Serious games for energy social science research

This paper proposes a set of criteria for evaluation of serious games (SGs) which are intended as effective methods of engaging energy users and lowering consumption. We discuss opportunities for using SGs in energy research which go beyond existing feedback mechanisms, including use of immersive virtual worlds for learning and testing behaviours, and sparking conversations within households. From a review of existing SG evaluation criteria, we define a tailored set of criteria for energy SG development and evaluation. The criteria emphasise the need for the game to increase energy literacy through applicability to real-life energy use/management; clear, actionable goals and feedback; ways of comparing usage socially and personal relevance. Three existing energy games are evaluated according to this framework. The paper concludes by outlining directions for future development of SGs as an effective tool in social science research, including games which inspire reflection on trade-offs and usage at different scales

Automatic coronary artery segmentation of CCTA images using UNet with a local contextual transformer

Coronary artery segmentation is an essential procedure in the computer-aided diagnosis of coronary artery disease. It aims to identify and segment the regions of interest in the coronary circulation for further processing and diagnosis. Currently, automatic segmentation of coronary arteries is often unreliable because of their small size and poor distribution of contrast medium, as well as the problems that lead to over-segmentation or omission. To improve the performance of convolutional-neural-network (CNN) based coronary artery segmentation, we propose a novel automatic method, DR-LCT-UNet, with two innovative components: the Dense Residual (DR) module and the Local Contextual Transformer (LCT) module. The DR module aims to preserve unobtrusive features through dense residual connections, while the LCT module is an improved Transformer that focuses on local contextual information, so that coronary artery-related information can be better exploited. The LCT and DR modules are effectively integrated into the skip connections and encoder-decoder of the 3D segmentation network, respectively. Experiments on our CorArtTS2020 dataset show that the dice similarity coefficient (DSC), Recall, and Precision of the proposed method reached 85.8%, 86.3% and 85.8%, respectively, outperforming 3D-UNet (taken as the reference among the 6 other chosen comparison methods), by 2.1%, 1.9%, and 2.1%

A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information

We propose a region growing vessel segmentation algorithm based on spectrum information. First, the algorithm does Fourier transform on the region of interest containing vascular structures to obtain its spectrum information, according to which its primary feature direction will be extracted. Then combined edge information with primary feature direction computes the vascular structure’s center points as the seed points of region growing segmentation. At last, the improved region growing method with branch-based growth strategy is used to segment the vessels. To prove the effectiveness of our algorithm, we use the retinal and abdomen liver vascular CT images to do experiments. The results show that the proposed vessel segmentation algorithm can not only extract the high quality target vessel region, but also can effectively reduce the manual intervention.</jats:p

SoK: FHE-Friendly Symmetric Ciphers and Transciphering

Fully Homomorphic Encryption (FHE) enables computation on encrypted data without decryption, demonstrating significant potential for privacy-preserving applications. However, FHE faces several challenges, one of which is the significant plaintext-to-ciphertext expansion ratio, resulting in high communication overhead between client and server. The transciphering technique can effectively address this problem by first encrypting data with a space-efficient symmetric cipher, then converting symmetric ciphertext to FHE ciphertext without decryption. Numerous FHE-friendly symmetric ciphers and transciphering methods have been developed by researchers, each with unique advantages and limitations. These often require extensive knowledge of both symmetric cryptography and FHE to fully grasp, making comparison and selection among these schemes challenging. To address this, we conduct a comprehensive survey of over 20 FHE-friendly symmetric ciphers and transciphering methods, evaluating them based on criteria such as security level, efficiency, and compatibility. We have designed and executed experiments to benchmark the performance of the feasible combinations of symmetric ciphers and transciphering methods across various application scenarios. Our findings offer insights into achieving efficient transciphering tailored to different task contexts. Additionally, we make our example code available open-source, leveraging state-of-the-art FHE implementations

