Translation, cross-cultural adaptation, and measurement properties of the Traditional Chinese version of the Fear of Falling Avoidance Behavior Questionnaire in Taiwanese community-dwelling adults.

PURPOSE: This study aimed to translate the Fear of Falling Avoidance Behavior Questionnaire (FFABQ) into Traditional Chinese (FFABQ-TC) and to evaluate the psychometric properties of FFABQ-TC in Taiwanese adults. METHODS: We translated and culturally adapted the FFABQ into Traditional Chinese, ensuring linguistic accuracy and cultural relevance. A total of 230 Taiwanese community-dwelling adults participated in the study. Test-retest reliability was assessed in 30 participants, while 200 participants were included in the validity analysis. Known-groups validity was investigated by comparing the FFABQ-TC scores between fallers and non-fallers. Convergent validity was examined by correlating FFABQ-TC scores with Activities-specific Balance Confidence Scale (ABC), Geriatric Fear of Falling Measure (GFFM), and Timed-Up-and-Go (TUG) test. RESULTS: The FFABQ-TC demonstrated excellent test-retest reliability (Intraclass Correlation Coefficient = 0.884) and excellent internal consistency (Cronbach's alpha = 0.930). Known-groups analysis revealed that FFABQ-TC significantly differentiated between fallers and non-fallers. Convergent validity was examined and showed significant correlations of FFABQ-TC with the ABC, the GFFM, and TUG. CONCLUSION: The psychometric properties of FFABQ-TC was established in Taiwanese adults for assessing FOF-related avoidance behaviors. The translated and adapted FFABQ-TC is a reliable and valid clinical tool for evaluating fall risk in this population.

The current evidence supports the reliability and validity of the Traditional Chinese version of the Fear of Falling Avoidance Behavior Questionnaire (FFABQ-TC) in Taiwanese community-dwelling adults.FFABQ-TC is recommended as a reliable measurement to determine fall risk in clinical and research settings.

SLAPP: Subgraph-level attention-based performance prediction for deep learning models.

The intricacy of the Deep Learning (DL) landscape, brimming with a variety of models, applications, and platforms, poses considerable challenges for the optimal design, optimization, or selection of suitable DL models. One promising avenue to address this challenge is the development of accurate performance prediction methods. However, existing methods reveal critical limitations. Operator-level methods, proficient at predicting the performance of individual operators, often neglect broader graph features, which results in inaccuracies in full network performance predictions. On the contrary, graph-level methods excel in overall network prediction by leveraging these graph features but lack the ability to predict the performance of individual operators. To bridge these gaps, we propose SLAPP, a novel subgraph-level performance prediction method. Central to SLAPP is an innovative variant of Graph Neural Networks (GNNs) that we developed, named the Edge Aware Graph Attention Network (EAGAT). This specially designed GNN enables superior encoding of both node and edge features. Through this approach, SLAPP effectively captures both graph and operator features, thereby providing precise performance predictions for individual operators and entire networks. Moreover, we introduce a mixed loss design with dynamic weight adjustment to reconcile the predictive accuracy between individual operators and entire networks. In our experimental evaluation, SLAPP consistently outperforms traditional approaches in prediction accuracy, including the ability to handle unseen models effectively. Moreover, when compared to existing research, our method demonstrates a superior predictive performance across multiple DL models.

Data of a high temperature heat injection test.

This document compiles the data related to a high temperature heat injection test, which was carried out at an injection temperature of 74 °C in a shallow aquifer and is presented by Heldt et al. [1]. The data set contains transient measurements of temperatures at 18 wells in 10 depths and measurements of the experimental boundary conditions (injection temperature and flow rate) at a temporal resolution of up to 1 min. The spatial configuration and the technical details about where and how the data have been measured are provided. In addition, data of a multilevel multi well pumping test are shown. The presented data is useful to gain insights into the thermohydraulic processes induced by a high temperature heat injection test and can furthermore be used for the development and verification of numerical models of the presented experiment and similar applications like high temperature aquifer thermal energy storage.

Single nucleotide polymorphism of RANKL and OPG genes may play a role in bone and joint injury in rheumatoid arthritis.

