Tight-binding inhibitory sequences against pp60(c-src) identified using a random 15-amino-acid peptide library

A method is presented for matching wedge field dose distributions on different treatment units, simplifying the transfer of patients between machines during machine failure or scheduled downtime and avoiding the need for a full re-plan in most cases. Differences in wedge field characteristics between machines are accounted for and differences in energy are easily accommodated.     

Congestion‐Aware Handover in LTE Systems for Load Balancing in Transport Network

Long‐Term Evolution employs a hard handover procedure. To reduce the interruption of data flow, downlink data is forwarded from the serving eNodeB (eNB) to the target eNB during handover. In cellular networks, unbalanced loads may lead to congestion in both the radio network and the backhaul network, resulting in bad end‐to‐end performance as well as causing unfairness among the users sharing the bottleneck link. This work focuses on congestion in the transport network. Handovers toward less loaded cells can help redistribute the load of the bottleneck link; such a mechanism is known as load balancing. The results show that the introduction of such a handover mechanism into the simulation environment positively influences the system performance. This is because terminals spend more time in the cell; hence, a better reception is offered. The utilization of load balancing can be used to further improve the performance of cellular systems that are experiencing congestion on a bottleneck link due to an uneven load.     

A flexible UV nanosensor based on reduced graphene oxide decorated ZnO nanostructures

A low-cost, compatible with flexible electronics, high performance UV sensor has been achieved from a reduced graphene oxide (RGO) decorated hydrangea-like ZnO film on a PDMS substrate. The hydrangea-like ZnO UV sensor has the best UV sensing performance among devices made of three kinds of ZnO nanostructures synthesized by a hydrothermal method, and demonstrated a dramatic enhancement in on/off ratio and photoresponse current by introducing an appropriate weight ratio of RGO. The on/off ratio of the 0.05% RGO/ZnO sensor increases almost one order of magnitude compared to that of a pristine hydrangea-like ZnO UV sensor. While for the 5% RGO decorated ZnO sensor, the photoresponse current reaches as high as ～1 μA and exceeds 700 times that of a ZnO UV sensor. These results indicate that RGO is an appropriate material to enhance the performance of ZnO nanostructure UV sensors based on its unique features, especially the high optical transparency and excellent electronic conductivity. Our findings will make RGO/ZnO nanohybrids extraordinarily promising in optoelectronics, flexible electronics and sensor applications.     

Association of Methylentetraydrofolate Reductase (MTHFR) 677 C > T gene polymorphism and homocysteine levels in psoriasis vulgaris patients from Malaysia: a case-control study

Background  

The methylenetetrahydrofolate reductase (MTHFR) enzyme catalyzes the reduction of 5, 10-methylenetetrahydrofolate to 5-methyltetrahydrofolate and methyl donors. The methyl donors are required for the conversion of homocysteine to methionine. Mutation of MTHFR 677 C > T disrupts its thermostability therefore leads to defective enzyme activities and dysregulation of homocysteine levels.     

CNR: A Cluster-Based Solution for Connectivity Restoration for Mobile WSNs

Wireless Sensor Networks (WSNs) are an integral part of the Internet of Things (IoT) and are widely used in a plethora of applications. Typically, sensor networks operate in harsh environments where human intervention is often restricted, which makes battery replacement for sensor nodes impractical. Node failure due to battery drainage or harsh environmental conditions poses serious challenges to the connectivity of the network. Without a connectivity restoration mechanism, node failures ultimately lead to a network partition, which affects the basic function of the sensor network. Therefore, the research community actively concentrates on addressing and solving the challenges associated with connectivity restoration in sensor networks. Since energy is a scarce resource in sensor networks, it becomes the focus of research, and researchers strive to propose new solutions that are energy efficient. The common issue that is well studied and considered is how to increase the network’s life span by solving the node failure problem and achieving efficient energy utilization. This paper introduces a Cluster-based Node Recovery (CNR) connectivity restoration mechanism based on the concept of clustering. Clustering is a well-known mechanism in sensor networks, and it is known for its energy-efficient operation and scalability. The proposed technique utilizes a distributed cluster-based approach to identify the failed nodes, while Cluster Heads (CHs) play a significant role in the restoration of connectivity. Extensive simulations were conducted to evaluate the performance of the proposed technique and compare it with the existing techniques. The simulation results show that the proposed technique efficiently addresses node failure and restores connectivity by moving fewer nodes than other existing connectivity restoration mechanisms. The proposed mechanism also yields an improved field coverage as well as a lesser number of packets exchanged as compared to existing state-of-the-art mechanisms.     

