Gold nanorods with a hematoporphyrin-loaded silica shell for dual-modality photodynamic and photothermal treatment of tumors in vivo

Nanocomposites （NCs） consisting of a gold nanorod core and a mesoporous silica shell doped with hematoporphyrin （HP） have been fabricated in order to improve the efficiency of cancer treatment by combining photothermal and photodynamic therapies （PDT ＋ PTT） in vivo. In addition to the long-wavelength plasmon resonance near 810-830 nm, the fabricated NCs exhibited a 400-nm absorbance peak corresponding to bound HP, generated singlet oxygen under 633-nm excitation near the 632.5-nm Q-band, and produced heat under a 808-nm near-infrared （NIR） laser irradiation. These modalities were used for a combined PDT ＋ PTT treatment of large （about 3 cm3） solid tumors in vivo with a xenorafted tumor rat model. NCs were directly injected into tumors and irradiated simultaneously with 633-nm and 808-nm lasers to stimulate the combined photodynamic and photothermal activities of NCs. The efficiency of the combined therapy was evaluated by optical coherence tomography, histological analysis, and by measurements of the tumor volume growth during a 21-day period. The NC-mediated PDT led to weak changes in tissue histology and to a moderate 20% decrease in the tumor volume. In contrast, the combined PDT ＋ PTT treatment resulted in the large-area tumor necrosis and led to dramatic decrease in the tumor volume.     

Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain

Recently, the applications of Blockchain technology have begun to revolutionise different aspects of supply chain (SC) management. Among others, Blockchain is a platform to execute the smart contracts in the SC as transactions. We develop and test a new model for smart contract design in the SC with multiple logistics service providers and show that this problem can be presented as a multi-processor flexible flow shop scheduling. A distinctive feature of our approach is that the execution of physical operations is modelled inside the start and completion of cyber information services. We name this modelling concept ‘virtual operation’. The constructed model and the developed experimental environment constitute an event-driven dynamic approach to task and service composition when designing the smart contract. Our approach is also of value when considering the contract execution stage. The use of state control variables in our model allows for operations status updates in the Blockchain that in turn, feeds automated information feedbacks, disruption detection and control of contract execution. The latter launches the re-scheduling procedure, comprehensively combining planning and adaptation decisions within a unified methodological framework of dynamic control theory. The modelling complex developed can be used to design and control smart contracts in the SC.     

Trifluoromethylation of [60]- and [70]Fullerene in the Ionization Chamber of a Mass Spectrometer

Abstract

Both [60]- and [70]fullerene react with either the Scherer radical (perfluorodiisopropylethylmethyl, C₉F₁₉), a mixture of branched perfluorononenes (C₉F₁₈, the product of hexafluoropropene trimerization), or β-fluorosulphatotetrafluoroethyldiheptafluoroisopropylmethyl radical (C₉F₁₈OSO₂F) in the ionization chamber of a mass spectrometer to give the positive parent ions of trifluoromethylation products, the reaction being accompanied by hydrogen addition. The reaction occurs at least partly on the walls of the ionization chamber, by a radical mechanism employing CF₃ radicals formed from the radical reactants both thermally and under electron impact; only the latter route occurs with the perfluorononenes.     

Focusing of Novosibirsk Free Electron Laser (NovoFEL) radiation into paraxial segment

Abstract

We demonstrate results of studies of a silicon binary diffractive optical element (DOE) focusing a terahertz laser Gaussian beam into a paraxial segment. The characteristics of the DOE were examined on a Novosibirsk Free Electron Laser beam of 141-μm wavelength.     

Development and optimization of a mid-infrared hollow waveguide gas sensor combined with a supported capillary membrane sampler

A gas sensor for application in water analysis was developed by combination of a mid-infrared (MIR) hollow waveguide with a Fourier transform infrared (FT-IR) spectrometer and coupling of the hollow waveguide gas sensor module to a supported capillary membrane sampler (SCMS) for continuous liquid-gas extraction. Different hollow waveguides have been characterized in this study for developing an optimized optical configuration. Analysis of industrially relevant compounds has been performed, investigating chlorinated hydrocarbons (CHCs), such as dichloromethane and chloroform, representing highly volatile analytes, and 1,4-dioxane as an example of target compounds with low volatility. The suitability of this spectroscopic IR sensing system for industrial applications is demonstrated under simulated real-world conditions with limits of detection in the ppb (v/v) and ppm (v/v) concentration range for CHCs and 1,4-dioxane, respectively.     

