Effects of ranibizumab on human corneal endothelial cells

AbstractPurposeThis study aims to evaluate corneal endothelial changes occurring over a 3-month period after intravitreal injections of ranibizumab in patients with wet age-related macular degeneration.MethodsThis is a prospective case series. A total of 29 patients (29 eyes) received a 0.5-mg intravitreal injection of ranibizumab. Specular microscopy, including measurement of central corneal thickness and endothelial cell count, was performed on each patient prior to and after completing three intravitreal injections.ResultsAll patients received three intravitreal injections and were followed up for a mean of 3 months. There was no significant change in corneal thickness (p = 0.32) or endothelial cell density (p = 0.38) after ranibizumab injections.ConclusionIntravitreal ranibizumab injections (0.5 mg) have no harmful effects on corneal endothelial cells

Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection

Semi-supervised object detection is crucial for 3D scene understanding, efficiently addressing the limitation of acquiring large-scale 3D bounding box annotations. Existing methods typically employ a teacher-student framework with pseudo-labeling to leverage unlabeled point clouds. However, producing reliable pseudo-labels in a diverse 3D space still remains challenging. In this work, we propose Diffusion-SS3D, a new perspective of enhancing the quality of pseudo-labels via the diffusion model for semi-supervised 3D object detection. Specifically, we include noises to produce corrupted 3D object size and class label distributions, and then utilize the diffusion model as a denoising process to obtain bounding box outputs. Moreover, we integrate the diffusion model into the teacher-student framework, so that the denoised bounding boxes can be used to improve pseudo-label generation, as well as the entire semi-supervised learning process. We conduct experiments on the ScanNet and SUN RGB-D benchmark datasets to demonstrate that our approach achieves state-of-the-art performance against existing methods. We also present extensive analysis to understand how our diffusion model design affects performance in semi-supervised learning.Comment: Accepted in NeurIPS 2023. Code is available at https://github.com/luluho1208/Diffusion-SS3

Consumer personality, privacy concerns and usage of location-based services (LBS)

This paper examines the effects of the Big Five personality traits on concern for information privacy (CFIP) and the effects of the formulated concern for information privacy towards perceived risk, which in turn determine location-based services (LBS) usage intention. Data for this research was collected from 291 users and non-users of LBS. Result from Pearson correlation analysis indicated significant relationships exist between: (1) extraversion, and openness with collection; (2) extraversion, conscientiousness, and openness with improper access; (3) extraversion, conscientiousness, and openness with errors; (4) agreeableness, neuroticism, and openness with secondary use. All four dimensions of CFIP are found to have a significant direct relationship with perceived risk of using LBS. Implications for research and practice for location-based service providers are discussed

Dish Discovery via Word Embeddings on Restaurant Reviews

ABSTRACT This paper proposes a novel framework for automatic dish discovery via word embeddings on restaurant reviews. We collect a dataset of user reviews from Yelp and parse the reviews to extract dish words. Then, we utilize the processed reviews as training texts to learn the embedding vectors of words via the skip-gram model. In the paper, a nearestneighbor like score function is proposed to rank the dishes based on their learned representations. We brief some analyses on the preliminary experiments and present a web-based visualization at http://clip.csie.org/yelp/. Keywords dish discovery, word embeddings, dish-word extraction BACKGROUND With the growth of social media, corporations, such as Yelp, have accumulated a great number of user generated content (UGC). In the literature, some studies have been conducted with a perspective of finding critical information hidden in the content METHODOLOGY Copyright held by the author(s). RecSys 2016 Poster Proceedings, September 15-19, 2016, USA, Boston. Our methodology mainly consists of three parts: 1) dishword recognition, 2) word embedding learning, and 3) dish score calculation. As alluded to earlier, UGC usually incorporates a degree of noise and different language usages; therefore, extracting dish names from user reviews is a complicated task. For example, observed from the dataset, users tend not to write the full name of a dish in their reviews; instead, the last word or the last two words are often written in the reviews. To grapple with this issue, we use regular expressions (regexps) to extract dish names from the user reviews. However, this also give rise to an issue that a certain dish in a restaurant may be of the same name in other restaurants, which may induce the problem of ambiguity and lower the accuracy of matching the correct dish name. So, we attach a dish name with its restaurant name to solve the ambiguity problem. We then utilize the collection of processed reviews as training texts to learn embeddings of each word in the reviews via a continuous space language model, the skip-gram model. After the training phase, each word (including every dish) is represented by an n-dimensional vector (called the embedding of this word). Inspired by the k-nearest neighbors algorithm, we define the score for every dish d as: where , m is the total number of positive sentiment words considered, λi (i = 1, · · · , m) is a weighting parameter. In addition, si denotes the i-nearest positive sentiment words of the given dish d, and w d , ws i ∈ R n are the vector representations of the dish d and the sentiment word si, respectively. In an extreme case (1) of λm = 1 and λi = 0 for i = 1, · · · , m − 1, this score function implements the concept of the average Euclidean distance between a dish and all the positive sentiment words; while in the case (2) λ1 = 1 and λi = 0 for i = 2, · · · , m, the scored is obtained with the closest positive sentiment words to the dish. EXPERIMENTS Our preliminary experiments involve a real-world restaurant review dataset collected from Yelp Data Challenge

