Distance Score Research Articles

The Effect of Abdominal Binders on Mobilization and Pain in the Postoperative Period after Emergency Laparotomy

Background: In order to augment the postoperative recovery process in patients undergoing laparotomy, various methods have been evaluated in the past. One such strategy is the use of postoperative abdominal binder. Objective: We compared the efficacy of abdominal binder use in patients undergoing emergency laparotomy by objective comparison of 6-minute walk test and pain on visual analogue scale. Place of study: Departments of Surgery in both Benazir Bhutto Hospital and District Head Quarter Hospital affiliated with Rawalpindi Medical University, Rawalpindi Material and Methods: It was a randomized controlled trial that was carried out at Departments of Surgery of Rawalpindi Medical University, from October 2021 till May 2022. It included 100 patients, 50 in binder group and 50 in non-binder group. The study included patients from 18 to 65 years of age undergoing emergency exploratory laparotomy for acute abdomen or abdominal trauma having ASA Class I-II. In the postoperative period mobility was assessed by 6-minute walk test (6MWT) and pain was assessed using the VAS. Data was analyzed using SPSS version 20. The mean 6 MWT distance and pain score (VAS) was compared between the binder and no-binder group using the independent samples t-test. Results were considered statistically significant if the p value was < 0.05. Results: The 6MWT distance and the pain scores of patients in the binder group did not differ significantly from the pain scores in the non-binder group on first, third, fifth and fourteenth postoperative day (p>0.05). Conclusion: We did not find a statistically significant difference between the patients using binder and the patients not using binder after surgery with respect to mobilization and pain in the postoperative period. Keywords: major abdominal surgery; exploratory laparotomy, abdominal binder; 6-minute walk test; visual analogue scale

Spatiotemporal Dynamics of Wetland in Dongting Lake Based on Multi-Source Satellite Observation Data during Last Two Decades.

Monitoring the dynamics of wetland resources has practical value for wetland protection, restoration and sustainable utilization. Dongting Lake wetland reserves are well known for both their intra-annual and inter-annual dynamic changes due to the effects of natural or human factors. However, most wetland monitoring research has failed to consider the seasonal wetlands, which is the most fragile wetland type, requiring more attention. In this study, we used multi-source time series remote sensing data to monitor three Dongting Lake wetland reserves between 2000 and 2020, and the seasonal wetlands were separated from permanent wetlands. Multispectral and indices time series were generated at 30 m resolution using a two-month composition strategy; the optimal features were then selected using the extension of the Jeffries-Matusita distance (JBh) and random forest (RF) importance score; yearly wetland maps were identified using the optimal features and the RF classifier. Results showed that (1) the yearly wetland maps had good accuracy, and the overall accuracy and kappa coefficients of all wetland maps from 2000 to 2020 were above 89.6% and 0.86, respectively. Optimal features selected by JBh can improve both computational efficiency and classification accuracy. (2) The acreage of seasonal wetlands varies greatly among multiple years due to inter-annual differences in precipitation and evaporation. (3) Although the total wetland area of the three Dongting Lake wetland reserves remained relatively stable between 2000 and 2020, the acreage of the natural wetland types still decreased by 197.0 km2, and the change from natural wetland to human-made wetland (paddy field) contributed the most to this decrease. From the perspective of the ecological community, the human-made wetland has lower ecological function value than natural wetlands, so the balance between economic development and ecological protection in the three Dongting Lake wetland reserves requires further evaluation. The outcomes of this study could improve the understanding of the trends and driving mechanisms of wetland dynamics, which has important scientific significance and application value for the protection and restoration of Dongting Lake wetland reserves.

Belt Electrode-Skeletal Muscle Electrical Stimulation in Older Hemodialysis Patients with Reduced Physical Activity: A Randomized Controlled Pilot Study.

