Vision Problems Research Articles

Relationship between Serum Zinc Level and Retinopathy in Type 1 Diabetic Patients

Abstract Background Diabetes mellitus is one of the common chronic metabolic diseases associated with various micro- and macro-vascular complications. Diabetic retinopathy (DR) is a microvascular disorder with various grades which leads to visual problems or even blindness. Nearly all patients with type 1 diabetes and more than 60% of those with type 2 have some degree of retinopathy after 20 years. Zinc is one of the micro-nutrients abundant in the human body and possess an important role in various metabolic reactions. Previous studies reported that decreased serum zinc levels was associated with certain diabetic microvascular complications. Zinc depletion has a major impact on the pathogenesis of diabetic complications. However, the correlation between zinc level and diabetic retinopathy needed more studies and especially in type 1diabetic patients which has not been studied at all. AIM/ Objectives Assess the correlation between serum zinc and diabetic retinopathy in type 1 diabetic patient. Subjects and Methods This observational study was conducted on 60 subjects with their ages ranging from 18-60, selected from diabetes outpatient clinics of Ain Shams University Hospitals for 7 months in a period from June 2022 to January 2023; 40 patients and 20 non diabetic as control divided into three groups: 20 Patients with Type 1 diabetes without diabetic retinopathy, 20 Patients with Type 1 diabetes with diabetic retinopathy and 20 apparently healthy individuals. All patients included in the study will be screened for diabetic retinopathy using fundus photography camera. Photos were assessed and graded by an expert ophthalmologist. Assessment of zinc level by automated chemistry analyzer will be done. Results The study shows that there was statistically significant negative correlation found between zinc level and duration of diabetes, HbA1c, LDL, TC, FPS, 2PP and serum creatinine level in all diabetic type 1 group. And in groups of patients with and without retinopathy. There was no statistically significant difference found between control group and DM type1 with and without retinopathy group regarding zinc level although there was numerical differences. Conclusion Positive relationship between decreased zinc level and diabetic retinopathy suggesting the contribution of this factors in the pathogenesis of DR through acting in a same pathway Further studies using larger numbers of patients are recommended to get benefit of giving zinc supplements to these patients

Texting while driving is a visual problem influenced by phone viewing angle and working distance in young individuals

PurposeTo investigate the impact of smartphone viewing distance and angle on reaction times. DesignA prospective, self-controlled, single-center study. MethodsParticipants engaged in a driving simulation facing a large screen with a simulated brake pedal. They were tasked to stop the simulation once recognizing the deceleration of upcoming traffic. Tests were conducted without distraction and with a standardized distraction simulating texting while driving (TWD). Smartphone positions varied at distances of 30 cm and 60 cm, and at angles parallel to and 30° below the road plane. Reaction times were measured from the onset of simulated closure to detection. Stopping distances were extrapolated using data from the National Highway Traffic Safety Administration. ResultsNinety-four participants were included with a mean age of 24 ± 2.7 years. The control reaction time was 11.5 ± 4.1 s. Reaction times significantly decreased with smartphone placement at a closer distance of 30 cm parallel (17.0 ± 3.3 s) vs 60 cm parallel (15.4 ± 3.8 s), P < 0.001. A 30-degree downward placement at 30 cm (18.6 ± 4.0 s) and 60 cm (17.9 ± 3.6 s), further decreased reaction time compared to parallel phone positioning, P < 0.001. Extrapolating to stopping distances based on real-world data, smartphone distractions placed at 30 cm 30° below the dashboard had the greatest effect, resulting in a 3 times increase of stopping distance compared to the control, 1201 vs 394 ft respectively, P < 0.001. ConclusionTWD significantly delays reaction time in young participants. Both the distance and viewing angle of a smartphone significantly influences reaction times during driving simulations. The greatest delays are observed when the smartphone is positioned closer to the user and at a 30-degree angle which we hypothesize is due to vision blur from increased accommodation, loss of stereopsis, and fixation with the peripheral retina.

