Bee Bread Ameliorates Vascular Inflammation and Impaired Vasorelaxation in Obesity-Induced Vascular Damage Rat Model: The Role of eNOS/NO/cGMP-Signaling Pathway

Obesity and hyperlipidemia are major risk factors for developing vascular diseases. Bee bread (BB) has been reported to exhibit some biological actions, including anti-obesity and anti-hyperlipidemic. This study aims to investigate whether bee bread can ameliorate vascular inflammation and impaired vasorelaxation activity through eNOS/NO/cGMP pathway in obese rats. Forty male Sprague-Dawley rats were randomly divided into four groups (n = 10/group), namely: control (normal group), obese rats (OB group), obese rats treated with bee bread (0.5 g/kg/day, OB/BB group) and obese rats treated with orlistat (10 mg/kg/day, OB/OR group). The latter three groups were given a high-fat diet (HFD) for 6 weeks to induced obesity before being administered with their respective treatments for another 6 weeks. After 12 weeks of the total experimental period, rats in the OB group demonstrated significantly higher Lee obesity index, lipid profile (total cholesterol, triglyceride, low-density lipoprotein), aortic proinflammatory markers (tumor necrosis factor-α, nuclear factor-κβ), aortic structural damage and impairment in vasorelaxation response to acetylcholine (ACh). Bee bread significantly ameliorated the obesity-induced vascular damage manifested by improvements in the lipid profile, aortic inflammatory markers, and the impaired vasorelaxation activity by significantly enhancing nitric oxide release, promoting endothelial nitric oxide synthase (eNOS) and cyclic guanosine monophosphate (cGMP) immunoexpression. These findings suggest that the administration of bee bread ameliorates the impaired vasorelaxation response to ACh by improving eNOS/NO/cGMP-signaling pathway in obese rats, suggesting its vascular therapeutic role.     

FlowMate: scalable on-line flow clustering

We design and implement an efficient on-line approach, FlowMate, for clustering flows (connections) emanating from a busy server, according to shared bottlenecks. Clusters can be periodically input to load balancing, congestion coordination, aggregation, admission control, or pricing modules. FlowMate uses in-band (passive) end-to-end delay measurements to infer shared bottlenecks. Delay information is piggybacked on feedback from the receivers, or, if impossible, TCP or application round-trip time estimates are used. We simulate FlowMate and examine the effects of network load, traffic burstiness, network buffer sizes, and packet drop policies on clustering correctness, evaluated via a novel accuracy metric. We find that coordinated congestion management techniques are more fair when integrated with FlowMate. We also implement FlowMate in the Linux kernel v2.4.17 and evaluate its performance on the Emulab testbed, using both synthetic and tcplib-generated traffic. Our results demonstrate that clustering of medium to long-lived flows is accurate, even with bursty background traffic. Finally, we validate our results on the Internet Planetlab testbed.     

Ontology-based similarity for product information retrieval

Product development of today is becoming increasingly knowledge intensive. Specifically, design teams face considerable challenges in making effective use of increasing amounts of information. In order to support product information retrieval and reuse, one approach is to use case-based reasoning (CBR) in which problems are solved “by using or adapting solutions to old problems.” In CBR, a case includes both a representation of the problem and a solution to that problem. Case-based reasoning uses similarity measures to identify cases which are more relevant to the problem to be solved. However, most non-numeric similarity measures are based on syntactic grounds, which often fail to produce good matches when confronted with the meaning associated to the words they compare. To overcome this limitation, ontologies can be used to produce similarity measures that are based on semantics. This paper presents an ontology-based approach that can determine the similarity between two classes using feature-based similarity measures that replace features with attributes. The proposed approach is evaluated against other existing similarities. Finally, the effectiveness of the proposed approach is illustrated with a case study on product–service–system design problems.     

Fuzzy-based hunger games search algorithm for global optimization and feature selection using medical data

Neural Computing and Applications - Feature selection (FS) is one of the basic data preprocessing steps in data mining and machine learning. It is used to reduce feature size and increase model...     

