Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning

We address two major challenges in scientific machine learning (SciML): interpretability and computational efficiency. We increase the interpretability of certain learning processes by establishing a new theoretical connection between optimization problems arising from SciML and a generalized Hopf formula, which represents the viscosity solution to a Hamilton-Jacobi partial differential equation (HJ PDE) with time-dependent Hamiltonian. Namely, we show that when we solve certain regularized learning problems with integral-type losses, we actually solve an optimal control problem and its associated HJ PDE with time-dependent Hamiltonian. This connection allows us to reinterpret incremental updates to learned models as the evolution of an associated HJ PDE and optimal control problem in time, where all of the previous information is intrinsically encoded in the solution to the HJ PDE. As a result, existing HJ PDE solvers and optimal control algorithms can be reused to design new efficient training approaches for SciML that naturally coincide with the continual learning framework, while avoiding catastrophic forgetting. As a first exploration of this connection, we consider the special case of linear regression and leverage our connection to develop a new Riccati-based methodology for solving these learning problems that is amenable to continual learning applications. We also provide some corresponding numerical examples that demonstrate the potential computational and memory advantages our Riccati-based approach can provide

Modelling and Performance Analysis of the Over-the-Air Computing in Cellular IoT Networks

Ultra-fast wireless data aggregation (WDA) of distributed data has emerged as a critical design challenge in the ultra-densely deployed cellular internet of things network (CITN) due to limited spectral resources. Over-the-air computing (AirComp) has been proposed as an effective solution for ultra-fast WDA by exploiting the superposition property of wireless channels. However, the effect of access radius of access point (AP) on the AirComp performance has not been investigated yet. Therefore, in this work, the mean square error (MSE) performance of AirComp in the ultra-densely deployed CITN is analyzed with the AP access radius. By modelling the spatial locations of internet of things devices as a Poisson point process, the expression of MSE is derived in an analytical form, which is validated by Monte Carlo simulations. Based on the analytical MSE, we investigate the effect of AP access radius on the MSE of AirComp numerically. The results show that there exists an optimal AP access radius for AirComp, which can decrease the MSE by up to 12.7%. It indicates that the AP access radius should be carefully chosen to improve the AirComp performance in the ultra-densely deployed CITN

Coffee: Cost-Effective Edge Caching for 360 Degree Live Video Streaming

While live 360 degree video streaming delivers immersive viewing experience, it poses significant bandwidth and latency challenges for content delivery networks. Edge servers are expected to play an important role in facilitating live streaming of 360 degree videos. In this paper, we propose a novel predictive edge caching algorithm (Coffee) for live 360 degree video that employ collaborative FoV prediction and predictive tile prefetching to reduce bandwidth consumption, streaming cost and improve the streaming quality and robustness. Our light-weight caching algorithms exploit the unique tile consumption patterns of live 360 degree video streaming to achieve high tile caching gains. Through extensive experiments driven by real 360 degree video streaming traces, we demonstrate that edge caching algorithms specifically designed for live 360 degree video streaming can achieve high streaming cost savings with small edge cache space consumption. Coffee, guided by viewer FoV predictions, significantly reduces back-haul traffic up to 76% compared to state-of-the-art edge caching algorithms. Furthermore, we develop a transcoding-aware variant (TransCoffee) and evaluate it using comprehensive experiments, which demonstrate that TransCoffee can achieve 63\% lower cost compared to state-of-the-art transcoding-aware approaches

Adverse renal outcomes following targeted therapies in renal cell carcinoma: a systematic review and meta-analysis

Introduction: To clarify the prevalence of adverse renal outcomes following targeted therapies in renal cell carcinoma (RCC).Methods: A systematic search was performed in MEDLINE, EMBASE, and Cochrane Central Library. Studies that had reported adverse renal outcomes following targeted therapies in RCC were eligible. Outcomes included adverse renal outcomes defined as either renal dysfunction as evidenced by elevated serum creatinine levels or the diagnosis of acute kidney injury, or proteinuria as indicated by abnormal urine findings. The risk of bias was assessed according to Cochrane handbook guidelines. Publication bias was assessed using Funnel plot analysis and Egger Test.Results: The occurrences of the examined outcomes, along with their corresponding 95% confidence intervals (CIs), were combined using a random-effects model. In all, 23 studies including 10 RCTs and 13 observational cohort studies were included. The pooled incidence of renal dysfunction and proteinuria following targeted therapies in RCC were 17% (95% CI: 12%–22%; I2 = 88.5%, p < 0.01) and 29% (95% CI: 21%–38%; I2 = 93.2%, p < 0.01), respectively. The pooled incidence of both types of adverse events varied substantially across different regimens. Occurrence is more often in polytherapy compared to monotherapy. The majority of adverse events were rated as CTCAE grades 1 or 2 events. Four studies were assessed as having low risk of bias.Conclusion: Adverse renal outcomes reflected by renal dysfunction and proteinuria following targeted therapies in RCC are not uncommon and are more often observed in polytherapy compared to monotherapy. The majority of the adverse events were of mild severity.Systematic Review Registration: Identifier CRD42023441979

Indian Summer Monsoon variations and competing influences between hemispheres since ~35 ka recorded in Tengchongqinghai Lake, southwest China

The southwestern Yunnan Province of China, which is located at the southeastern margin of the Tibetan Plateau and close to Bay of Bengal, is significantly influenced by the Indian Summer Monsoon (ISM). In this study, we reconstruct proxies for the ISM from 35 to 1 ka through detailed analysis of grain-size distribution, geochemical composition and environmental magnetism from a 7.96 m sediment core from Tengchongqinghai Lake, Yunnan Province, China. Globally recognized, abrupt climatic events, including Heinrich Events 0–3 (H0−H3) and the Bølling-Allerød (B/A) warm period are identified in most of our proxies, and the long-term trend is consistent with other published records such as stalagmite oxygen isotopes (δ18O) from Sangxing Cave. Northern Hemisphere (NH) temperature, which is influenced by NH solar insolation, is commonly suggested to play a dominant role in controlling the ISM. A comparison of our record with the δ18O variations of ice cores from Greenland and Antarctica, a sea surface temperature (SST) record from the Bay of Bengal, and summer solar insolation at 25°N latitude demonstrates that the general pattern of ISM change does follow variations in summer insolation; however, the ISM lags summer insolation by thousands of years. While the ISM fluctuations are highly correlated with NH temperature on shorter timescales (centennial-millennial), the gradually weakened ISM from 22.5 ka until the Last Glacial Maximum (LGM) indicates a close relationship with the rise of Southern Hemisphere (SH) temperature and the relatively cold background of the SH. Our record expands on the findings of ISM records from Heqing paleolake basin in southwestern China and the Arabian Sea sediments, suggesting that the NH and SH have a competitive influence on ISM by controlling the cross-equatorial pressure gradient. This relationship means that when NH temperatures are relatively high, it has a stronger influence on the ISM than SH influences. In contrast, when the SH temperature is relatively low, it has a dominant influence on ISM. In addition, we speculate that the change of SH temperature not only influences the cross-equatorial pressure gradient directly, but also likely modulates the circulation system of ocean energy by influencing the Atlantic Meridional Overturning Circulation (AMOC)

Full-Color Micro-LED Devices Based on Quantum Dots

Quantum dots (QDs) show remarkable optical and electrical characteristics. They offer the advantage of combining micro-LEDs (μLEDs) for full-color display devices due to their exceptional features. In addition, μLED used in conjunction with QDs as color-conversion layers also provide efficient white LEDs for high-speed visible light communication (VLC). In this article, we comprehensively review recent progress in QD-based μLED devices. It includes the research status of various QDs and white LEDs based on QDs’ color conversion layers. The fabrication of QD-based high-resolution full-color μLEDs is also discussed. Including charge-assisted layer-by-layer (LbL), aerosol jet printing, and super inkjet printing methods to fabricate QD-based μLEDs. The use of quantum dot photoresist in combination with semipolar μLEDs is also described. Finally, we discuss the research of QD-based μLEDs for visible light communication

Factors influencing the level of insight and treatment attitude: a cross-sectional study of 141 elderly patients of major depression in Guangzhou, China

ObjectiveTo explore the insight, treatment attitude, and related influencing factors of hospitalized elderly patients suffering from major depression.MethodsA total of 141 hospitalized elderly patients with depression were selected as the research objects. Insight was evaluated by the total score of the Insight and Treatment Attitude questionnaire (ITAQ). The data collected included sociodemographic characteristics, psychiatric symptoms, delirium status, social functioning, social support, suicide risk, and cognitive function.ResultsThe sample included 74.5% of female patients, and the mean age was 67.53 (sd=7.19) years. The influencing factors of inpatients with depression included alcohol consumption, length of hospitalization, admission types, and the main caregivers (P<0.05). The various factors were further analyzed by linear regression, revealing that the insight and treatment attitude of elderly depressed hospitalized patients were mainly related to the Mini-Mental State Examination (MMSE) (β= 0.225, 95% CI 0.055–0.395, P=0.01), dependent on a caregiver (β=-5.810, 95% CI -8.086~-3.535, P<0.001), the type of admission (involuntary admission) (β=-3.365, 95% CI -5.448~-1.283, P=0.002), Functional Activities Questionnaire (FAQ) (β=-0.156, 95% CI -0.303~-0.010, P=0.037), and length of stay (≤28 days) (β=2.272, 95% CI 0.055~-4.489, P=0.045).ConclusionThe level of insight was affected by cognitive function, involuntary admission, dependent on a caregiver, social function and length of stay. Future studies should focus on cognitive function recovery, observation of admission mode, and self-care ability in elderly patients with depression