Blood Vessel Segmentation and Classification of Diabetic Retinopathy with Machine Learning-Based Ensemble Model

The incidence of diabetes has increased in recent times due to factors such as obesity and genetic predisposition. Diabetes wears out the eye vessels over time. Diabetic retinopathy (DR) is a serious disease that leads to vision problems. DR can be diagnosed by specialists who examine the fundus images of the eye at regular intervals. With 537 million diabetics in 2021, this method can be time-consuming, costly and inadequate. Artificial intelligence algorithms can provide fast and cost-effective solutions for DR diagnosis. In this study, the noise of blood vessels in fundus images was eliminated using the LinkNet-RCB7 model, and diabetic retinopathy was categorized into five classes using a machine learning-based ensemble model. Artificial intelligence-based classification training using images as input takes a long time and requires high resource requirements such as Random Access Memory (RAM) and Graphics Processing Unit (GPU). By using Gray Level Cooccurrence Matrix (GLCM) attributes in the classification phase, a lower resource requirement was aimed for. A Dice coefficient of 85.95% was achieved for the segmentation of blood vessels in the Stare dataset, in addition to 97.46% accuracy for binary classification and 96.10% accuracy for classifying DR into five classes in the dataset APTOS 2019.

ANALISIS KESULITAN MENYIMAK SISWA KELAS III DENGAN PENGGUNAAN MEDIA PEMBELAJARAN AUDIO VISUAL

Difficulty in listening is a difficulty in understanding what they are listening to and this difficulty in listening can be an obstacle during learning in class, because students can miscapture information or perceptions. This study aims to find out the difficulties of listening experienced by students using audio visual learning media. The research method used is qualitative descriptive. The subjects studied were grade III students of SDN Tanah Tinggi 7 Tangerang. The data collection technique uses test sheets, observation sheets, and interview sheets. The results showed that the causes of students' difficulty listening were students feeling bored, having difficulty concentrating, experiencing visual impairment problems, lack of understanding of listening vocabulary, students being noisy and unsettled when approaching the time to go home, lack of interest in fairy tales, dark room conditions and class hours that started too early. This is based on the internal factors of the student, namely from within the student himself and external factors, namely from the physical and social environment around the student.

Deformable surface reconstruction via Riemannian metric preservation

Estimating the pose of an object from a monocular image is a fundamental inverse problem in computer vision. Due to its ill-posed nature, solving this problem requires incorporating deformation priors. In practice, many materials do not perceptibly shrink or extend when manipulated, constituting a reliable and well-known prior. Mathematically, this translates to the preservation of the Riemannian metric. Neural networks offer the perfect playground to solve the surface reconstruction problem as they can approximate surfaces with arbitrary precision and allow the computation of differential geometry quantities. This paper presents an approach for inferring continuous deformable surfaces from a sequence of images, which is benchmarked against several techniques and achieves state-of-the-art performance without the need for offline training. Being a method that performs per-frame optimization, our method can refine its estimates, contrary to those based on performing a single inference step. Despite enforcing differential geometry constraints at each update, our approach is the fastest of all the tested optimization-based methods.

Eye care service utilization and associated factors among adults in Debre Berhan Town, North Shewa, Ethiopia, 2023.

Globally, the utilization of eye care services varies widely, ranging from 18 to 90%. Low utilization of eye care services can lead to delayed detection of vision problems. However, there are limited data on the proportion of eye care service utilization and its associated factors in Ethiopia at the community level. The objective of this study was to determine the proportion of eye care service utilization and its associated factors among adults in Debre Birhan town, North Shewa, Ethiopia. Using a multistage sampling method, a community-based cross-sectional study was conducted on 960 adults in Debre Birhan town from 8 May to 8 June 2023. Binary logistic regression was performed. Variables with a p-value of less than 0.05 were considered significant. A total of 940 study participants participated, resulting in a response rate of 97.9%. The mean age of the participants was 54.67 years (SD ± 8.69). The proportion of good-level eye care service utilization was found to be 32.98% [95% confidence interval (CI): 29.97, 35.99]. Factors positively associated with good-level eye care service utilization included older age [adjusted odds ratio (AOR) = 1.58, 95%CI: 1.00, 2.51], higher educational status (AOR = 2.25, 95%CI: 1.25, 4.06), high family monthly income (AOR = 8.70, 95%CI: 4.99,15.18), awareness of regular eye checkups (AOR = 1.77, 95%CI: 1.15, 2.73), a history of eye disease (AOR = 2.57, 95%CI: 1.77,3.74), health insurance (AOR = 1.99, 95% CI: 1.34, 2.95), and history of spectacle use (AOR = 1.94, 95%CI:1.34, 2.80). The study revealed that the proportion of good-level eye care service utilization was low. Older age, higher educational status, high family monthly income, awareness of regular eye checkups, a history of eye disease, health insurance, and history of spectacle use were significantly associated with a good level of eye care service utilization.