Background: Although patients receiving hemodialysis are more likely to develop metabolic disorders and muscle weakness at an earlier stage than healthy individuals, many older dialysis patients have difficulty establishing exercise habits to prevent these problems. Therefore, we evaluated the use of belt electrode-skeletal muscle electrical stimulation (B-SES), which can stimulate a wider area than conventional electrical muscle stimulation (EMS), to examine its application and safety in older hemodialysis patients as a means to improve lower extremity function without voluntary effort. Methods: This study was a randomized controlled trial (RCT) involving 20 older dialysis patients (>65 years old) with reduced physical activity. The control group received 12 weeks of routine care only and the intervention group received 12 weeks of B-SES during hemodialysis in addition to routine care. The primary endpoint was the 6 min walk test (6MWT) distance, while the Short Physical Performance Battery (SPPB), body composition, Functional Independence Measure (FIM), biochemistry test, and blood pressure/pulse measurements were used as secondary endpoints. Results: As a result of the 12-week B-SES intervention, no increase in creatine kinase or C-reactive protein levels was observed after the intervention in either group, and no adverse events attributed to the B-SES intervention were observed in the intervention group. Furthermore, the intervention group showed a significant improvement in the 6MWT and SPPB scores after the intervention. Conclusions: The results of this study suggest that a 12-week B-SES intervention during hemodialysis sessions safely improves 6MWT distance and SPPB scores in older patients with a reduced level of physical activity.

Automatic generation of retinal optical coherence tomography images based on generative adversarial networks.

The automatic generation algorithm of optical coherence tomography (OCT) images based on generative adversarial networks (GAN) can generate a large number of simulation images by a relatively small number of real images, which can effectively improve the classification performance. We proposedan automatic generation algorithm for retinal OCT images based on GAN to alleviate the problem of insufficient images with high quality in deep learning, and put the diagnosis algorithm toward clinical application. We designed a generation network based on GAN and trained the network with a data set constructed by 2014_BOE_Srinivasan and OCT2017 to acquire three models. Then, we generated a large number of images by the three models to augment age-related macular degeneration (AMD), diabetic macular edema (DME), and normal images. We evaluated the generated images by subjective visual observation, Fréchet inception distance (FID) scores, and a classification experiment. Visual observation shows that the generated images have clear and similar features compared with the real images. Also, the lesion regions containing similar features in the real image and the generated image are randomly distributed in the image field of view. When the FID scores of the three types of generated images are lowest, three local optimal models are obtained for AMD, DME, and normal images, indicating the generated images have high quality and diversity. Moreover, the classification experiment results show that the model performance trained with the mixed images is better than that of the model trained with real images, in which the accuracy, sensitivity, and specificity are improved by 5.56%, 8.89%, and 2.22%. In addition, compared with the generation method based on variational auto-encoder (VAE), the method improved the accuracy, sensitivity, and specificity by 1.97%, 2.97%, and 0.99%, for the same test set. The results show that our method can augment the three kinds of OCT images, not only effectively alleviating the problem of insufficient images with high quality but also improving the diagnosis performance.

Realistic image synthesis of COVID-19 chest X-rays using depthwise boundary equilibrium generative adversarial networks

<span>Researchers in various related fields research preventing and controlling the spread of the coronavirus disease (COVID-19) virus. The spread of the COVID-19 is increasing exponentially and infecting humans massively. Preliminary detection can be observed by looking at abnormal conditions in the airways, thus allowing the entry of the virus into the patient's respiratory tract, which can be represented using computer tomography (CT) scan and chest X-ray (CXR) imaging. Particular deep learning approaches have been developed to classify COVID-19 CT or CXR images such as convolutional neural network (CNN), and deep convolutional neural network (DCNN). However, COVID-19 CXR dataset was measly opened and accessed. Particular deep learning method performance can be improved by augmenting the dataset amount. Therefore, the COVID-19 CXR dataset was possibly augmented by generating the synthetic image. This study discusses a fast and real-like image synthesis approach, namely depthwise boundary equilibrium generative adversarial network (DepthwiseBEGAN). DepthwiseBEGAN was reduced memory load 70.11% in training processes compared to the conventional BEGAN. DepthwiseBEGAN synthetic images were inspected by measuring the Fréchet inception distance (FID) score with the real-to-real score equal to 4.3866 and real-to-fake score equal to 4.4674. Moreover, generated DepthwiseBEGAN synthetic images improve 22.59% accuracy of conventional CNN models.</span>

Hausdorff GAN: Improving GAN Generation Quality With Hausdorff Metric.

Data usually resides on a manifold, and the minimal dimension of such a manifold is called its intrinsic dimension. This fundamental data property is not considered in the generative adversarial network (GAN) model along with its its variants; such that original data and generated data often hold different intrinsic dimensions. The different intrinsic dimensions of both generated and original data may cause generated data distribution to not match original data distribution completely, and it certainly will hurt the quality of generated data. In this study, we first show that GAN is often unable to generate simulation data, holding the same intrinsic dimension as the original data with both theoretical analysis and experimental illustration. Next, we propose a new model, called Hausdorff GAN, which removes the issue of different intrinsic dimensions and introduces the Hausdorff metric into GAN training to generate higher quality data. This provides new insights into the success of Hausdorff GAN. Specifically, we utilize a mapping function to map both original and generated data into the same manifold. We then calculate the Hausdorff distance to measure the difference between the mapped original data and the mapped generated data, toward pushing generated data to the side of original data. Finally, we conduct extensive experiments (using MNIST, CIFAR10, and CelebA datasets) to demonstrate the significant performance improvement of the Hausdorff GAN in achieving the largest Inception Score and the smallest Frechet inception distance (FID) score as well as producing diverse generated data at different resolutions.

Part of town as an independent factor: thenorth-forcemerger in Manchester

AbstractThis paper investigates the question of whether, as is often popularly believed, there may be systematic linguistic differences between different neighborhoods within a city by testing the independence of “part of town” as a factor separate from social class in thenorth-forcemerger in Manchester, UK, in a sample of 122 speakers. The phonemic contrast is explored in minimal-pair tests, Cartesian distance, and Pillai scores. In opposition to most dialects of English, thenorth-forcecontrast is still present in Manchester, displaying a pattern of fine social stratification, with lower socioeconomic levels having a stronger distinction. The merger is in progress in the city, but it is slower in north Manchester, showing a significantly greater distinction than the rest of the city, independent of social class. The results indicate a degree of social evaluation of the vowels, with implications for the question of the social meaning of a merger in progress.

P.122 Comparative safety and efficacy of different corticosteroid regimens in boys with Duchenne muscular dystrophy: results of a randomized controlled trial

Corticosteroids (CS) improve muscle function in boys with DMD and are part of the care recommendations. However, there is uncertainty about optimum regimen and dosage leading to great variability in CS use worldwide. The FOR DMD study (Find the Optimum corticosteroid Regimen for Duchenne Muscular Dystrophy) compared efficacy and side effects of the 3 most commonly prescribed CS regimens in young boys with DMD. We completed a randomized, double-blind, parallel-group clinical trial (32 sites, 5 countries). Boys were randomized 1:1:1 to daily prednisone (0.75 mg/kg), daily deflazacort (0.9 mg/kg), or intermittent prednisone (0.75 mg/kg 10 days on/10 days off). A total of 196 corticosteroid-naïve boys with DMD ages 4-7 years were enrolled and followed up for 3 years. The primary outcome comprised rise from the floor velocity, forced vital capacity, and participant/parent global satisfaction with treatment. Secondary efficacy outcomes (10 meter walk/run velocity, 6-minute walking distance and North Star Ambulatory Assessment total score) and safety outcomes (height, weight, behavioral measures, adverse events) were monitored. Daily prednisone and daily deflazacort resulted in significantly better efficacy outcomes compared to intermittent, 10 days on 10 days off, prednisone. There were no significant differences in efficacy between the 2 daily regimens. Results were consistent between age groups (4-5 vs. 6-7). There was no significant difference in weight gain between the daily and intermittent prednisone groups, both of which gained more weight than the deflazacort group. Slowing of growth was less severe with the intermittent than with the daily regimens, with daily deflazacort associated with the greatest slowing of growth. This study supports use of a daily corticosteroid regimen over an intermittent prednisone regimen that alternates dosing with 10 days on and 10 days off as initial treatment for boys with DMD.

C3-DINO: Joint Contrastive and Non-Contrastive Self-Supervised Learning for Speaker Verification

Self-supervised learning (SSL) has drawn an increased attention in the field of speech processing. Recent studies have demonstrated that contrastive learning is able to learn discriminative speaker embeddings in a self-supervised manner. However, base contrastive self-supervised learning (CSSL) assumes that the pairs generated from a view of anchor instance and any view of other instances are all negative, which introduces many false negative pairs in constructing the loss function. The problem is referred as $class$-$collision$, which remains as one major issue that impedes the CSSL based speaker verification (SV) systems from achieving better performances. In the meanwhile, studies reveal that negative sample free SSL frameworks perform well in learning speaker or image representations. In this study, we investigate SSL techniques that lead to an improved SV performance. We first analyse the impact of false negative pairs in the CSSL systems. Then, a multi-stage Class-Collision Correction (C3) method is proposed, which leads to the state-of-the-art CSSL based speaker embedding system. On the basis of the pretrained CSSL model, we further propose to employ a negative sample free SSL objective (i.e., DINO) to fine-tune the speaker embedding network. The resulting speaker embedding system (C3-DINO) achieves 2.5% EER with a simple Cosine Distance Scoring method on Voxceleb1 test set, which outperforms the previous SOTA SSL system (4.86%) by a significant +45% relative improvement. With speaker clustering and pseudo labeling on Voxceleb2 training set, a LDA/CDS back-end applying on the C3-DINO speaker embeddings is able to further push the EER to 2.2%. Comprehensive experimental investigations of the Voxceleb benchmarks and our internal dataset demonstrate the effectiveness of our proposed methods, and the performance gap between the SSL SV and the supervised counterpart narrows further.

Location Models with Multy Criterious Networks (Case Study: The Industrial of Rice Processing in The Batubara District)

Determining location is a problem encountered in many areas of everyday life. Determining this location becomes complex when many factors are taken into consideration, where one factor and another can conflict. One of the issues that will be discussed in this research is determining the location of the rice processing industry. This problem needs to be studied considering that the opportunity to establish a rice industry in several regions in Indonesia is very high considering that the potential for the main raw material (rice) is very large, as is the rice market where the largest population of the Indonesian nation makes rice the main food ingredient. The case study that will be discussed in this research is the rice processing industry in Batu Bara Regency. Batu Bara Regency is one of the districts/cities in North Sumatra Province which has enormous rice potential. In order to improve the welfare of farmers and provide good quality rice for the community, a Rice Processing Industry is needed. The problem in the rice processing industry is very complex, apart from the seasonal availability of rice raw materials, is the location where the rice processing factory is located. Various criteria need to be considered in this determination relating to the distance of the rice processing industry factory to each source of the main raw material (rice). Determining this location is very complex because it involves multiple criteria. This research will provide a location determination model using a Multi Criteria Network. The criteria used to determine the location of the rice processing industry in Batu Bara Regency are the transportation distance from the raw material center, travel time, and the condition of the road connecting the raw material center to the factory location. Based on the criteria for distance between rice centers and rice processing industrial factories, a route with a total minimum distance score of 0.71 is obtained. Meanwhile, based on travel time, the best route was obtained with a minimum total time score of 1.61. Based on the quality of the road taken, the best route was obtained with a maximum total score of 0.25. By considering the three criteria, the best route was obtained with a total optimum score of 2.96.

Virtual surface morphology generation of Ti-6Al-4V directed energy deposition via conditional generative adversarial network

ABSTRACT The core challenge in directed energy deposition is to obtain high surface quality through process optimisation, which directly affects the mechanical properties of fabricated parts. However, for expensive materials like Ti-6Al-4V, the cost and time required to optimise process parameters can be excessive in inducing good surface quality. To mitigate these challenges, we propose a novel method with artificial intelligence to generate virtual surface morphology of Ti-6Al-4V parts by given process parameters. A high-resolution surface morphology image generation system has been developed by optimising conditional generative adversarial networks. The developed virtual surface matches experimental cases well with an Fréchet inception distance score of 174, in the range of accurate matching. Microstructural analysis with parts fabricated with artificial intelligence guidance exhibited less textured microstructural behaviour on the surface which reduces the anisotropy in the columnar structure. This artificial intelligence guidance of virtual surface morphology can help to obtain high-quality parts cost-effectively.

Assessment of distance-near control disparity in basic and divergence excess paediatric intermittent exotropia

