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.     

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.     

Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

Hydrogen annealing effect on DC and low-frequency noise characteristics in CMOS FinFETs

The hydrogen annealing process has been used to improve surface roughness of the Si-fin in CMOS FinFETs for the first time. Hydrogen annealing was performed after Si-fin etch and before gate oxidation. As a result, increased saturation current with a lowered threshold voltage and a decreased low-frequency noise level over the entire range of drain current have been attained. The low-frequency noise characteristics indicate that the oxide trap density is reduced by a factor of 3 due to annealing. These results suggest that hydrogen annealing is very effective for improving device performance and for attaining a high-quality surface of the etched Si-fin.     

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.     

The organization and animal-vegetal asymmetry of cytokeratin filaments in stage VI Xenopus oocytes is dependent upon F-actin and microtubules

Confocal immunofluorescence microscopy with anti-cytokeratin antibodies revealed a continuous and polarized network of cytokeratin (CK) filaments in the cortex of stage VI Xenopus oocytes. In the animal cortex, CK filaments formed a dense meshwork that both was thicker and exhibited a finer mesh than the network of CK filaments previously observed in the vegetal cortex (Klymkowsky et al., 1987). CK filaments first appeared in association with germinal vesicle (GV) and mitochondrial mass (MM) of oocytes in early mid stage I, indicating that CK filaments are the last of the three cytoskeletal networks to be assembled. By late stage I, CK filaments formed complex networks surrounding the GV, surrounding and penetrating the MM, and linking these networks to a meshwork of CK filaments in the oocyte cortex. During stage III-early IV, CK filaments formed a highly interconnected, apparently unpolarized, radial array linking the perinuclear and cortical CK filament networks. Polarization of the CK filament network was observed during mid stage IV-stage V, as first the animal, then the vegetal CK filament networks adopted the organization characteristic of stage VI oocytes. Treatment of stage VI oocytes with cytochalasin B disrupted the organization of both cortical and cytoplasmic CK filaments, releasing CK filaments from the oocyte cortex and inducing formation of numerous cytoplasmic CK filament aggregates. CB also disrupted the organization of cytoplasmic microtubules (MTs) in stage VI oocytes. Disassembly of oocyte MTs with nocodazole resulted in loss of the characteristic A-V polarity of the cortical CK filament network. In contrast, disruption of cytoplasmic CK filaments by microinjection of anti-CK antibodies had no apparent effect on cytoplasmic or MT organization. We propose a model in which the organization and polarization of the cortical network of CK filaments in stage VI Xenopus oocytes are dependent upon a hierarchy of interactions with actin filaments and microtubules.     

Comparison of single-fiber and macro electrode recordings: relationship to motor unit action potential duration

The factors contributing to the duration of a motor unit action potential (MUAP) are believed to be well known, with both manual measurements and computer simulations agreeing with respect to MUAP durations approaching 10 ms. In this investigation, it is clearly demonstrated that use of a wide-open amplifier bandpass combined with signal-to-noise ratio enhancement results in MUAP durations approaching 30 ms recorded with either a macro or single-fiber electrode. Why the clinically recorded MUAP duration differs significantly from these physiologic durations is discussed. A hypothesis is presented whereby the major contributing factor toward MUAP duration is the total time of action potential transmembrane current flow along the muscle fiber from end-plate zone to musculotendinous junction.     

The postmodernity of football hooliganism

By using a 'cultural' definition of 'postmodernism' (derived from Jameson and Martin) in which postmodernism is regarded as the transgression of modern boundaries, this article traces the emergence of postmodern aspects to violent male fandom at football games since the 1960s. It is argued that at games, male fans have created imaginary masculine and national boundaries by which they have affirmed their identities but that in fighting they have sought to breach these boundaries in postmodern fashion.     

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.