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BACKGROUND: Early complications after arthroplasty for geriatric femoral neck fractures are known to negatively affect postoperative recovery and increase postoperative mortality. Identifying risk factors associated with early complications after arthroplasty may offer an opportunity to address and prevent these complications in many patients. OBJECTIVE: To evaluate preoperative risk factors for early complications after arthroplasty in elderly patients with a femoral neck fracture. METHODS: 119 elderly patients with femoral neck fractures who had been treated with arthroplasty (hemiarthroplasty or total hip arthroplasty) between December 2015 and December 2018 were retrospectively analysed. Early complications were defined as any complications that did not exist preoperatively, and occurred during hospital stay after arthroplasty Preoperative clinical, epidemiological and laboratory data were collected. Binary univariable and multivariable logistic regression analysis were applied to identify predictors of early complications after arthroplasty for geriatric femoral neck fractures. RESULTS: Median age of all patients was 80.0 (IQR 74.0–84.0) years. We identified 28 (23.5%) early complications after arthroplasty. Univariable logistic regression analysis found that preoperative body mass index (BMI p= 0.031), C-reactive protein (CRP p= 0.017) and serum Albumin (p= 0.006) were potential risk factors for early complications. Then preoperative BMI, CRP and serum Albumin were stratified and used for multivariable logistic regression analysis The multivariate logistic regression analysis showed that preoperative higher BMI (⩾ 28 kg/m2; OR 10.440; 95% CI 2.674–41.170; p= 0.001) and lower serum Albumin (⩽ 35 g/L; OR 3.933; 95% CI 1.509–10.800; p= 0.006) were independent risk factors for early complications after arthroplasty in geriatric femoral neck fractures. However, preoperative higher CRP levels (> 10 mg/L; OR 1.139; 95% CI 1034–1428; p= 0.833) was found to be not an independent risk factor for early complications. CONCLUSION: Our results demonstrate that obesity and hypoalbuminemia are independent predictors for early complications during hospital stay after arthroplasty, which should be meticulously noted to minimize these risk factors in geriatric femoral neck fractures.

Aim Diabetes health economic (HE) models play important roles in decision making. For most HE models of diabetes 2 diabetes (T2D), the core model concerns the prediction of complications. However, reviews of HE models pay little attention to the incorporation of prediction models. The objective of the current review is to investigate how prediction models have been incorporated into HE models of T2D and to identify challenges and possible solutions. Methods PubMed, Web of Science, Embase, and Cochrane were searched from January 1, 1997, to November 15, 2022, to identify published HE models for T2D. All models that participated in The Mount Hood Diabetes Simulation Modeling Database or previous challenges were manually searched. Data extraction was performed by two independent authors. Characteristics of HE models, their underlying prediction models, and methods of incorporating prediction models were investigated. Results The scoping review identified 34 HE models, including a continuous-time object-oriented model (n = 1), discrete-time state transition models (n = 18), and discrete-time discrete event simulation models (n = 15). Published prediction models were often applied to simulate complication risks, such as the UKPDS (n = 20), Framingham (n = 7), BRAVO (n = 2), NDR (n = 2), and RECODe (n = 2). Four methods were identified to combine interdependent prediction models for different complications, including random order evaluation (n = 12), simultaneous evaluation (n = 4), the ‘sunflower method’ (n = 3), and pre-defined order (n = 1). The remaining studies did not consider interdependency or reported unclearly. Conclusions The methodology of integrating prediction models in HE models requires further attention, especially regarding how prediction models are selected, adjusted, and ordered.

In this work, Ag/Bi5O7I nanocomposite was prepared and firstly applied in piezo/photocatalytic reduction of N2 to NH3 and methyl orange (MO) degradation. Bi5O7I was synthesized via a hydrothermal-calcination method and shows nanorods morphology. Ag nanoparticles (NPs) were photo deposited on the Bi5O7I nanorods as electron trappers to improve the spatial separation of charge carriers, which was confirmed via XPS, TEM, and electronic chemical analyses. The catalytic test indicates that Bi5O7I presents the piezoelectric-like behavior, while the loading of Ag NPs can strengthen the character. Under ultrasonic vibration, the optimal Ag/Bi5O7I presents high efficiency in MO degradation. The degradation rate is determined to be 0.033 min−1, which is 4.7 folds faster than that of Bi5O7I. The Ag/Bi5O7I also presents a high performance in piezocatalytic N2 fixation. The piezocatalytic NH3 generation rate reaches 65.4 μmol L−1 g−1 h−1 with water as a hole scavenger. The addition of methanol can hasten the piezoelectric catalytic reaction. Interestingly, when ultrasonic vibration and light irradiation simultaneously act on the Ag/Bi5O7I catalyst, higher performance in NH3 generation and MO degradation is observed. However, due to the weak adhesion of Ag NPs, some Ag NPs would fall off from the Bi5O7I surface under long-term ultrasonic vibration, which would greatly reduce the piezoelectric catalytic performance. This result indicates that a strong binding force is required when preparing the piezoelectric composite catalyst. The current work provides new insights for the development of highly efficient catalysts that can use multiple energies.