ABSTRACT Clinical Relevance In intermittent exotropia (IXT), deviation is better controlled at near fixation. Understanding of the mechanism responsible for this common observation may improve clinical management of IXT. Background The physiological basis for the distance-near difference in control of deviation in IXT is vastly undetermined. A new parameter, ‘control score disparity (CSD)’, defined as the difference between distance and near control scores, is introduced. Association of CSD with positive fusional amplitude (PFA), accommodative convergence to accommodation (AC/A) ratio and distance angle of deviation was investigated to further understand the mechanisms. Method Patients aged between four and fifteen years with basic and divergence excess IXT were included. Subjects with previous strabismus surgery, amblyopia and inability to perform clinical tests were excluded. A standardized office-based scoring system was used to assess IXT controls. Subjects were sub-divided into group 1 (CSD <2) and group 2 (CSD ≥2). Pearson’s univariate and regression analysis were used to determine relationships between CSD and other independent variables. Results Mean age of the total 141 subjects (57.6% female) was 6.8 ± 2.5 years. Basic IXT was more common (60%) and 60% had CSD ≥2. The mean±SD distance angle of deviation, AC/A ratio, PFA and CSD were 22.1 ± 6.6 prism dioptres, 5.0 ± 1.0, 28.6 ± 6.3 prism dioptre and 2.0 ± 0.5, respectively. CSD was significantly correlated to PFA (r = 0.64, p < 0.001) and AC/A ratio (r = 0.27, p < 0.001) in overall samples and Group 2 subjects (r = 0.41, p = 0.001). Conclusions PFA is a major factor associated with the distance/near difference of IXT control. Individuals with a higher PFA demonstrated greater CSD. While AC/A ratio was associated in better control at near in divergence excess IXT, magnitude of angle appears irrelevant.

Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method.

Computer-vision-based target tracking is a technology applied to a wide range of research areas, including structural vibration monitoring. However, current target tracking methods suffer from noise in digital image processing. In this paper, a new target tracking method based on the sparse optical flow technique is introduced for improving the accuracy in tracking the target, especially when the target has a large displacement. The proposed method utilizes the Oriented FAST and Rotated BRIEF (ORB) technique which is based on FAST (Features from Accelerated Segment Test), a feature detector, and BRIEF (Binary Robust Independent Elementary Features), a binary descriptor. ORB maintains a variety of keypoints and combines the multi-level strategy with an optical flow algorithm to search the keypoints with a large motion vector for tracking. Then, an outlier removal method based on Hamming distance and interquartile range (IQR) score is introduced to minimize the error. The proposed target tracking method is verified through a lab experiment—a three-story shear building structure subjected to various harmonic excitations. It is compared with existing sparse-optical-flow-based target tracking methods and target tracking methods based on three other types of techniques, i.e., feature matching, dense optical flow, and template matching. The results show that the performance of target tracking is greatly improved through the use of a multi-level strategy and the proposed outlier removal method. The proposed sparse-optical-flow-based target tracking method achieves the best accuracy compared to other existing target tracking methods.

Image generation with self pixel-wise normalization

Region-adaptive normalization (RAN) methods have been widely used in the generative adversarial network (GAN)-based image-to-image translation technique. However, since these approaches need a mask image to infer the pixel-wise affine transformation parameters, they cannot be applied to the general image generation models having no paired mask images. To resolve this problem, this paper presents a novel normalization method, called self pixel-wise normalization (SPN), which effectively boosts the generative performance by performing the pixel-adaptive affine transformation without the mask image. In our method, the transforming parameters are derived from a self-latent mask that divides the feature map into the foreground and background regions. The visualization of the self-latent masks shows that SPN effectively captures a single object to be generated as the foreground. Since the proposed method produces the self-latent mask without external data, it is easily applicable in the existing generative models. Extensive experiments on various datasets reveal that the proposed method significantly improves the performance of image generation technique in terms of Frechet inception distance (FID) and Inception score (IS).

Association between early childhood caries and diet quality among Chinese children aged 2-5 years.

Early childhood caries (ECC) is a major oral problem affecting the health and wellbeing of children worldwide. Diet quality is a better predictor of ECC risk than single foods or specific nutrients. The purposes of this study were to assess the associations between ECC and diet quality among 2- to 5-year-old Chinese children. A total of 150 eligible children were included in this study. The decayed, missing, or filled surface (dmfs) score was recorded for each child by dental examination. All participants were divided into three groups based on their age and dmfs score [the caries-free group, the ECC group, and the severe early childhood caries (S-ECC) group]. Parents were invited to complete a questionnaire on the general characteristics and oral health behaviors of the participants. The information of 24-h dietary intake from each child was captured via a mobile APP. The Chinese diet balance index for preschool children (DBI_C) indicators score, high bound score (HBS), low bound score (LBS), and diet quality distance (DQD) score were calculated to assess the diet quality of study subjects. The associations of ECC with HBS, LBS, DQD score, and DBI_C indicators score were analyzed by Mann-Whitney U test and multivariable logistic regression analysis. In this study, 21, 31, and 98 children were diagnosed with caries-free, ECC, and S-ECC, respectively. Statistical analysis revealed that the risk of ECC and S-ECC were significantly increased with the DQD score (OR = 1.283 and 1.287, respectively), but both were not associated with HBS and LBS (P > 0.05). In the meantime, the risk of ECC and S-ECC were significantly increased with the Grains score (OR = 1.623 and 1.777, respectively), and significantly decreased with the Food diversity score (OR = 0.271 and 0.315, respectively). Moreover, the risk of S-ECC also significantly decreased with the Vegetables score (OR = 0.137). Both ECC and S-ECC were associated with a high degree of dietary imbalance and grains intake as well as a low degree of food diversity among Chinese children aged 2-5 years. In addition, S-ECC was also associated with a low degree of vegetable intake.

