Calibration Methods of Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) has gained great attention over the past two decades due to its many advantages, such as needless sample preparation, capability of remote measurement and fast multielement simultaneous analysis. However, because of its inherent uncertainty features of plasma, it is still a big challenge for LIBS community worldwide to realize high sensitivity and accurate quantitative analysis. Currently, many chemometric analytical methods have been applied to LIBS calibration analysis, including univariate regression, multivariate regression, principal component regression (PCR), partial least squares regression (PLSR) and so on. In addition, appropriate sample and spectral pretreatment can effectively improve the analytical performance (i.e., limit of detection (LOD), accuracy and repeatability) of LIBS. In this chapter, we briefly summarize the progress of these calibration methods and their applications on LIBS and provide our recommendations

The determinants of public acceptance of telemedicine apps: an innovation diffusion perspective

With the rapid advancement of information technology, telemedicine apps have gradually become an indispensable tool for providing patients with more convenient, efficient, and accessible healthcare services. However, the successful implementation of these apps largely depends on widespread acceptance among the public. To thoroughly investigate the factors influencing the public’s acceptance of these apps and the relationships between these factors, this study developed a theoretical model based on the Diffusion of Innovation theory and the Theory of Perceived Value. To validate this model, we conducted a survey of 387 residents in Beijing, China, and employed structural equation modeling to analyze the collected data. The research findings indicate that attributes of innovation diffusion, including relative advantage, compatibility, complexity, trialability, and observability, significantly and positively influence the public’s perceived value. Particularly noteworthy is that perceived value partially mediates the relationship between innovation attributes and public acceptance, emphasizing the crucial role of perceived value in the public decision-making process. This study employed a theory-driven approach to elucidate the acceptance of telemedicine apps and offers fresh insights into the existing literature. By integrating the research paradigms of innovation diffusion and customer perceived value, we provide a coherent explanation of how individual cognitive processes lead to acceptance behavior. In summary, this research enriches the existing theoretical studies on the acceptance of telemedicine apps and holds positive implications for healthcare practice

catena-Poly[[aqua­dipyridine­copper(II)]-μ-fumarato]

The title compound, [Cu(C4H2O4)(C5H5N)2(H2O)]n, is a one-dimensional coordination polymer based on pyridine and fumarate ligands. Each CuII cation is coordinated by two carboxyl­ate O atoms belonging to two fumarate anions, two N atoms from two pyridine mol­ecules and one water mol­ecule, in a square-based pyramidal geometry. Each fumarate anion bridges two CuII cations through the two carboxyl­ate groups in a bis-monodentate fashion to form a one-dimensional polymeric chain along the c axis. Neighbouring chains are linked together to form a two-dimensional network parallel to the ac plane via hydrogen bonding inter­actions between uncoordinated carboxyl­ate O atoms and coordinated water mol­ecules of adjecent chains

Constraint-based automatic symmetry detection

10.1109/ASE.2013.66930622013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings15-2

Inflammation-Mediated Memory Dysfunction and Effects of a Ketogenic Diet in a Murine Model of Multiple Sclerosis

A prominent clinical symptom in multiple sclerosis (MS), a progressive disorder of the central nervous system (CNS) due to heightened neuro-inflammation, is learning and memory dysfunction. Here, we investigated the effects of a ketogenic diet (KD) on memory impairment and CNS-inflammation in a murine model of experimental autoimmune encephalomyelitis (EAE), using electrophysiological, behavioral, biochemical and in vivo imaging approaches. Behavioral spatial learning deficits were associated with motor disability in EAE mice, and were observed concurrently with brain inflammation. The KD improved motor disability in the EAE model, as well as CA1 hippocampal synaptic plasticity (long-term potentiation) and spatial learning and memory (assessed with the Morris Water Maze). Moreover, hippocampal atrophy and periventricular lesions in EAE mice were reversed in KD-treated EAE mice. Finally, we found that the increased expression of inflammatory cytokines and chemokines, as well as the production of reactive oxygen species (ROS), in our EAE model were both suppressed by the KD. Collectively, our findings indicate that brain inflammation in EAE mice is associated with impaired spatial learning and memory function, and that KD treatment can exert protective effects, likely via attenuation of the robust immune response and increased oxidative stress seen in these animals

Experimental observation of Dirac-like surface states and topological phase transition in Pb1−x_{1-x}Snx_xTe(111) films