Preparation of grass-like GaN nanostructures: Its PL and excellent field emission properties

We here report highly pure and single crystalline grass-like gallium nitride (GaN) nanostructures obtained on silicon substrate via catalyst-assisted CVD route under NH₃ atmosphere inside horizontal tube furnace (HTF) by pre-treating the precursors with aqueous NH₃. The as-obtained GaN nanostructures were characterized by XRD, SEM, EDS, HRTEM and SAED. The field emission (FE) characteristics of grass-like GaN nanostructures exhibited a turn-on field of 7.82 V μm^− 1 and a threshold field of 8.96 V μm^− 1 which are quite reasonable for applications in electron emission devices, field emission displays and vacuum microelectronic devices. Room temperature photoluminescence (PL) measurements of grass-like GaN nanostructures exhibited a strong near-band-edge emission at 368.8 nm (3.36 eV) without any defects related emissions which shows its potential applications in optoelectronics.     

Tungsten Oxide@Polypyrrole Core–Shell Nanowire Arrays as Novel Negative Electrodes for Asymmetric Supercapacitors

Among active pseudocapacitive materials, polypyrrole (PPy) is a promising electrode material in electrochemical capacitors. PPy‐based materials research has thus far focused on its electrochemical performance as a positive electrode rather than as a negative electrode for asymmetric supercapacitors (ASCs). Here high‐performance electrochemical supercapacitors are designed with tungsten oxide@PPy (WO₃@PPy) core–shell nanowire arrays and Co(OH)₂ nanowires grown on carbon fibers. The WO₃@PPy core–shell nanowire electrode exhibits a high capacitance (253 mF/cm²) in negative potentials (–1.0–0.0 V). The ASCs packaged with CF‐Co(OH)₂ as a positive electrode and CF‐WO₃@PPy as a negative electrode display a high volumetric capacitance up to 2.865 F/cm³ based on volume of the device, an energy density of 1.02 mWh/cm³, and very good stability performance. These findings promote the application of PPy‐based nanostructures as advanced negative electrodes for ASCs.     

Deep transfer learning based hepatitis B virus diagnosis using spectroscopic images

Accurate identification of Hepatitis B virus (HBV) disease by analyzing the Raman spectroscopic images is a challenge for pathologists. To save precious human lives, an efficient technique is required with higher diagnostic accuracy at early‐stage of HBV. We proposed a novel method of HBV diagnosis using deep neural networks with the concept of transfer learning and Raman spectroscopic images. The proposed approach developed by utilizing pretrained convolutional neural networks ResNet101 by employing transfer learning on a real dataset of HBV‐infected blood plasma samples. Dataset consists of 1000 Raman images in which 600 are HBV‐infected blood plasma samples, and 400 are healthy ones. The developed model is capable to detect minute variation between infected and healthy samples and achieved enhanced performance. The proposed approach has been assessed and attained high classification accuracy, sensitivity, specificity, and AUC of 99.7%, 100%, 99.25%, and 98.7%, respectively. The proposed TL‐ResNet101 model outperformed the conventional approaches such as PCA‐SVM and PCA‐LDA and demonstrated improved accuracy more than 7%. High performance indicates that the developed TL‐ResNet101 model has potential to use for HBV diagnosis. Moreover, the developed automated approach can be extended for other disease.     

Improved power-saving medium-access protocol for IEEE 802.11e QoS-enabled wireless networks

The performance of a new pointer-based medium-access control protocol that was designed to significantly improve the energy efficiency of user terminals in quality-of-service-enabled wireless local area networks was analysed. The new protocol, pointer- controlled slot allocation and resynchronisation protocol (PCSARe), is based on the hybrid coordination function-controlled channel access mode of the IEEE 802.11e standard. PCSARe reduces energy consumption by removing the need for power-saving stations to remain awake for channel listening. Discrete event network simulations were performed to compare the performance of PCSARe with the non-automatic power save delivery (APSD) and scheduled-APSD power- saving modes of IEEE 802.11e. The simulation results show a demonstrable improvement in energy efficiency without significant reduction in performance when using PCSARe. For a wireless network consisting of an access point and eight stations in power-saving mode, the energy saving was up to 39% when using PCSARe instead of IEEE 802.11e non-APSD. The results also show that PCSARe offers significantly reduced uplink access delay over IEEE 802.11e non-APSD, while modestly improving the uplink throughput. Furthermore, although both had the same energy consumption, PCSARe gave a 25% reduction in downlink access delay compared with IEEE 802.11e S-APSD.