to determine consensus. The steering group members and Delphi survey participants included members from the British Society of Children’s Orthopaedic Surgery (BSCOS) and the Association of Paediatric Chartered Physiotherapists (APCP). The statements included definition, assessment, treatment indications, nonoperative and operative interventions, and outcomes. Descriptive statistics were used for analysis of the Delphi survey results. The AGREE checklist was followed for reporting the results.

Results

A total of 227 participants (54% APCP and 46% BSCOS members) completed the first round, and 222 participants (98%) completed the second round. Out of 54 proposed statements included in the first round Delphi, 17 reached ‘consensus in’, no statements reached ‘consensus out’, and 37 reached ‘no consensus’. These 37 statements were then discussed, reworded, amalgamated, or deleted before the second round Delphi of 29 statements. A total of 12 statements reached ‘consensus in’, four ‘consensus out’, and 13 ‘no consensus’. In the final consensus meeting, 13 statements were voted upon. Five were accepted, resulting in a total of 31 approved statements.

Conclusion

In the aspects of practice where sufficient evidence is not available, a consensus statement can provide a strong body of opinion that acts as a benchmark for excellence in clinical care. This statement can assist clinicians managing children with ITW to ensure consistent and reliable practice, and reduce geographical variability in practice and outcomes. It will enable those treating ITW to share the published consensus document with both carers and patient groups.

Cite this article: Bone Joint J 2024;106-B(10):1190–1196.
Development and Simulation of 26 GHz Beamforming Systems and Antenna Array 5G Network Base Stations
Authors: Alazzawi Abd Al Menam A. , Rahim Mohamad Kamal A. , Ayop Osman
Published: October 2024

This paper focuses on designing a new structure of beamforming networks with an array antenna to control the beams. The 3×4 array antenna structure connects to the 3×3 Rotman lens beamformers to achieve this goal. The middle time delay line is around 14 mm. The design allows the x-axis to cover +25, 0, −25 degrees. Therefore, this work targets fifth generation (5G) application, which necessitates coverage in all directions by other base stations or users. Computer Simulation Technology (CST) microwave software facilitates the simulation process. The design begins with a single microstrip patch antenna, designed to function as an array antenna resonating at 26 GHz. The half-lambda separation (λ/2) among antennas gives 13.8 dBi gain with S11<−10 dB. The final structure for beamforming networks has a gain of 14 dBi. This work uses the Roger 5880 substrate, which has a dielectric constant of 2.2, a loss tangent of 0.0009, and a thickness of 0.127 mm.