Dalian University of Technology

A review on dye-sensitized solar cells (DSCs). Some brief notes on solar energy in general and DSC in particular are given, followed by a discussion of the operational principles of DSC (energetics and kinetics). Then, the development of material components and some specific exptl. techniques to characterize DSC are described. The current status of module development is also discussed, and finally a brief future outlook is given.

Recently, channel attention mechanism has demonstrated to offer great potential in improving the performance of deep convolutional neural networks (CNNs). However, most existing methods dedicate to developing more sophisticated attention modules for achieving better performance, which inevitably increase model complexity. To overcome the paradox of performance and complexity trade-off, this paper proposes an Efficient Channel Attention (ECA) module, which only involves a handful of parameters while bringing clear performance gain. By dissecting the channel attention module in SENet, we empirically show avoiding dimensionality reduction is important for learning channel attention, and appropriate cross-channel interaction can preserve performance while significantly decreasing model complexity. Therefore, we propose a local cross-channel interaction strategy without dimensionality reduction, which can be efficiently implemented via 1D convolution. Furthermore, we develop a method to adaptively select kernel size of 1D convolution, determining coverage of local cross-channel interaction. The proposed ECA module is both efficient and effective, e.g., the parameters and computations of our modules against backbone of ResNet50 are 80 vs. 24.37M and 4.7e-4 GFlops vs. 3.86 GFlops, respectively, and the performance boost is more than 2% in terms of Top-1 accuracy. We extensively evaluate our ECA module on image classification, object detection and instance segmentation with backbones of ResNets and MobileNetV2. The experimental results show our module is more efficient while performing favorably against its counterparts.

BACKGROUND: Modern medicine often clashes with traditional medicine such as Chinese herbal medicine because of the little understanding of the underlying mechanisms of action of the herbs. In an effort to promote integration of both sides and to accelerate the drug discovery from herbal medicines, an efficient systems pharmacology platform that represents ideal information convergence of pharmacochemistry, ADME properties, drug-likeness, drug targets, associated diseases and interaction networks, are urgently needed. DESCRIPTION: The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 Chinese herbs registered in the Chinese pharmacopoeia with 29,384 ingredients, 3,311 targets and 837 associated diseases. Twelve important ADME-related properties like human oral bioavailability, half-life, drug-likeness, Caco-2 permeability, blood-brain barrier and Lipinski's rule of five are provided for drug screening and evaluation. TCMSP also provides drug targets and diseases of each active compound, which can automatically establish the compound-target and target-disease networks that let users view and analyze the drug action mechanisms. It is designed to fuel the development of herbal medicines and to promote integration of modern medicine and traditional medicine for drug discovery and development. CONCLUSIONS: The particular strengths of TCMSP are the composition of the large number of herbal entries, and the ability to identify drug-target networks and drug-disease networks, which will help revealing the mechanisms of action of Chinese herbs, uncovering the nature of TCM theory and developing new herb-oriented drugs. TCMSP is freely available at http://sm.nwsuaf.edu.cn/lsp/tcmsp.php.

We report classes of electronic systems that achieve thicknesses, effective elastic moduli, bending stiffnesses, and areal mass densities matched to the epidermis. Unlike traditional wafer-based technologies, laminating such devices onto the skin leads to conformal contact and adequate adhesion based on van der Waals interactions alone, in a manner that is mechanically invisible to the user. We describe systems incorporating electrophysiological, temperature, and strain sensors, as well as transistors, light-emitting diodes, photodetectors, radio frequency inductors, capacitors, oscillators, and rectifying diodes. Solar cells and wireless coils provide options for power supply. We used this type of technology to measure electrical activity produced by the heart, brain, and skeletal muscles and show that the resulting data contain sufficient information for an unusual type of computer game controller.