Load balancing of IoT tasks in the cloud computing by using sparrow search algorithm

IoT is one of the most important technologies that are used over the past few years, where everything is connected to the Internet; it is used in many fields; one of these fields is healthcare system that includes mobile health and remote patient monitoring (patients with kidney, heart disease, cancer, blood pressure, diabetes, respiratory disease and stroke). Integration of IoT and cloud computing can improve the performance of healthcare system and the development of the innovative applications in future. One of the major problems that cannot be ignored in cloud computing system is load balancing. Solving that problem leads to reduce the response time, power consumption, cost and increase server availability. This paper is comprised of two parts which are creating and implementing healthcare system by using IoT, and solving the problem of load balancing of the cloud computing by using intelligent algorithm called sparrow search algorithm (SSA). The SSA is used to select the best virtual machine (VM) among a group of VMs depending on the its fitness value; also many and varied tasks are scheduled with priority and assign to the best VMs depending on the its instruction millions (IM), where the task that has high IM is assigned to the best VM that has high fitness value. The outcomes demonstrated that the proposed method focuses to reduce the latency and packet loss while maximizing the throughput in healthcare systems; also the SSA has proved its robustness, efficiency and success when compared to other methods in terms of reducing makespan time, total processing time and provides load balancing among VMs, where the value of makespan time, processing time and degree of imbalance has decreased into (23.05), (899.8979) and (177.7675), respectively, in case of applying 500 tasks.

     

Structural evolution and dopant occupancy preference of yttrium-doped potassium sodium niobate thin films

Sodium potassium niobate (KNN) is the most promising candidate for lead-free piezoelectric material, owing to its high Curie temperature and piezoelectric coefficients among the non-lead piezoelectric. Numerous studies have been carried out to enhance piezoelectric properties of KNN through composition design. This research studied the effects of yttrium concentrations and lattice site occupancy preference in KNN films. For this research, the yttrium-doped KNN thin films (mol% = 0, 0.1, 0.3, 0.5, 0.7 and 0.9) were fabricated using the sol-gel spin coating technique and had revealed the orthorhombic perovskite structures. Based on the replacement of Y³⁺ ions for K⁺/ Na⁺ ions, it was found that the films doped with 0.1 to 0.5 mol% of yttrium had less lattice strain, while films with more than 0.5 mol% of Y³⁺ ions had increased strain due to the tendency of Y³⁺ to occupy the B-site in the perovskite lattice. Furthermore, by analysing the vibrational attributes of octahedron bonding, the dopant occupancy at A-site and B-site lattices could be identified. O-Nb-O bonding was asymmetric and became distorted due to the B-site occupancy of yttrium dopants at high dopant concentrations of >0.5 mol%. Extra conduction electrons had resulted in better resistivity of 2.153× 10⁶ Ω at 0.5 mol%, while higher resistivity was recorded for films prepared with higher concentration of more than 0.5 mol%. The introduction of Y³⁺ improved the grain distribution of KNN structure. Further investigations indicated that yttrium enhances the surface smoothness of the films. However, at high concentrations (0.9 mol%), the yttrium increases the roughness of the surface. Within the studied range of Y³⁺ _, the film with 0.5 mol% Y³⁺ represented a relatively desirable improvement in dielectric loss, tan δ and quality factor, Q_m.     

Rational design on photoelectrodes and devices to boost photoelectrochemical performance of solar-driven water splitting: a mini review

As an eco-friendly, efficient, and low-cost technique, photoelectrochemical water splitting has attracted growing interest in the production of clean and sustainable hydrogen by the conversion of abundant solar energy. In the photoelectrochemical system, the photoelectrode plays a vital role in absorbing the energy of sunlight to trigger the water splitting process and the overall efficiency depends largely on the integration and design of photoelectrochemical devices. In recent years, the optimization of photoelectrodes and photoelectrochemical devices to achieve highly efficient hydrogen production has been extensively investigated. In this paper, a concise review of recent advances in the modification of nanostructured photoelectrodes and the design of photoelectrochemical devices is presented. Meanwhile, the general principles of structural and morphological factors in altering the photoelectrochemical performance of photoelectrodes are discussed. Furthermore, the performance indicators and first principles to describe the behaviors of charge carriers are analyzed, which will be of profound guiding significance to increasing the overall efficiency of the photoelectrochemical water splitting system. Finally, current challenges and prospects for an in-depth understanding of reaction mechanisms using advanced characterization technologies and potential strategies for developing novel photoelectrodes and advanced photoelectrochemical water splitting devices are demonstrated.     