Assessing the awareness and knowledge of the adverse ocular side effects associated with oral contraceptives among women between the ages of 16 and 40 in Benin-city, Edo state, Nigeria

PurposeOral contraceptives are routinely used by women, because they are effective birth control methods, but few women are aware of their adverse ocular side effects. This study was carried out to determine the level of awareness and knowledge of the adverse ocular side effects associated with oral contraceptive use among women in Benin-City, Edo State, Nigeria. MethodThis was a cross-sectional study conducted over an eight-month period from February 2023 to September 2023, including 402 women (n = 402). The study employed both self-administered online and printed questionnaires. ResultsThe mean age of the participants was 27.76 ± 7.03. A total of 196 had tertiary education, 131 had secondary education and 75 had no educational background. Two-hundred thirty-seven participants were users of oral contraceptives, while 165 had never used them. Of the participants that were users of oral contraceptives, 44 had previously experienced visual problems as a side. The study results reveal that 289 participants (71.9%) were not aware of the potential adverse effects of oral contraceptives, while only 82 participants (20.4%) were aware. ConclusionThe results of this study show that there is poor awareness of the side effects of oral contraceptives, more specifically, the adverse effects on the eyes. It is recommended that more public health awareness campaigns be initiated, with the goal of accurately educating women about the ocular pathologic risks associated with oral contraceptives. Furthermore, healthcare workers should effectively communicate the risks associated with oral contraceptives to their patients. This can help women looking for contraception options make informed decisions about using oral contraceptives.

BAKTI SOSIAL SKRINING MATA DAN OPERASI KATARAK GRATIS RS. AHMAD WARDI DAN DOMPET DHUAFA BERSAMA MAHASISWA KULIAH KERJA MAHASISWA (KKM)

This free eye screening and cataract surgery social service activity is a tangible form of concern for Ahmad Wardi Hospital and Dompet Dhuafa, which collaborate with Student Work Lecture (KKM) students. The main goal of this activity is to help the underprivileged to get free access to eye health checks and treatments, especially for those who suffer from cataracts. Through eye screening, the medical team can detect vision problems early, while cataract surgery is given to patients who meet the criteria to improve their vision. KKM students play an important role in this activity, starting from helping with preparations, providing education to the community, to being directly involved in the implementation in the field. With this program, it is hoped that people can feel the improvement in the quality of life, especially in terms of eye health, as well as grow awareness of the importance of maintaining eye health and conducting early checkups.

Poverty and Vision: The Effect of Title 1 Status on Vision Screening Referral Rates in School-Aged Children in Western South Dakota

ABSTRACT Purpose Interventions such as eye exams and glasses are used to correct visual problems that may lead to amblyopia, an irreversible decrease in visual acuity. Children with limited access to these interventions are more likely to have unaddressed visual problems that can lead to amblyopia or negatively impact school performance. This study compared vision screening results of children in schools with Title 1 or Non-Title 1 designation to investigate the link between poverty and vision. Methods Data from KidsFIRST vision screenings conducted with the SPOTTM photoscreener performed in Rapid City Area elementary schools were compared across multiple parameters. Students were referred for eye examinations based on identifying the following problems: anisometropia, anisocoria, astigmatism, myopia, hyperopia, gaze misalignment, or a combination. Results Overall, eye exam referral rates have increased since 2012 (11.9% in 2012, 19.7% in 2023), with a disproportionate increase in referrals from Title 1 schools (25.2% in 2023) vs. Non-Title 1 schools (11.9% in 2023) (p < 0.001). This is largely due to a significantly higher prevalence of astigmatism referrals in Title 1 students (20.9%) compared to Non-Title 1 students (7.5%). Although a higher percentage of Title 1 students are reported to have eye correction (24.4% vs 16.6%), only a slightly higher percentage of Title 1 students wore eye correction during screening (11.5% vs 10.5%). Conclusion Students at Title 1 schools may have a higher rate of amblyopia risk factors. Additional eye care-based interventions should be taken to reduce the risk of amblyopia in this population.

