Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial Intelligence in Ophthalmic Surgery: Current Applications and Expectations

Abstract Artificial Intelligence (AI) has found rapidly growing applications in ophthalmology, achieving robust recognition and classification in most kind of ocular diseases. Ophthalmic surgery is one of the most delicate microsurgery, requiring high fineness and stability of surgeons. The massive demand of the AI assist ophthalmic surgery will constitute an important factor in boosting accelerate precision medicine. In clinical practice, it is instrumental to update and review the considerable evidence of the current AI technologies utilized in the investigation of ophthalmic surgery involved in both the progression and innovation of precision medicine. Bibliographic databases including PubMed and Google Scholar were searched using keywords such as “ophthalmic surgery”, “surgical selection”, “candidate screening”, and “robot-assisted surgery” to find articles about AI technology published from 2018 to 2023. In addition to the Editorials and letters to the editor, all types of approaches are considered. In this paper, we will provide an up-to-date review of artificial intelligence in eye surgery, with a specific focus on its application to candidate screening, surgery selection, postoperative prediction, and real-time intraoperative guidance.
High Step-Down Isolated PWM DC–DC Converter Based on Combining a Forward Converter With the Series-Capacitor Structure

Incorporating switched-capacitor structures into isolated dc-dc converters is a promising approach to alleviate the limitations of topologies fully based on the use of high step-down transformers. In this paper, the combination of a forward converter with a series-capacitor structure is proposed for applications that require a very high step-down conversion ratio, low output voltage ripple, high output current and isolation. The result of the combination only adds one series-capacitor, one inductor, one switch and one diode (or synchronous rectifier switch) to the component count of a conventional forward converter, thus avoiding the use of a complete second phase. The topology provides high step-down conversion ratio and low output voltage ripple, a characteristic that can be used to decrease the total energy stored by inductors (i.e., higher power density) and/or to reduce the switching frequency (i.e., higher efficiency). Moreover, the converter provides inherent current sharing between the two inductors, natural balance of the voltage across the series-capacitor and lower conduction losses. The converter operation is validated with a 100W and 48V-to-5/3.3/2.5/1.8V prototype that achieves a peak efficiency of 95.8% and a full load efficiency of 91.1%.
Key Factors affecting Entrepreneurship and Self-Employment Intentions among Social Sciences and Humanities Students

The concept of self-employment through entrepreneurial activities needs to be given attention by all parties, especially in helping to solve problems and challenges related to employment opportunities. Therefore, this study aims to examine the factors that influence the self-employment opportunity through entrepreneurial activities. Based on previous studies, there were four identified factors namely self-efficacy, recognition of opportunities, entrepreneurship education and attitudes towards entrepreneurship. For the purpose of this study, a survey was conducted using a questionnaire instrument and involved a total of 111 respondents consisting of year one to year three students from the Faculty of Social Sciences and Humanities. The data of this study was analysed using SPSS version 27 software which involved descriptive analysis, correlation and multiple regression. The findings of the study showed that the factors of self-efficacy and attitude towards entrepreneurship had an established and significant relationship with the intention to be self-employed while opportunity recognition and entrepreneurship education had a moderately strong relationship with intention to be self-employed. The findings also revealed that only two critical factors, namely self-efficacy and attitude towards entrepreneurship had a significant relationship with the self-employment intention while the other two variables; opportunity recognition and entrepreneurship education did not contribute to the intention to be self-employed. Based on the findings of the study, there is a need to improve the entrepreneurship education system and the exposure on opportunities in entrepreneurial activities that should be strengthened so that students can obtain benefits and knowledge regarding the concept of self-employment through entrepreneurial activities.
An Off-Pump Repair Technique for Postinfarction Apical Left Ventricular Aneurysm