Introduction Multiple myeloma (MM) patients with renal impairment (RI), especially dialysis-dependent (DD) RI, have poorer outcomes than MM patients with normal renal function. Autologous stem cell transplantation (ASCT) is a treatment option, but there is concern at a perceived higher risk of complications which may be limiting consideration of the use of ASCT in this population. The evidence is inconsistent among studies and interpretation is complicated by heterogeneous datasets, some dating to before the availability of novel agents. Finally, the reversibility of RI following ASCT is an important prognostic factor for both survival and quality of life. Aim To evaluate the safety and efficacy of ASCT in MM patients with DD RI transplanted in EBMT centres between 1997 and 2017. Methods Baseline characteristics at diagnosis, patient treatment regimens and clinical outcomes were collected using standardised report forms. OS was defined as the period between the date of ASCT and the date of death or the date of last observation. PFS was defined as the period between the date of ASCT and date of progression/relapse or death of any causes or the date of the last observation. Cox proportional hazard regression analysis was applied to assess risk factors for progression and death. Survival curves were plotted by the Kaplan-Meier method and compared using log-rank test. P Results A total of 109,959 adult MM patients are registered in the EBMT database as having undergone ASCT between 1997 and 2017. We further analysed 118 DD MM patients who had a first ASCT during this period. The median (range) age was 57 (27-71) years. Seventy (59%) patients were males. Forty nine patients (49/94 patients, 52%) had Karnofsky score ≥90. One hundred and ten patients were treated with hemodialysis and eight with peritoneal dialysis. A total of 68 (58%) patients had Light Chain MM, 43 kappa and 25 Lambda. In first-line induction therapy, 47/76 (62%) patients received bortezomib-based regimens. Forty-four (37%) patients achieved at least VGPR pre-ASCT. The median time from diagnosis to ASCT was 0.7 years (0.3-4.9). Melphalan doses were as follows: 140 mg/m2 (n=55, 67%), 70-100 mg/m2 (n=15, 18%), and >140 mg/m2 (n=12, 15%). The times to Neutrophil (>0.5) and Platelet (>20) engraftment were 12 (10-37) and 14 (4-128) days, respectively. The 30-day and 100-day transplant-related mortality (TRM) rates were 0.0% and 0.9%, respectively. ASCT was associated with a significant deepening of response (at least VGPR pre- vs post-ASCT: 36/93 (39%) vs 48/93 (52%), p < 0.001). The median PFS was 37 months (95% CI: 24-43) and 5-year PFS was 31% (95% CI: 20-41). The median OS was 102 months (95% CI: 67-129). Five-year OS post-ASCT was 62% (52-72) and 10-year OS 36% (17-55). Thirty-one (26%) DD MM patients achieved dialysis independence. There were no differences in PFS or OS when comparing the 1997-2007 and 2008-2017 cohorts: 5-year PFS - 28% (6-49) vs 31% (19-43) (p=0.7) and 5-year OS - 61% (38-84) vs 63% (51-74) (p=0.9), respectively. On univariate analysis of factors affecting PFS, achievement of an Overall Response Rate (ORR) (CR+VGPR+PR vs. Other) pre-ASCT was associated with a lower risk (HR 0.467, p=0.032) and older age (>55 years) with a higher risk (HR 1.786, p=0.035) of post-ASCT progression. Age higher than 55 (HR 2.033, 95%CI: 0.992 - 4.166, p=0.053) increased and achievement of at least VGPR pre-transplant (HR 0.494, 95%CI: 0.224 - 1.091, p=0.081, on the verge of statistical significance) decreased the risk of death. Conclusion To the best of our knowledge, the DIADEM study is the largest analysis of ASCT in DD MM pts to date. This cohort of 118 unselected patients had an OS comparable to patients without RI. This may reflect patient selection based on younger age, Karnofsky scores and pre-ASCT response. The low TRM and excellent outcomes support consideration of the use of ASCT in pts with DD RI. Notably, more than a quarter of patients became dialysis independent, an outcome likely to confer an improved Quality-of-Life.. These results can also inform the debate around the role of renal transplantation in younger DD MM patients who do not achieve dialysis independence. Disclosures Snowden: IDMC: Honoraria; Kiadis: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; Mallinckrodt: Honoraria; Jazz: Honoraria; Gilead: Honoraria. Dreger:MSD: Membership on an entity's Board of Directors or advisory committees, Other: Sponsoring of Symposia; AbbVie, AstraZeneca, Gilead, Janssen, Novartis, Riemser, Roche: Consultancy; AbbVie, Gilead, Novartis, Riemser, Roche: Speakers Bureau; Neovii, Riemser: Research Funding. Illés:Takeda, Seattle: Research Funding; Janssen, Celgene, Novartis, Takeda, Roche, Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees. Basak:Teva: Honoraria; Celgene: Honoraria. Gyan:Pfizer: Honoraria. Hayden:Alnylam: Honoraria; Amgen: Honoraria. Beksac:Amgen: Consultancy; Celgene: Consultancy; Janssen&Janssen: Consultancy; Takeda: Consultancy. Schönland:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Medac: Other: Travel Grant; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding.

