Summarizing consumer reviews

Journal of Intelligent Information Systems - E-commerce giants like Amazon rely on consumer reviews to allow buyers to inform other potential buyers about a product’s pros and cons. While...     

Query-oriented topical influential users detection for top-k trending topics in twitter

Applied Intelligence - Online Social Networks (OSNs) have become inevitable for any new methodology both for viral promoting applications and instructing the creation of inciting information and...     

Phase Distribution and Magnetic Properties of Mechanically Alloyed Hard/Soft Ferrite Nanocomposites

Improvement in the magnetic properties of hard/ soft ferrite nanocomposites was studied by varying the composition of the soft phase in SrFe₁₂O₁₉/Ni_0.5Zn_0.5Fe₂O₄ nanocomposites. The SrFe₁₂O₁₉/Ni_0.5Zn_0.5Fe₂O₄ nanocomposites were prepared using the mechanical alloying method. The samples were prepared by varying the amount of the soft phase from 10 to 50 wt% while the amount of the hard phase remained 100 wt% in the ferrite nanocomposites. X-ray diffraction (XRD), a vibrating sample magnetometer (VSM), and a transmission electron microscope (TEM) were used to characterize the samples. From the result, it was found that the nanocomposite magnet with 10 wt% of soft phase content had the highest remanence ratio, M _r / M _s , which was 0.61, while the values of the coercivity, H _c , and magnetization, M _s , measured were 4482.4 G and 9.71 emu/g, respectively, and the average particle size of the ferrite nanocomposites was < 50 nm for all the samples. It was also shown that H _c decreased as the weight percent of the soft ferrite increased, which resulted from the dipolar interaction that occurred in the ferrite nanocomposites, showing the effect of phase distribution on the magnetic properties.     

Optimal locations of on-line and off-line rework stations in a serial production system

The production rate and product quality are two vital concerns for any manufacturing industry. Number of defective items reduces production rate and increases unit production cost. Moreover, if nonconforming items reach to the customers then manufacturer’s goodwill may drastically go down. Thus, quality inspection is treated as an inherent part of manufacturing. In this research, an N-stage serial production line with an inspection station at the end of it is considered to make decisions concerning this issue. On detecting a defective item at the end of the line it is scrapped or repaired at regular workstation or is sent to an off-line rework station for repair. Assuming each workstation produces a single type of defect a unit cost function is developed for alternative decisions on each type of defect. In order to minimise the unit cost of production and determine an appropriate decision for individual defect types, a fractional mixed integer nonlinear programming is formulated. After transformation to a mixed integer linear programming problem it is solved optimally. A small problem from garments industry is described in detail to show the solution procedure with a branch and bound method. Empirical tests with up to 40 workstations are permed to show the efficiency of the solution process.     

Immobilization of Photo‐Immunoconjugates on Nanoparticles Leads to Enhanced Light‐Activated Biological Effects

The past three decades have witnessed notable advances in establishing photosensitizer–antibody photo‐immunoconjugates for photo‐immunotherapy and imaging of tumors. Photo‐immunotherapy minimizes damage to surrounding healthy tissue when using a cancer‐selective photo‐immunoconjugate, but requires a threshold intracellular photosensitizer concentration to be effective. Delivery of immunoconjugates to the target cells is often hindered by I) the low photosensitizer‐to‐antibody ratio of photo‐immunoconjugates and II) the limited amount of target molecule presented on the cell surface. Here, a nanoengineering approach is introduced to overcome these obstacles and improve the effectiveness of photo‐immunotherapy and imaging. Click chemistry coupling of benzoporphyrin derivative (BPD)–Cetuximab photo‐immunoconjugates onto FKR560 dye‐containing poly(lactic‐co‐glycolic acid) nanoparticles markedly enhances intracellular photo‐immunoconjugate accumulation and potentiates light‐activated photo‐immunotoxicity in ovarian cancer and glioblastoma. It is further demonstrated that co‐delivery and light activation of BPD and FKR560 allow longitudinal fluorescence tracking of photoimmunoconjugate and nanoparticle in cells. Using xenograft mouse models of epithelial ovarian cancer, intravenous injection of photo‐immunoconjugated nanoparticles doubles intratumoral accumulation of photo‐immunoconjugates, resulting in an enhanced photoimmunotherapy‐mediated tumor volume reduction, compared to “standard” immunoconjugates. This generalizable “carrier effect” phenomenon is attributed to the successful incorporation of photo‐immunoconjugates onto a nanoplatform, which modulates immunoconjugate delivery and improves treatment outcomes.     

Topological alternate centrality measure capturing drug targets in the network of MAPK pathways

A new centrality of the nodes in the network is proposed called alternate centrality, which can isolate effective drug targets in the complex signalling network. Alternate centrality metric defined over the network substructure (four nodes – motifs). The nodes involving in alternative activation in the motifs gain in metric values. Targeting high alternative centrality nodes hypothesised to be destructive free to the network due to their alternative activation mechanism. Overlapping and crosstalk among the gene products in the conserved network of MAPK pathways selected for the study. In silico knock‐out of high alternate centrality nodes causing rewiring in the network is investigated using MCF‐7 breast cancer cell line‐based data. Degree of top alternate centrality nodes lies between the degree of bridging and pagerank nodes. Node deletion of high alternate centrality on the centralities such as eccentricity, closeness, betweenness, stress, centroid and radiality causes low perturbation. The authors identified the following alternate centrality nodes ERK1, ERK2, MEKK2, MKK5, MKK4, MLK3, MLK2, MLK1, MEKK4, MEKK1, TAK1, P38alpha, ZAK, DLK, LZK, MLTKa/b and P38beta as efficient drug targets for breast cancer. Alternate centrality identifies effective drug targets and is free from intertwined biological processes and lethality.Inspec keywords: biochemistry, molecular biophysics, cellular biophysics, cancer, drugs, genetics, biomedical materialsOther keywords: MAPK pathways, complex signalling network, pagerank nodes, node deletion, drug targets, MCF‐7 breast cancer cell line‐based data, cellular mechanisms, ERK1 nodes, ERK2 nodes, MEKK2 nodes, MKK5 nodes, MKK4 nodes, MLK3 nodes, MLK2 nodes, MLK1 nodes, MEKK4 nodes, MEKK1 nodes, TAK1 nodes, P38alpha nodes, ZAK nodes, DLK nodes, LZK nodes, MLTKa/b nodes, P38beta nodes     

Inorganic-Based Printed Thermoelectric Materials and Devices

One of the simplest ways to generate electric power from waste heat is thermoelectric (TE) energy conversion. So far, most of the research on thermoelectrics has focused on inorganic bulk TE materials and their device applications. However, high production costs per power output and limited shape conformity hinder applications of state-of-the-art thermoelectric devices (TEDs). In recent years, printed thermoelectrics has emerged as an exciting pathway for their potential in the production of low-cost shape-conformable TEDs. Although several inorganic bulk TE materials with high performance are successfully developed, achieving high performance in inorganic-based printed TE materials is still a challenge. Nevertheless, significant progress has been made in printed thermoelectrics in recent years. In this review article, it is started with an introduction signifying the importance of printed thermoelectrics followed by a discussion of theoretical concepts of thermoelectricity, from fundamental transport phenomena to device efficiency. Afterward, the general process of inorganic TE ink formulation is summarized, and the current development of the inorganic and hybrid inks with the mention of their TE properties and their influencing factors is elaborated. In the end, TEDs with different architecture and geometries are highlighted by documenting their performance and fabrication techniques.     

Central Aggregator Intrusion Detection System for Denial of Service Attacks

Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles (EVs) to be used by the smart grid through the central aggregator. Since the central aggregator is connected to the smart grid through a wireless network, it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection system. However, existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid network. In this paper, the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of the vehicle-to-grid network is investigated and an intrusion detection system for the vehicle-to-grid network is proposed. The proposed system, central aggregator–intrusion detection system (CA-IDS), works as a security gateway for EVs to analyze and monitor incoming traffic for possible DoS attacks. EVs are registered with a Central Aggregator (CAG) to exchange authenticated messages, and malicious EVs are added to a blacklist for violating a set of predefined policies to limit their interaction with the CAG. A denial of service (DoS) attack is simulated at CAG in a vehicle-to-grid (V2G) network manipulating various network parameters such as transmission overhead, receiving capacity of destination, average packet size, and channel availability. The proposed system is compared with existing intrusion detection systems using different parameters such as throughput, jitter, and accuracy. The analysis shows that the proposed system has a higher throughput, lower jitter, and higher accuracy as compared to the existing schemes.     

An Optimal Algorithm for Resource Allocation in D2D Communication

The number of mobile devices accessing wireless networks is skyrocketing due to the rapid advancement of sensors and wireless communication technology. In the upcoming years, it is anticipated that mobile data traffic would rise even more. The development of a new cellular network paradigm is being driven by the Internet of Things, smart homes, and more sophisticated applications with greater data rates and latency requirements. Resources are being used up quickly due to the steady growth of smartphone devices and multimedia apps. Computation offloading to either several distant clouds or close mobile devices has consistently improved the performance of mobile devices. The computation latency can also be decreased by offloading computing duties to edge servers with a specific level of computing power. Device-to-device (D2D) collaboration can assist in processing small-scale activities that are time-sensitive in order to further reduce task delays. The task offloading performance is drastically reduced due to the variation of different performance capabilities of edge nodes. Therefore, this paper addressed this problem and proposed a new method for D2D communication. In this method, the time delay is reduced by enabling the edge nodes to exchange data samples. Simulation results show that the proposed algorithm has better performance than traditional algorithm.     

Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples

One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness. The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary, for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis. Fourier Transform Infrared Spectroscopy (FTIR) is used in this work to identify lard adulteration in cow, lamb, and chicken samples. A simplified extraction method was implied to obtain the lipids from pure and adulterated meat. Adulterated samples were obtained by mixing lard with chicken, lamb, and beef with different concentrations (10%–50% v/v). Principal component analysis (PCA) and partial least square (PLS) were used to develop a calibration model at 800–3500 cm⁻¹. Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken, lamb, and beef samples. The corresponding FTIR peaks for the lard have been observed at 1159.6, 1743.4, 2853.1, and 2922.5 cm⁻¹, which differentiate chicken, lamb, and beef samples. The wavenumbers offer the highest determination coefficient R² value of 0.846 and lowest root mean square error of calibration (RMSEC) and root mean square error prediction (RMSEP) with an accuracy of 84.6%. Even the tiniest fat adulteration up to 10% can be reliably discovered using this methodology.