Adaptation of Rice to the Nordic Climate Yields Potential for Rice Cultivation at Most Northerly Site and the Organic Production of Low-Arsenic and High-Protein Rice

There is an urgent demand for low-arsenic rice in the global market, particularly for consumption by small children. Soils in Uppsala, Sweden, contain low concentrations of arsenic (As). We hypothesize that if certain japonica paddy rice varieties can adapt to the cold climate and long day length in Uppsala and produce normal grains, such a variety could be used for organic production of low-arsenic rice for safe rice consumption. A japonica paddy rice variety, "Heijing 5," can be cultivated in Uppsala, Sweden, after several years' adaptation, provided that the rice plants are kept under a simple plastic cover when the temperature is below 10 degrees C. Uppsala-adapted "Heijing 5" has a low concentration of 0.1 mg per kg and high protein content of 12.6% per dry weight in brown rice grain, meaning that it thus complies with all dietary requirements determined by the EU and other countries for small children. The high protein content is particularly good for small children in terms of nutrition. Theoretically, Uppsala-adapted "Heijing 5" can produce a yield of around 5100 kg per ha, and it has a potential for organic production. In addition, we speculate that cultivation of paddy rice can remove nitrogen and phosphorus from Swedish river water and reduce nutrient loads to the Baltic Sea and associated algae blooms

SiMaN: Sign-to-Magnitude Network Binarization

Binary neural networks (BNNs) have attracted broad research interest due to their efficient storage and computational ability. Nevertheless, a significant challenge of BNNs lies in handling discrete constraints while ensuring bit entropy maximization, which typically makes their weight optimization very difficult. Existing methods relax the learning using the sign function, which simply encodes positive weights into +1s, and -1s otherwise. Alternatively, we formulate an angle alignment objective to constrain the weight binarization to {0,+1} to solve the challenge. In this paper, we show that our weight binarization provides an analytical solution by encoding high-magnitude weights into +1s, and 0s otherwise. Therefore, a high-quality discrete solution is established in a computationally efficient manner without the sign function. We prove that the learned weights of binarized networks roughly follow a Laplacian distribution that does not allow entropy maximization, and further demonstrate that it can be effectively solved by simply removing the $\ell_2$ regularization during network training. Our method, dubbed sign-to-magnitude network binarization (SiMaN), is evaluated on CIFAR-10 and ImageNet, demonstrating its superiority over the sign-based state-of-the-arts. Our source code, experimental settings, training logs and binary models are available at https://github.com/lmbxmu/SiMaN

High fructan barley lines produced by selective breeding may alter beta-glucan and amylopectin molecular structure

Six cross-bred barley lines developed by a breeding strategy with the target to enhance the fructan synthesis activity and reduce the fructan hydrolysis activity were analyzed together with their parental lines, and a reference line (Gustav) to determine whether the breeding strategy also affected the content and molecular structure of amylopectin and beta-glucan. The highest fructan and beta-glucan content achieved in the novel barley lines was 8.6 % and 12 %, respectively (12.3-fold and 3.2-fold higher than in Gustav). The lines with low fructan synthesis activity had higher starch content, smaller building blocks in amylopectin, and smaller structural units of beta-glucans than the lines with high-fructan synthesis activity. Correlation analysis confirmed that low starch content was associated with high amylose, fructan, and beta-glucan content, and larger building blocks in amylopectin

Achieving of high-diet-fiber barley via managing fructan hydrolysis

High fructan content in the grain of cereals is an important trait in agriculture such as environmental resilience and dietary fiber food production. To understand the mechanism in determining final grain fructan content and achieve high fructan cereal, a cross breeding strategy based on fructan synthesis and hydrolysis activities was set up and have achieved barley lines with 11.8% storage fructan in the harvested grain. Our study discovered that high activity of fructan hydrolysis at later grain developmental stage leads to the low fructan content in mature seeds, simultaneously increasing fructan synthesis at early stage and decreasing fructan hydrolysis at later stage through crossing breeding is an efficient way to elevate grain diet-fiber content. A good correlation between fructan and beta glucans was also discovered with obvious interest. Field trials showed that the achieved high fructan barley produced over seven folds higher fructan content than control barley and pull carbon-flux to fructan through decreasing fructan hydrolysis without disruption starch synthesis will probably not bring yield deficiency

GeoEval : benchmark for evaluating LLMs and Multi-Modal Models on geometry problem-solving

Recent advancements in Large Language Models (LLMs) and Multi-Modal Models (MMs) have demonstrated their remarkable capabilities in problem-solving. Yet, their proficiency in tackling geometry math problems, which necessitates an integrated understanding of both textual and visual information, has not been thoroughly evaluated. To address this gap, we introduce the GeoEval benchmark, a comprehensive collection that includes a main subset of 2000 problems, a 750 problem subset focusing on backward reasoning, an augmented subset of 2000 problems, and a hard subset of 300 problems. This benchmark facilitates a deeper investigation into the performance of LLMs and MMs on solving geometry math problems. Our evaluation of ten LLMs and MMs across these varied subsets reveals that the WizardMath model excels, achieving a 55.67\% accuracy rate on the main subset but only a 6.00\% accuracy on the challenging subset. This highlights the critical need for testing models against datasets on which they have not been pre-trained. Additionally, our findings indicate that GPT-series models perform more effectively on problems they have rephrased, suggesting a promising method for enhancing model capabilities