A supercapacitor with graphene-based electrodes was found to exhibit a specific energy density of 85.6 Wh/kg at room temperature and 136 Wh/kg at 80 °C (all based on the total electrode weight), measured at a current density of 1 A/g. These energy density values are comparable to that of the Ni metal hydride battery, but the supercapacitor can be charged or discharged in seconds or minutes. The key to success was the ability to make full utilization of the highest intrinsic surface capacitance and specific surface area of single-layer graphene by preparing curved graphene sheets that will not restack face-to-face. The curved morphology enables the formation of mesopores accessible to and wettable by environmentally benign ionic liquids capable of operating at a voltage >4 V.

Abstract Globalization results in both pressure and drivers for Chinese enterprises to improve their environmental performance. As a developing country, China has to balance economic and environmental performance. Green supply chain management (GSCM) is emerging to be an important approach for Chinese enterprises to improve performance, possibly on both these dimensions. Using empirical results from 186 respondents on GSCM practice in Chinese manufacturing enterprises, we examine the relationships between GSCM practice and environmental and economic performance. Using moderated hierarchical regression analysis, we evaluate the general relationships between specific GSCM practices and performance. We then investigate how two primary types of management operations philosophies, quality management and just‐in‐time (or lean) manufacturing principles, influence the relationship between GSCM practices and performance. Significant findings were determined for a number of relationships. Managerial implications are also identified.

Most existing bottom-up methods measure the foreground saliency of a pixel or region based on its contrast within a local context or the entire image, whereas a few methods focus on segmenting out background regions and thereby salient objects. Instead of considering the contrast between the salient objects and their surrounding regions, we consider both foreground and background cues in a different way. We rank the similarity of the image elements (pixels or regions) with foreground cues or background cues via graph-based manifold ranking. The saliency of the image elements is defined based on their relevances to the given seeds or queries. We represent the image as a close-loop graph with super pixels as nodes. These nodes are ranked based on the similarity to background and foreground queries, based on affinity matrices. Saliency detection is carried out in a two-stage scheme to extract background regions and foreground salient objects efficiently. Experimental results on two large benchmark databases demonstrate the proposed method performs well when against the state-of-the-art methods in terms of accuracy and speed. We also create a more difficult benchmark database containing 5,172 images to test the proposed saliency model and make this database publicly available with this paper for further studies in the saliency field.

MXenes, a new family of 2D materials, combine hydrophilic surfaces with metallic conductivity. Delamination of MXene produces single-layer nanosheets with thickness of about a nanometer and lateral size of the order of micrometers. The high aspect ratio of delaminated MXene renders it promising nanofiller in multifunctional polymer nanocomposites. Herein, Ti3C2T(x) MXene was mixed with either a charged polydiallyldimethylammonium chloride (PDDA) or an electrically neutral polyvinyl alcohol (PVA) to produce Ti3C2T(x)/polymer composites. The as-fabricated composites are flexible and have electrical conductivities as high as 2.2 × 10(4) S/m in the case of the Ti3C2T(x)/PVA composite film and 2.4 × 10(5) S/m for pure Ti3C2T(x) films. The tensile strength of the Ti3C2T(x)/PVA composites was significantly enhanced compared with pure Ti3C2T(x) or PVA films. The intercalation and confinement of the polymer between the MXene flakes not only increased flexibility but also enhanced cationic intercalation, offering an impressive volumetric capacitance of ∼530 F/cm(3) for MXene/PVA-KOH composite film at 2 mV/s. To our knowledge, this study is a first, but crucial, step in exploring the potential of using MXenes in polymer-based multifunctional nanocomposites for a host of applications, such as structural components, energy storage devices, wearable electronics, electrochemical actuators, and radiofrequency shielding, to name a few.

