Childhood adversities and unmet needs of older Chinese adults: the mediation effects of family relationships

Ensuring equality and adequacy of care for older adults is vitally important. This study investigates the relationships between childhood adversities and unmet long-term care needs of older adults in China and the mediation effects of family relationships. The data came from a nationally representative sample of older Chinese adults aged 60 and over with long-term care needs (N = 2186). We conducted mediation analyses and decomposed the total effects of childhood adversities on unmet needs into direct and indirect effects. The probability of unmet needs is significantly higher among older adults experiencing childhood adversities. Satisfaction with marriage mediates the association between childhood adversities and unmet personal care needs. Relationships with children mediate the association between childhood adversities and unmet domestic care needs. The causes of unmet needs can be traced back to early life, which underscores the importance of concerted efforts in family, education and long-term care policies to tackle unmet needs

Biochar as additive for enhanced dark fermentation and anaerobic digestion

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Chemical biology of metalloproteases and cysteine proteases

Ph.DDOCTOR OF PHILOSOPH

Micromagnetic Modeling and Waves in Magnetic Materials

This thesis investigates magnetization dynamics in different types of magnetic materials via the continuum approximation using a single or coupled Landau-Liftshitz (LL) partial differential equations (PDEs). Linear and nonlinear wave solutions are obtained analytically using approximation methods and with numerical simulations. Two types of magnetic materials are studied: 1) ferromagnets (FMs), where the atomic spin vectors are of the same magnitude and prefer a parallel configuration; 2) antiferromagnets (AFMs), where two sets of atomic spin vectors are of the same magnitude but prefer an antiparallel alignment. Both types are special cases of the more general magnetic order in a ferrimagnet (FIM), where two sets of atomic spin vectors may have different magnitudes and preferred orientations. The first part of this thesis studies an initial-boundary value problem analogous to the piston problem in gas dynamics modeling in a FM channel. On a sufficiently short timescale where magnetic damping is weak, a complete analytical classification of the nonlinear wave dynamics is realized. The solutions include rarefaction waves, dispersive shock waves, and solitons that are described using nonlinear wave modulation theory and are confirmed by numerical simulations. For a sufficiently long timescale, magnetic damping drives the dynamics to steady states that exhibit time-periodic dynamics. A hydrodynamic interpretation is essential in these findings where subsonic/supersonic conditions and convex/nonconvex flux play determinative roles. The second part of the thesis studies the dynamics of AFMs and FIMs. A two-sublattice micromagnetic model in terms of coupled Landau-Lifshitz-type equations describing the continuous magnetization dynamics is derived based on a semiclassical atomic crystal lattice of spins. From the derived model, several simple solutions describing fundamental magnetic configurations are identified. These include hydrodynamic-like states. An analysis of the corresponding energy functional for the system is used to identify phase transitions between different states. In addition, the dynamical stability of local energy minima is analyzed. Ill-posedness of the continuum equations for an AFM is identified with an unphysical short wave instability. The instability is found to manifest for wavelengths that are likely smaller than typical micromagnetic discretizations. Nevertheless, means to regularize the equations using higher-order or nonlocal terms are introduced.</p

Production and characterization of HTC solids from lignin-rich biomass and downstream application in anaerobic digestion

Lignocellulosic biomass is mainly composed of three pseudo components, namely hemicellulose, cellulose, and lignin. Of these three, lignin as a cross-linked network hydrophobic polymer has a strong resistance to biodegradation such as anaerobic digestion (Hatfield and Fukushima 2005, Fernandes, Klaasse Bos et al. 2009), but can be decomposed thermally. Hydrothermal carbonization is a promising method of processing biomass with high moisture content for value-added products. This study evaluates and compares the physicochemical characteristics of hydrochar derived from rice husk, wheat straw pellets, oil rape straw pellets and reference alkali lignin. The results indicated wide variation in the physicochemical properties and quality of hydrochar depending on biomass feedstock composition. Mass yields of lignocelluosic biomass increased with the increase of lignin content, however, higher lignin content biomass exhibited lower hydrogen/carbon ratio. The results of this study also identified that hydrochar were more acidic than biochar produced from same feedstocks, however, Kraft lignin hydrochar exhibited higher pH 9.52. The study also seeks to explain the role of biomass composition on surface functional groups of hydrochar via attenuated total reflection - Fourier transform infrared spectroscopy (ATR-FTIR). The ATR-FTIR spectra were used to identify the functional groups qualitatively. It would give further insight into surface functional groups of hydrochars and the changes in the chemical composition of lignin and biomass during the conversion process. Please click Additional Files below to see the full abstract

LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning

Cooperative multi-agent reinforcement learning (MARL) has made prominent progress in recent years. For training efficiency and scalability, most of the MARL algorithms make all agents share the same policy or value network. However, in many complex multi-agent tasks, different agents are expected to possess specific abilities to handle different subtasks. In those scenarios, sharing parameters indiscriminately may lead to similar behavior across all agents, which will limit the exploration efficiency and degrade the final performance. To balance the training complexity and the diversity of agent behavior, we propose a novel framework to learn dynamic subtask assignment (LDSA) in cooperative MARL. Specifically, we first introduce a subtask encoder to construct a vector representation for each subtask according to its identity. To reasonably assign agents to different subtasks, we propose an ability-based subtask selection strategy, which can dynamically group agents with similar abilities into the same subtask. In this way, agents dealing with the same subtask share their learning of specific abilities and different subtasks correspond to different specific abilities. We further introduce two regularizers to increase the representation difference between subtasks and stabilize the training by discouraging agents from frequently changing subtasks, respectively. Empirical results show that LDSA learns reasonable and effective subtask assignment for better collaboration and significantly improves the learning performance on the challenging StarCraft II micromanagement benchmark and Google Research Football

Spin-Injection-Generated Shock Waves and Solitons in a Ferromagnetic Thin Film

Unsteady nonlinear magnetization dynamics are studied in an easy-plane ferromagnetic channel subject to spin injection at one edge. The Landau-Lifshitz equation is known to support steady-state solutions, termed dissipative exchange flows (DEFs) or spin superfluids. In this work, by means of numerical simulations and theoretical analysis, we provide a full description of the injection-induced, large-amplitude, nonlinear magnetization dynamics up to the steady state. The dynamics prior to reaching steady state are driven by spin injection, a perpendicular applied magnetic field, the exchange interaction, and local demagnetizing fields. We show that the dynamics result in well-defined profiles in the form of rarefaction waves (RWs), dispersive shock waves (DSWs), and solitons. The realization of these coherent structures depends on the interplay between the spin injection strength and the applied magnetic field. A soliton at the injection boundary, signaling the onset of the magnetic 'supersonic' condition, rapidly develops and persists in the steady-state configuration of a contact soliton DEF. We also demonstrate the existence of sustained soliton-train dynamics in long time that can only arise in a nonzero applied magnetic field scenario. The dynamical evolution of spin-injection-induced magnetization dynamics presented here may help guide observations in long-distance spin transport experiments

Chain of Natural Language Inference for Reducing Large Language Model Ungrounded Hallucinations

Large language models (LLMs) can generate fluent natural language texts when given relevant documents as background context. This ability has attracted considerable interest in developing industry applications of LLMs. However, LLMs are prone to generate hallucinations that are not supported by the provided sources. In this paper, we propose a hierarchical framework to detect and mitigate such ungrounded hallucination. Our framework uses Chain of Natural Language Inference (CoNLI) for hallucination detection and hallucination reduction via post-editing. Our approach achieves state-of-the-art performance on hallucination detection and enhances text quality through rewrite, using LLMs without any fine-tuning or domain-specific prompt engineering. We show that this simple plug-and-play framework can serve as an effective choice for hallucination detection and reduction, achieving competitive performance across various contexts.Comment: The source code is available at https://github.com/microsoft/CoNLI_hallucinatio