Tris(propionitrile-κN)[1,4,7-tris­(cyano­meth­yl)-1,4,7-triaza­cyclo­nonane-κ3 N 1,N 4,N 7]copper(II) bis­(perchlorate) dihydrate

In the title compound, [Cu(C3H5N)3(C12H18N6)](ClO4)2·2H2O, the CuII atom lies on a threefold rotation axis and is coordinated in a distorted N6 octa­hedral environment by three tertiary amines from the tridentate chelating aza­macrocyclic ligand and three propionitrile mol­ecules. Inter­molecular non-classical C—H⋯N hydrogen bonding inter­links the [Cu(C3H5N)3(C12H18N6)]2+ cations into a two-dimensional supra­molecular sheet extending along the ab plane. The crystal packing also exhibits weak C—H⋯O inter­actions

Domestic Activities Classification from Audio Recordings Using Multi-scale Dilated Depthwise Separable Convolutional Network

Domestic activities classification (DAC) from audio recordings aims at classifying audio recordings into pre-defined categories of domestic activities, which is an effective way for estimation of daily activities performed in home environment. In this paper, we propose a method for DAC from audio recordings using a multi-scale dilated depthwise separable convolutional network (DSCN). The DSCN is a lightweight neural network with small size of parameters and thus suitable to be deployed in portable terminals with limited computing resources. To expand the receptive field with the same size of DSCN's parameters, dilated convolution, instead of normal convolution, is used in the DSCN for further improving the DSCN's performance. In addition, the embeddings of various scales learned by the dilated DSCN are concatenated as a multi-scale embedding for representing property differences among various classes of domestic activities. Evaluated on a public dataset of the Task 5 of the 2018 challenge on Detection and Classification of Acoustic Scenes and Events (DCASE-2018), the results show that: both dilated convolution and multi-scale embedding contribute to the performance improvement of the proposed method; and the proposed method outperforms the methods based on state-of-the-art lightweight network in terms of classification accuracy.Comment: 5 pages, 2 figures, 4 tables. Accepted for publication in IEEE MMSP202

Priprema, identifikacija i antioksidacijska svojstva kelatnog kompleksa željeza i oligopeptida izoliranog iz mesa japanske svilaste crne kokoši (Gallus galllus domesticus Brisson)

Black-bone silky fowl iron(II)-oligopeptide chelate was synthesized from iron(II) solution and the black-bone silky fowl oligopeptide, which was extracted from the muscle protein of black-bone silky fowl (Gallus gallus domesticus Brisson). Orthogonal array analysis was used to determine the optimal conditions for the iron(II)-oligopeptide chelate preparation. Ultraviolet-visible (UV-Vis) spectroscopy, electron microscopy, and Fourier transform infrared (FTIR) spectroscopy were used to identify the structure of iron(II)-oligopeptide chelate. 2-Diphenyl-1-picrylhydrazyl (DPPH) and superoxide radical scavenging assays were performed to compare the antioxidant abilities of the black-bone silky fowl oligopeptide and iron(II)-oligopeptide chelate. The optimal conditions for iron(II) oligopeptide chelate preparation were 4 % of the black-bone silky fowl oligopeptide and a ratio of the black-bone silky fowl oligopeptide to FeCl2·4H2O of 5:1 at pH=4. Under these conditions, the chelation rate was (84.9±0.2) % (p<0.05), and the chelation yield was (40.3±0.1) % (p<0.05). The structures detected with UV-Vis spectroscopy, electron microscopy and FTIR spectra changed significantly after chelation, suggesting that Fe(II) ions formed coordinate bonds with carboxylate (-RCOO¯) and amino (-NH2) groups in the oligopeptides, confirming that this is a new oligopeptide-iron chelate. The iron(II)-oligopeptide chelate had stronger scavenging activity towards DPPH and superoxide radicals than did the black-bone silky fowl oligopeptide.Kelatni kompleks željeza i oligopeptida sintetiziran je dodatkom praha proteina izoliranog iz mesa japanske svilaste crne kokoši (Gallus galllus domesticus Brisson) otopini iona Fe2+. Optimalni uvjeti keliranja određeni su pomoću ortogonalnog plana. Struktura kelata ispitana je pomoću UV-Vis spektroskopije, elektronskog mikroskopa i FTIR spektroskopije. Uspoređena je antioksidacijska aktivnost oligopeptida i kelata, i to ispitivanjem sposobnosti uklanjanja DPPH i superoksidnih radikala. Optimalni uvjeti keliranja bili su: omjer mase oligopeptida i volumena otopine od 4 %, maseni omjer oligopeptida i otopine željezovog(II) klorida od 5:1 i pH-vrijednost od 4. Pri tim je uvjetima uspješnost keliranja bila (84,9±0,2) % (p˂0,05), a prinos kelata (40,3±0,1) % (p˂0,05). Isptivanjem spojeva pomoću UV-Vis spektroskopije, elektronskog mikroskopa i FTIR spektroskopije utvrđeno je da se struktura kelata bitno promijenila, te da je nastao novi spoj, najvjerojatnije vezivanjem iona Fe2+ s karboksilnom i amino skupinom oligopeptida. Kelatni kompleks imao je izraženiju sposobnost uklanjanja DPPH i superoksidnih radikala od oligopeptida

