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Objective To examine the efficacy and safety of aquatic exercise for people with knee osteoarthritis. Data sources PubMed, Web of Science, Embase, CENTRAL, CNKI and WanFang databases were searched from 1966 to September 2022. Review methods Randomized controlled trials evaluating aquatic exercise for people with knee osteoarthritis compared with no exercise and land-based exercise were included. The Grading of Recommendations Assessment, Development and Evaluation system was used to evaluate the certainty of evidence. Results Twenty-two studies with 1394 participants were included. Compared with no exercise (13 trials with 746 participants), low-to high-certainty evidence revealed that aquatic exercise yielded significant improvements in patient-reported pain (SMD −0.58, 95% CI −0.82 to −0.33), stiffness (SMD −0.57, 95% CI −1.03 to −0.11) and physical function (SMD −0.35, 95% CI −0.52 to −0.18) immediately postintervention. A sustained effect was observed only for pain at three months postintervention (SMD −0.48, 95% CI −0.91 to −0.06). The confidence intervals demonstrated that the pooled results do not exclude the minimal clinically important differences. There were no significant differences between the effects of aquatic exercise and land-based exercise (13 trials with 648 participants) on pain (SMD −0.12, 95% CI −0.29 to 0.04), stiffness (SMD −0.17, 95% CI −0.49 to 0.16) or physical function (SMD −0.13, 95% CI −0.28 to 0.02). No study reported a serious adverse event in relation to aquatic exercise. Conclusion Aquatic exercise provides a short-term clinical benefit that is sustained for at least three months postintervention in terms of pain in people with knee osteoarthritis.

BACKGROUND: Lower-extremity muscle strength and ankle flexibility play key roles in underwater swimming movements. OBJECTIVES: To investigate the relationship between knee isokinetic strength and the speed of underwater dolphin kicks (UDK-S) in competitive male swimmers and identify whether ankle flexibility affects the association between knee isokinetic strength and UDK-S. METHODS: Fifty-two highly trained male swimmers participated in this study. The speed at which the participants travelled 15 m performing UDKs was calculated as UDK-S. Knee flexor and extensor concentric isokinetic strength at fast (240∘/s) and slow (60∘/s) velocities and ankle flexibility were evaluated. Bayesian framework analysis was conducted to examine the relationship between these variables and determine whether this relationship is influenced by ankle flexibility. RESULTS: There was strong-to-extremely strong evidence (Bayes factor = 24.4 to 198.3) that knee extensor (60∘/s) and knee flexor (60∘/s and 240∘/s) strength are positively and generally moderately correlated with UDK-S. Ankle plantar flexion flexibility was identified to be a moderator between knee extensor strength (60∘/s) and UDK-S. CONCLUSIONS: Knee extensor and knee flexor strength were significantly correlated with UDK-S, and the relationship between knee muscle strength and UDK-S was influenced by ankle plantar flexion flexibility in male competitive swimmers.

A special layered structure helps to suppress the concentration quenching to achieve high dysprosium–thulium co-doping single-phase white light.

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.92 for predicting outcomes at 24 and 72 h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site’s data. For prediction of mechanical ventilation treatment or death at 24 h at the largest independent test site, EXAM achieved a sensitivity of 0.950 and specificity of 0.882. In this study, FL facilitated rapid data science collaboration without data exchange and generated a model that generalized across heterogeneous, unharmonized datasets for prediction of clinical outcomes in patients with COVID-19, setting the stage for the broader use of FL in healthcare. Federated learning, a method for training artificial intelligence algorithms that protects data privacy, was used to predict future oxygen requirements of symptomatic patients with COVID-19 using data from 20 different institutes across the globe.