The surface of a topological crystalline insulator (TCI) carries an even number of Dirac cones protected by crystalline symmetry. We epitaxially grew high quality Pb$_{1-x}$Sn$_x$Te(111) films and investigated the TCI phase by in-situ angle-resolved photoemission spectroscopy. Pb$_{1-x}$Sn$_x$Te(111) films undergo a topological phase transition from trivial insulator to TCI via increasing the Sn/Pb ratio, accompanied by a crossover from n-type to p-type doping. In addition, a hybridization gap is opened in the surface states when the thickness of film is reduced to the two-dimensional limit. The work demonstrates an approach to manipulating the topological properties of TCI, which is of importance for future fundamental research and applications based on TCI

Nicotinic Receptor β2 Determines Nk Cell-Dependent Metastasis In A Murine Model Of Metastatic Lung Cancer

Cigarette smoke exposure markedly compromises the ability of the immune system to protect against invading pathogens and tumorigenesis. Nicotine is a psychoactive component of tobacco products that acts as does the natural neurotransmitter, acetylcholine, on nicotinic receptors (nAChRs). Here we demonstrate that natural killer (NK) cells strongly express nAChR β2. Nicotine exposure impairs the ability of NK cells to kill target cells and release cytokines, a process that is largely abrogated by nAChR β2 deficiency. Further, nicotinic suppression of NF-κB-induced transcriptional activity in NK cells is dependent on nAChR β2. This nAChR subtype also plays a large role in the NK cell-mediated control of melanoma lung metastasis, in a murine lung metastasis model exposed to nicotine. Our findings suggest nAChR β2 as a prominent pathway for nicotine induced impairment of NK cell functions which contributes to the occurrence of smoking-related pathologies. © 2013 Hao et al

Eight-input optical programmable logic array enabled by parallel spectrum modulation

Despite over 40 years' development of optical logic computing, the studies have been still struggling to support more than four operands, since the high parallelism of light has not been fully leveraged blocked by the optical nonlinearity and redundant input modulation in existing methods. Here, we propose a scalable multi-input optical programmable logic array (PLA) with minimal logical input, enabled by parallel spectrum modulation. By making full use of the wavelength resource, an eight-input PLA is experimentally demonstrated, and there are 2^256 possible combinations of generated logic gates. Various complex logic fuctions, such as 8-256 decoder, 4-bit comparator, adder and multiplier are experimentally demonstrated via leveraging the PLA. The scale of PLA can be further extended by fully using the dimensions of wavelength and space. As an example, a nine-input PLA is implemented to realize the two-dimensional optical cellular automaton for the first time and perform Conway's Game of Life to simulate the evolutionary process of cells. Our work significantly alleviates the challenge of extensibility of optical logic devices, opening up new avenues for future large-scale, high-speed and energy-efficient optical digital computing

Valley: Video Assistant with Large Language model Enhanced abilitY

Large language models (LLMs), with their remarkable conversational capabilities, have demonstrated impressive performance across various applications and have emerged as formidable AI assistants. In view of this, it raises an intuitive question: Can we harness the power of LLMs to build multimodal AI assistants for visual applications? Recently, several multi-modal models have been developed for this purpose. They typically pre-train an adaptation module to align the semantics of the vision encoder and language model, followed by fine-tuning on instruction-following data. However, despite the success of this pipeline in image and language understanding, its effectiveness in joint video and language understanding has not been widely explored. In this paper, we aim to develop a novel multi-modal foundation model capable of comprehending video, image, and language within a general framework. To achieve this goal, we introduce Valley, a Video Assistant with Large Language model Enhanced abilitY. The Valley consists of a LLM, a temporal modeling module, a visual encoder, and a simple projection module designed to bridge visual and textual modes. To empower Valley with video comprehension and instruction-following capabilities, we construct a video instruction dataset and adopt a two-stage tuning procedure to train it. Specifically, we employ ChatGPT to facilitate the construction of task-oriented conversation data encompassing various tasks, including multi-shot captions, long video descriptions, action recognition, causal relationship inference, etc. Subsequently, we adopt a pre-training-then-instructions-tuned pipeline to align visual and textual modalities and improve the instruction-following capability of Valley. Qualitative experiments demonstrate that Valley has the potential to function as a highly effective video assistant that can make complex video understanding scenarios easy