All Ag Nanoparticles Are Not the Same: Covalent Interactions between Ag Nanoparticles and Nitrile Groups Help Combat Drug- and Ag-Resistant Bacteria

Antimicrobial resistance has long been viewed as a lethal threat to global health. Despite the availability of a wide range of antibacterial medicines all around the world, organisms have evolved a resistance mechanism to these therapies. As a result, a scenario has emerged requiring the development of effective antibacterial drugs/agents. In this article, we exclusively highlight a significant finding reported by Zbořil and associates (Adv. Sci. 2021, 2003090). The authors construct a covalently bounded silver-cyanographene (GCN/Ag) with the antibacterial activity of 30 fold higher than that of free Ag ions or typical Ag nanoparticles (AgNPs). Ascribed to the strong covalent bond between nitrile and Ag, an immense cytocompatibility is shown by the GCN/Ag towards healthy human cells with a minute leaching of Ag ions. Firm interactions between the microbial membrane and the GCN/Ag are confirmed by molecular dynamics simulations, which rule out the dependence of antibacterial activity upon the Ag ions alone. Thus, this study furnishes ample scope to unfold next-generation hybrid antimicrobial drugs to confront infections arising from drug and Ag-resistant bacterial strains.     

Performing Efficient NURBS Modeling Operations on the GPU

We present algorithms for evaluating and performing modeling operations on NURBS surfaces using the programmable fragment processor on the Graphics Processing Unit (GPU). We extend our GPU-based NURBS evaluator that evaluates NURBS surfaces to compute exact normals for either standard or rational B-spline surfaces for use in rendering and geometric modeling. We build on these calculations in our new GPU algorithms to perform standard modeling operations such as inverse evaluations, ray intersections, and surface-surface intersections on the GPU. Our modeling algorithms run in real time, enabling the user to sketch on the actual surface to create new features. In addition, the designer can edit the surface by interactively trimming it without the need for retessellation. Our GPU-accelerated algorithm to perform surface-surface intersection operations with NURBS surfaces can output intersection curves in the model space as well as in the parametric spaces of both the intersecting surfaces at interactive rates. We also extend our surface-surface intersection algorithm to evaluate self-intersections in NURBS surfaces.     

GPU-accelerated minimum distance and clearance queries

We present practical algorithms for accelerating distance queries on models made of trimmed NURBS surfaces using programmable Graphics Processing Units (GPUs). We provide a generalized framework for using GPUs as coprocessors in accelerating CAD operations. By supplementing surface data with a surface bounding-box hierarchy on the GPU, we answer distance queries such as finding the closest point on a curved NURBS surface given any point in space and evaluating the clearance between two solid models constructed using multiple NURBS surfaces. We simultaneously output the parameter values corresponding to the solution of these queries along with the model space values. Though our algorithms make use of the programmable fragment processor, the accuracy is based on the model space precision, unlike earlier graphics algorithms that were based only on image space precision. In addition, we provide theoretical bounds for both the computed minimum distance values as well as the location of the closest point. Our algorithms are at least an order of magnitude faster and about two orders of magnitude more accurate than the commercial solid modeling kernel ACIS.     

Comparison of satellite and cellular architectures for downlink broadcast data transmission

Traditional voice and video‐oriented networks such as the cellular and satellite networks are being increasingly used to carry data traffic. We endeavour to compare the downlink broadcast performance of the two architectures against each other on the basis of energy consumption, end‐to‐end delay and maximum stable throughput. The architectures are modelled as systems of Geo/G/1 queues. Queuing theory arguments and then sample‐path based comparisons are used to show that the satellite architecture while being more energy‐efficient has a higher delay and a lower maximum throughput. The variation of energy and delay with the total number of receiver nodes is also studied. Copyright © 2006 John Wiley & Sons, Ltd.     

CuII Pyrazolyl-Benzimidazole Dinuclear Complexes with Remarkable Antioxidant Activity

Three dinuclear coordination complexes generated from 1-n-butyl-2-((5-methyl-1H-pyrazole-3-yl)methyl)-1H-benzimidazole ( L ), have been synthesized and characterized spectroscopically and structurally by single crystal X-ray diffraction analysis. Reaction with iron(II) chloride and then copper(II) nitrate led to a co-crystal containing 78 % of [Cu(NO₃)(μ-Cl)( L’ )]₂ ( C₁ ) and 22 % of [Cu(NO₃)(μ-NO₃)( L’ )]₂ ( C₂ ), where L was oxidized to a new ligand L^’ . A mechanism is provided. Reaction with copper chloride led to the dinuclear complex [Cu(Cl)(μ-Cl)( L) ]₂ ( C₃ ). The presence of N−H⋅⋅⋅O and C−H⋅⋅⋅O intermolecular interactions in the crystal structure of C₁ and C₂ , and C−H⋅⋅⋅N and C−H⋅⋅⋅Cl hydrogen bonding in the crystal structure of C₃ led to supramolecular structures that were confirmed by Hirshfeld surface analysis. The ligands and their complexes were tested for free radical scavenging activity and ferric reducing antioxidant power. The complex C₁ / C₂ shows remarkable antioxidant activities as compared to the ligand L and reference compounds.     

