On Degeneracy Issues in Multi-parametric Programming and Critical Region Exploration based Distributed Optimization in Smart Grid Operations

Improving renewable energy resource utilization efficiency is crucial to reducing carbon emissions, and multi-parametric programming has provided a systematic perspective in conducting analysis and optimization toward this goal in smart grid operations. This paper focuses on two aspects of interest related to multi-parametric linear/quadratic programming (mpLP/QP). First, we study degeneracy issues of mpLP/QP. A novel approach to deal with degeneracies is proposed to find all critical regions containing the given parameter. Our method leverages properties of the multi-parametric linear complementary problem, vertex searching technique, and complementary basis enumeration. Second, an improved critical region exploration (CRE) method to solve distributed LP/QP is proposed under a general mpLP/QP-based formulation. The improved CRE incorporates the proposed approach to handle degeneracies. A cutting plane update and an adaptive stepsize scheme are also integrated to accelerate convergence under different problem settings. The computational efficiency is verified on multi-area tie-line scheduling problems with various testing benchmarks and initial states

Distributed Multi-Area Optimal Power Flow via Rotated Coordinate Descent Critical Region Exploration

We consider the problem of distributed optimal power flow (OPF) for multi-area electric power systems. A novel distributed algorithm is proposed, referred to as the rotated coordinate descent critical region exploration (RCDCRE). It allows each entity to independently update its boundary information and optimally solve its local OPF in an asynchronous fashion. RCDCRE method stitches coordinate descent and parametric programming using coordinate system rotation to reduce coordination, keep privacy and ensure convergence. The solution process does not require warm starts and can iterate from infeasible initial points using penalty-based formulations. The effectiveness of RCDCRE is verified based on IEEE 2-area 44-bus and 4-area 472-bus systems

MuseGNN: Interpretable and Convergent Graph Neural Network Layers at Scale

Among the many variants of graph neural network (GNN) architectures capable of modeling data with cross-instance relations, an important subclass involves layers designed such that the forward pass iteratively reduces a graph-regularized energy function of interest. In this way, node embeddings produced at the output layer dually serve as both predictive features for solving downstream tasks (e.g., node classification) and energy function minimizers that inherit desirable inductive biases and interpretability. However, scaling GNN architectures constructed in this way remains challenging, in part because the convergence of the forward pass may involve models with considerable depth. To tackle this limitation, we propose a sampling-based energy function and scalable GNN layers that iteratively reduce it, guided by convergence guarantees in certain settings. We also instantiate a full GNN architecture based on these designs, and the model achieves competitive accuracy and scalability when applied to the largest publicly-available node classification benchmark exceeding 1TB in size

Model to estimate the trapping parameters of cross-linked polyethylene cable peelings of different service years and their relationships with dc breakdown strengths

In this study, an improved trapping/detrapping model was used to simulate the charge dynamics in cross-linked polyethylene peelings from different-year aged cables. Injection barrier of trapping parameters was estimated by the model fitted to experimental data for each type of sample. Moreover, dc breakdown tests were operated on those samples. It has been found that the dc breakdown strength of inner-layer samples is the lowest in cable sections with thicker insulation layer taken from high-voltage ac (HVAC) 220 kV service condition, whereas for the cable with thinner insulation from HVAC 110 kV, middle-layer samples have worst breakdown performance. This might be explained by the space charge issues under long-term HVAC condition. More importantly, a clear relationship between estimated model parameters, including injection barrier, trap depth and trap density, with the dc breakdown strength in each layer has been reported in this study

Isolation and Identification of Pediococcus lactis in Human Intestinal Tract and Its Performance Analysis of Fermented Goji Berry Juice

In order to obtain candidate strains with strong colonization ability and excellent fermentation performance of goji berry juice, 3 strains of lactic acid bacteria were isolated and screened from human intestinal tract. They were identified by morphological, physiological and biochemical, 16S rDNA sequence analysis and phylogenetic tree construction, and their acid resistance, bile salt resistance, artificial gastric fluid, intestinal fluid resistance and fermentation performance were studied. The results showed that all three strains were identified as Pediococcus lactis, numbered NXU_220218, NXU_220219 and NXU_220220, respectively. The growth rate from 2 to 8 h, the ability of NXU 220218 to produce acid was stronger, and the tolerance to acid, bile salt and artificial gastric juice was better than NXU 220219 and NXU 220220. The survival rate of NXU_220218 was 67% at pH2, 65% in bovine bile salt at 0.3% concentration, 72% tolerance to artificial gastric juice, and 95% tolerance to artificial intestinal juice. Finally, the NXU_220218 strain was inoculated and used in the preparation of fermented goji berry juice. It was found that the reducing sugar content and the free radical scavenging rate in the fermented goji berry juice were significantly reduced and increased, respectively, compared with the unfermented goji berry juice, indicating that the NXU_220218 strain had good fermentation performance for goji berry juice and could be used as a candidate strain of lactic acid bacteria for the fermentation of goji berry juice

Is the NH4+-induced growth inhibition caused by the NH4+ form of the nitrogen source or by soil acidification?