Weighted gene co-expression network analysis and CIBERSORT screening of key genes related to m6A methylation in Hirschsprung’s disease

Hirschsprung’s disease (HSCR) is a neural crest disease that results from the failure of enteric neural crest cells (ENCCs) to migrate to the corresponding intestinal segment. The RET gene, which regulates enteric neural crest cell proliferation and migration, is considered one of the main risk factors for HSCR and is commonly used to construct HSCR mouse models. The epigenetic mechanism of m6A modification is involved in HSCR. In this study, we analyzed the GEO database (GSE103070) for differentially expressed genes (DEGs) and focused on m6A–related genes. Comparing the RNA-seq data of Wide Type and RET Null, a total of 326 DEGs were identified, of which 245 genes were associated with m6A. According to the CIBERSORT analysis, the proportion of Memory B-cell in RET Null was significantly higher than that of Wide Type. Venn diagram analysis was used to identify key genes in the selected memory B-cell modules and DEGs associated with m6A. Enrichment analysis showed that seven genes were mainly involved in focal adhesion, HIV infection, actin cytoskeleton organization and regulation of binding. These findings could provide a theoretical basis for molecular mechanism studies of HSCR

Optimization of Traced Neuron Skeleton Using Lasso-Based Model

Reconstruction of neuronal morphology from images involves mainly the extraction of neuronal skeleton points. It is an indispensable step in the quantitative analysis of neurons. Due to the complex morphology of neurons, many widely used tracing methods have difficulties in accurately acquiring skeleton points near branch points or in structures with tortuosity. Here, we propose two models to solve these problems. One is based on an L1-norm minimization model, which can better identify tortuous structure, namely, a local structure with large curvature skeleton points; the other detects an optimized branch point by considering the combination patterns of all neurites that link to this point. We combined these two models to achieve optimized skeleton detection for a neuron. We validate our models in various datasets including MOST and BigNeuron. In addition, we demonstrate that our method can optimize the traced skeletons from large-scale images. These characteristics of our approach indicate that it can reduce manual editing of traced skeletons and help to accelerate the accurate reconstruction of neuronal morphology

Extraction, Component Analysis and Biological Activity Evaluation of Total Flavonoids from Phellinus igniarius

In order to study the extraction technology of total flavonoids from Phellinus igniarius systematically, clarify the composition and content of flavonoids in total flavonoids, and explore the biological activity of total flavonoids from Phellinus igniarius. The extraction technology of Phellinus igniarius total flavonoids was optimized by response surface method, the composition of Phellinus igniarius total flavonoids was analyzed, and some of its biological activities were also detected. The results showed that the optimal extraction conditions were extraction temperature of 73 ℃, solid-liquid ratio of 1:50 g/mL and extraction time of 3 h, under which the yield of Phellinus igniarius total flavonoids reached 2.68%. The types and contents of flavonoids in Phellinus igniarius total flavonoids were determined by HPLC. Total flavonoids of Phellinus igniarius mainly contained taxifolin, quercetin and kaempferol, and the content of taxifolin was 3727.31 mg/kg. The analysis of biological activities of Phellinus igniarius total flavonoids showed that it had certain antioxidant, lipid-lowering and hypoglycemic activities in vitro, and the scavenging rate of DPPH free radicals reached 58.63%±0.45% when its concentration was 14 μg/mL, and the scavenging rate of hydroxyl free radicals reached 52.51%±1.49% when its concentration was 0.08 mg/mL. The experimental results of lipid-lowering activity showed that the inhibitory rate of Phellinus igniarius total flavonoids on pancreatic lipase reached 10.56%±0.06% at the concentration of 6 mg/mL, and the inhibitory rate on cholesterol micelle solubility reached 32.59%±0.78% at the concentration of 4 mg/mL. Phellinus igniarius total flavonids had obvious hypoglycemic activity, and its IC50 for α-glucosidase and α-amylase was 71.42 mg/mL and 97.28 mg/mL respectively