Investigation on "Chinese Spirit" of Architectural Students in Higher Vocational Colleges

At the beginning of 2020, China suffered a sudden epidemic, in which many extraordinary stories occurred. These stories in extraordinary times have stronger appeal to people than usual. In order to investigate which "Chinese spirit" stories have the deepest impact on higher vocational students, as well as the communication path of "Chinese spirit" loved by students and the effect of integrating "Chinese spirit" into classroom ideology and politics, a questionnaire was issued to architectural students to fully grasp the impact of "Chinese spirit" on higher vocational students. The results show that the most impressed "Chinese spirit" figures are medical personnel. Most students understand and agree with the "Chinese spirit", think that patriotism and "helping each other in the same boat" can best represent the Chinese spirit, and think that the integration of the "Chinese spirit" into classroom teaching has had a positive impact on them.

High Definition Acoustic and Temperature Logging for the Diagnosis of Complex Annuli Leaks and Communication

Maintaining annuli integrity is critical for safe and optimized well operations. Monitoring of tubing casing annulus (TCA) and casing-casing annulus (CCA) pressures is mandatory as it gives a direct indication of possible seal or tubular failures that may lead to a negative impact on HSE or well production. In cases where the observed annuli pressures suggest leaks and possible communication between tubing and TCA or TCA and CCA, a comprehensive plan should be put in place to detect and evaluate the possible leak sources and paths that will allow for proper remedial actions. Logging techniques using spectral noise logging (SNL), and high precision temperature Logging (HPT) are one way to diagnose the source of a leak and communication path between 2 adjacent casings (for example TCA and CCA). The operation is performed by running the HPT and SNL log under shut in conditions to establish a base line, followed by logging under dynamic conditions. Dynamic conditions can include bleeding off the TCA pressure while all other annuli and tree valves are shut-in and injecting into the tubing-casing annulus while bleeding off the CCA. The dynamic passes aim to activate the leak points. The SNL and HPT will capture the corresponding temperature and Spectral noise events revealed by the fluid flow though the leak points. These are compared to the base line shut in logs. The SNL is run in stations and can capture noise generated by fluid movement in a wide range of strength (decibels) and frequency within a wide scanning radius, while HPT can capture minor temperature changes of 0.02 Deg F. The paper will discuss an example where the HPT and SNL were run along with a set of conventional sensors such as GR, CCL, and pressure in a HPHT gas well to diagnose leak points and a possible communication path between the TCA and CCA. The Logging operation was carried out rig-less with minimum intervention using wire line under the shut in and dynamic conditions. Spectral noise logging precisely captured the leak points and drew a clear picture of the casing integrity breaches in multiple points. The results of the diagnostics and evaluation will now be used to design the appropriate remedial actions required to restore the well to the desired condition for production.

Loss of radio waves energy on radio lines satellite-earth station

The main contribution of this paper is to study the influence of various natural factors on the conditions for the radio signals propagation on the satellite - Earth links. It is shown that the ionosphere practically does not interfere with satellite radio communications at frequencies above 5 GHz. The mathematical model is proposed for the numerical determination of the attenuation of the radio signal depending on the optical visibility during dust storms along the communication path.

PINC: Pickup Non-Critical Node Based k-Connectivity Restoration in Wireless Sensor Networks

A Wireless Sensor Network (WSN) is connected if a communication path exists among each pair of sensor nodes (motes). Maintaining reliable connectivity in WSNs is a complicated task, since any failure in the nodes can cause the data transmission paths to break. In a k-connected WSN, the connectivity survives after failure in any k-1 nodes; hence, preserving the k-connectivity ensures that the WSN can permit k-1 node failures without wasting the connectivity. Higher k values will increase the reliability of a WSN against node failures. We propose a simple and efficient algorithm (PINC) to accomplish movement-based k-connectivity restoration that divides the nodes into the critical, which are the nodes whose failure reduces k, and non-critical groups. The PINC algorithm pickups and moves the non-critical nodes when a critical node stops working. This algorithm moves a non-critical node with minimum movement cost to the position of the failed mote. The measurements obtained from the testbed of real IRIS motes and Kobuki robots, along with extensive simulations, revealed that the PINC restores the k-connectivity by generating optimum movements faster than its competitors.

Novel dynamic residue network analysis approaches to study homodimeric allosteric modulation in SARS-CoV-2 Mpro and in its evolutionary mutations

The rational search for allosteric modulators and the allosteric mechanisms of these modulators in the presence of evolutionary mutations, including resistant ones, is a relatively unexplored field. Here, we established novel in silico approaches and applied to SARS-CoV-2 main protease (Mpro). First, we identified six potential allosteric modulators (SANC00302, SANC00303, SANC00467, SANC00468, SANC00469, SANC00630) from the South African Natural Compounds Database (SANCDB) bound to the allosteric pocket of Mpro that we determined in our previous work. We also checked the stability of these compounds against Mpro of laboratory strain HCoV-OC43 and identified differences due to residue changes between the two proteins. Next, we focused on understanding the allosteric effects of these modulators on each protomer of the reference Mpro protein, while incorporating the symmetry problem in the functional homodimer. In general, asymmetric behavior of multimeric proteins is not commonly considered in computational analysis. We introduced a novel combinatorial approach and dynamic residue network (DRN) analysis algorithms to examine patterns of change and conservation of critical nodes, according to five independent criteria of network centrality (betweenness centrality (BC), closeness centrality (CC), degree centrality (DC), eigencentrality (EC) and katz centrality (KC)). The relationships and effectiveness of each metric in characterizing allosteric behavior were also investigated. We observed highly conserved network hubs for each averaged DRN metric on the basis of their existence in both protomers in the absence and presence of all ligands, and we called them persistent hubs (residues 17, 111, 112 and 128 for averaged BC; 6, 7, 113, 114, 115, 124, 125, 126, 127 and 128 for averaged CC; 36, 91, 146, 150 and 206 for averaged DC; 7, 115 and 125 for EC; 36, 125 and 146 for KC). We also detected ligand specific signal changes some of which were in or around functional residues (i.e. chameleon switch PHE140). Using EC persistent hubs and ligand introduced hubs we identified a residue communication path between allosteric binding site and catalytic site. Finally, we examined the effects of the mutations on the behavior of the protein in the presence of selected potential allosteric modulators and investigated the ligand stability. The hit compounds showed various levels of stability in the presence of SARS-CoV-2 Mpro mutations, being most stable in A173V, N274D and R279C, and least stable in R60C, N151D V157I, C160S and A255V. SANC00468 was the most stable compound in the 43 mutant protein systems. We further used DRN metric analysis to define cold spots as being those regions that are least impacted, or not impacted, by mutations. One crucial outcome of this study was to show that EC centrality hubs form an allosteric communication path between the allosteric ligand binding site to the active site going through the interface residues of Domain I and II; and this path was either weakened or lost in the presence of some of the mutations. Overall, the results of this study revealed crucial aspects that need to be considered in drug discovery in COVID-19 specifically and in general for rational computational drug design purposes.

Measuring and Localising Congestion in Mobile Broadband Networks

The paper presents a method to localize bottleneck in an end-to-end communication path with UE inside an LTE network.<br>

Measuring and Localising Congestion in Mobile Broadband Networks

The paper presents a method to localize bottleneck in an end-to-end communication path with UE inside an LTE network.<br>

A Node Localization Algorithm for Wireless Sensor Networks Based on Virtual Partition and Distance Correction

The coordinates of nodes are very important in the application of wireless sensor networks (WSN). The range-free localization algorithm is the best method to obtain the coordinates of sensor nodes at present. Range-free localization algorithm can be divided into two stages: distance estimation and coordinate calculation. For reduce the error in the distance estimation stage, a node localization algorithm for WSN based on virtual partition and distance correction (VP-DC) is proposed in this paper. In the distance estimation stage, firstly, the distance of each hop on the shortest communication path between the unknown node and the beacon node is calculated with the employment of virtual partition algorithm; then, the length of the shortest communication path is obtained by summing the distance of each hop; finally, the unknown distance between nodes is obtained according to the optimal path search algorithm and the distance correction formula. This paper innovative proposes the virtual partition algorithm and the optimal path search algorithm, which effectively avoids the distance estimation error caused by hop number and hop distance, and improves the localization accuracy of unknown nodes.

EARP: Extended Area Multihop Node Localization Algorithm for Anisotropic Wireless Sensor Networks

Localization is one of the essential problems in the Internet of Things (IoT) and other wireless sensor applications. Most traditional range-free localization algorithms ignore the anisotropy factors, which are frequently observed in wireless sensor networks (WSNs) and result in low positioning precision. To mitigate the impact of anisotropy on localization, this paper proposes an extended area multihop node localization method. The proposed method classifies and discusses the boundaries of the concave area within the communication range of the node and then uses the maximum split communication distance of the node to identify and mark the boundary of the concave area. When the shortest communication path between the nodes is affected by the concave area, the boundary of the concave area is expanded to obtain the new shortest communication path, and the node distance is obtained by comparing the changes in the communication path. After a large number of simulation tests, it is shown that the calculation accuracy of this scheme is better than that of similar modern mainstream localization algorithms.