Purpose: The conventional surgical treatment for postinfarction left ventricular aneurysm (LVA) is open-heart repair with cardiopulmonary bypass. However, the risk of the open-heart surgery under cardiopulmonary bypass may result in an unacceptable risk for many patients with multiple comorbidities. Here, we reported a new off-pump repair technique for postinfarction apical LVA. Methods: A new off-pump repair technique, circular banding and occlusion technique, was applied to repair the postinfarction apical LVA in 12 patients. Clinical data of all those 12 patients were retrospectively reviewed. Patients were followed up prospectively by direct interviews and echocardiographic examination. Results: The new repair technique was successfully performed in all these 12 patients. Acute reduction of the LVA mouth diameter, the left ventricular (LV) end-diastolic volume and end-systolic volume, and an increase in the LV ejection fraction (EF) were immediately obtained after the repair. Patients had an uneventful postoperative course. They were in New York Heart Association class 1–2, and the LV volume and EF detected by echocardiography remained unchanged during an average 28.4 ± 9.9 months (range 13 to 45 months) follow-up. Conclusions: Circular banding and occlusion is a simple, safe, and effective off-pump repair technique for postinfarction apical LVA. It can allow effective LV remodeling and improve heart function.
Generative Twin for 6G and Beyond 5G Networks: Vision, Challenges and Architecture

Within the current 6G and beyond 5G research, digital twins have become an indispensable asset for network management. These digital twins offer real-time and dynamic system representations, enabling precise decision-making and comprehensive testing in simulation environments before deployment. Going further, we introduce the novel concept of “Generative Twin”, an approach enabling the automatic generation system configurations and test system situations using Generative Artificial Intelligence (AI) and surpassing the limitations of human administrators. Our work reaches further, presenting a high-level architecture that outlines the additional functional elements and interfaces required to enhance the digital twins for 5G networks. We also demonstrate a mock-up simulation of information generation using the Large Language Model (LLM) ChatGPT and a best-practices digital twin based on the Open5GCore toolkit. Furthermore, we present a practical implementation roadmap, offering guidance for effective integration of generative twins and the technology challenges that necessitate further research, highlighting the very large potential of leveraging generative AI as an integral part of network management.
Estimating cardiac output from coronary CT angiography: an individualized compartment model in comparison to the Stewart–Hamilton method

Background Attenuation is correlated with the concentration of contrast medium (CM) in the arteries. The cardiac output (CO) affects the concentration of CM in the circulatory system; therefore, CO affects the time–density curve (TDC). Thus, estimating CO using TDC from test-bolus images acquired in computed tomography (CT) is possible. In this study, we compare two methods of estimating CO, namely, an individualized mathematical compartment model, integrating patient, contrast, and scanning factors with TDC, and the Stewart–Hamilton method based on the area under the curve of the TDC. Materials and methods Attenuation in the aorta was measured during test-bolus in 40 consecutive patients with a clinical indication for coronary CT angiography (CCTA). Each participant underwent cardiac magnetic resonance imaging following CCTA to validate the estimated CO. The individual compartment model used TDC in conjunction with scanning and patient-specific parameters to estimate the concentration of CM and CO over time. This was compared to the CO calculated from the area under the curve using the Stewart–Hamilton method. Results Both CO estimated with our individualized compartment model (r = 0.66, p < 0.01) and the Stewart–Hamilton method (r = 0.53, p < 0.01) were moderately correlated with CO measured with cardiac MRI. Body surface area (BSA) and time to peak (TTP) affected the accuracy of our model. Lower BSA resulted in overestimation, and lower TTP resulted in CO underestimation, respectively. We found no gender-specific difference in the accuracy of our model when correcting for BSA. The Stewart–Hamilton method performed better with a more complete TDC, whereas the compartment model performed better overall with a partial TDC. Conclusion The TDC acquired in CCTA allows for CO estimation. Both the Stewart–Hamilton method and our mathematical compartment model show moderate correlation when applied to our data, although each method has its strengths and limitations. If the majority of the TDC is known, the Stewart–Hamilton method may be more reliable, but an individual compartment model is preferable when there are insufficient data points in the TDC. Regardless, both methods can potentially increase the diagnostic information acquired from a CCTA, which is increasingly recommended in clinical guidelines.
Privacy-Preserving Spatial Keyword Search With Lightweight Access Control in Cloud Environments