SoK: FHE-Friendly Symmetric Ciphers and Transciphering

Fully Homomorphic Encryption (FHE) enables computation on encrypted data without decryption, demonstrating significant potential for privacy-preserving applications. However, FHE faces several challenges, one of which is the significant plaintext-to-ciphertext expansion ratio, resulting in high communication overhead between client and server. The transciphering technique can effectively address this problem by first encrypting data with a space-efficient symmetric cipher, then converting symmetric ciphertext to FHE ciphertext without decryption. Numerous FHE-friendly symmetric ciphers and transciphering methods have been developed by researchers, each with unique advantages and limitations. These often require extensive knowledge of both symmetric cryptography and FHE to fully grasp, making comparison and selection among these schemes challenging. To address this, we conduct a comprehensive survey of over 20 FHE-friendly symmetric ciphers and transciphering methods, evaluating them based on criteria such as security level, efficiency, and compatibility. We have designed and executed experiments to benchmark the performance of the feasible combinations of symmetric ciphers and transciphering methods across various application scenarios. Our findings offer insights into achieving efficient transciphering tailored to different task contexts. Additionally, we make our example code available open-source, leveraging state-of-the-art FHE implementations

Prognostic value of the ascites characteristics in pseudomyxoma peritonei originating from the appendix

BackgroundPseudomyxoma peritonei (PMP) is a rare disease, with the overall survival (OS) influenced by many factors. To date, no ascites characteristics have been reported to predict OS of patients with PMP. The present study therefore aims to describe the ascites characteristics for PMP and identify prognostic factors for survival.MethodsBetween June 2010 and June 2020, 473 PMP patients who underwent cytoreductive surgery and hyperthermic intraperitoneal chemotherapy were included in a retrospective study. Survival analysis was performed with the Kaplan–Meier method by the log-rank test and a Cox proportional hazards model. Associations between categorical variables were analyzed using the chi-squared test.ResultsAmong all included patients, 61% were women. The median OS was 47 months (range, 4–124 months) at the last follow-up in December 2020. Ascites characteristics can be divided into light blood ascites, “Jelly” mucus ascites, and faint yellow and clear ascites. Multivariate Cox analysis showed that the degree of radical surgery, ascites characteristics, and pathological grade were independently associated with OS in PMP patients. The chi-squared test documented that faint yellow “Jelly” ascites were related to low-grade PMP and light blood ascites were associated with high-grade PMP (P &lt; 0.01).ConclusionsLight blood ascites, incomplete cytoreduction surgery, and high-grade histopathology may predict poor OS in appendix-derived PMP

Mechanism of Bazhen decoction in the treatment of colorectal cancer based on network pharmacology, molecular docking, and experimental validation

ObjectiveBazhen Decoction (BZD) is a common adjuvant therapy drug for colorectal cancer (CRC), although its anti-tumor mechanism is unknown. This study aims to explore the core components, key targets, and potential mechanisms of BZD treatment for CRC.MethodsThe Traditional Chinese Medicine Systems Pharmacology (TCMSP) was employed to acquire the BZD’s active ingredient and targets. Meanwhile, the Drugbank, Therapeutic Target Database (TTD), DisGeNET, and GeneCards databases were used to retrieve pertinent targets for CRC. The Venn plot was used to obtain intersection targets. Cytoscape software was used to construct an “herb-ingredient-target” network and identify core targets. GO and KEGG pathway enrichment analyses were conducted using R language software. Molecular docking of key ingredients and core targets of drugs was accomplished using PyMol and Autodock Vina software. Cell and animal research confirmed Bazhen Decoction efficacy and mechanism in treating colorectal cancer.ResultsBZD comprises 173 effective active ingredients. Using four databases, 761 targets related to CRC were identified. The intersection of BZD and CRC yielded 98 targets, which were utilized to construct the “herb-ingredient-target” network. The four key effector components with the most targets were quercetin, kaempferol, licochalcone A, and naringenin. Protein-protein interaction (PPI) analysis revealed that the core targets of BZD in treating CRC were AKT1, MYC, CASP3, ESR1, EGFR, HIF-1A, VEGFR, JUN, INS, and STAT3. The findings from molecular docking suggest that the core ingredient exhibits favorable binding potential with the core target. Furthermore, the GO and KEGG enrichment analysis demonstrates that BZD can modulate multiple signaling pathways related to CRC, like the T cell receptor, PI3K-Akt, apoptosis, P53, and VEGF signaling pathway. In vitro, studies have shown that BZD dose-dependently inhibits colon cancer cell growth and invasion and promotes apoptosis. Animal experiments have shown that BZD treatment can reverse abnormal expression of PI3K, AKT, MYC, EGFR, HIF-1A, VEGFR, JUN, STAT3, CASP3, and TP53 genes. BZD also increases the ratio of CD4+ T cells to CD8+ T cells in the spleen and tumor tissues, boosting IFN-γ expression, essential for anti-tumor immunity. Furthermore, BZD has the potential to downregulate the PD-1 expression on T cell surfaces, indicating its ability to effectively restore T cell function by inhibiting immune checkpoints. The results of HE staining suggest that BZD exhibits favorable safety profiles.ConclusionBZD treats CRC through multiple components, targets, and metabolic pathways. BZD can reverse the abnormal expression of genes such as PI3K, AKT, MYC, EGFR, HIF-1A, VEGFR, JUN, STAT3, CASP3, and TP53, and suppresses the progression of colorectal cancer by regulating signaling pathways such as PI3K-AKT, P53, and VEGF. Furthermore, BZD can increase the number of T cells and promote T cell activation in tumor-bearing mice, enhancing the immune function against colorectal cancer. Among them, quercetin, kaempferol, licochalcone A, naringenin, and formaronetin are more highly predictive components related to the T cell activation in colorectal cancer mice. This study is of great significance for the development of novel anti-cancer drugs. It highlights the importance of network pharmacology-based approaches in studying complex traditional Chinese medicine formulations

