Ir(III) and Ru(II) Complexes in Photoredox Catalysis and Photodynamic Therapy: A New Paradigm towards Anticancer Applications

Individually, photoredox catalysis (PC) and photodynamic therapy (PDT) are well-established concepts that have experienced a remarkable resurgence in recent years, leading to significant progress in organic synthesis for PC and clinical approval of anticancer drugs for PDT. But, very recently, new photoredox catalyst systems based on Ir(III) and Ru(II) complexes have garnered significant interest because they can simultaneously be used as PDT agents apart from their demonstrated PC activity. This highlight discusses the unique PC behavior of emerging Ir(III)- and Ru(II)-based systems while also examining their potential PDT activity in cancer treatment.     

Hybrid wideband transceiver design for achievable rate maximization in millimeter-wave MIMO systems

Telecommunication Systems - This paper proposes two algorithms for hybrid (Analog–Digital) beamforming in a single-user millimeter-wave (mm-wave) multi-input multi-output (MIMO) systems under...     

Al2O3/Yttria‐Stabilized Zirconia Hollow‐Fiber Membrane Incorporated with Iron Oxide for Pb(II) Removal

Removal by absorptive ceramic membranes can simultaneously absorb and separate metal ions from water. Alumina/yttria‐stabilized zirconia (Al₂O₃/YSZ) hollow‐fiber membranes, fabricated using phase inversion and sintering process, were deposited with iron oxide by an in‐situ hydrothermal process. The results showed that α‐Fe₂O₃ was produced and incorporated across the membranes. A reduction in flux was recorded with the deposition of α‐Fe₂O_3. However, it improved the adsorption capacity for heavy metal adsorption. The adsorption‐separation test demonstrated that the optimized membrane is able to completely remove Pb(II) ions after two hours.     

On the synergy between electrical and photonic switching

This article focuses on the values of electrical switching vs. photonic switching in the context of telecom transport networks. In particular, we show that the requirement of providing agility at the optical layer in the face of traffic forecast uncertainties is served better through photonic switching. On the other hand, some of the network-level functions, such as fast protection, subwavelength aggregation, and flexible client connectivity, require electrical switching. We further argue that additional values are achieved with hybrid photonic and electrical switching, which do not exist when either of these options is used in isolation.     

Design of sample adaptive product quantizers for noisy channels

Channel-optimized vector quantization (COVQ) has proven to be an effective joint source-channel coding technique that makes the underlying quantizer robust to channel noise. Unfortunately, COVQ retains the high encoding complexity of the standard vector quantizer (VQ) for medium-to-high quantization dimensions and moderate-to-good channel conditions. A technique called sample adaptive product quantization (SAPQ) was recently introduced by Kim and Shroff to reduce the complexity of the VQ while achieving comparable distortions. In this letter, we generalize the design of SAPQ for the case of memoryless noisy channels by optimizing the quantizer with respect to both source and channel statistics. Numerical results demonstrate that the channel-optimized SAPQ (COSAPQ) achieves comparable performance to the COVQ (within 0.2 dB), while maintaining considerably lower encoding complexity (up to half of that of COVQ) and storage requirements. Robustness of the COSAPQ system against channel mismatch is also examined.     

Palogue油田复合油藏动态响应及特征描述

以简单的复合油藏模型理论和方法为基础,以Palogue油田的实际测试井为例,介绍了复合油藏模型的试井动态识别与模型拟合,及与地质静态资料相结合的油藏综合描述过程.该描述方法将会对实际试井解释和油藏综合描述工作有所借鉴和帮助.     

Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants

Neural Computing and Applications - Preserving red-chili quality is of utmost importance in which the authorities demand quality techniques to detect, classify, and prevent it from impurities. For...     

Lung nodules detection using semantic segmentation and classification with optimal features

Neural Computing and Applications - Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of...     

Autonomous mapping of HL7 RIM and relational database schema

Healthcare systems need to share information within and across the boundaries in order to provide better care to the patients. For this purpose, they take advantage of the full potential of current state of the art in healthcare standards providing interoperable solutions. HL7 V3 specification is an international message exchange and interoperability standard. HL7 V3 messages exchanged between healthcare applications are ultimately recorded into local healthcare databases, mostly in relational databases. In order to bring these relational databases in compliance with HL7, mappings between HL7 RIM (Reference Information Model) and relational database schema are required. Currently, RIM and database mapping is largely performed manually, therefore it is tedious, time consuming, error prone and expensive process. It is a challenging task to determine all correspondences between RIM and schema automatically because of extreme heterogeneity issues in healthcare databases. To reduce the amount of manual efforts as much as possible, autonomous mapping approaches are required. This paper proposes a technique that addresses the aforementioned mapping issue and aligns healthcare databases to HL7 V3 RIM specifications. Furthermore, the proposed technique has been implemented as a working application and tested on real world healthcare systems. The application loads the target healthcare schema and then identifies the most appropriate match for tables and the associated fields in the schema by using domain knowledge and the matching rules defined in the Mapping Knowledge Repository. These rules are designed to handle the complexity of semantics found in healthcare databases. The GUI allows users to view and edit/re-map the correspondences. Once all the mappings are defined, the application generates Mapping Specification, which contains all the mapping information i.e. database tables and fields with associated RIM classes and attributes. In order to enable the transactions, the application is facilitated with the autonomous code generation from the Mapping Specification. The Code Generator component focuses primarily on generating custom classes and hibernate mapping files against the runtime system to retrieve and parse the data from the data source—thus allows bi-directional HL7 to database communication, with minimum programming required. Our experimental results show 35–65% accuracy on real laboratory systems, thus demonstrating the promise of the approach. The proposed scheme is an effective step in bringing the clinical databases in compliance with RIM, providing ease and flexibility.