Effect of iron content on permeability and power loss characteristics of Li0.35Cd0.3Fe2.35O4 and Li0.35Zn0.3Fe2.35O4

Substituted lithium ferrites having the chemical formula, Li_0.35Cd_0.3Fe_2.35O₄ and Li_0.35Zn_0.3Fe_2.35O₄, with different iron (metal) contents (2, 4, 6, 8 and 10) in wt% have been prepared by solid-state technique. Complex permeability and power loss of all samples have been measured by network analyser in the frequency range of 50–5000 kHz. Magnetic properties like saturation magnetization, coercivity, retentivity have been measured by vibrating sample magnetometer (VSM). The permeability of cadmium doped lithium ferrites exhibited higher values than zinc doped lithium ferrites. The power loss of cadmium doped lithium ferrites is lesser as compared to zinc doped lithium ferrites in the frequency range of 50–5000 kHz and at flux density of 10 mT. The behaviour of power loss with flux density has been found near about same for both series. Magnetic and power loss behaviour of the samples suggest that a small amount of Fe content can improve the properties of ferrite samples for microwave devices.     

Temperature-dependent electrical resistance of conductive polylactic acid filament for fused deposition modeling

This study characterizes the microstructure and temperature dependence of resistance of two commercially available electrically conductive polylactic acid (PLA) composites for fused deposition modeling (FDM): PLA-carbon black and PLA-graphene. No microstructural changes were observed between the filament and the printed parts; however, the resistivity of the filament was found to drop by four to six times upon FDM. Also, compared to the resistivity of individual extruded wire, the resistivity of the printed parts was found to be up to 1500 times higher for PLA-graphene and up to 300 times higher for PLA-carbon black. The raw PLA-carbon black filament and printed wire showed a positive temperature coefficient of resistance (α) value between ~?0.03 and 0.01 °C^?1, which makes them more suitable for sensor development. The raw PLA-graphene filament and printed wire did not exhibit a significant α, which makes them more suitable for printing wires. However, the parts made with multilayer FDM exhibited a negative or a negligible α up to a certain temperature prior to exhibiting a positive α; further, these α values were significantly lower than those obtained for the filaments before or after extrusion. These findings enable proper selection of commercial conductive FDM filaments for enabling quicker prototyping of electronics and sensors.     

Exploitability prediction of software vulnerabilities

The number of security failure discovered and disclosed publicly are increasing at a pace like never before. Wherein, a small fraction of vulnerabilities encountered in the operational phase are exploited in the wild. It is difficult to find vulnerabilities during the early stages of software development cycle, as security aspects are often not known adequately. To counter these security implications, firms usually provide patches such that these security flaws are not exploited. It is a daunting task for a security manager to prioritize patches for vulnerabilities that are likely to be exploitable. This paper fills this gap by applying different machine learning techniques to classify the vulnerabilities based on previous exploit-history. Our work indicates that various vulnerability characteristics such as severity, type of vulnerabilities, different software configurations, and vulnerability scoring parameters are important features to be considered in judging an exploit. Using such methods, it is possible to predict exploit-prone vulnerabilities with an accuracy >85%. Finally, with this experiment, we conclude that supervised machine learning approach can be a useful technique in predicting exploit-prone vulnerabilities.     

Assessing Self-Organization in Agile Software Development Teams

Self-organization, based on the Socio-Technical Design (STS) work design principles, is considered a hallmark of agile software development (SD) teams and an antecedent of motivation and innovation at work. However, while self-organization is considered a salient success factor in agile SD, past research has shown that there are many hurdles in self-organizing. Yet, the actual level of self-organization practiced in agile teams has not been investigated. In this study we develop a measure to do so using the nine principles of STS work design by Cherns [15]. We found that while the level of self-organization varies across agile projects, on each of the nine dimensions the level of self-organization in agile teams was found to be significantly higher than those using plan-driven methods. Furthermore, self-organization was found to positively affect the motivation and innovativeness of SD teams.