OBJECTIVES: This paper aims to investigate the influence of single-nucleotide polymorphisms (SNPs) in the receptor of activator of nuclear factor kappaB ligand (RANKL) gene (TNFSF11) and osteoprotegerin (OPG) gene (TNFRSF11B) on bone and joint injury in patients with rheumatoid arthritis (RA). METHODS: Two hundred RA patients and 201 matched controls were analysed by case-control design, and their samples were genotyped. Bone mineral density (BMD) and serum OPG and RANKL levels were measured. Clinical and laboratory parameters were recorded, and the radiographic changes in both hands of RA were evaluated by Sharp's method. RESULTS: Our results showed no significant differences in the distribution frequency of the alleles and genotypes of TNFRSF11B (rs2073618 and rs3102735) and TNFSF11 (rs2277438) between the RA group and controls (p>0.05). Compared to patients with TNFSF11 (rs2277438) AA or GG genotype, RA with TNFSF11 (rs2277438) AG genotype had significantly decreased BMD values at lumbar spine 3, lumbar spine 4, lumbar spine 2-4 (p<0.05-0.01), and apparently elevated Sharp scores (p<0.05), respectively. The RA group showed significantly higher serum levels of RANKL, RANKL/OPG ratio and a lower serum level of OPG than that of the controls (p<0.05-0.0001). RA patients with RANKL-rs2277438 heterozygotic genotype (AG) had significantly increased serum levels of RANKL (p<0.05), compared to homozygotic genotype (AA or GG). CONCLUSIONS: These results indicate that SNP of TNFRSF11B (rs2073618 and rs3102735) and TNFSF11 (rs2277438) may not be susceptibility factors for RA in Chinese Han population. SNP of TNFSF11 (rs2277438) may have an important influence on bone and joint injury in RA.

[Exploration of risk factors on the occurrence of osteoporotic vertebral fracture in patients with rheumatoid arthritis].

OBJECTIVE: To explore the prevalence of osteoporosis (OP) and vertebral osteoporotic fracture (OPF) and related risk factors in patients with rheumatoid arthritis (RA). METHOD: A total of 644 patients with RA from Jan. 2010 to Oct. 2013 were recruited, anteroposterior and lateral X-rays examination of vertebral column (T5-L5) were conducted, and semi-quantity method were used as the standard for judging vertebral OPF. Meanwhile, patients' clinical and laboratory data including daily dosage of glucocorticoid, duration of glucocorticoid usage, cumulative amount dosage of glucocorticoid were recorded in details. 158 normal subjects were selected as control group. RESULTS: (1)The prevalence of vertebral OPF in patients with RA was 16.6%. Bone mineral density (BMD) of all measured lumbar vertebra in RA group were markedly decreased [(0.97 ± 0.22) g/cm(2)]. The total prevalence of OP at lumbar vertebra in RA was 17.9% (81/452), which was significantly higher than that of control group (4.4%, 7/158) (P < 0.001). (2) The percentage of OP in RA patients with vertebral OPF was significantly higher than that in patients without OPF [40.6% (41/101) vs 11.4% (40/351); P < 0.001]. Patients with OPF were of older age, longer use of glucocorticoid, more cumulative amount dosage of glucocorticoid, longer disease duration, higher scores of health assessment questionnaires (HAQ) and increased ESR (P < 0.05). (3) Logistic regression analysis revealed that age (OR = 1.094, 95% CI 1.065-1.125, P < 0.001) and gender (1 = male, 2 = female) (OR = 5.600, 95% CI 2.097-15.087, P = 0.001) were the risk factors for the development of OP in RA, while body mass index (BMI) was the protective factor (OR = 0.770, 95% CI 0.696-0.853, P < 0.001). Age (OR = 1.031, 95% CI 1.009-1.053, P = 0.005) and occurrence of OP at lumbar vertebra (OR = 3.765, 95% CI 2.092-6.776, P < 0.001) were risk factors of the development of OPF in RA patients. Logistic regression analysis also showed that RA was the risk factor of OPF (OR = 4.716, 95% CI 1.987-11.192, P < 0.001), even after the adjustment of age, gender and BMI. (4) Receiver operator characteristic(ROC) curve in RA patients with OPF has found that age-OPF and daily dosage of glucocorticoid-OPF AUCROC were 0.689 and 0.636 respectively. The cut-off value in ROC curve of age and daily dose or treatment course of glucocorticoid-OPF were 54.5 years and 6.25 mg (P < 0.001) , while duration of glucocorticoid usage-OPF AUCROC was 0.685, with cut-off value in ROC of age-OPF 135 days (P < 0.001). CONCLUSION: Prevalence of OPF in patients with RA increases remarkably. Old age and OP at spine are risk factors related to the development of OPF in patients with RA.