Macrophages exist in various tissues, several body cavities, and around mucosal surfaces and are a vital part of the innate immune system for host defense against many pathogens and cancers. Macrophages possess binary M1/M2 macrophage polarization settings, which perform a central role in an array of immune tasks via intrinsic signal cascades and, therefore, must be precisely regulated. Many crucial questions about macrophage signaling and immune modulation are yet to be uncovered. In addition, the clinical importance of tumor-associated macrophages is becoming more widely recognized as significant progress has been made in understanding their biology. Moreover, they are an integral part of the tumor microenvironment, playing a part in the regulation of a wide variety of processes including angiogenesis, extracellular matrix transformation, cancer cell proliferation, metastasis, immunosuppression, and resistance to chemotherapeutic and checkpoint blockade immunotherapies. Herein, we discuss immune regulation in macrophage polarization and signaling, mechanical stresses and modulation, metabolic signaling pathways, mitochondrial and transcriptional, and epigenetic regulation. Furthermore, we have broadly extended the understanding of macrophages in extracellular traps and the essential roles of autophagy and aging in regulating macrophage functions. Moreover, we discussed recent advances in macrophages-mediated immune regulation of autoimmune diseases and tumorigenesis. Lastly, we discussed targeted macrophage therapy to portray prospective targets for therapeutic strategies in health and diseases.

Superhydrophobic self-cleaning surfaces are based on the surface micro/nanomorphologies; however, such surfaces are mechanically weak and stop functioning when exposed to oil. We have created an ethanolic suspension of perfluorosilane-coated titanium dioxide nanoparticles that forms a paint that can be sprayed, dipped, or extruded onto both hard and soft materials to create a self-cleaning surface that functions even upon emersion in oil. Commercial adhesives were used to bond the paint to various substrates and promote robustness. These surfaces maintained their water repellency after finger-wipe, knife-scratch, and even 40 abrasion cycles with sandpaper. The formulations developed can be used on clothes, paper, glass, and steel for a myriad of self-cleaning applications.

Model distillation is an effective and widely used technique to transfer knowledge from a teacher to a student network. The typical application is to transfer from a powerful large network or ensemble to a small network, in order to meet the low-memory or fast execution requirements. In this paper, we present a deep mutual learning (DML) strategy. Different from the one-way transfer between a static pre-defined teacher and a student in model distillation, with DML, an ensemble of students learn collaboratively and teach each other throughout the training process. Our experiments show that a variety of network architectures benefit from mutual learning and achieve compelling results on both category and instance recognition tasks. Surprisingly, it is revealed that no prior powerful teacher network is necessary - mutual learning of a collection of simple student networks works, and moreover outperforms distillation from a more powerful yet static teacher.

High-entropy alloys (HEAs) can have either high strength or high ductility, and a simultaneous achievement of both still constitutes a tough challenge. The inferior castability and compositional segregation of HEAs are also obstacles for their technological applications. To tackle these problems, here we proposed a novel strategy to design HEAs using the eutectic alloy concept, i.e. to achieve a microstructure composed of alternating soft fcc and hard bcc phases. As a manifestation of this concept, an AlCoCrFeNi2.1 (atomic portion) eutectic high-entropy alloy (EHEA) was designed. The as-cast EHEA possessed a fine lamellar fcc/B2 microstructure, and showed an unprecedented combination of high tensile ductility and high fracture strength at room temperature. The excellent mechanical properties could be kept up to 700°C. This new alloy design strategy can be readily adapted to large-scale industrial production of HEAs with simultaneous high fracture strength and high ductility.

A multiple-perspective co-citation analysis method is introduced for characterizing and interpreting the structure and dynamics of co-citation clusters. The method facilitates analytic and sense making tasks by integrating network visualization, spectral clustering, automatic cluster labeling, and text summarization. Co-citation networks are decomposed into co-citation clusters. The interpretation of these clusters is augmented by automatic cluster labeling and summarization. The method focuses on the interrelations between a co-citation cluster's members and their citers. The generic method is applied to a three-part analysis of the field of Information Science as defined by 12 journals published between 1996 and 2008: 1) a comparative author co-citation analysis (ACA), 2) a progressive ACA of a time series of co-citation networks, and 3) a progressive document co-citation analysis (DCA). Results show that the multiple-perspective method increases the interpretability and accountability of both ACA and DCA networks.

Recent studies suggest that months to years of intensive and systematic meditation training can improve attention. However, the lengthy training required has made it difficult to use random assignment of participants to conditions to confirm these findings. This article shows that a group randomly assigned to 5 days of meditation practice with the integrative body-mind training method shows significantly better attention and control of stress than a similarly chosen control group given relaxation training. The training method comes from traditional Chinese medicine and incorporates aspects of other meditation and mindfulness training. Compared with the control group, the experimental group of 40 undergraduate Chinese students given 5 days of 20-min integrative training showed greater improvement in conflict scores on the Attention Network Test, lower anxiety, depression, anger, and fatigue, and higher vigor on the Profile of Mood States scale, a significant decrease in stress-related cortisol, and an increase in immunoreactivity. These results provide a convenient method for studying the influence of meditation training by using experimental and control methods similar to those used to test drugs or other interventions.

Due to the biological importances of thiols, such as cysteine, homocysteine and glutathione, the development of optical probes for thiols has been an active research area in recent few years. This critical review focuses on the fluorescent or colorimetric sensors for thiols according to their unique mechanisms between sensors and thiols, including Michael addition, cyclization with aldehyde, cleavage of sulfonamide and sulfonate ester by thiols, cleavage of selenium-nitrogen bond by thiols, cleavage of disulfide by thiols, metal complexes-oxidation-reduction, metal complexes-displace coordination, nano-particles and others (110 references).

Triplet photosensitizers (PSs) are compounds that can be efficiently excited to the triplet excited state which subsequently act as catalysts in photochemical reactions. The name is originally derived from compounds that were used to transfer the triplet energy to other compounds that have only a small intrinsic triplet state yield. Triplet PSs are not only used for triplet energy transfer, but also for photocatalytic organic reactions, photodynamic therapy (PDT), photoinduced hydrogen production from water and triplet-triplet annihilation (TTA) upconversion. A good PS should exhibit strong absorption of the excitation light, a high yield of intersystem crossing (ISC) for efficient production of the triplet state, and a long triplet lifetime to allow for the reaction with a reactant molecule. Most transition metal complexes show efficient ISC, but small molar absorption coefficients in the visible spectral region and short-lived triplet excited states, which make them unsuitable as triplet PSs. One obstacle to the development of new triplet PSs is the difficulty in predicting the ISC of chromophores, especially of organic compounds without any heavy atoms. This review article summarizes some molecular design rationales for triplet PSs, based on the molecular structural factors that facilitate ISC. The design of transition metal complexes with large molar absorption coefficients in the visible spectral region and long-lived triplet excited states is presented. A new method of using a spin converter to construct heavy atom-free organic triplet PSs is discussed, with which ISC becomes predictable, C60 being an example. To enhance the performance of triplet PSs, energy funneling based triplet PSs are proposed, which show broadband absorption in the visible region. Applications of triplet PSs in photocatalytic organic reactions, hydrogen production, triplet-triplet annihilation upconversion and luminescent oxygen sensing are briefly introduced.

Abstract A multiple‐perspective cocitation analysis method is introduced for characterizing and interpreting the structure and dynamics of cocitation clusters. The method facilitates analytic and sense making tasks by integrating network visualization, spectral clustering, automatic cluster labeling, and text summarization. Cocitation networks are decomposed into cocitation clusters. The interpretation of these clusters is augmented by automatic cluster labeling and summarization. The method focuses on the interrelations between a cocitation cluster's members and their citers. The generic method is applied to a three‐part analysis of the field of information science as defined by 12 journals published between 1996 and 2008: (a) a comparative author cocitation analysis (ACA), (b) a progressive ACA of a time series of cocitation networks, and (c) a progressive document cocitation analysis (DCA). Results show that the multiple‐perspective method increases the interpretability and accountability of both ACA and DCA networks.