Recognizing topological attributes and spatiotemporal patterns in spotted seals (Phoca largha) trophic networks based on eDNA metabarcoding

Spotted seals, a protected species, face multifaceted threats to their habitat, which in turn impact the closely associated trophic networks. These threats will lead to irreversible structural variations within the ecosystem. Therefore, investigating the topological variability of trophic networks in spotted seals is important. Applying environmental DNA methods, field sample collection was conducted in 2021 during both the sea fishing moratorium period and the fishing period to decode fish diversity. Assessing the current status of fish resources by using the multivariate statistics approach. Applying dietary information establishes the spotted seals’ trophic network. Selecting 12 network indexes to analyze the spatiotemporal patterns of network topological attributes. As a result, about 51 families, and 76 genera species were identified. During the sea fishing moratorium and the fishing period, there are 12 and 18 different food resources available for spotted seals, respectively. The diversity index revealed that the FP had greater species richness and diversity than the SP. Comparatively, the Fishing period exhibited higher species richness and biodiversity, likely influenced by habitat heterogeneity and anthropogenic activities. Additionally, the topological features of networks reflected the high clustering coefficients (CC=0.35) and the proportion of omnivorous species (O≈60%), indicating that the network structure in this region tends to form higher trophic-level clustering patterns, which facilitate the formation of weaker interactions between clusters, enhancing the robustness of the network. The higher connectivity complexity index during the fishing period (SC=12.3) supported that the spotted seal’s trophic network was relatively more stable in this period. Thus, during the fishing period, it is crucial to pay more attention to the intensity of human fishing on mid-to-high trophic-level omnivorous fish resources to ensure the sustainability of these potential food resources for spotted seals. This comprehensive study achieved three key objectives: (a) utilizing eDNA to characterize fish diversity during distinct periods, (b) establishing trophic networks of spotted seals, and (c) discerning topological attributes and spatiotemporal patterns within the ecological network. Overall, this study can provide technical and data support for integrated ecological network management and propose suggestions for protecting and recovering spotted seals

Surface functionalization of vertical graphene significantly enhances the energy storage capability for symmetric supercapacitors

Vertical graphene (VG) sheets, which consist of few-layer graphene vertically aligned on the substrate with three dimensionally interconnected porous network, make them become one of the most promising energy storage electrodes, especially for SCs. Nevertheless, the intrinsic hydrophobic nature of pristine VG sheets severely limited its application in aqueous SCs. Here, electrochemical oxidation strategy is adopted to increase the hydrophilicity of VG sheets by introducing oxygen functional groups so that the aqueous electrolyte can fully be in contact with the VG sheets to improve charge storage performance. Our work demonstrated that the introduction of oxygen functional groups not only greatly improved the hydrophilicity but also generated a pseudo capacitance to increase the specific capacitance. The resulting capacitance of electrochemically oxidized VG for 7 min (denoted as EOVG-7) exhibited three orders of magnitude higher (1605 mF/cm²) compared to pristine VG sheets. Through assembled two EOVG-7 electrodes, a symmetric supercapacitor demonstrated high specific capacitance of 307.5 mF/cm², high energy density of 138.3 μWh/cm2 as well as excellent cyclic stability (84% capacitance retention after 10000 cycles). This strategy provides a promising way for designing and engineering carbon-based aqueous supercapacitors with high performance

Research on the displacement change of construction enclosure system of deep foundation

By analyzing the monitoring data of the excavation of foundation, the maximum lateral displacement depth and the top vertical displacement of the retaining wall, the vertical displacement of the column are studied. Research indicates that the 3rd power polynomial curve can better fit the depth change law of the maximum lateral deformation of retaining wall at each monitoring point；the fourth support demolition has great influence on the lateral displacement and deformation of retaining wall. The excavation of the third layer has greatly increased the deformation of the top of retaining wall. After the second support is removed, the vertical deformation of the top of the retaining wall change to negative. The vertical deformation of the column gradually decreases until the deformation becomes smooth after the first support is removed. The deep excavation should be paid attention to the monitoring of the internal displacement and the upward displacement of the retaining wall, the vertical displacement of the column from the excavation of the third layer to the removal of the fourth support

Simulation of steel corrosion and iron yield in LFR with lead coolant

Liquid lead is the main coolant of the fourth generation of advanced nuclear energy system — lead cooled fast reactor (LFR), due to its good neutron economy, high heat transfer performance, stable chemical properties, constant low melting point, high boiling point, etc. Although there are many advantages, the corrosion of metal materials in liquid lead is one of the decisive factors restricting the development of lead cooled fast reactor. In this study, an engineering model for simulating the oxide film growth in liquid lead coolant is established, and the time-dependence of steel flux is analyzed based on the experimental data in the literature. The effects of circuit temperature, hydraulic diameter of section simulated, coolant velocity and steel types on the steel corrosion were investigated. The results showed that the oxide film formed on the steels is of micron grade and the diffusion yield of iron produced in pure lead coolant is of kilogram grade after ten years’ corrosion. The temperature and the coolant velocity have significant effects on the steel corrosion while the effect of hydraulic diameter is mild. Also, the steel types affect the growth of oxide film. The findings provide basic data for the evaluation of radioactive corrosion products of LFR