As cloud computing continues to gain popularity, various applications have been deployed under Industrial Internet of Things (IIoT) scenarios. In order to alleviate the heavy burden of local storage and processing, a substantial amount of data is entrusted to the cloud server (CS), but attendant security risks like privacy leakages begin to appear. In addition, another vital security issue, access control, has come to attention. Many existing spatial keyword similarity search schemes are unable to implement access control. To solve these issues, we propose a novel scheme privacy-preserving spatial keyword similarity search with lightweight access control (PSKSSA) scheme. Specifically, we design an efficient access control IR-tree (ACIR-tree) that achieves sublinear query efficiency. Access control is implemented through role-based polynomial technology, which is integrated into the ACIR-tree and the query vector, so that spatial keywords and access control information are uniformly encoded into a vector. Meanwhile, privacy is protected by enhanced asymmetric scalar-product-preserving encryption (EASPE), which guarantees indistinguishability against the chosen-plaintext attack (IND-CPA) model. The most similar $k$ results are found by the CS while implementing access control for data users. Through formal analysis and extensive experiments, it has proved that the proposed scheme is safe and effective, with good scalability.
Automated Change Detection for Updates of Digital Map Databases

Updating digital map databases to reflect continuous changes is a major task, which could be significantly reduced by introducing an automated change-detection process. We suggest an algorithm inspired by the specific problem of updating the Danish National Topographic Map Database (TOP10DK). The emphasis is on buildings, which are very important mapping objects. The algorithm uses vector and spectral data as input to an unsupervised spectral classification method which controls a subsequent Mahalanobis classification step. For evaluation, we present four test cases based on the TOP10DK database in combination with RGB and color-infrared (CIR) aerial photos. A main problem is roofs covered with roofing felt, which are hard to discriminate spectrally from roads. Apart from that, RGB photos are barely sufficient for change detection, while CIR data give more satisfactory results. Refinements are, however, still needed to reduce the number of false alarms.
Genetic Susceptibility to Tardive Dyskinesia and Cognitive Impairments in Chinese Han Schizophrenia: Role of Oxidative Stress-Related and Adenosine Receptor Genes

Objective Tardive dyskinesia (TD) is a severe rhythmic movement disorder caused by long-term antipsychotic medication in chronic patients with schizophrenia (SCZ). We aimed to investigate the association between polymorphisms in oxidative stress-related genes (GSTM1, SOD2, NOS1, and NOS3) and adenosine receptor gene (ADORA2A), as well as their interactions, with the occurrence and severity of TD, and cognitive impairments in a Chinese Han population of SCZ patients. Methods Two hundred and sixteen SCZ patients were recruited and divided into TD group (n=157) and non-TD group (n=59). DNA extraction was performed by a high-salt method, followed by SNP genotyping using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The severity of TD, psychopathology and cognitive functioning were assessed using the Abnormal Involuntary Movement Scale (AIMS), the Positive and Negative Syndrome Scale (PANSS) and the Repeated Battery for Assessment of Neuropsychological Status (RBANS), respectively. Results The combination of GSTM1-rs738491, NOS1-rs738409 and ADORA2A-rs229883 was identified as the best three-point model to predict TD occurrence (p=0.01). Additionally, GSTM-rs738491 CC or NOS3-rs1800779 AG genotypes may be protective factors for psychiatric symptoms in TD patients. TD patients carrying the NOS1-rs738409 AG or ADORA2A-rs229883 TT genotypes exhibited poorer cognitive performance. Conclusion Our findings suggest that the interaction of oxidative stress-related genes and adenosine receptor gene may play a role in the susceptibility and severity of TD in Chinese Han SCZ patient. Furthermore, these genes may also affect the psychiatric symptoms and cognitive function of TD patients.
The Data Journalism Practices in the Production of Investigative News Videos by Narasi TV