Soil acidification often occurs when the concentration of ammonium (NH4+) in soil rises, such as that observed in farmland. Both soil acidification and excess NH4+ have serious adverse effects on crop growth and food production. However, we still do not know which of these two inhibitors has a greater impact on the growth of crops, and the degree of their inhibitory effect on crop growth have not been accurately evaluated. 31 wheat cultivars originating in various areas of China were planted under 5 mM sole NH4+ (ammonium nitrogen, AN) or nitrate nitrogen in combined with two pH levels resembling acidified conditions (5.0 and 6.5). The results showed that the shoots and roots biomass were severely reduced by AN in both and these reduction effects were strengthened by a low medium pH. The concentration of free NH4+ and amino acids, the glutamine synthetase activity were significantly higher, but the total soluble sugar content was reduced under NH4+ conditions, and the glutamine synthetase activity was reduced by a low medium pH. Cultivar variance was responsible for the largest proportion of the total variance in plant dry weight, leaf area, nodal root number, total root length and root volume; the nitrogen (N) form explains most of the variation in N and C metabolism; the effects of pH were the greatest for plant height and root average diameter. So, soil acidification and excess NH4+ would cause different degrees of inhibition effects on different plant tissues. The findings are expected to be useful for applying effective strategies for reducing NH4+ stress in the field

Study on the Optimization of the Formula of Potato Scone andIts Texture Characteristics

In order to enrich potato staple products and improve the sensory quality of scones, the rheological properties of mixed dough of potato flour and wheat flour were studied. With sensory score and texture characteristics as evaluation indexes, the formulation of potato flour scone was optimized by single factor experiments and orthogonal test. The results showed that potato flour could improve the water absorption of wheat flour and shorten the formation time of dough, but it would lead to a decline in the elasticity and strength of the dough, resulting in a decrease in its quality. Therefore, the appropriate substitution ratio for whole potato flour was considered to be 20%. The best process recipe for scones was based on a mixture of wheat flour and whole potato flour quality, with 20% whole potato flour added, 68% water added, 0.8% yeast added and 6% sugar added. The hardness of the scone prepared under the optimal condition was 342.63 g, and the chewiness was 106.76 N. The research results provided a theoretical basis for the quality improvement of the scones and the development of whole potato flour products

Structure-Guided Image Completion with Image-level and Object-level Semantic Discriminators

Structure-guided image completion aims to inpaint a local region of an image according to an input guidance map from users. While such a task enables many practical applications for interactive editing, existing methods often struggle to hallucinate realistic object instances in complex natural scenes. Such a limitation is partially due to the lack of semantic-level constraints inside the hole region as well as the lack of a mechanism to enforce realistic object generation. In this work, we propose a learning paradigm that consists of semantic discriminators and object-level discriminators for improving the generation of complex semantics and objects. Specifically, the semantic discriminators leverage pretrained visual features to improve the realism of the generated visual concepts. Moreover, the object-level discriminators take aligned instances as inputs to enforce the realism of individual objects. Our proposed scheme significantly improves the generation quality and achieves state-of-the-art results on various tasks, including segmentation-guided completion, edge-guided manipulation and panoptically-guided manipulation on Places2 datasets. Furthermore, our trained model is flexible and can support multiple editing use cases, such as object insertion, replacement, removal and standard inpainting. In particular, our trained model combined with a novel automatic image completion pipeline achieves state-of-the-art results on the standard inpainting task.Comment: 18 pages, 16 figure

O2ATH: An OpenMP Offloading Toolkit for the Sunway Heterogeneous Manycore Platform

The next generation Sunway supercomputer employs the SW26010pro processor, which features a specialized on-chip heterogeneous architecture. Applications with significant hotspots can benefit from the great computation capacity improvement of Sunway many-core architectures by carefully making intensive manual many-core parallelization efforts. However, some legacy projects with large codebases, such as CESM, ROMS and WRF, contain numerous lines of code and do not have significant hotspots. The cost of manually porting such applications to the Sunway architecture is almost unaffordable. To overcome such a challenge, we have developed a toolkit named O2ATH. O2ATH forwards GNU OpenMP runtime library calls to Sunway's Athread library, which greatly simplifies the parallelization work on the Sunway architecture.O2ATH enables users to write both MPE and CPE code in a single file, and parallelization can be achieved by utilizing OpenMP directives and attributes. In practice, O2ATH has helped us to port two large projects, CESM and ROMS, to the CPEs of the next generation Sunway supercomputers via the OpenMP offload method. In the experiments, kernel speedups range from 3 to 15 times, resulting in 3 to 6 times whole application speedups.Furthermore, O2ATH requires significantly fewer code modifications compared to manually crafting CPE functions.This indicates that O2ATH can greatly enhance development efficiency when porting or optimizing large software projects on Sunway supercomputers.Comment: 15 pages, 6 figures, 5 tables