sasdim: self-adaptive noise scaling diffusion model for spatial time series imputation

Spatial time series imputation is critically important to many real applications such as intelligent transportation and air quality monitoring. Although recent transformer and diffusion model based approaches have achieved significant performance gains compared with conventional statistic based methods, spatial time series imputation still remains as a challenging issue due to the complex spatio-temporal dependencies and the noise uncertainty of the spatial time series data. Especially, recent diffusion process based models may introduce random noise to the imputations, and thus cause negative impact on the model performance. To this end, we propose a self-adaptive noise scaling diffusion model named SaSDim to more effectively perform spatial time series imputation. Specially, we propose a new loss function that can scale the noise to the similar intensity, and propose the across spatial-temporal global convolution module to more effectively capture the dynamic spatial-temporal dependencies. Extensive experiments conducted on three real world datasets verify the effectiveness of SaSDim by comparison with current state-of-the-art baselines

Semi-Instruct: Bridging Natural-Instruct and Self-Instruct for Code Large Language Models

Instruction tuning plays a pivotal role in Code Large Language Models (Code LLMs) for the task of program synthesis. Presently, two dominant paradigms for collecting tuning data are natural-instruct (human-written) and self-instruct (automatically generated). Natural-instruct includes diverse and correct codes but lacks instruction-code pairs, and exists improper code formats like nested single-line codes. In contrast, self-instruct automatically generates proper paired data. However, it suffers from low diversity due to generating duplicates and cannot ensure the correctness of codes. To bridge the both paradigms, we propose \textbf{Semi-Instruct}. It first converts diverse but improper codes from natural-instruct into proper instruction-code pairs through a method similar to self-instruct. To verify the correctness of generated codes, we design a novel way to construct test cases by generating cases' inputs and executing correct codes from natural-instruct to get outputs. Finally, diverse and correct instruction-code pairs are retained for instruction tuning. Experiments show that semi-instruct is significantly better than natural-instruct and self-instruct. Furthermore, the performance steadily improves as data scale increases

Production and Purification of a Novel Xanthan Lyase from a Xanthan-Degrading Microbacterium

A xanthan lyase was produced and purified from the culture supernatant of an excellent xanthan-modifying strain Microbacterium sp. XT11. Xanthan lyase was induced by xanthan but was inhibited by its structural monomer glucose. Its production by strain XT11 is much higher than that by all other reported strains. The purified xanthan lyase has a molecular mass of 110 kDa and a specific activity of 28.2 U/mg that was much higher than that of both Paenibacillus and Bacillus lyases. It was specific on the pyruvated mannosyl residue in the intact xanthan molecule, but about 50% lyase activity remained when xanthan was partially depyruvated. Xanthan lyase was optimally active at pH 6.0–6.5 and 40°C and alkali-tolerant at a high pH value of 11.0. The metal ions including K+, Ca2+, Na+, Mg2+, Mn2+, and Li+ strongly stimulated xanthan lyase activity but ions Zn2+ and Cu2+ were its inhibitor. Xanthan lyase should be a novel enzyme different from the other xanthan lyases ever reported

Substantially enhanced plasticity of bulk metallic glasses by densifying local atomic packing

Common wisdom to improve ductility of bulk metallic glasses (BMGs) is to introduce local loose packing regions at the expense of strength. Here the authors enhance structural fluctuations of BMGs by introducing dense local packing regions, resulting in simultaneous increase of ductility and strength

Non-destructive 3D Microtomography of Cerebral Angioarchitecture Changes Following Ischemic Stroke in Rats Using Synchrotron Radiation

A better understanding of functional changes in the cerebral microvasculature following ischemic injury is essential to elucidate the pathogenesis of stroke. Up to now, the simultaneous depiction and stereological analysis of 3D micro-architectural changes of brain vasculature with network disorders remains a technical challenge. We aimed to explore the three dimensional (3D) microstructural changes of microvasculature in the rat brain on 4, 6 hours, 3 and 18 days post-ischemia using synchrotron radiation micro-computed tomography (SRμCT) with a per pixel size of 5.2 μm. The plasticity of angioarchitecture was distinctly visualized. Quantitative assessments of time-related trends after focal ischemia, including number of branches, number of nodes, and frequency distribution of vessel diameter, reached a peak at 6 h and significantly decreased at 3 days and initiated to form cavities. The detected pathological changes were also proven by histological tests. We depicted a novel methodology for the 3D analysis of vascular repair in ischemic injury, both qualitatively and quantitatively. Cerebral angioarchitecture sustained 3D remodeling and modification during the healing process. The results might provide a deeper insight into the compensatory mechanisms of microvasculature after injury, suggesting that SRμCT is able to provide a potential new platform for deepening imaging pathological changes in complicated angioarchitecture and evaluating potential therapeutic targets for stroke

Neural Correlates of Feedback Processing in Visuo-Tactile Crossmodal Paired-Associate Learning

Previous studies have examined the neural correlates for crossmodal paired-associate (PA) memory and the temporal dynamics of its formation. However, the neural dynamics for feedback processing of crossmodal PA learning remain unclear. To examine this process, we recorded event-related scalp electrical potentials for PA learning of unimodal visual-visual pairs and crossmodal visual-tactile pairs when participants performed unimodal and crossmodal tasks. We examined event-related potentials (ERPs) after the onset of feedback in the tasks for three effects: feedback type (positive feedback vs. negative feedback), learning (as the learning progressed) and the task modality (crossmodal vs. unimodal). The results were as follows: (1) feedback type: the amplitude of P300 decreased with incorrect trials and the P400/N400 complex was only present in incorrect trials; (2) learning: progressive positive voltage shifts in frontal recording sites and negative voltage shifts in central and posterior recording sites were identified as learning proceeded; and (3) task modality: compared with the unimodal PA learning task, positive voltage shifts in frontal sites and negative voltage shifts in posterior sites were found in the crossmodal PA learning task. To sum up, these results shed light on cortical excitability related to feedback processing of crossmodal PA learning

Application of the Coordination Control Strategy of pH and SO2 Concentration in the Desulphurization Slurry Supply

The desulphurization slurry flow of the coal-fired unit is usually regulated by a single PID loop that controls the pH value of the gypsum slurry. And the desulphurization system is characterized with large inertia and serious hysteresis, which often results in SO2 concentration of the outlet exceeding the standard, and leads the operators to turn the regulating valve to manual mode. The SO2 concentration of the outlet was taken into consideration into the optimized control strategy of desulphurization slurry supply introduced in this paper, and it is with the gypsum slurry pH value for cooperative control of the slurry regulating valve. Finally, the experiment proved that after the optimization of the control strategy, the desulfurization loop could be automatically put into operation for a long time, and the SO2 concentration of the outlet keeps stable, and the comprehensive utilization rate of limestone and the automation level of auxiliary equipment are significantly improved

Application of the Coordination Control Strategy of pH and SO

The desulphurization slurry flow of the coal-fired unit is usually regulated by a single PID loop that controls the pH value of the gypsum slurry. And the desulphurization system is characterized with large inertia and serious hysteresis, which often results in SO2 concentration of the outlet exceeding the standard, and leads the operators to turn the regulating valve to manual mode. The SO2 concentration of the outlet was taken into consideration into the optimized control strategy of desulphurization slurry supply introduced in this paper, and it is with the gypsum slurry pH value for cooperative control of the slurry regulating valve. Finally, the experiment proved that after the optimization of the control strategy, the desulfurization loop could be automatically put into operation for a long time, and the SO2 concentration of the outlet keeps stable, and the comprehensive utilization rate of limestone and the automation level of auxiliary equipment are significantly improved