To explore and evaluate the long-term effects of diverse online teaching methods to minimize the negative influences of online teaching of basic courses in clinical medicine during the COVID-19 pandemic. Forty-nine students in grade 2017 majoring in clinical medicine (five-year program) were enrolled in this study (study group). They received online teaching of six basic clinical courses, including diagnostics, basic clinical skills, general surgery, medical imaging, and doctor‒patient communication, from March to July 2020. The study first introduced the process of online teaching, especially basic clinical skills such as history taking, physical examination, internal punctures, electrocardiography and so on. Then, they reviewed the schedules to reinforce these skills when the students returned to school. The final exam scores of four clinical courses, including internal medicine, surgery, obstetrics and gynaecology, and paediatrics, and the scores of graduation examinations were used to evaluate the long-term effects of online teaching. These scores were compared with students in grade 2014 who learned through offline teaching (control group). After graduation examinations, questionnaires were distributed to understand the influence of online teaching on learning clinical courses, internships and postgraduate entrance examinations. The results showed that the scores of internal medicine part I and surgery part II in the study group were higher than those in the control group, and the differences were statistically significant (P < 0.05). Differences were not statistically significant in scores of internal medicine part II, surgery part I, obstetrics and gynaecology, and paediatrics between the two groups (P > 0.05). Two students postponed graduation in grade 2017, so 47 students took part in the graduation examination. The scores for knotting, dressing change, and cardiopulmonary resuscitation in the study group were significantly lower than those in the control group (P < 0.05). For the three items internal punctures, four-step palpation in obstetrics, and assessment of children's growth and development, the scores in the study group were higher than those in the control group, and the differences were statistically significant (P 0.05). All 47 participants in the study group completed the questionnaire survey, with a response rate of 100%. Twenty students thought that the online learning experience had a great influence on learning clinical courses such as internal medicine, surgery, obstetrics and gynaecology and paediatrics, whereas 27 students thought it had a slight influence. There were 23 students who thought online learning had a great influence and 24 students who thought it had a slight influence when attending the internship qualification examination. Thirteen students thought that the influence on the internship was great, 30 students thought it was slight, and 4 thought that online learning had no influence. Regarding which course had the most influence on the internship, 36 students thought it was diagnostics, 7 students thought it was general surgery, and 3 students thought it was other courses. Among the 40 students who participated in the entrance examination for a master's degree, 2 thought the online learning experience had a great influence, 19 thought it had a slight influence, and 11 students thought it had no influence. Among the six courses that influenced the re-examination for postgraduate students, 16 students thought the most influential course was diagnostics, 5 students chose general surgery, and 1 student thought it was another course. Exploration of diverse online teaching methods is helpful and successful for mastering clinical knowledge. However, online teaching had a great influence on some basic clinical skills that require more practice. The strategy used to reinforce these skills after returning to school makes up for the shortage of these practical skills in online courses to a certain extent.

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC)0.92 for predicting outcomes at 24 and 72 h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site's data. For prediction of mechanical ventilation treatment or death at 24 h at the largest independent test site, EXAM achieved a sensitivity of 0.950 and specificity of 0.882. In this study, FL facilitated rapid data science collaboration without data exchange and generated a model that generalized across heterogeneous, unharmonized datasets for prediction of clinical outcomes in patients with COVID-19, setting the stage for the broader use of FL in healthcare.

Liming Song,1,* Wenkuan Wang,2,* Qinxin Zhao,3,* Yuhong Wen,4 Xiaoguang Zhou,1 Hu Han,1 Xiaodong Zhang1 1Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Department of Urology, Beijing Haidian Hospital/Haidian Hospital of Beijing University Third Hospital, Beijing, People’s Republic of China; 3Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 4Department of Urology, Huhehaote First Hospital, Inner Mongolia, People’s Republic of China*These authors contributed equally to this workCorrespondence: Liming SongDepartment of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, People’s Republic of ChinaEmail bjslm2020@163.comBackground: The traditional surgical treatment for upper urinary tract urothelial carcinoma (UTUC) is time-consuming owing to changing the surgical position and larger surgical trauma because of open surgery in handling the distal ureter. Therefore, we created a new surgical technique of combination retroperitoneal with transperitoneal (CRT) laparoscopic nephroureterectomy (LNU) in a single position and here report our early outcomes.Methods: From January 2017 to December 2019, a total of 106 patients underwent LNU by a single surgeon at our department, of whom 50 patients underwent standard technique and 56 patients underwent CRT technique. Relevant clinical data were collected including each patient’s characteristics, surgical outcomes, and follow-up results. A comparative analysis between standard LNU cases and CRT LNU cases was performed.Results: LNU was performed successfully on all 106 patients. There was no significant difference in patients’ characteristics. Compared to the standard group, patients in the CRT group had shorter operative time (P=0.001), less estimated blood loss (EBL) (P< 0.001), lower visual analogue scale (VAS) pain score (P=0.020) and less scarring (P=0.013). The median time of surgical drain stay decreased from 5 to 2 days (P=0.004) and median hospital stay after surgery decreased from 5 to 3 days (P=0.001). The complication rates did not show statistical differences between the two groups within the first 30 days postoperatively (P=0.263). For the long-term complications, the incidence of abdomen bulge or incisional hernia in the CRT group was less than that in the standard group (P< 0.001).Conclusion: The CRT technique, which combines both the advantages of retroperitoneal and transperitoneal approaches, is a more minimally invasive, simplified and effective way to perform the LNU.Keywords: nephroureterectomy, laparoscopy, retroperitoneal, transperitoneal, single position

This research aimed to define the key factors in freestyle flip turns via a kinesiology analysis to diagnose swimmers. Hence, specially designed drills were created to improve swimmers’ flip-turn skills and assess the effects of training. Nine Chinese national modern pentathlon athletes ranging in age from 20 to 26 years with an average of 10 years of training experience were tested and trained in this study. The Kistler Performance Analysis System for Swimming was used for the pre- and post-test analyses. A kinesiology analysis of the data from the pre-test was used for the diagnosis and specific drills were adopted for 10 weeks, 3 times per week before the post-test. The comparison of the pre- and post-test performances was used to assess the effects of training. After 10 weeks of specific drill training for flip turns, participants’ turning skills significantly improved. Speed in approaching, somersaulting, pushing-off and gliding all increased. The angles of the knees and hips as well as the force applied improved, which contributed to swimmers’ increased speed. Since the skills needed for a flip turn are complex and not easily diagnosed via observation alone, this kinesiology analysis will make diagnosis objective and easy.

We outline an extension of Java for programming with distributed arrays. The basic programming style is Single Program Multiple Data (SPMD), but parallel arrays are provided as new language primitives. Further extensions include three distributed control constructs, the most important being a data-parallel loop construct. Communications involving distributed arrays are handled through a standard library of collective operations. Because the underlying programming model is SPMD programming, direct calls to MPI or other communication packages are also allowed in an HPJava program. © 1998 John Wiley & Sons, Ltd.

Traditional, software development was normally treated as an engineering process, which can be a lengthy and inflexible process. Recently, as the demand for software is increasing dramatically, new ways of developing software have been sought, among which developing software creatively is attracting attention. Media products are normally creatively developed and naturally learning how these products were developed can be a good starting point for applying creative techniques in software development. The proposed workshop activity plans to conduct an experiment to observe and then summarise the knowledge of creativity in media product development, in particular in the stage of requirements elicitation, taking movie making as an example, and then speculate how this knowledge can be applied to requirements elicitation and software development.

With the development of parallel processing technology, more and more high-performance parallel computer systems have been developed. The convenient and flexible parallel programming environment plays an important role in the spread of parallel computing. How to write efficient parallel codes and how to convert the existing sequential applications into parallel codes have become a very important issue in parallel processing. We introduce a parallel programming environment based on message passing, which is simple to develop parallel applications and has high performance.

In order to provide Java with the ability for supporting scientific parallel computing, we introduce a data parallel extension to Java language with runtime system support. We provide the distributed array extension to Java, and discuss the related operation and control over the new distributed array. Communication involving distributed arrays are handles through a standard of a collective communication library. We consider the programming in a Single Program Multiple Data (SPMD) model.

The NPAC kernel runtime, developed in the PCRC (Parallel Compiler Runtime Consortium) project, is a runtime library with special support for the High Performance Fortran data model. It provides array descriptors for a generalized class of HPF like distributed arrays, support for parallel access to their elements, and a rich library of collective communication and arithmetic operations for manipulating these arrays. The library has been successfully used as a component in experimental HPF translation systems. With prospects for early appearance of fully featured, efficient HPF compilers looking questionable, we discuss a class of more easily implementable data parallel language extensions that preserve many of the attractive features of HPF, while providing the programmer with direct access to runtime libraries such as the NPAC PCRC kernel.

As a relatively straightforward object-oriented language, Java is a plausible basis for a scientific parallel programming language. We outline a conservative set of language extensions to support this kind of programming. The programming style advocated is Single Program Multiple Data (SPMD), with parallel arrays added as language primitives. Communications involving distributed arrays are handled through a standard library of collective operations. Because the underlying programming model is SPMD programming, direct calls to other communication packages are also possible from this language.

This paper describes an ongoing effort supported by ARPA PCRC (Parallel Compiler Runtime Consortium) project. In particular, we discuess the design and implementation of an HPF compilation system based on PCRC runtime. The approaches to issues such as directive analysis and communication detection are discussed in detail. The discussion includes fragments of code generated by the compiler.