The utilization of fossil fuels has enabled an unprecedented era of prosperity and advancement of well-being for human society. However, the associated increase in anthropogenic carbon dioxide (CO2) emissions can negatively affect global temperatures and ocean acidity. Moreover, fossil fuels are a limited resource and their depletion will ultimately force one to seek alternative carbon sources to maintain a sustainable economy. Converting CO2 into value-added chemicals and fuels, using renewable energy, is one of the promising approaches in this regard. Major advances in energy-efficient CO2 conversion can potentially alleviate CO2 emissions, reduce the dependence on nonrenewable resources, and minimize the environmental impacts from the portions of fossil fuels displaced. Methanol (CH3OH) is an important chemical feedstock and can be used as a fuel for internal combustion engines and fuel cells, as well as a platform molecule for the production of chemicals and fuels. As one of the promising approaches, thermocatalytic CO2 hydrogenation to CH3OH via heterogeneous catalysis has attracted great attention in the past decades. Major progress has been made in the development of various catalysts including metals, metal oxides, and intermetallic compounds. In addition, efforts are also put forth to define catalyst structures in nanoscale by taking advantage of nanostructured materials, which enables the tuning of the catalyst composition and modulation of surface structures and potentially endows more promising catalytic performance in comparison to the bulk materials prepared by traditional methods. Despite these achievements, significant challenges still exist in developing robust catalysts with good catalytic performance and long-term stability. In this review, we will provide a comprehensive overview of the recent advances in this area, especially focusing on structure–activity relationship, as well as the importance of combining catalytic measurements, in situ characterization, and theoretical studies in understanding reaction mechanisms and identifying key descriptors for designing improved catalysts.

Abstract Purpose – Green supply chain management (GSCM) has emerged as a key approach for enterprises seeking to become environmentally sustainable. This paper aims to evaluate and describe GSCM drivers, practices and performance among various Chinese manufacturing organizations. Design/methodology/approach – Based on a literature review, four propositions are put forward. An empirical study using survey research was completed. The survey questionnaire was designed with 54 items using literature and industry expert input. An exploratory factor analysis was conducted to derive groupings of GSCM pressures, practice and performance from the survey data which included 314 responses. A categorical and descriptive nature of the results is then presented with an evaluation and comparative analysis with previous research findings. Findings – Chinese enterprises have increased their environmental awareness due to regulatory, competitive, and marketing pressures and drivers. However, this awareness has not been translated into strong GSCM practice adoption, let alone into improvements in some areas of performance, where it was expected. Research limitations/implications – The investigation and its findings are still relatively exploratory. Future research can investigate relationships identified in this work, as well as tease out mediating and moderating relationships. A more broadly‐based and random sample study across China would also provide a better picture of this GSCM situation. Practical implications – Efforts made by Chinese enterprises together with the Chinese government have established a good foundation for further development. After China's entry into the WTO, a win‐win relationship between foreign companies and Chinese manufacturers is still possible. Originality/value – This work is one of the few and pioneering efforts to investigate GSCM practices in China.

In this study, carbon dioxide is one of the end products of combustion, and is not a benign component of the atmosphere. The concentration of CO₂ in the atmosphere has reached unprecedented levels and continues to increase owing to an escalating rate of fossil fuel combustion, causing concern about climate change and rising sea levels. In view of the inevitable depletion of fossil fuels, a possible solution to this problem is the recycling of carbon dioxide, possibly captured at its point of generation, to fuels. Researchers in this field are using solar energy for CO₂ activation and utilization in several ways: (i) so-called artificial photosynthesis using photo-induced electrons; (ii) bulk electrolysis of a CO₂ saturated solution using electricity produced by photovoltaics; (iii) CO₂ hydrogenation using solar-produced H₂; and (iv) the thermochemical reaction of metal oxides at extremely high temperature reached by solar collectors. Since the thermodynamics of CO₂ at high temperature (> 1000 ºC) are quite different from those near room temperature, only chemistry below 200 ºC is discussed in this review.