Evaluation of Science Education for Students with Visual Impairment: Views of Teachers and Administrators

Introduction: Science education for students with visual impairment requires an inclusive education system. Understanding the science learning process of these students and determining their problems and needs in education constitute the basis of inclusive education. Therefore, it is crucial to evaluate the teaching strategies and material choices of science teachers to create an effective and accessible learning environment. School administrators are also decisive in providing support and resources, developing teachers and meeting the needs of this process. Therefore, this study aimed to examine the opinions of science teachers and school administrators working in secondary schools for the visually impaired about the difficulties encountered by students with visual impairment in science education and solution suggestions. Method: The present study was designed with case study, one of the qualitative research designs. The study group consisted of 24 participants, including 14 science teachers and 10 school administrators working in secondary schools for the visually impaired in Türkiye in the 2022-2023 academic year. The data were obtained through a semi-structured interview technique. Content analysis was used to analyse the data. Findings: The findings showed that the content of the curriculum was prepared intensively, the course duration was insufficient and the acquisitions were too many, teaching materials for many senses should be prepared and there were printing errors in the textbooks. It was determined that students had difficulties arising from the reader in the measurement and evaluation process. Discussion: The findings obtained in this study suggest that there are needs in providing science education for students with visual impairment. In the teaching of science course, the problems arising from the visual problems of students affected by visual impairment make it difficult for them to have the same opportunities as their peers with normal development. Thus, there is a need to determine the special needs of the students and make educational arrangements for their disability levels.

Localization and recognition of human action in 3D using transformers

Understanding a person’s behavior from their 3D motion sequence is a fundamental problem in computer vision with many applications. An important component of this problem is 3D action localization, which involves recognizing what actions a person is performing, and when the actions occur in the sequence. To promote the progress of the 3D action localization community, we introduce a new, challenging, and more complex benchmark dataset, BABEL-TAL (BT), for 3D action localization. Important baselines and evaluating metrics, as well as human evaluations, are carefully established on this benchmark. We also propose a strong baseline model, i.e., Localizing Actions with Transformers (LocATe), that jointly localizes and recognizes actions in a 3D sequence. The proposed LocATe shows superior performance on BABEL-TAL as well as on the large-scale PKU-MMD dataset, achieving state-of-the-art performance by using only 10% of the labeled training data. Our research could advance the development of more accurate and efficient systems for human behavior analysis, with potential applications in areas such as human-computer interaction and healthcare.

Remote sensing image road network detection based on channel attention mechanism

Extracting and detecting road network consistency from high-resolution remote sensing images has been a hot and difficult problem in the computer vision. Although it has made significant progress, there is still a phenomenon of high training accuracy but unsatisfactory actual extraction and detection results. The attention mechanism is one of the efficient and practical mechanisms in deep learning. It improves the performance of deep learning by selectively focusing on a portion of all information while ignoring other visible information, while effectively utilizing computing resources. Numerous experiments have also confirmed that the attention mechanism is resource-saving and effective. Its plug and play feature brings great convenience to programmers. In order to provide better road network detection results and solve the above problem, this paper combines the channel attention mechanism with ResNet and proposes SE-ResNet and ECA-ResNet for remote sensing image road network detection, making networks extract and learn road network features and ignore some non-road network features. The experimental results show that on the Massachusetts roads (MR) and CHN6-CUG roads datasets, ECA-ResNet and SE-ResNet based on channel attention mechanism perform similar to LeNet7 and ResNet in terms of accuracy, loss, accuracy convergence, and loss convergence, and even increase a certain computational burden. However, their final road network detection results (including road network detection pixel count, precision, recall, accuracy, IOU, F1 score, and actual road network detection result) of the former are significantly better than those of the latter. The channel attention mechanism makes the deep neural network pay more attention to the extraction and learning of road network features, while ignoring the extraction and learning of some non-road network features, which improves the accuracy of containing road network samples and reduces the accuracy of not containing road network samples. Therefore, the performance of ECA-ResNet and SE-ResNet is similar to that of LeNet7 and ResNet in the accuracy, loss, accuracy convergence and loss convergence, but the final road network detection results of ECA-ResNet and SE-ResNet are significantly better than those of LeNet7 and ResNet. Therefore, the proposed ECA-ResNet and SE-ResNet have broad application prospects in road network detection, especially ECA-ResNet.

Adenomas hipofisarios no funcionantes. Incidentaloma hipofisario

Non-functioning pituitary adenomas (NFPAs) are tumors of the pituitary gland that are usually benign and show no clinical or biochemical signs of excessive hormone production. These tumors manifest clinically when they are large enough to exert pressure on surrounding structures. Among pituitary incidentaloma, NFPAs are the most common, as they are often diagnosed accidentally during imaging tests performed for other reasons. To properly evaluate these tumors and their relationship to other structures, the use of contrast-enhanced MRI is preferred. In addition, it is necessary to perform a hormonal analysis to rule out hormonal alterations and a neuro-ophthalmological examination in those cases in which the adenomas are close to the optic chiasm or cavernous sinuses, or in patients who present vision problems. In cases where the tumors are symptomless, observation is an option. However, transsphenoidal surgery is the first-line treatment for patients with symptoms or large tumors. Other options include radiation therapy and medical treatment with dopaminergic agonists and other drugs that are being explored more recently.

MED13L-related disorder characterized by severe motor speech impairment.

MED13L-related disorder is associated with intellectual disability, motor delay, and speech deficits. Previous studies have focused on broad clinical descriptions of individuals, but limited information regarding specific speech diagnoses and results of direct testing has been published to date. We conducted deep phenotyping to characterize the speech, language, motor, cognitive, and adaptive phenotypes of individuals with MED13L-related disorder. In this cross-sectional study, we administered standardized articulation, language, motor, and cognitive testing to 17 children and adolescents (mean age 9y 9m; SD 4y 5m; range 4y 2m to 19y 7m). In-person testing was supplemented with broad developmental, medical, and behavioral information collected virtually from a cohort of 67 individuals. All individuals who completed in-person articulation testing met diagnostic criteria for speech apraxia, dysarthria, or both. Language impairment was present in all of the in-person cohort and almost all (97%) of the virtual cohort. Those who were able to complete motor testing demonstrated significant deficits in visual motor integration (mean 57.08, SD 9.26). Full scale IQs fell in the borderline to intellectual disability range, consistent with reported cognitive impairment in 97% of the virtual cohort. Notable medical features included hypotonia (83%), vision problems (72%), recurrent otitis media (58%), gastrointestinal problems (57%), and seizures (31%). MED13L-related disorder is characterized by a high rate of motor speech disorders that occur in the context of globally impaired motor, language, and cognitive skills. Children would benefit from intensive, individualized speech therapy and the early adoption of augmentative communication strategies.

Eye health knowledge, attitude, and practice among special school managers and barriers to eye health programmes in special schools in Hyderabad, India.

Children with special education needs (SEN) are at high risk of developing vision problems. In India, there is no data available on the awareness level of eye health needs of children with SEN among special school managers (SSM) and on the barriers to providing eye care for these children in schools. This study aimed to identify the awareness level among SSM and the barriers to organizing School Eye Health (SEH) programmes in special schools, as reported by the eye health program organizers. A mixed-method study was conducted between July and August 2020 among SSM and eye health programme organizers from a local eye care provider in Hyderabad, India. SSM participants completed an online questionnaire assessing their knowledge, attitude, and practice concerning the eye health needs of children with SEN. Quantitative responses were described with summary statistics. Qualitative interviews with eye health programme organizers were conducted via telephone, and transcripts were thematically analysed. Results: In total, 13/67 (19.4%) invited SSM participated and 2/4 invited eye health programme organizers (50%) were interviewed. Among the SSM participants, 92.3% were aware of vision impaired (VI) children in their schools. Awareness of potential causes of VI ranged from 53.9%-92.3%, common eye conditions ranged from 7.7%-69.2%, and difficulties experienced by children with SEN in classroom activities ranged from 46.2%-76.9%. Only 30.8% of the special schools organized SEH programmes at least once a year. Eye health programme organizers reported barriers, such as a lack of interest from SSM, unavailability of qualified screening staff, and a lack of provision for spectacles and low-vision devices. This study identified varied levels of knowledge, attitudes, and practices of SSM related to the eye health needs of children with SEN. Key barriers to conducting SEH programmes included a lack of demand, inadequate human resource availability, and limited access to government-funded resources. As the study was negatively impacted by the Covid pandemic, further research with wider representation is needed to plan comprehensive eye health programmes for children with SEN.

Deformable Capsules for Object Detection

Capsule networks promise significant benefits over convolutional neural networks (CNN) by storing stronger internal representations and routing information based on the agreement between intermediate representations’ projections. Despite this, their success has been limited to small‐scale classification datasets due to their computationally expensive nature. Though memory‐efficient, convolutional capsules impose geometric constraints that fundamentally limit the ability of capsules to model the pose/deformation of objects. Further, they do not address the bigger memory concern of class capsules scaling up to bigger tasks such as detection or large‐scale classification. Herein, a new family of capsule networks, deformable capsules (DeformCaps), is introduced to address object detection problem in computer vision. Two new algorithms associated with our DeformCaps, a novel capsule structure (SplitCaps), and a novel dynamic routing algorithm (SE‐Routing), which balance computational efficiency with the need for modeling a large number of objects and classes, are proposed. This has never been achieved with capsule networks before. The proposed methods efficiently scale up to create the first‐ever capsule network for object detection in the literature. The proposed architecture is a one‐stage detection framework and it obtains results on microsoft common objects in context which are on par with state‐of‐the‐art one‐stage CNN‐based methods, while producing fewer false‐positive detection, generalizing to unusual poses/viewpoints of objects.