Application of mid-infrared spectroscopy: measuring hydrogen peroxide concentrations in bleaching baths

The presented work applies mid-infrared attenuated total reflection (ATR) spectroscopy to the measurment of hydrogen peroxide in aqueous matrices. The performance of different ATR crystals mounted in flow cells was investigated in the presence of aqueous hydrogen peroxide solutions. Quantitative determination has been achieved by evaluation of specific OH stretching and deformation vibrations with linear correlation between peak areas or peak heights and hydrogen peroxide concentration in the range of 1-10% (weight in water). Important aspects such as chemical stability of the waveguide material and influences of pH and ionic strength on the performance are discussed. Feasibility for the investigation of real world samples is demonstrated by measuring industrial bleaching solutions with known concentrations of hydrogen peroxide fitting well with calibration graphs established with neat hydrogen peroxide solutions. The presented sensor system is capable of determining hydrogen peroxide within complex matrices and clearly corroborates the potential of providing an in situ measurement concept for on-line hydrogen peroxide detection.     

Highly Exposed ?NH2 Edge on Fragmented g-C3N4 Framework with Integrated Molybdenum Atoms for Catalytic CO2 Cycloaddition: DFT and Techno-Economic Assessment

This study focuses on the applicability of single-atom Mo-doped graphitic carbon nitride (GCN) nanosheets which are specifically engineered with high surface area (exfoliated GCN),  NH₂ rich edges, and maximum utilization of isolated atomic Mo for propylene carbonate (PC) production through CO₂ cycloaddition of propylene oxide (PO). Various operational parameters are optimized, for example, temperature (130 °C), pressure (20 bar), catalyst (Mo₂GCN), and catalyst mass (0.1 g). Under optimal conditions, 2% Mo-doped GCN (Mo₂GCN) has the highest catalytic performance, especially the turnover frequency (TOF) obtained, 36.4 h⁻¹ is higher than most reported studies. DFT simulations prove the catalytic performance of Mo₂GCN significantly decreases the activation energy barrier for PO ring-opening from 50–60 to 4.903 kcal mol⁻¹. Coexistence of Lewis acid/base group improves the CO₂ cycloaddition performance by the formation of coordination bond between electron-deficient Mo atom with O atom of PO, while  NH₂ surface group disrupts the stability of CO₂ bond by donating electrons into its low-level empty orbital. Steady-state process simulation of the industrial-scale consumes 4.4 ton h⁻¹ of CO₂ with PC production of 10.2 ton h⁻¹. Techno-economic assessment profit from Mo₂GCN is estimated to be 60.39 million USD year⁻¹ at a catalyst loss rate of 0.01 wt% h⁻¹.     

Geiringer theorems: from population genetics to computational intelligence, memory evolutive systems and Hebbian learning

The classical Geiringer theorem addresses the limiting frequency of occurrence of various alleles after repeated application of crossover. It has been adopted to the setting of evolutionary algorithms and, a lot more recently, reinforcement learning and Monte-Carlo tree search methodology to cope with a rather challenging question of action evaluation at the chance nodes. The theorem motivates novel dynamic parallel algorithms that are explicitly described in the current paper for the first time. The algorithms involve independent agents traversing a dynamically constructed directed graph that possibly has loops and multiple edges. A rather elegant and profound category-theoretic model of cognition in biological neural networks developed by a well-known French mathematician, professor Andree Ehresmann jointly with a neurosurgeon, Jan Paul Vanbremeersch over the last thirty years provides a hint at the connection between such algorithms and Hebbian learning.     

Patterns of self-stabilization in database consistency maintenance

A substantial portion of the database programming efforts are invested in integrity constraints enforcement. Traditionally, both the constraint semantics and their enforcement were embedded inside application programs. In recent years several studies have dealt with specifying integrity constraints as separate entities (e.g. rules), and relating the database consistency requirements to these rules. In this paper we deal with the complementary issue of stabilizing the database when update exceptions occur. While a simplistic approach is to abort any transaction that inflicts consistency violations, this is not always the desired action. We take advantage of the empirical observation that most of the exception-handling policies follow a small number of behavior patterns. Unlike some previous approaches that base their repair solution on syntactic analysis of the constraints and performance issues, we base our approach on the application semantics as reflected in these behavioral patterns. We describe a model that uses high-level abstractions called stabilizer types denoting these behavior patterns for consistency restorations, whose exact semantics is case dependent. It follows the fault tolerance's self-stabilization approach. An inference mechanism translates these abstractions into executable active rules. This approach provides high-level language to the exception handling portion of the application and substantially reduces the required programming.     

Archetypes of open-source business models

Electronic Markets - The open-source paradigm offers a plethora of opportunities for innovative business models (BMs) as the underlying codebase of the technology is accessible and extendable by...