Self-Sparse Generative Adversarial Networks

Generative Adversarial Networks (GANs) are an unsupervised generative model that learns data distribution through adversarial training. However, recent experiments indicated that GANs are difficult to train due to the requirement of optimization in the high dimensional parameter space and the zero gradient problem. In this work, we propose a Self Sparse Generative Adversarial Network (Self-Sparse GAN) that reduces the parameter space and alleviates the zero gradient problem. In the Self-Sparse GAN, we design a Self-Adaptive Sparse Transform Module (SASTM) comprising the sparsity decomposition and feature-map recombination, which can be applied on multi-channel feature maps to obtain sparse feature maps. The key idea of Self-Sparse GAN is to add the SASTM following every deconvolution layer in the generator, which can adaptively reduce the parameter space by utilizing the sparsity in multi-channel feature maps. We theoretically prove that the SASTM can not only reduce the search space of the convolution kernel weight of the generator but also alleviate the zero gradient problem by maintaining meaningful features in the Batch Normalization layer and driving the weight of deconvolution layers away from being negative. The experimental results show that our method achieves the best FID scores for image generation compared with WGAN-GP on MNIST, Fashion-MNIST, CIFAR-10, STL-10, mini-ImageNet, CELEBA-HQ, and LSUN bedrooms, and the relative decrease of FID is 4.76% ~ 21.84%.

Bridging the resources gap: deep learning for fluorescein angiography and optical coherence tomography macular thickness map image translation

BackgroundTo assess the ability of the pix2pix generative adversarial network (pix2pix GAN) to synthesize clinically useful optical coherence tomography (OCT) color-coded macular thickness maps based on a modest-sized original fluorescein angiography (FA) dataset and the reverse, to be used as a plausible alternative to either imaging technique in patients with diabetic macular edema (DME).MethodsOriginal images of 1,195 eyes of 708 nonconsecutive diabetic patients with or without DME were retrospectively analyzed. OCT macular thickness maps and corresponding FA images were preprocessed for use in training and testing the proposed pix2pix GAN. The best quality synthesized images using the test set were selected based on the Fréchet inception distance score, and their quality was studied subjectively by image readers and objectively by calculating the peak signal-to-noise ratio, structural similarity index, and Hamming distance. We also used original and synthesized images in a trained deep convolutional neural network (DCNN) to plot the difference between synthesized images and their ground-truth analogues and calculate the learned perceptual image patch similarity metric.ResultsThe pix2pix GAN-synthesized images showed plausible subjectively and objectively assessed quality, which can provide a clinically useful alternative to either image modality.ConclusionUsing the pix2pix GAN to synthesize mutually dependent OCT color-coded macular thickness maps or FA images can overcome issues related to machine unavailability or clinical situations that preclude the performance of either imaging technique.Trial registrationClinicalTrials.gov Identifier: NCT05105620, November 2021. “Retrospectively registered”.

Characterizing eye-gaze positions of people with severe motor dysfunction: Novel scoring metrics using eye-tracking and video analysis.