A red-black (RB) tree is a data structure with red and black nodes coloration. The red and black color of nodes make up the principal component for balancing a RB tree. A balanced tree has an equal number of black nodes on any simple path. But when a black leaf node is deleted, a double-black (DB) node is formed, thus, causing a reduction in black heights and the tree becomes unbalanced. Rebalancing a RB tree with a DB node is a fairly complex process. Teaching and learning the removal of DB nodes is also challenging. This paper introduces a simplified novel method which is a symbolic-algebraic arithmetic procedure for the removal of DB nodes and the rebalancing of black heights in RB trees. This simplified approach has enhanced student learning of the DB node removal in RB trees. Feedback from students showed the learnability, workability and acceptance of the symbolic-algebraic method in balancing RB trees after a delete operation.

Gesture detection based on radio frequency signals has gained increasing popularity in recent years due to several benefits it has brought, such as eliminating the need to carry additional devices and providing better privacy. In traditional methods, significant breakthroughs have been made to improve recognition accuracy and scene robustness, but the limited computing power of edge devices (the first-level equipment to receive signals) and the requirement of fast response for detection have not been adequately addressed. In this article, we propose a lightweight Wi-Fi gesture recognition system, referred to as WiFine, which is designed and implemented for deployment on low-end edge devices without the use of any additional high-performance services in the process. Toward these goals, we first design algorithms for phase difference selection and amplitude enhancement, respectively, to tackle the problem of data drift caused by user change. Then, we design a cross-dimension fusion method to extract features of finer granularity from information of different dimensions, thus solving the precision problem of feature granularity. Finally, we design a lightweight neural network architecture by leveraging redundancy to reduce computational cost while ensuring satisfactory recognition accuracy. Extensive experimental results show that the proposed system achieves fast recognition of various actions with an accuracy up to 96.03% in 0.19 seconds.

Watermark imperceptibility and robustness in the present watermarking algorithm based on discrete wavelet transform (DWT) could be weakened due to data truncation. To solve this problem, a strong robustness watermarking algorithm based on the lifting wavelet transform is proposed. First, the color channels of the original image are separated, and the selected channels are processed through lifting wavelet transform to obtain low-frequency information. The information is then split into blocks, with Hesseneberg decomposition performed on each block. Arnold algorithm is used to scramble the watermark image, and the scrambled watermark is transformed into a binary sequence that is then embedded into the maximum element of Hessenberg decomposed matrix by quantization modulation. The experimental results exhibit a good robustness of this new algorithm in defending against a wide variety of conventional attacks.

Though superliquid-repelling surfaces are universally important in the fields of fundamental research and industrial production, the understanding and development of these surfaces to impacting liquid droplets remain elusive, especially the changes of wettability states. Surface roughness is required to obtain superliquid-repelling surfaces. However, the effect of surface roughness on the transition of these surfaces' wettability states is uncertain. Herein, we unveiled the relationship of surface roughness on regulating the wettability states of superliquid-repelling surfaces with randomly distributed rough structures through experiment and calculations. The roughness was controlled via regulating the size of surface rough structures, which were formed by a facile coating method. The results indicated that the surface rough structures could impact the value of the polar component (γ

Streams and rivers are important sources of nitrous oxide (N