Co-composting of tail vegetable with flue-cured tobacco leaves: analysis of nitrogen transformation and estimation as a seed germination agent for halophyte

Resource utilization of tail vegetables has raised increasing concerns in the modern agriculture. However, the effect and related mechanisms of flue-cured tobacco leaves on the product quality, phytotoxicity and bacterially-mediated nitrogen (N) transformation process of tail vegetable composting were poorly understood. Amendments of high-dosed (5% and 10% w/w) tobacco leaves into the compost accelerated the heating process, prolonged the time of thermophilic stage, increased the peak temperature, thereby improving maturity and shortening composting duration. The tobacco leaf amendments at the 10% (w/w) increased the N conservation (TN and NH4-N content) of compost, due to the supply of N-containing nutrient and promotion of organic matter degradation by tobacco leaves. Besides, tobacco leaf amendments promoted the seed germination and root development of wild soybean, exhibiting the feasibility of composting product for promoting the growth of salt-tolerant plants, but no dose-dependent effect was found for tobacco leaf amendments. Addition of high dosed (5% and 10% w/w) tobacco leaves shifted the bacterial community towards lignocellulosic and N-fixing bacteria, contributing to increasing the compost maturity and N retention. PICRUSt 2 functional prediction revealed that N-related bacterial metabolism (i.e., hydroxylamine oxidation and denitrifying process) was enhanced in the tobacco leaf treatments, which contributed to N retention and elevated nutrient quality of composting. To the best knowledge, this was the first study to explore the effect of tobacco waste additives on the nutrient transformation and halophyte growth promotion of organic waste composting. These findings will deepen the understanding of microbially-mediated N transformation and composting processes involving flue-cured tobacco leaves

Fine-tuning of microglia polarization prevents diabetes-associated cerebral atherosclerosis

Diabetes increases the occurrence and severity of atherosclerosis. When plaques form in brain vessels, cerebral atherosclerosis causes thickness, rigidity, and unstableness of cerebral artery walls, leading to severe complications like stroke and contributing to cognitive impairment. So far, the molecular mechanism underlying cerebral atherosclerosis is not determined. Moreover, effective intervention strategies are lacking. In this study, we showed that polarization of microglia, the resident macrophage in the central nervous system, appeared to play a critical role in the pathological progression of cerebral atherosclerosis. Microglia likely underwent an M2c-like polarization in an environment long exposed to high glucose. Experimental suppression of microglia M2c polarization was achieved through transduction of microglia with an adeno-associated virus (serotype AAV-PHP.B) carrying siRNA for interleukin-10 (IL-10) under the control of a microglia-specific TMEM119 promoter, which significantly attenuated diabetes-associated cerebral atherosclerosis in a mouse model. Thus, our study suggests a novel translational strategy to prevent diabetes-associated cerebral atherosclerosis through in vivo control of microglia polarization