Nonverbal communication with people who have physical disabilities is difficult. Eye-tracking technologies have recently been developed and applied to help people with physical disabilities in their communication. However, the eye-gaze patterns of people with severe motor dysfunction (SMD) have not been analyzed in detail. To clarify characterization of people with SMD, we aimed to develop gaze position-based evaluation metrics and analyze detailed eye-gaze patterns of people with SMD. We developed two new scoring metrics: (1) saliency score based on three saliency maps-spectral residual (SR), fine grained (FG), and motion (Mo); and (2) the distance score, which represents to what extent people can chase an object in a video. The evaluation was performed on 102 participants, consisting of 35 subjects with profound intellectual and multiple disabilities (PIMD; SMD with IQ < 20), 19 with severe physical disabilities (SPD; SMD with IQ ≥ 20), and 48 healthy individuals. We observed that two saliency scores (SR and FG) and the distance score showed significant differences between the PIMD/SPD and healthy groups for the entire video, whereas Mo scores did not. Moreover, the distance score was analyzed separately for each scene, where scenes were categorized into three patterns-running, explanation, and hiding-according to the behavior of the moving objects. In the SPD and healthy groups, the explanation scenes accounted for the highest percentage of all scenes with the best distance score (63.6% and 61.9%, respectively), whereas in the PIMD group, the running scenes accounted for the highest percentage (54.5%). In conclusion, the new metrics were successful in quantitatively assessing the gaze responsiveness of people with SMD, which could not be assessed using a conventional metric, gaze-acquisition time. This study is expected to expand the possibilities of nonverbal communication using eye-tracking devices for people with SMD.

Cryoneurolysis Is a Safe, Effective Modality to Improve Rehabilitation after Total Knee Arthroplasty.

Although long term pain and mobility outcomes in total knee arthroplasties (TKA) are successful, many patients experience significant amount of debilitating pain during the immediate post-operative period that necessitates narcotic use. Percutaneous cryoneurolysis to the infrapatellar saphenous and anterior femoral cutaneous nerves may help to better restore function and rehabilitation after surgery while limiting narcotic consumption. A retrospective chart review of primary TKA patients receiving pre-operative cryoneurolysis from 2019 to 2020 was performed to assess total opioid morphine milligram equivalents (MME) consumed inpatient and at interval follow-up. Demographics and medical comorbidities were compared between cryoneurolysis and age-matched control patients to assess baseline characteristics. Functional rehabilitation outcomes, including knee range of motion (ROM), ambulation distance, and Boston AM-PAC scores, as well as patient reported outcomes using the KOOS JR and SF-12 scores were analyzed using STATA 17 Software. The analysis included 29 cryoneurolysis and 28 age-matched control TKA patients. Baseline demographics and operative technique were not significant between groups. Although not statistically significant, cryoneurolysis patients had a shorter length of stay (2.5 vs. 3.5 days) and overall less inpatient and outpatient MME requirements. Cryoneurolysis patients had statistically significant improved 6-week ROM and 1-year follow-up KOOS JR and SF-12 mental scores compared to the control. There were no differences in complication rates. Cryoneurolysis is a safe, effective treatment modality to improve active functional recovery and patient satisfaction after TKA by reducing MME requirements. Patients who underwent cryoneurolysis had on average fewer MME prescribed during the perioperative period, improved active ROM, and improved patient-reported outcomes with no associated increased risk of infections, deep vein thrombosis, or neurologic complications.

Cultural influences on the quality of corporate social responsibility disclosures: an examination of carbon disclosure

PurposeAs more companies choose to disclose corporate social responsibility (CSR) information, it is important to gain an understanding of the quality of disclosures and factors that influence quality. The purpose of this study is to examine the role of culture as a determinant of the quality of voluntary carbon emission disclosures.Design/methodology/approachThis study uses regression analysis to test the influence of culture on the quality of carbon disclosures. The sample of this study comes from companies who voluntarily report to the carbon disclosure project. The authors operationalize the quality of disclosure using the Carbon Disclosure Leadership Index. The authors operationalize cultural values using both Hofstede’s metrics (Hofstede, 1980) and Project GLOBE (House et al., 2004).FindingsThis study predicts and finds a negative relationship between quality of disclosure and high individualism scores. This study also finds that the quality of disclosure is lower for companies located in countries with high power distance scores. The authors find that the quality of disclosure is higher for companies located in countries with gender/assertiveness scores that indicate a higher value on the environment than on the importance of economic growth. While quality is marginally related to uncertainty avoidance using Hofstede's measure, quality is not related to uncertainty avoidance using the Project GLOBE metric. The authors did not find a hypothesized negative significant relationship between quality and long-term orientation.Practical implicationsQuality is a measure of importance to users and regulators of disclosures.Social implicationsNational culture is an important determinant of CSR disclosure quality.Originality/valueThis study extends the previous research by using a metric for quality based on an independent evaluation of disclosures and by the role of culture in a multi-country study.