The Impact of Information Explicitness and Timing on Facilitating Online Learning: A Field Experiment

Online learning systems aim to support learners’ learning process by providing various kinds of information. However, scarce research has focused on examining whether such information support can indeed foster an active learning process and ultimately achieve enhanced learning outcome. This study draws upon active learning theory, which posits that effective information support should facilitate learners’ “generation” and “reflection” process. We examined two characteristics of information support to facilitate such an active learning process, information explicitness and presentation timing (during or after a learning task). A field experiment was conducted on an online learning platform. Our findings revealed that when provided during a task, less explicit information would improve learning outcomes by encouraging generation activities. Furthermore, for learners with a stronger knowledge base, more explicit information support provided after a task assisted in the reflection process, leading to improved learning outcomes. The mechanisms were revealed by using cursor tracking technology

Swashplateless-elevon Actuation for a Dual-rotor Tail-sitter VTOL UAV

In this paper, we propose a novel swashplateless-elevon actuation (SEA) for dual-rotor tail-sitter vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs). In contrast to the conventional elevon actuation (CEA) which controls both pitch and yaw using elevons, the SEA adopts swashplateless mechanisms to generate an extra moment through motor speed modulation to control pitch and uses elevons solely for controlling yaw, without requiring additional actuators. This decoupled control strategy mitigates the saturation of elevons' deflection needed for large pitch and yaw control actions, thus improving the UAV's control performance on trajectory tracking and disturbance rejection performance in the presence of large external disturbances. Furthermore, the SEA overcomes the actuation degradation issues experienced by the CEA when the UAV is in close proximity to the ground, leading to a smoother and more stable take-off process. We validate and compare the performances of the SEA and the CEA in various real-world flight conditions, including take-off, trajectory tracking, and hover flight and position steps under external disturbance. Experimental results demonstrate that the SEA has better performances than the CEA. Moreover, we verify the SEA's feasibility in the attitude transition process and fixed-wing-mode flight of the VTOL UAV. The results indicate that the SEA can accurately control pitch in the presence of high-speed incoming airflow and maintain a stable attitude during fixed-wing mode flight. Video of all experiments can be found in youtube.com/watch?v=Sx9Rk4Zf7sQComment: 8 pages, 13 figure

Case report: Oxaliplatin-induced idiopathic non-cirrhotic portal hypertension: a case report and literature review

Oxaliplatin has become a widely used agent in neoadjuvant chemotherapy for gastrointestinal tract tumors and is an integral part of the therapeutic approach for managing colorectal cancer recurrences and metastases, resulting in a more favorable prognosis for patients. Nevertheless, oxaliplatin can give rise to idiopathic non-cirrhotic portal hypertension (INCPH). The emergence of INCPH can disrupt tumor chemotherapy and incite persistent adverse reactions in later stages, significantly complicating clinical management. Consequently, we have presented a case report of INCPH induced by oxaliplatin chemotherapy with the aim of advancing the diagnosis and treatment of this condition, with a particular focus on the clinical manifestations. This study has ascertained that the condition is primarily attributed to complications related to portal hypertension, such as gastrointestinal bleeding, splenomegaly, and hypersplenism. The pathological features primarily involve hepatic sinus dilation and congestion, portal obstruction, absence, stenosis, shunting, localized venous and perisinusoidal fibrosis, as well as hepatocellular atrophy. Treatment primarily concentrates on strategies typically employed for cirrhosis. Endoscopic ligation, sclerotherapy, and non-selective beta-blockers (NSBBs) can be selected to prevent and treat variceal hemorrhage. Transjugular intrahepatic portosystemic shunt (TIPS) and liver transplantation can also be chosen for severe cases. Notably, despite the timely discontinuation of oxaliplatin, most patients continue to experience disease progression, ultimately resulting in a poor prognosis due to either tumor advancement or the ongoing progression of portal hypertension. This emphasizes the importance for physicians to be aware of and consider the risk of INCPH when prescribing oxaliplatin

One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusion

Recent advancements in open-world 3D object generation have been remarkable, with image-to-3D methods offering superior fine-grained control over their text-to-3D counterparts. However, most existing models fall short in simultaneously providing rapid generation speeds and high fidelity to input images - two features essential for practical applications. In this paper, we present One-2-3-45++, an innovative method that transforms a single image into a detailed 3D textured mesh in approximately one minute. Our approach aims to fully harness the extensive knowledge embedded in 2D diffusion models and priors from valuable yet limited 3D data. This is achieved by initially finetuning a 2D diffusion model for consistent multi-view image generation, followed by elevating these images to 3D with the aid of multi-view conditioned 3D native diffusion models. Extensive experimental evaluations demonstrate that our method can produce high-quality, diverse 3D assets that closely mirror the original input image. Our project webpage: https://sudo-ai-3d.github.io/One2345plus_page

Accio: Variable-Amount, Optimized-Unlinkable and NIZK-Free Off-Chain Payments via Hubs