Synthesis of thermoresponsive block and graft copolymers via the combination of living cationic polymerization and RAFT polymerization using a vinyl ether-type RAFT agent

A novel vinyl ether-type RAFT agent, benzyl 2-(vinyloxy)ethyl carbonotrithioate (BVCT) was synthesized for various block copolymers via the combination of living cationic polymerization of vinyl ethers and reversible addition−fragmentation chain transfer (RAFT) polymerization. The novel BVCT–trifluoroacetic acid adduct play an important role to produce well-defined block copolymers, which is both as a cationogen under EtAlCl₂ initiation system in the presence of ethyl acetate for living cationic polymerization and a RAFT agent for blocks by RAFT polymerization. The resulting polymer, poly(vinyl ether)s, by living cationic polymerization had a high number average α-end functionality (≥0.9) as determined by both ¹H NMR and MALDI-TOF-MS spectrometry. In addition, this poly(vinyl ether)s worked well as a macromolecular chain transfer agent for RAFT polymerization. The RAFT polymerization of radically polymerizable monomers was conducted in toluene using 2,2′-azobis(isobutyronitrile) at 70 °C. For example, a double thermoresponsive block copolymer (MOVE₆₁-b-NIPAM₁₅₀) consisting of 2-methoxyethyl vinyl ether (MOVE) and N-isopropylacrylamide (NIPAM) was prepared via the combination of living cationic polymerization and RAFT polymerization. The block copolymer reversibly formed and deformed micellar assemblies above the phase separation temperature (T_ps) of poly(NIPAM) block in water. This BVCT is not only functioned as an initiator, but also acted as a monomer. When BVCT was copolymerized with MOVE by living cationic polymerization, followed by graft copolymerization with NIPAM via RAFT polymerization, well-defined graft copolymers (MOVE_n-co-BVCT_m)-g-NIPAM_x (n = 62–73, m = 1–9, x = 19–214) were successfully obtained. However, no micelle formed in water above T_ps of poly(NIPAM) graft chain unlike the case of block copolymers.     

Application of transmission FT-IR spectroscopy for the trans fat determination in the industrially processed edible oils

The amount of trans fatty acids (TFA) in fourteen industrially hydrogenated and deodorized oils was determined. To achieve better sensitivity 200 μm KCl cell was used in transmission Fourier transform infrared (FT-IR) spectroscopy. The results of transmission FT-IR spectroscopy were evaluated by gas chromatography (GC) with flame ionization detector (FID), and found to be comparable. All analyzed cooking oil samples had a lower trans content of 0.4–1.8%. Trans fatty acid contents of partially hydrogenated oil samples were relatively higher as comparable to those of the cooking oils. Among the samples examined, the highest level was found to be at 26.5% and 25.7% by the GC–FID and FT-IR spectroscopy, respectively. Due to harmful effects, high amounts of trans fatty acids in partially hydrogenated oils is an alarming issue for the consumer’s health and quality control authorities.     

Bipolar resistive switching in p-type Co3O4 nanosheets prepared by electrochemical deposition

Metal oxide nanosheets have potential applications in novel nanoelectronics as nanocrystal building blocks. In this work, the devices with a structure of Au/p-type Co₃O₄ nanosheets/indium tin oxide/glass having bipolar resistive switching characteristics were successfully fabricated. The experimental results demonstrate that the device have stable high/low resistance ratio that is greater than 25, endurance performance more than 200 cycles, and data retention more than 10,000 s. Such a superior performance of the as-fabricated device could be explained by the bulk film and Co₃O₄/indium tin oxide glass substrate interface effect.