Simultaneous image patch attention and pruning for patch selective transformer

Vision transformer models provide superior performance compared to convolutional neural networks for various computer vision tasks but require increased computational overhead with large datasets. This paper proposes a patch selective vision transformer that effectively selects patches to reduce computational costs while simultaneously extracting global and local self-representative patch information to maintain performance. The inter-patch attention in the transformer encoder emphasizes meaningful features by capturing the inter-patch relationships of features, and dynamic patch pruning is applied to the attentive patches using a learnable soft threshold that measures the maximum multi-head importance scores. The proposed patch attention and pruning method provides constraints to exploit dominant feature maps in conjunction with self-attention, thus avoiding the propagation of noisy or irrelevant information. The proposed patch-selective transformer also helps to address computer vision problems such as scale, background clutter, and partial occlusion, resulting in a lightweight and general-purpose vision transformer suitable for mobile devices.

Investigation of Spinocerebellar Ataxia (SCA) Disease in Iranian Patients and Accurate Trinucleotide Repeat Detection in the SCA3 by TP-PCR Method.

SCA (spinocerebellar ataxia) which is autosomal dominantly transferred is a subset of inherited cerebellar ataxia. These progressive neurological diseases have clinical features of ataxia and are derived from the destruction of the cerebellum. These diseases can also affect other areas, including the brainstem. Frequent proliferation of CAG nucleotides can encode polyglutamine and, as a result, produce the toxic polyglutamine (poly Q) protein that leads to many types of SCAs. They are categorized based on specific genetic mutations. The main symptoms of SCA, gait ataxia and incoordination, nystagmus, vision problems, and dysarthria, can be mentioned. In this study, 31 Iranians who were suspected of SCA disease were clinically diagnosed from November 2019 to September 2021. For these 31 patients suspected of spinocerebellar ataxia, PCR was performed, and the analysis was based on vertical electrophoresis. For SCA3 patients, the TP-PCR technique was carried out and evaluated by capillary electrophoresis. For all 31 patients, PCR function was successful according to the results attained by conventional PCR. The number of three nucleotide replications was within the normal range for 22 people, and nine patients were reported. Studies showed that three people suspected of SCA were infected with SCA3 according to the TP-PCR technique, and this was while seven people were diagnosed with SCA3 using the PCR method. As the purpose of this test is to provide a more accurate diagnostic method and prenatal diagnosis of this disease, the TP-PCR method proved to be more suitable when applied for the diagnosis of abnormal trinucleotides CAG in spinocerebellar ataxia type 3.

Quantum deep generative prior with programmable quantum circuits

Exploiting the utility of near-term quantum devices is a long-standing challenge whereas hybrid quantum machine learning emerges as a promising candidate. Here we propose a quantum-enhanced deep generative algorithm based on programmable quantum circuit-induced quantum latent codes. To validate the effectiveness of the algorithm, we conduct optical ghost imaging experiments, collecting dataset under varying physical sampling rates. Leveraging a physically enhanced loss function and a pretrained neural network, the quantum algorithm exhibits superior reconstruction performance compared to conventional algorithms. We observe the learnable quantum latent space enhances the out-of-distribution generalization capability of the pretrained model. In the context of computer vision problems, numerical results indicate that quantum latent space can increase the generation diversity of the pretrained model. Furthermore, the algorithm outperforms classical counterparts, particularly in image inpainting and colorization, by a significant margin. Our study demonstrates the utility of hybrid quantum-classical algorithms in enhancing generalization capability, highlighting the potential of near-term quantum devices in large-scale generative artificial intelligence.

Charles Bonnet Syndrome asssociated with glaucoma in a 95-year old female: A case report

Vision problems increase with age and evaluation of visual perception is important in geriatric practice. Visual hallucinations may occur in elderly individuals for various reasons. Hallucinations secondary to loss of severe visual acuity or visual field, also known as Charles Bonnet Syndrome(CBS), may be rarely seen. We reported a case of CBS secondary to glaucoma in a 95-year-old female patient. It is stated that this patient's visual hallucination has been developing for the last 3 years. The patient had simple hallucinations that were not related to dementia or psychotic disorder. The patient had accompanying depressive mood and fear of being alone. Visual hallucinations decreased after antidepressant treatment. The oldest known case of CBS is presented.