Payment channel hubs (PCHs) serve as a promising solution to achieving quick off-chain payments between pairs of users. They work by using an untrusted tumbler to relay the payments between the payer and payee and enjoy the advantages of low cost and high scalability. However, the most recent privacy-preserving payment channel hub solution that supports variable payment amounts suffers from limited unlinkability, e.g., being vulnerable to the abort attack. Moreover, this solution utilizes non-interactive zero-knowledge proofs, which bring huge costs on both computation time and communication overhead. Therefore, how to design PCHs that support variable amount payments and unlinkability, but reduce the use of huge-cost cryptographic tools as much as possible, is significant for the large-scale practical applications of off-chain payments. In this paper, we propose Accio, a variable amount payment channel hub solution with optimized unlinkability, by deepening research on unlinkability and constructing a new cryptographic tool. We provide the detailed Accio protocol and formally prove its security and privacy under the Universally Composable framework. Our prototype demonstrates its feasibility and the evaluation shows that Accio outperforms the other state-of-the-art works in both communication and computation costs

Risk factors and prediction model of sleep disturbance in patients with maintenance hemodialysis: A single center study

ObjectivesThis study aimed to explore the risk factors and develop a prediction model of sleep disturbance in maintenance hemodialysis (MHD) patients.MethodsIn this study, 193 MHD patients were enrolled and sleep quality was assessed by Pittsburgh Sleep Quality Index. Binary logistic regression analysis was used to explore the risk factors for sleep disturbance in MHD patients, including demographic, clinical and laboratory parameters, and that a prediction model was developed on the basis of risk factors by two-way stepwise regression. The final prediction model is displayed by nomogram and verified internally by bootstrap resampling procedure.ResultsThe prevalence of sleep disturbance and severe sleep disturbance in MHD patients was 63.73 and 26.42%, respectively. Independent risk factors for sleep disturbance in MHD patients included higher 0.1*age (OR = 1.476, 95% CI: 1.103–1.975, P = 0.009), lower albumin (OR = 0.863, 95% CI: 0.771–0.965, P = 0.010), and lower 10*calcium levels (OR = 0.747, 95% CI: 0.615–0.907, P = 0.003). In addition, higher 0.1*age, lower albumin levels, and anxiety were independently associated with severe sleep disturbance in MHD patients. A risk prediction model of sleep disturbance in MHD patients showed that the concordance index after calibration is 0.736, and the calibration curve is approximately distributed along the reference line.ConclusionsOlder age, lower albumin and calcium levels are higher risk factors of sleep disturbance in MHD, and the prediction model for the assessment of sleep disturbance in MHD patients has excellent discrimination and calibration

Heliaquanoids A–E, five sesquiterpenoid dimers from Inula helianthus-aquatica

Heliaquanoid A (1), the first exo-2,4-linked Diels−Alder adduct between a pseudoguaianolide dienophile and a guaianolide diene, and heliaquanoids B−E (2−5), four new 2,4-linked Diels−Alder adducts between a xanthanolide dienophile and a guaianolide diene, were isolated from stems and leaves of Inula helianthus-aquatica. Their structures were determined by the NMR spectroscopy, modified Mosher′s method, electronic circular dichroism, and X-ray diffraction analysis. Compounds 2 and 3 exhibited moderate cytotoxic activities against HL-60 cells with IC50 values of 7.5 and 4.9 μM, respectively

Multi-Granularity Detector for Vulnerability Fixes

With the increasing reliance on Open Source Software, users are exposed to third-party library vulnerabilities. Software Composition Analysis (SCA) tools have been created to alert users of such vulnerabilities. SCA requires the identification of vulnerability-fixing commits. Prior works have proposed methods that can automatically identify such vulnerability-fixing commits. However, identifying such commits is highly challenging, as only a very small minority of commits are vulnerability fixing. Moreover, code changes can be noisy and difficult to analyze. We observe that noise can occur at different levels of detail, making it challenging to detect vulnerability fixes accurately. To address these challenges and boost the effectiveness of prior works, we propose MiDas (Multi-Granularity Detector for Vulnerability Fixes). Unique from prior works, Midas constructs different neural networks for each level of code change granularity, corresponding to commit-level, file-level, hunk-level, and line-level, following their natural organization. It then utilizes an ensemble model that combines all base models to generate the final prediction. This design allows MiDas to better handle the noisy and highly imbalanced nature of vulnerability-fixing commit data. Additionally, to reduce the human effort required to inspect code changes, we have designed an effort-aware adjustment for Midas's outputs based on commit length. The evaluation results demonstrate that MiDas outperforms the current state-of-the-art baseline in terms of AUC by 4.9% and 13.7% on Java and Python-based datasets, respectively. Furthermore, in terms of two effort-aware metrics, EffortCost@L and Popt@L, MiDas also outperforms the state-of-the-art baseline, achieving improvements of up to 28.2% and 15.9% on Java, and 60% and 51.4% on Python, respectively