DualTalker: A Cross-Modal Dual Learning Approach for Speech-Driven 3D Facial Animation

In recent years, audio-driven 3D facial animation has gained significant attention, particularly in applications such as virtual reality, gaming, and video conferencing. However, accurately modeling the intricate and subtle dynamics of facial expressions remains a challenge. Most existing studies approach the facial animation task as a single regression problem, which often fail to capture the intrinsic inter-modal relationship between speech signals and 3D facial animation and overlook their inherent consistency. Moreover, due to the limited availability of 3D-audio-visual datasets, approaches learning with small-size samples have poor generalizability that decreases the performance. To address these issues, in this study, we propose a cross-modal dual-learning framework, termed DualTalker, aiming at improving data usage efficiency as well as relating cross-modal dependencies. The framework is trained jointly with the primary task (audio-driven facial animation) and its dual task (lip reading) and shares common audio/motion encoder components. Our joint training framework facilitates more efficient data usage by leveraging information from both tasks and explicitly capitalizing on the complementary relationship between facial motion and audio to improve performance. Furthermore, we introduce an auxiliary cross-modal consistency loss to mitigate the potential over-smoothing underlying the cross-modal complementary representations, enhancing the mapping of subtle facial expression dynamics. Through extensive experiments and a perceptual user study conducted on the VOCA and BIWI datasets, we demonstrate that our approach outperforms current state-of-the-art methods both qualitatively and quantitatively. We have made our code and video demonstrations available at https://github.com/sabrina-su/iadf.git

A Predictive Analysis of China's Energy Security Based on Supply Chain Theory

AbstractChina's energy dependence on energy supply chain have been increasing rapidly in recent years. The long-term energy supply plays an important role to guarantee the energy security. Therefore, our emphasis placed on energy supply chain predictive analysis and security evaluation in China. In this study, a linked MARKAL-CGE-EIA model system is proposed to simulate the macro-level energy technology, macro-level economy and environmental impacts of China. The CGE module is used to produce a multi-sector simulation of economic growth and industrial structure change. A MARKAL module is used to analyze particular technologies within the energy system, given estimates of associated energy demand and the relative prices of fuel and other inputs. A third module of Environmental Impact is applied to make an analysis of pollutant emissions. The energy indicators are used to perform an assessment of the dynamic behavior and security trends of a national energy system's trajectory from 2000 to 2050. The results of our study will enable energy policy planners to understand these inter-linkages by addressing energy early-warming indicators and scenarios to the aggregate industrial sectors, the energy technology details, and environmental impacts

Photoinduced oxygen release and persistent photoconductivity in ZnO nanowires

Photoconductivity is studied in individual ZnO nanowires. Under ultraviolet (UV) illumination, the induced photocurrents are observed to persist both in air and in vacuum. Their dependence on UV intensity in air is explained by means of photoinduced surface depletion depth decrease caused by oxygen desorption induced by photogenerated holes. The observed photoresponse is much greater in vacuum and proceeds beyond the air photoresponse at a much slower rate of increase. After reaching a maximum, it typically persists indefinitely, as long as good vacuum is maintained. Once vacuum is broken and air is let in, the photocurrent quickly decays down to the typical air-photoresponse values. The extra photoconductivity in vacuum is explained by desorption of adsorbed surface oxygen which is readily pumped out, followed by a further slower desorption of lattice oxygen, resulting in a Zn-rich surface of increased conductivity. The adsorption-desorption balance is fully recovered after the ZnO surface is exposed to air, which suggests that under UV illumination, the ZnO surface is actively "breathing" oxygen, a process that is further enhanced in nanowires by their high surface to volume ratio

Xuebijing injection alleviates liver injury by inhibiting secretory function of Kupffer cells in heat stroke rats

AbstractObjectiveTo evaluate the effects of Xuebijing (XBJ) injection in heat stroke (HS) rats and to investigate the mechanisms underlying these effects.MethodsSixty anesthetized rats were randomized into three groups and intravenously injected twice daily for 3 days with 4 mL XBJ (XBJ group) or phosphate buffered saline (HS and Sham groups) per kg body weight. HS was initiated in the HS and XBJ groups by placing rats in a simulated climate chamber (ambient temperature 40°C, humidity 60%). Rectal temperature, aterial pressure, and heart rate were monitored and recorded. Time to HS onset and survival were determined, and serum concentrations of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, alanine-aminotransferase (ALT), and aspartate-aminotransferase (AST) were measured. Hepatic tissue was harvested for pathological examination and electron microscopic examination. Kupffer cells (KCs) were separated from liver at HS initiation, and the concentrations of secreted TNF-α, IL-β and IL-6 were measured.ResultsTime to HS onset and survival were significantly longer in the XBJ than in the HS group. Moreover, the concentrations of TNF-α, IL-1β, IL-6, ALT and AST were lower and liver injury was milder in the XBJ than in the HS group. Heat-stress induced structural changes in KCs and hepatic cells were more severe in the HS than in the XBJ group and the concentrations of TNF-α, IL-β and IL-6 secreted by KCs were lower in the XBJ than in the HS group.ConclusionXBJ can alleviate HS-induced systemic inflammatory response syndrome and liver injury in rats, and improve outcomes. These protective effects may be due to the ability of XBJ to inhibit cytokine secretion by KCs

25-Hydroxyvitamin D and Vitamin D Binding Protein Levels in Patients With Primary Hyperparathyroidism Before and After Parathyroidectomy

Objective: To evaluate vitamin D binding protein and free 25-hydroxyvitamin D [25(OH)D] levels in healthy controls compared to primary hyperparathyroidism (PHPT) patients, and to examine PHPT before and after surgery.Methods: Seventy-five PHPT patients and 75 healthy age, gender, and body mass index (BMI) -matched control subjects were examined. In addition, 25 PHPT patients underwent parathyroidectomy and had a 3-month follow up visit. Levels of total and free 25(OH)D, DBP, and intact parathyroid hormone (iPTH) were determined before and 3 months after surgery.Results: There was no significant difference in age and BMI between PHPT patients and controls. Levels of 25(OH)D and DBP were lower in PHPT patients compared to controls (p < 0.01). There was no significant difference in calculated free and bioavailable 25(OH)D levels between PHPT patients and controls. Calcium and iPTH levels decreased to normal but DBP and DBP-bound-25(OH)D increased (P < 0.001) after parathyroidectomy. Levels of DBP were inversely correlated with iPTH (r = −0.406, P < 0.001) and calcium levels (r = −0.423, P < 0.001).Conclusion: Serum DBP levels were lower in patients with PHPT and parathyroidectomy restored DBP levels. We suggest that lower DBP levels is one of contributing mechanisms of low total 25(OH)D in PTHP patients and the total 25(OH)D levels might not reflect true vitamin D status in PHPT patients

Sensitivity of Mesoscale Modeling of Smoke Direct Radiative Effect to the Emission Inventory: a Case Study in Northern Sub-Saharan African Region

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15degW-42degE, 13degS-17degN) and monthly averages of column PM(sub 2.5) loading, surface PM(sub 2.5) concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA

Sensitivity of Mesoscale Modeling of Smoke Direct Radiative Effect to the Emission Inventory: A Case Study in Northern Sub-Saharan African Region

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15°W–42°E, 13°S–17°N) and monthly averages of column PM2.5 loading, surface PM2.5 concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA