Dysprosium doped copper oxide (Cu1-xDyxO) nanoparticles enabled bifunctional electrode for overall water splitting

The production of hydrogen, a favourable alternative to an unsustainable fossil fuel remains as a significant hurdle with the pertaining challenge in the design of proficient, highly productive and sustainable electrocatalyst for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Herein, the dysprosium (Dy) doped copper oxide (Cu_1-xDy_xO) nanoparticles were synthesized via solution combustion technique and utilized as a non-noble metal based bi-functional electrocatalyst for overall water splitting. Due to the improved surface to volume ratio and conductivity, the optimized Cu_1-xDy_xO (x = 0.01, 0.02) electrocatalysts exhibited impressive HER and OER performance respectively in 1 M KOH delivering a current density of 10 mAcm^?2 at a potential of ?0.18 V vs RHE for HER and 1.53 V vs RHE for OER. Moreover, the Dy doped CuO electrocatalyst used as a bi-functional catalyst for overall water splitting achieved a potential of 1.56 V at a current density 10 mAcm^?2 and relatively high current density of 66 mAcm^?2 at a peak potential of 2 V. A long term stability of 24 h was achieved for a cell voltage of 2.2 V at a constant current density of 30 mAcm^?2 with only 10% of the initial current loss. This showcases the accumulative opportunity of dysprosium as a dopant in CuO nanoparticles for fabricating a highly effective and low-cost bi-functional electrocatalyst for overall water splitting.     

Object Detection in RGB-D Images via Anchor Box with Multi-Reduced Region Proposal Network and Multi-Pooling

Journal of Signal Processing Systems - With the latest development of automation technology, object detection technology has received more and more research attention. Automated object detection...     

Discovery of Affinity-Based Probes for Btk Occupancy Assays

Bruton's tyrosine kinase (Btk) is an attractive target for the treatment of a wide array of B-cell malignancies and autoimmune diseases. Small-molecule covalent irreversible Btk inhibitors targeting Cys481 have been developed for the treatment of such diseases. In clinical trials, probe molecules are required in occupancy studies to measure the level of engagement of the protein by these covalent irreversible inhibitors. The result of this pharmacodynamic (PD) activity provides guidance for appropriate dosage selection to optimize inhibition of the drug target and correlation of target inhibition with disease treatment efficacy. This information is crucial for successful evaluation of drug candidates in clinical trials. Based on the pyridine carboxamide scaffold of a novel solvent-accessible pocket (SAP) series of covalent irreversible Btk inhibitors, we successfully developed a potent and selective affinity-based biotinylated probe 12 (2-[(4-{4-[5-(1-{5-[(3aS,4S,6aR)-2-oxo-hexahydro-1H-thieno[3,4-d]imidazol-4-yl]pentanamido}-3,6,9,12-tetraoxapentadecan-15-amido)pentanoyl]piperazine-1-carbonyl}phenyl)amino]-6-[1-(prop-2-enoyl)piperidin-4-yl]pyridine-3-carboxamide). Compound 12 has been used in Btk occupancy assays for preclinical studies to determine the therapeutic efficacy of Btk inhibition in two mouse lupus models driven by TLR7 activation and type I interferon.     

Assessing stem cell research productivity

Honour Index (HoI), a method to evaluate research performance within different research fields, was derived from the impact factor (IF). It can be used to rate and compare different categories of journals. HoI was used in this study to determine the scientific productivity of stem cell research in the Asian Four Dragons (Hong Kong, Singapore, South Korea and Taiwan) from 1981 to 2001. The methodology applied in this study represents a synthesis of universal indicator studies and bibliometric analyses of subfields at the micro-level. We discuss several comparisons, and conclude the developmental trend in stem cell research for two decades. This revised version was published online in August 2006 with corrections to the Cover Date.     

Formation of a geometric pattern with a mobile wireless sensor network

Mobile wireless sensor networks (MWSNs) will enable information systems to gather detailed information about the environment on an unprecedented scale. These self‐organizing, distributed networks of sensors, processors, and actuators that are capable of movement have a broad range of potential applications, including military reconnaissance, surveillance, planetary exploration, and geophysical mapping. In many of the foreseen applications, the MWSN will need to form a geometric pattern without assistance from the user. In military reconnaissance, for example, the nodes will be dropped onto the battlefield from a plane and land at random positions. The nodes will be expected to arrange themselves into a predetermined formation in order to perform a specific task. Thus, we present algorithms for forming a line, circle, and regular polygon from a given set of random positions. The algorithms are distributed and use no communication between the nodes to minimize energy consumption. Unlike past studies of geometric problems where algorithms are either tested in simulations where each node has global knowledge of all the other nodes or implemented on a small number of robots, the robustness of our algorithms has been studied with simulations that model the sensor system in detail. The simulations demonstrate that the algorithms are robust against random errors in the sensors and actuators. © 2004 Wiley Periodicals, Inc.     

Phosphorus‐containing polyaryloxydiphenylsilanes with high flame retardance arising from a phosphorus–silicon synergistic effect

Polyaryloxydiphenylsilanes were prepared from phosphorus‐containing diols and diphenydichlorolsilane through solution polymerization. With a stoichiometric imbalance in feed monomers, the resulting polymers exhibited moderate melting points and good processing properties. The polymers prepared showed initial decomposition temperatures above 340 °C, excellent thermal stability, high char yields at 850 °C and very high limited oxygen index values of 56–59. The polymers' char yields and their (P + Si) contents showed linear relationships. © 2003 Society of Chemical Industry     

Hemodynamic response to in situ latissimus dorsi muscle stimulation: implications in dynamic cardiomyoplasty

Dynamic cardiomyoplasty (DCM) involves the electrical stimulation of a pedicled latissimus dorsi muscle flap wrapped around the falling ventricle as a means of cardiac assist. To further elucidate a potential neurohumoral mechanism for improvement of cardiac output after myoplasty, we evaluated the hemodynamic effects of in situ stimulation of the latissimus dorsi muscle (in the absence of cardiomyoplasty). In seven mongrel dogs, a nerve cuff electrode (Medtronic 6901) was placed around the left thoracodorsal nerve (TDN). This was attached to a pulse generator (Medtronic, Itrel 7420), delivering a 4.0 volt, 0.19 second on, 0.81 second off, 33 Hz, 210 microsecond pulse width, cyclic bursts similar to that used in DCM. Stroke volume index (SVI) and other hemodynamic parameters as well as plasma norepinephrine (NE) levels were measured at five stages: baseline, stimulator on at 0, 2, and 5 minutes, and stimulator off at 30 minutes after. The animals were then subjected to 4 weeks of rapid pacing at 240 beats/min (Medtronic 8329) to induce heart failure, and as the rapid pacing was discontinued, measurements were repeated as above. After rapid pacing, cardiac function was significantly depressed, and NE was elevated (133 +/- 69 versus 500 +/- 353 pg/mL, p < 0.05). In the normal hearts, TDN stimulation increased SVI, heart rate, systemic pressure, and NE levels. In heart failure, however, no significant changes in cardiac function and NE levels were noted. In conclusion, our data indicate that in the normal hearts, afferent impulses from TDN stimulation alone may augment cardiac function by means of a neurohumoral effect that is not seen in severe heart failure. The implications of these findings in DCM are discussed.     

Situating natural language understanding within experience-based design

Building useful systems with an ability to understand "real" natural language input has long been an elusive goal for Artificial Intelligence. Well-known problems such as ambiguity, indirectness, and incompleteness of natural language inputs have thwarted efforts to build natural language interfaces to intelligent systems. In this article, we report on our work on a model of understanding natural language design specifications of physical devices such as simple electrical circuits. Our system, called KA, solves the classical problems of ambiguity, incompleteness and indirectness by exploiting the knowledge and problem-solving processes in the situation of designing simple physical devices. In addition, KA acquires its knowledge structures (apart from a basic ontology of devices) from the results of its problem-solving processes. Thus, KA can be bootstrapped to understand design specifications and user feedback about new devices using the knowledge structures it acquired from similar devices designed previously.In this paper, we report on three investigations in the KA project. Our first investigation demonstrates that KA can resolve ambiguities in design specifications as well as infer unarticulated requirements using the ontology, the knowledge structures, and the problem-solving processes provided by its design situation. The second investigation shows that KA's problem-solving capabilities help ascertain the relevance of indirect design specifications, and identify unspecified relations between detailed requirements. The third investigation demonstrates the extensibility of KA's theory of natural language understanding by showing that KA can interpret user feedback as well as design requirements. Our results demonstrate that situating language understanding in problem solving, such as device design in KA, provides effective solutions to unresolved problems in natural language processing.