Trends and characteristics of pethidine use in Taiwan: a six-year-long survey

OBJECTIVES: To investigate the trends and characteristics of pethidine prescriptions and users in Taiwan from 2002 to 2007. METHOD: All pethidine users (n = 3,301,136) in Taiwan from 2002 to 2007 were linked to National Health Insurance claims to identify pethidine prescriptions. We examined the trends in pethidine user prevalence and the proportion of pethidine prescriptions according to health care characteristics. A logistic regression model was used to compare patient demographics and health care characteristics associated with pethidine prescriptions between 2002 and 2007. RESULTS: Despite the decline in the number of pethidine users and prescriptions over the six-year period, more than half a million people were prescribed pethidine annually. In fact, an increasing proportion of pethidine prescriptions were observed in clinics, outpatient settings, and patients who had both operations and cancer diagnoses. Pethidine prescriptions were mostly associated with a non-operation status without a cancer diagnosis (>;60%). However, approximately 10% of the total pethidine prescriptions were found in patients with a cancer diagnosis but no operation. Compared to those in 2002, pethidine prescriptions in 2007 were more likely to be found in people 80 years or older, rural residents, patients from clinics, outpatient settings and operation patients with cancer diagnoses. CONCLUSIONS: A population-based survey in Taiwan demonstrated decreasing consumption of pethidine from 2002 to 2007; however, an increased proportion of prescriptions in certain health care settings was observed. In addition, 10% of the pethidine prescriptions were for cancer patients without operations. These cases need further evaluation for the determination of appropriate pethidine use

External Validation of the RESCUE-IHCA Score as a Predictor for In-Hospital Cardiac Arrest Patients Receiving Extracorporeal Cardiopulmonary Resuscitation

Background: Extracorporeal cardiopulmonary resuscitation (ECPR) improves the prognosis of in-hospital cardiac arrest (IHCA). The six-factor RESCUE-IHCA score (resuscitation using ECPR during IHCA) was developed to predict outcomes of post-IHCA ECPR-treated adult patients. Our goal was to validate the score in an Asian medical center with a high volume and experience of ECPR performance and to compare the differences in patient characteristics between the current study and the original cohort in a 2022 observational study. Method: For this single-center, retrospective cohort study we enrolled 324 ECPR-treated adult IHCA patients. The primary outcome was in-hospital mortality. We used the area under the receiver operating curve (AUROC) to externally validate the RESCUE-IHCA score. The calibration of the model was tested by the decile calibration plot as well as Hosmer–Lemeshow goodness-of-fit with an associated P-value. Results: Of the 324 participants, 231 (71%) died before hospital discharge. The discriminative performance of the RESCUE-IHCA score was comparable with the originally validated cohort, with an AUC of 0.63. A prolonged duration of cardiac arrest was associated with an increased risk of mortality (odds ratio [OR] 1.02, 95% confidence interval [CI] 1.01–1.03, P = .006). An initial rhythm of ventricular tachycardia (OR 0.14, 95% CI 0.04–0.51, P = .003), ventricular fibrillation (OR 0.11, 95% CI 0.03–0.46, P = .003), and palpable pulse (OR 0.26, 95% CI 0.07–0.92, P = 0.04) were associated with a reduced mortality risk compared to asystole or pulseless electrical activity. In contrast to the original study, age (P = 0.28), resuscitation timing (P = 0.14), disease category (P = 0.18), and pre-existing renal insufficiency (P = 0.12) were not associated with in-hospital death. Conclusion: In external validation, the RESCUE-IHCA score exhibited performance comparable to its original validation within the single-center population. Further investigation on hospital experience, time-of-day effect, and specific disease categories is warranted to improve the selection criteria for ECPR candidates during IHCA

Magnon-induced non-Markovian friction of a domain wall in a ferromagnet

Motivated by the recent study on the quasiparticle-induced friction of solitons in superfluids, we theoretically study magnon-induced intrinsic friction of a domain wall in a one-dimensional ferromagnet. To this end, we start by obtaining the hitherto overlooked dissipative interaction of a domain wall and its quantum magnon bath to linear order in the domain-wall velocity and to quadratic order in magnon fields. An exact expression for the pertinent scattering matrix is obtained with the aid of supersymmetric quantum mechanics. We then derive the magnon-induced frictional force on a domain wall in two different frameworks: time-dependent perturbation theory in quantum mechanics and the Keldysh formalism, which yield identical results. The latter, in particular, allows us to verify the fluctuation-dissipation theorem explicitly by providing both the frictional force and the correlator of the associated stochastic Langevin force. The potential for magnons induced by a domain wall is reflectionless, and thus the resultant frictional force is non-Markovian similarly to the case of solitons in superfluids. They share an intriguing connection to the Abraham-Lorentz force that is well-known for its causality paradox. The dynamical responses of a domain wall are studied under a few simple circumstances, where the non-Markovian nature of the frictional force can be probed experimentally. Our work, in conjunction with the previous study on solitons in superfluids, shows that the macroscopic frictional force on solitons can serve as an effective probe of the microscopic degrees of freedom of the system.Comment: 13 pages, 2 figure