Entropy plays a pivotal role in catalysis, and extensive research efforts have been directed to understanding the enthalpy-entropy relationship that defines the reaction pathways of molecular ...species. On the other side, surface of the catalysts, entropic effects have been rarely investigated because of the difficulty in deciphering the increased complexities in multicomponent systems. Recent advances in high-entropy materials (HEMs) have triggered broad interests in exploring entropy-stabilized systems for catalysis, where the enhanced configurational entropy affords a virtually unlimited scope for tailoring the structures and properties of HEMs. In this review, we summarize recent progress in the discovery and design of HEMs for catalysis. The correlation between compositional and structural engineering and optimization of the catalytic behaviors is highlighted for high-entropy alloys, oxides, and beyond. Tuning composition and configuration of HEMs introduces untapped opportunities for accessing better catalysts and resolving issues that are considered challenging in conventional, simple systems.
SVDNet for Pedestrian Retrieval Yifan Sun; Liang Zheng; Weijian Deng ...
2017 IEEE International Conference on Computer Vision (ICCV),
2017-Oct.
Conference Proceeding
Odprti dostop
This paper proposes the SVDNet for retrieval problems, with focus on the application of person re-identification (reID). We view each weight vector within a fully connected (FC) layer in a ...convolutional neuron network (CNN) as a projection basis. It is observed that the weight vectors are usually highly correlated. This problem leads to correlations among entries of the FC descriptor, and compromises the retrieval performance based on the Euclidean distance. To address the problem, this paper proposes to optimize the deep representation learning process with Singular Vector Decomposition (SVD). Specifically, with the restraint and relaxation iteration (RRI) training scheme, we are able to iteratively integrate the orthogonality constraint in CNN training, yielding the so-called SVDNet. We conduct experiments on the Market-1501, CUHK03, and DukeMTMC-reID datasets, and show that RRI effectively reduces the correlation among the projection vectors, produces more discriminative FC descriptors, and significantly improves the re-ID accuracy. On the Market-1501 dataset, for instance, rank-1 accuracy is improved from 55.3% to 80.5% for CaffeNet, and from 73.8% to 82.3% for ResNet-50.
•The applications of decision making techniques in healthcare and medical industry are reviewed.•We evaluated 202 published studies selected from 85 high-ranking journals.•Selected studies were ...classified into nine application areas.•AHP and fuzzy AHP techniques were the most frequently used decision-making technique.
Decision making techniques have been widely used in healthcare and medical industry. This study systematically reviews the conventional and fuzzy decision-making techniques applied in healthcare and medical problems. In total, we evaluated 202 published studies selected from 85 high-ranking journals, in which 130 of those published studies were directly related to the decision-making processes in healthcare and medical issues. Selected studies were classified into nine application areas: environmental sustainability, waste management, service quality, risk management, medical equipment and material selection, health technology, operation researches in healthcare, hospital healthcare services and other application areas. Furthermore, we classified the selected studies by numerous significant perspectives such as the authors, application areas, utilized techniques, publication time periods, decision-making and study goals, and significant results of the papers. The statistical results show that the year 2012 was ranked first in terms of developed studies within the period of 1989–2018. The techniques of AHP and hybrid approaches were the most frequently implemented decision-making technique in healthcare fields. Notably, the results also show that decision-making approaches and techniques are mostly applied to evaluate and rank different applications of service quality in healthcare and medical industries.
This paper provides a pair similarity optimization viewpoint on deep feature learning, aiming to maximize the within-class similarity s_p and minimize the between-class similarity s_n. We find a ...majority of loss functions, including the triplet loss and the softmax cross-entropy loss, embed s_n and s_p into similarity pairs and seek to reduce (s_n-s_p). Such an optimization manner is inflexible, because the penalty strength on every single similarity score is restricted to be equal. Our intuition is that if a similarity score deviates far from the optimum, it should be emphasized. To this end, we simply re-weight each similarity to highlight the less-optimized similarity scores. It results in a Circle loss, which is named due to its circular decision boundary. The Circle loss has a unified formula for two elemental deep feature learning paradigms, \emph {i.e.}, learning with class-level labels and pair-wise labels. Analytically, we show that the Circle loss offers a more flexible optimization approach towards a more definite convergence target, compared with the loss functions optimizing (s_n-s_p). Experimentally, we demonstrate the superiority of the Circle loss on a variety of deep feature learning tasks. On face recognition, person re-identification, as well as several fine-grained image retrieval datasets, the achieved performance is on par with the state of the art.
