Are plant growth and photosynthesis limited by pre-drought following rewatering in grass?

Although the relationship between grassland productivity and soil water status has been extensively researched, the responses of plant growth and photosynthetic physiological processes to long-term drought and rewatering are not fully understood. Here, the perennial grass (Leymus chinensis), predominantly distributed in the Euro-Asia steppe, was used as an experimental plant for an irrigation manipulation experiment involving five soil moisture levels [75–80, 60–75, 50–60, 35–50, and 25–35% of soil relative water content (SRWC), i.e. the ratio between present soil moisture and field capacity] to examine the effects of soil drought and rewatering on plant biomass, relative growth rate (RGR), and photosynthetic potential. The recovery of plant biomass following rewatering was lower for the plants that had experienced previous drought compared with the controls; the extent of recovery was proportional to the intensity of soil drought. However, the plant RGR, leaf photosynthesis, and light use potential were markedly stimulated by the previous drought, depending on drought intensity, whereas stomatal conductance (gs) achieved only partial recovery. The results indicated that gs may be responsible for regulating actual photosynthetic efficiency. It is assumed that the new plant growth and photosynthetic potential enhanced by pre-drought following rewatering may try to overcompensate the great loss of the plant's net primary production due to the pre-drought effect. The present results highlight the episodic effects of drought on grass growth and photosynthesis. This study will assist in understanding how degraded ecosystems can potentially cope with climate change

Inverse indefinite Sturm–Liouville problems with three spectra

AbstractWe prove that the potential q(x) of an indefinite Sturm–Liouville problem on the closed interval [a,b] with the indefinite weight function w(x) can be determined uniquely by three spectra, which are generated by the indefinite problem defined on [a,b] and two right-definite problems defined on [a,0] and [0,b], where point 0 lies in (a,b) and is the turning point of the weight function w(x)

Cross-chain between a Parent Chain and Multiple Side Chains

In certain Blockchain systems, multiple Blockchains are required to operate cooperatively for security, performance, and capacity considerations. This invention defines a cross-chain mechanism where a main Blockchain issues the tokens, which can then be transferred and used in multiple side Blockchains to drive their operations. A set of witnesses are created to securely manage the token exchange across the main chain and multiple side chains. The system decouples the consensus algorithms between the main chain and side chains. We also discuss the coexistence of the main tokens and the native tokens in the side chains.Comment: 14 pages, 9 figure

Split Unlearning

Split learning is emerging as a powerful approach to decentralized machine learning, but the urgent task of unlearning to address privacy issues presents significant challenges. Conventional methods of retraining from scratch or gradient ascending require all clients' involvement, incurring high computational and communication overhead, particularly in public networks where clients lack resources and may be reluctant to participate in unlearning processes they have no interest. In this short article, we propose \textsc{SplitWiper}, a new framework that integrates the concept of SISA to reduce retraining costs and ensures no interference between the unlearning client and others in public networks. Recognizing the inherent sharding in split learning, we first establish the SISA-based design of \textsc{SplitWiper}. This forms the premise for conceptualizing two unlearning strategies for label-sharing and non-label-sharing scenarios. This article represents an earlier edition, with extensive experiments being conducted for the forthcoming full version.Comment: An earlier edition, with extensive experiments being conducted for the forthcoming full versio

Leveraging Architectural Approaches in Web3 Applications -- A DAO Perspective Focused

Architectural design contexts contain a set of factors that influence software application development. Among them, \textit{\textbf{organizational}} design contexts consist of high-level company concerns and how it is structured, for example, stakeholders and development schedule, heavily impacting design considerations. Decentralized Autonomous Organization (DAO), as a vital concept in the Web3 space, is an organization constructed by automatically executed rules such as via smart contracts, holding features of the permissionless committee, transparent proposals, and fair contribution by stakeholders. In this work, we conduct a systematic literature review to summarize how DAO is structured as well as explore its benefits\&challenges in Web3 applications

Microfluidic production of porous chitosan/silica hybrid microspheres and its Cu(II) adsorption performance

AbstractWaste water with heavy metal ions has been of great concern because of its increased discharge, toxic and some other bad effects on human beings or the environment. In this article, monodispersed chitosan/silica hybrid microspheres with porous structure and large specific surface area were successfully prepared by using microfluidic technology and they have advantages in mechanical property and adsorption of heavy metal ions such as Cu(II). In the optimum condition, porous chitosan/silica hybrid microspheres with 1.0wt.% TEOS in the dispersed phase and pre-solidified for 3h have enhanced mechanical intensity, faster adsorption kinetic and larger equilibrium adsorption amount of Cu(II) compared to the porous chitosan microspheres. The mechanical intensity and adsorption rate of the porous hybrid microspheres were 1.5 times and two times of porous chitosan microspheres, respectively. Meantime, the adsorption capacity was increased by 25%. The porous hybrid microspheres have good potentials in the applications of removing heavy metal ions from waste water