The digital and open data era has given rise to the development of methods in data journalism to create an in-depth or investigative news report. The widespread use of social media, dominated by the Y and Z generations, has also encouraged journalists to present the story in attractive formats. As one of the digital media in Indonesia, Narasi TV has data-based long-form stories called Buka Mata, presented in video forms and published through various social media. This research aims to answer the question, “How does Narasi TV produce the data journalism videos in Buka Mata? ” to describe Narasi TV’s data journalism practices. This study uses a constructivist paradigm, a qualitative approach, and the case study method; and refers to the data journalism concept from The Data Journalism Handbook in 2012 to solve the research question. The findings show that Narasi TV has implemented data journalism practices such as gathering, verifying, analyzing, and visualizing data in producing Buka Mata. Furthermore, Narasi TV also uses an open-source intelligence (OSINT) method to create its investigative news videos.
Control of the Adsorption Behavior of Gas Molecule on Graphene by Strain: First-Principles Calculations for Development of Multi-Gas Selective Sensors

Graphene is a promising material for gas sensing because of its unique electrochemical properties. Previous studies have revealed that the adsorption and desorption of gas molecules on graphene were controlled by mechanical strain. In this study, first-principles calculation was applied to the investigation of the effect of tensile and compressive strains on the gas adsorption properties of graphene. It was found that the adsorption energy varied almost linearly with the applied strain due to the change of its electronic band structure and, consequently, it caused the change of the magnitude of the charge transfer between them. Among them, NO2 exhibited greater strain sensitivity, specifically, its adsorption energy increased by about 70% under compressive strain of 10%. The non-equilibrium green function (NEGF) method was also performed to confirm that the I-V characteristic was changed by the adsorption of gas molecules and strain. Notably, it was found that the change of current was about 14 times larger than that observed in 10%-tensile-strained graphene adsorbed with H2O system when no strain was applied. Overall, our results validated that tuning the gas binding behavior of graphene by application of strain is a promising approach for developing multi-gas sensors with high selectivity.
Quartz Crystal Microbalance Sensor Based on ZnO Nanofilm for Methanol Detection

Quartz crystal microbalance (QCM) gas sensors modified by ZnO nanofilms were prepared using a layer-by-layer self-assembly (LBLSA) technique for methanol detection under parts-per-million (ppm) concentration at room temperature. The ZnO nanofilm characterization results revealed the impact of the uniformly distributed surface, porous nanostructure, and the presence of oxygen vacancies on sensing performance. Moreover, a comparison was made on the gas sensing performance of ZnO nanofilms with various layer numbers (four–ten layers), and the results demonstrated that the eight-layer QCM sensor exhibited the best sensing performance, including a sensitivity of 0.17 Hz/ppm, a response time/recovery time of (10/179 s), a low detection limit of 1 ppm. The sensor exhibited an outstanding selectivity (48.6 Hz at 280 ppm) to methanol. Furthermore, the adsorption mechanism was presented to verify the gas adsorption–desorption phenomenon at different concentrations and the selectivity to methanol with the aid of density functional theory (DFT) calculation.
A time–frequency ridge extraction diagnostic method for composite faults of bearing gears in wind turbine gearboxes

The bearing and gear faults in the gearbox interact with each other, and the weak fault characteristics are often masked by the strong fault characteristics, making it difficult to accurately extract complete fault information. To solve this problem, a time–frequency ridge extraction diagnosis method based on multisynchrosqueezing transform (MSST) is proposed. This method utilizes MSST to enhance the compound fault features, especially the gear fault amplitude modulation components. It also utilizes the time–frequency ridge extraction method to separate the gear fault amplitude modulation components and the bearing fault impact pulse components. Additionally, it uses time shifting to substitute data and verifies the independence of the harmonic zero hypothesis to determine the accuracy of the fault components. This method provides a favorable basis for the extraction and identification of compound faults, especially weak faults, in complex dynamic signals of the gearbox. The effectiveness of this method is validated through simulation examples and practical applications.
Plume–Ridge Interaction: a Geochemical Perspective from the Reykjanes Ridge