1-[2-(1H-Benzimidazol-2-yl)eth­yl]-1H-1,2,3-benzotriazole

In the title compound, C15H13N5, the N-containing heterocycles are linked by an ethyl­ene spacer in a gauche conformation, the N—C—C—C torsion angle along the linker being 60.1 (3)°. The dihedral angle between the terminal benzotriazole and benzimidazole rings is 39.02 (6)°. In the crystal, adjacent mol­ecules are connected by N—H⋯N hydrogen bonds, forming an infinite chain along the c axis. π–π stacking inter­actions [centroid–centroid distance = 3.8772 (7) Å] between the benzotriazole rings of neighbouring chains extend these chains into a supra­molecular sheet in the bc plane. Weak inter­molecular C—H⋯N inter­actions further stabilize the crystal structure

Preparation, Identification and Antioxidant Properties of Black-Bone Silky Fowl (Gallus gallus domesticus Brisson) Iron(II)-Oligopeptide Chelate

Black-bone silky fowl iron(II)-oligopeptide chelate was synthesized from iron(II) solution and the black-bone silky fowl oligopeptide, which was extracted from the muscle protein of black-bone silky fowl (Gallus gallus domesticus Brisson). Orthogonal array analysis was used to determine the optimal conditions for the iron(II)-oligopeptide chelate preparation. Ultraviolet-visible (UV-Vis) spectroscopy, electron microscopy, and Fourier transform infrared (FTIR) spectroscopy were used to identify the structure of iron(II)-oligopeptide chelate. 2-Diphenyl-1-picrylhydrazyl (DPPH) and superoxide radical scavenging assays were performed to compare the antioxidant abilities of the black-bone silky fowl oligopeptide and iron(II)-oligopeptide chelate. The optimal conditions for iron(II) oligopeptide chelate preparation were 4 % of the black-bone silky fowl oligopeptide and a ratio of the black-bone silky fowl oligopeptide to FeCl2·4H2O of 5:1 at pH=4. Under these conditions, the chelation rate was (84.9±0.2) % (p<0.05), and the chelation yield was (40.3±0.1) % (p<0.05). The structures detected with UV-Vis spectroscopy, electron microscopy and FTIR spectra changed significantly after chelation, suggesting that Fe(II) ions formed coordinate bonds with carboxylate (-RCOO¯) and amino (-NH2) groups in the oligopeptides, confirming that this is a new oligopeptide-iron chelate. The iron(II)-oligopeptide chelate had stronger scavenging activity towards DPPH and superoxide radicals than did the black-bone silky fowl oligopeptide

Target Selection in Head-Mounted Display Virtual Reality Environments

Target selection is one of the most common and important tasks in interactive systems. Within virtual reality environments, target selection can pose extra challenges to users because targets can be located far away, clustered together, and occluded from view. Although selection techniques have been explored, it is often unclear which techniques perform better across different environmental target density levels and which have higher levels of usability especially for recently released commercial head-mounted display (HMD) virtual reality systems and input devices. In this paper, we first review previous studies on target selection in HMD VR environments. We then compare the performances of three main techniques or metaphors (RayCasting, Virtual Hand, and Hand-Extension) using recently marketed VR headsets and input devices under different density conditions and selection areas. After, we select the best two techniques (RayCasting and Virtual Hand) for the second experiment to explore their relative performance and usability by adding different feedback to these two techniques. In the third experiment, we implemented three techniques with pointing facilitators and compared them against the best techniques from the second experiment, RayCasting with visual feedback, to assess their performance, error rates, learning effects, and usability. The three studies altogether suggest the best target selection features, based on techniques, feedback, and pointing facilitators for target density conditions in HMD VR environments