The Privacy Pillar -- A Conceptual Framework for Foundation Model-based Systems

AI and its relevant technologies, including machine learning, deep learning, chatbots, virtual assistants, and others, are currently undergoing a profound transformation of development and organizational processes within companies. Foundation models present both significant challenges and incredible opportunities. In this context, ensuring the quality attributes of foundation model-based systems is of paramount importance, and with a particular focus on the challenging issue of privacy due to the sensitive nature of the data and information involved. However, there is currently a lack of consensus regarding the comprehensive scope of both technical and non-technical issues that the privacy evaluation process should encompass. Additionally, there is uncertainty about which existing methods are best suited to effectively address these privacy concerns. In response to this challenge, this paper introduces a novel conceptual framework that integrates various responsible AI patterns from multiple perspectives, with the specific aim of safeguarding privacy.Comment: 10 page

Dataset Obfuscation: Its Applications to and Impacts on Edge Machine Learning

Obfuscating a dataset by adding random noises to protect the privacy of sensitive samples in the training dataset is crucial to prevent data leakage to untrusted parties for edge applications. We conduct comprehensive experiments to investigate how the dataset obfuscation can affect the resultant model weights - in terms of the model accuracy, Frobenius-norm (F-norm)-based model distance, and level of data privacy - and discuss the potential applications with the proposed Privacy, Utility, and Distinguishability (PUD)-triangle diagram to visualize the requirement preferences. Our experiments are based on the popular MNIST and CIFAR-10 datasets under both independent and identically distributed (IID) and non-IID settings. Significant results include a trade-off between the model accuracy and privacy level and a trade-off between the model difference and privacy level. The results indicate broad application prospects for training outsourcing in edge computing and guarding against attacks in Federated Learning among edge devices.Comment: 6 page

Flotation of an Arsenic Bearing High Sulfur Gold Mine in Gansu Province

This is an article in the field of mineral processing engineering. The gold mineral in an arsenic bearing high sulfur gold mine has a close symbiotic relationship with pyrite and arsenopyrite, and the recovery rate of concentrate gold is not ideal in the actual production process. In order to improve the recovery rate of concentrate gold and take into account the grade of concentrate gold, according to the characteristics of this mineral, the flotation process parameters and process are obtained through system condition test, flotation time test and beneficiation test, and then the open circuit test and closed circuit test are carried out to obtain better flotation indexes. In order to further improve the flotation index, the regrinding and flotation test of flotation middling is carried out, and the cyanide leaching test of middling regrinding flotation tailings is carried out. Finally, the satisfactory index of 91.94% of the total recovery of gold dressing and metallurgy is obtained

Projecting terrestrial carbon sequestration of the southeastern United States in the 21st century

How terrestrial ecosystems respond to future environmental change in the 21st century is critically important for understanding the feedbacks of terrestrial ecosystems to global climate change. The southeastern United States (SEUS) has been one of the major regions acting as a carbon sink over the past century; yet it is unclear how its terrestrial ecosystems will respond to global environmental change in the 21st century. Applying a process-based ecosystem model (Dynamic Land Ecosystem Model, DLEM) in combination with three projected climate change scenarios (A1B, A2, and B1 from the IPCC report) and changes in atmospheric carbon dioxide, nitrogen deposition, and ozone pollution, we examined the potential changes of carbon storage and fluxes in the terrestrial ecosystems across the SEUS during 2000–2099. Simulation results indicate that SEUS\u27s terrestrial ecosystems will likely continue to sequester carbon in the 21st century, resulting in an increase in total carbon density (i.e., litter, vegetation biomass and soil carbon) from 13.5 kg C/m2 in the 2000s to 16.8 kg C/m2 in the 2090s. The terrestrial gross primary production and net primary production will probably continuously increase, while the net carbon exchange (positive indicates sink and negative indicates source) will slightly decrease. The carbon sequestration is primarily attributed to elevated atmospheric carbon dioxide and nitrogen deposition. Forests, including both deciduous and evergreen, show the largest increase in carbon storage as compared with other biomes, while cropland carbon storage shows a small decrease. The sequestered carbon will be primarily stored in vegetation for deciduous forest and in soil for evergreen forest. The central and eastern SEUS will sequester more carbon, while the western portion of the SEUS will release carbon to the atmosphere. The combined effects of climate and atmospheric changes on carbon fluxes and storage vary among climate models and climate scenarios. The largest increase in carbon storage would occur under the A1B climate scenario simulated by the NCAR climate model. Generally, the A1B scenario would result in more carbon sequestration than A2 and B1 scenarios; and the projected climate condition by the NCAR model would result in more carbon sequestration than other climate models