Exfoliated 2H molybdenum disulfide (MoS2) has unique properties and potential applications in a wide range of fields, but corresponding studies have been hampered by the lack of effective routes to ...it in bulk quantities. This study presents a rapid and efficient route to obtain exfoliated 2H MoS2, which combines fast sonication-assisted lithium intercalation and infrared (IR) laser-induced phase reversion. We found that the complete lithium intercalation of MoS2 with butyllithium could be effected within 1.5 h with the aid of sonication. The 2H to 1T phase transition that occurs during the lithium intercalation could be also reversed by IR laser irradiation with a DVD optical drive.
•A research model of continuance intention on mobile social-messaging applications based on guanxi theory is proposed.•Partial least squares path modelling was employed to test the proposed ...hypotheses.•Guanxi influences continuance intention, perceived usefulness and perceived enjoyment through mianzi and ganqing.
Social influence is an important research topic in the technology acceptance literature, in particular for social media. Prior empirical studies have for the most part employed social influence theory to investigate user intentions to continue with social media, while culture driven theories have been neglected. Rather than using social influence theory, we introduced guanxi theory to explore how guanxi social mechanisms (or processes) influence Chinese users’ continuance intentions in WeChat. Specifically, we developed a model that examines the role of guanxi as manifested by renqing, mianzi and ganqing in perceived usefulness, perceived enjoyment and continuance intention in WeChat. A survey research method was adopted to test the proposed hypotheses. This study found that ganqing has a positive impact on perceived usefulness and continuance intention. Mianzi exerts a negative effect on continuance intention but exhibits a positive effect on perceived usefulness. Renqing was found to have no significant impact on perceived usefulness and continuance intention. Our study advances the Technology Acceptance Model (TAM) by introducing guanxi-based constructs in a Chinese mobile social-messaging application context. Our study also offers alternative insights on guanxi-based social influence processes in the Chinese technology acceptance literature.
and
, two well-known medical plants with economic value, have a long history of use for managing various diseases in Asian countries. Accumulating clinical and experimental evidence suggests that ...notoginsenosides and ginsenosides, which are the major bioactive components of the plants, have a variety of beneficial effects on several types of disease, including metabolic, vascular, and central nervous system disease. Considerable attention has been focused on ginsenoside Rb1 derived from their common ownership as an anti-diabetic agent that can attenuate insulin resistance and various complications. Particularly, in vitro and in vivo models have suggested that ginsenoside Rb1 exerts various pharmacological effects on metabolic disorders, including attenuation of glycemia, hypertension, and hyperlipidemia, which depend on the modulation of oxidative stress, inflammatory response, autophagy, and anti-apoptosis effects. Regulation of these pathophysiological mechanisms can improve blood glucose and insulin resistance and protect against macrovascular/microvascular related complications. This review summarizes the pharmacological effects and mechanisms of action of ginsenoside Rb1 in the management of diabetes or diabetic complications. Moreover, a multi-target effect and mechanism analysis of its antidiabetic actions were performed to provide a theoretical basis for further pharmacological studies and new drug development for clinical treatment of type 2 diabetes. In conclusion, ginsenoside Rb1 exerts significant anti-obesity, anti-hyperglycemic, and anti-diabetic effects by regulating the effects of glycolipid metabolism and improving insulin and leptin sensitivities. All of these findings suggest ginsenoside Rb1 exerts protective effects on diabetes and diabetic complications by the regulation of mitochondrial energy metabolism, improving insulin resistance and alleviating the occurrence complications, which should be further explored. Hence, ginsenoside Rb1 may be developed as a potential anti-obesity, anti-hyperglycemic, and anti-diabetic agent with multi-target effects.
Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make fewer measurements than were considered necessary to record a signal, ...enabling faster or more precise measurement protocols in a wide range of applications. Using an interdisciplinary approach, we have recently proposed in Krzakala et al (2012 Phys. Rev. X 2 021005) a strategy that allows compressed sensing to be performed at acquisition rates approaching the theoretical optimal limits. In this paper, we give a more thorough presentation of our approach, and introduce many new results. We present the probabilistic approach to reconstruction and discuss its optimality and robustness. We detail the derivation of the message passing algorithm for reconstruction and expectation maximization learning of signal-model parameters. We further develop the asymptotic analysis of the corresponding phase diagrams with and without measurement noise, for different distributions of signals, and discuss the best possible reconstruction performances regardless of the algorithm. We also present new efficient seeding matrices, test them on synthetic data and analyze their performance asymptotically.
Mode locking is predicted in a nanolaser cavity forming an effective photonic harmonic potential. The cavity is substantially more compact than a Fabry-Perot resonator with a comparable pulsing ...period, which is here controlled by the potential. In the limit of instantaneous gain and absorption saturation, mode locking corresponds to a stable dissipative soliton, which is very well approximated by the coherent state of a quantum mechanical harmonic oscillator. This property is robust against noninstantaneous material response and nonzero phase-intensity coupling.
Cerebral ischemia-reperfusion is a complicated pathological process. The injury and cascade reactions caused by cerebral ischemia and reperfusion are characterized by high mortality, high recurrence, ...and high disability. However, only a limited number of antithrombotic drugs, such as recombinant tissue plasminogen activator (r-TPA), aspirin, and heparin, are currently available for ischemic stroke, and its safety concerns is inevitable which associated with reperfusion injury and hemorrhage. Therefore, it is necessary to further explore and examine some potential neuroprotective agents with treatment for cerebral ischemia and reperfusion injury to reduce safety concerns caused by antithrombotic drugs in ischemic stroke. Ginseng Rg1 (G-Rg1) is a saponin composed of natural active ingredients and derived from the roots or stems of
and ginseng in traditional Chinese medicine. Its pharmacological effects exert remarkable neurotrophic and neuroprotective effects in the central nervous system. To explore and summarize the protective effects and mechanisms of ginsenoside Rg1 against cerebral ischemia and reperfusion injury, we conducted this review, in which we searched the PubMed database to obtain and organize studies concerning the pharmacological effects and mechanisms of ginsenoside Rg1 against cerebral ischemia and reperfusion injury. This study provides a valuable reference and clues for the development of new agents to combat ischemic stroke. Our summarized review and analysis show that the pharmacological effects of and mechanisms underlying ginsenoside Rg1 activity against cerebral ischemia and reperfusion injury mainly involve 4 sets of mechanisms: anti-oxidant activity and associated apoptosis via the Akt, Nrf2/HO-1, PPARγ/HO-1, extracellular regulated protein kinases (ERK), p38, and c-Jun N-terminal kinase (JNK) pathways (or mitochondrial apoptosis pathway) and the caspase-3/ROCK1/MLC pathway; anti-inflammatory and immune stimulatory-related activities that involve apoptosis or necrosis via MAPK pathways (the JNK1/2 + ERK1/2 and PPARγ/HO-1 pathways), endoplasmic reticulum stress (ERS), high mobility group protein1 (HMGB1)-induced TLR2/4/9 and receptor for advanced glycation end products (RAGE) pathways, and the activation of NF-κB; neurological cell cycle, proliferation, differentiation, and regeneration via the MAPK pathways (JNK1/2 + ERK1/2, PI3K-Akt/mTOR, PKB/Akt and HIF-1α/VEGF pathways); and energy metabolism and the regulation of cellular ATP levels, the blood-brain barrier and other effects via N-methyl-D-aspartic acid (NMDA) receptors, ERS, and AMP/AMPK-GLUT pathways. Collectively, these mechanisms result in significant neuroprotective effects against cerebral ischemic injury. These findings will be valuable in that they should further promote the development of candidate drugs and provide more information to support the application of previous findings in stroke clinical trials.
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