Plume–ridge interaction in the Reykjanes Ridge and Iceland region of the underlying asthenosphere and focusing of melt is graphically demonstrated by several V-shaped ridges surrounding towards segment centres (Crane, 1985; Schouten et al., the spreading axis, indicating mantle flow away from Iceland. It 1985; Macdonald et al., 1988; Schouten & Whitehead, also has significant geochemical effects. Regionally, incompatible 1992). Yet despite a half-spreading rate of 10 mm/yr element concentrations increase northwards coinciding with decreasing (DeMets et al., 1994), the Reykjanes Ridge south of depth and increasing crustal thickness, depth of melting and proximity Iceland is continuous along strike for almost 1000 km to Iceland. Major and trace element data show that isolated magma (Talwani et al., 1971; Applegate & Shor, 1994). Thus its bodies feed individual volcanic systems along the ridge. Fractionation proximity to the Iceland plume appears to suppress ridge within these systems increases towards 60–61°N, where it coincides segmentation. One explanation for this may be that subwith the intersection of a V-shaped ridge, thicker crust and more horizontal asthenospheric flow beneath the ridge, driven abundant seamounts. Trace element, Nd and Sr isotopic data away from the Iceland plume by local buoyancy forces reveal dynamic melting and mixing within a southward-thinning, (Sleep, 1996), prevents organization in upwelling and heterogeneous mantle wedge beneath the Reykjanes Ridge. Melting melting. Such outflow, at a rate of 10–15 cm/yr, is is variable and locally enhanced at 58°N, 59°N, 60°N and 61°N. indicated by the presence of southward-closing V-shaped A total of six mantle components are identified. Some are specific ridges located symmetrically about the Reykjanes Ridge to Iceland whereas others are found only beneath the ridge axis. (Vogt, 1971, 1974; Vogt & Avery, 1974; Sandwell & The geographical distribution of these components reflects their origin Smith, 1992; White et al., 1995; Searle et al., 1998). within the deep upper and lower mantle and subsequent translation Alternatively, the Reykjanes Ridge may have segby plume outflow along the entire length of the ridge. mentation similar to other slow-spreading ridges but its tectonic and bathymetric expression is obscured by alongaxis flow of the lower crust resulting from higher mantle temperatures and thicker crust (Bell & Buck, 1992).
Maritime target identification in gated viewing imagery

The growing interest in unmanned surface vehicles, accident avoidance for naval vessels and automated maritime surveillance leads to a growing need for automatic detection, classification and pose estimation of maritime objects in medium and long ranges. Laser radar imagery is a well proven tool for near to medium range, but up to now for higher distances neither the sensor range nor the sensor resolution was satisfying. As a result of the mentioned limitations of laser radar imagery the potential of laser illuminated gated viewing for automated classification and pose estimation was investigated. The paper presents new techniques for segmentation, pose estimation and model-based identification of naval vessels in gated viewing imagery in comparison with the corresponding results of long range data acquired with a focal plane array laser radar system. The pose estimation in the gated viewing data is directly connected with the model-based identification which makes use of the outline of the object. By setting a sufficient narrow gate, the distance gap between the upper part of the ship and the background leads to an automatic segmentation. By setting the gate the distance to the object is roughly known. With this distance and the imaging properties of the camera, the width of the object perpendicular to the line of sight can be calculated. For each ship in the model library a set of possible 2D appearances in the known distance is calculated and the resulting contours are compared with the measured 2D outline. The result is a match error for each reasonable orientation of each model of the library. The result gained from the gated viewing data is compared with the results of target identification by laser radar imagery of the same maritime objects.