Seismic Design of Bolted Connections in Steel Structures—A Critical Assessment of Practice and Research

The importance of connections in steel structures is paramount, not only because it greatly influences the cost of construction and provides room for innovations, but also due to the connections’ impact on global structural behaviour. Therefore, research into innovative connections for seismic applications and related design criteria has significantly grown in recent years. However, it has been pursued mostly on local—connection or frame—levels, leaving the system analysis and code compliance levels with a meagre investigation. Moreover, less than 1% of published papers concerning steel connections and earthquake engineering are review articles. To overcome this gap, this systematic review of more than 240 references, including scientific contributions and design codes in the field aimed to cover both recent research and current shortcomings in practice and regulations. It has been found that European design rules updated to a fully performance-based design philosophy is imminent and is deemed to bring pre-qualified joints and increased complexity. Design rules have been systematized, and current hindrances have been highlighted. A deeper look into research needs and trends showed that investigations in connections for concentrically X braced frames are still a necessity, while developments in self-centring and replaceable connections as well as in simple solutions for increasing damping are expected to modify how joints are designed, as soon as semi-rigid and partial strength connections are more easily allowed by design codes.

Bubble NoC – A Low Energy Network-on-Chip with Small Footprint and High Performance

<div>The Bubble NoC is based on simplicity and provides outstanding performance. Flow control is implemented by <i>bubbles</i>, which are inserted between the flits. The logic resembles a traffic situation where a vehicle only moves if the next position is empty. When a flit moves, a bubble is created behind it, and when there is a blocking the bubbles are collapsed as the flits behind are packed together. Even when the Bubble NoC is saturated, it degrades gracefully, and the execution continues.</div><div> Deterministic prerouting is used, with the address stored as markers in a 2 out of 32 code. The routing algorithm shifts the address one step at each hop and turns or finishes when a marker starts the address.</div><div> The physical implementation is a mesh of <i>streets</i> containing duplex links of 38 wires carrying 32-bit payload. Signaling is based on current injection that charges the wires. A switch is placed in a four-way crossing, with a fifth local connection into a street. The switch contains input registers for each approaching street. Straight through traffic is simply passed on, and a diagonal gate is used for turning traffic.</div><div> All switches are bidirectional transmission gates, and the control is distributed as a sidewalk in a few µm of the periphery surrounding the intersection. In a 14 nm technology, the streets are 8 μm wide, the crossing is 17 μm in square, the hop frequency 6.67 GHz and the energy for a datapath 4.1 fJ/bit/hop (150 µm).</div>

EXPRESS: How to Go Glocal: Omni-Brand Orientation Framework

The authors develop an omni-brand orientation framework: a bi-dimensional conceptualization that allows global (local) brand elements to coexist alongside local (global) elements in creating a gloCal brand. Based on an interpretive analysis of interviews with 50 top executives, the authors offer new insights into building and succeeding as a gloCal brand. The study finds global brands trying to become gloCal by building and nurturing local authenticity. The building blocks of local authenticity are brand image local connection, local iconness, local insights, and originality. Local brands, in turn, try to become gloCal by achieving global acceptance, a perception identified closely with global brands. The building blocks of global acceptance are perceived brand globalness, innovation, product performance quality, and global brand power. Based on follow-up interviews with nineteen executives, the study dives deeper into the drivers of success and conceptualizes a GloCal Success Cycle, which identifies components and strategies that enable brands to win both globally and locally.

Bubble NoC – A Low Energy Network-on-Chip with Small Footprint and High Performance

<div>The Bubble NoC is based on simplicity and provides outstanding performance. Flow control is implemented by <i>bubbles</i>, which are inserted between the flits. The logic resembles a traffic situation where a vehicle only moves if the next position is empty. When a flit moves, a bubble is created behind it, and when there is a blocking the bubbles are collapsed as the flits behind are packed together. Even when the Bubble NoC is saturated, it degrades gracefully, and the execution continues.</div><div> Deterministic prerouting is used, with the address stored as markers in a 2 out of 32 code. The routing algorithm shifts the address one step at each hop and turns or finishes when a marker starts the address.</div><div> The physical implementation is a mesh of <i>streets</i> containing duplex links of 38 wires carrying 32-bit payload. Signaling is based on current injection that charges the wires. A switch is placed in a four-way crossing, with a fifth local connection into a street. The switch contains input registers for each approaching street. Straight through traffic is simply passed on, and a diagonal gate is used for turning traffic.</div><div> All switches are bidirectional transmission gates, and the control is distributed as a sidewalk in a few µm of the periphery surrounding the intersection. In a 14 nm technology, the streets are 8 μm wide, the crossing is 17 μm in square, the hop frequency 6.67 GHz and the energy for a datapath 4.1 fJ/bit/hop (150 µm).</div>

A New Method of Identifying Core Designers and Teams Based on the Importance and Similarity of Networks

In the process of product collaborative design, the association between designers can be described by a complex network. Exploring the importance of the nodes and the rules of information dissemination in such networks is of great significance for distinguishing its core designers and potential designer teams, as well as for accurate recommendations of collaborative design tasks. Based on the neighborhood similarity model, combined with the idea of network information propagation, and with the help of the ReLU function, this paper proposes a new method for judging the importance of nodes—LLSR. This method not only reflects the local connection characteristics of nodes but also considers the trust degree of network propagation, and the neighbor nodes’ information is used to modify the node value. Next, in order to explore potential teams, an LA-LPA algorithm based on node importance and node similarity was proposed. Before the iterative update, all nodes were randomly sorted to get an update sequence which was replaced by the node importance sequence. When there are multiple largest neighbor labels in the propagation process, the label with the highest similarity is selected for update. The experimental results in the related networks show that the LLSR algorithm can better identify the core nodes in the network, and the LA-LPA algorithm has greatly improved the stability of the original LPA algorithm and has stably mined potential teams in the network.

VPN SITE TO SITE IMPLEMENTATION USING PROTOCOL L2TP AND IPSEC

Data exchange communication has developed, which leads to centralized communication, and to achieve this communication requires a type of data communication whose data is accommodated on the server and can be accessed by clients, such as at organization. As a company engaged in education, the development of centralized data communication by utilizing the intranet network has been formed. The use of an intranet network allows data communication that is vulnerable to wiretapping. To fix this using a VPN network. L2TP and IPsec VPNs have different performances, especially in the level of security provided. In this study, an analysis of the L2TP and IPsec VPN network performance was carried out on the SMB Server on the Ubuntu server and the Mikrotik router for its VPN configuration. In this study, the L2TP and IPsec VPN was designed by configuring the Mikrotik RB 450G router and the SMB Server configuration using Command Line Interface on Ubuntu 18.04 server. For security analysis, use hacking methods to get VPN Server login data and sniffing methods to get SMB Server login data and SMB data. For performance analysis using parameters of delay, throughput, and packet loss. Wireshark is software for checking by capturing each packet of data from an interface. The research objective to be achieved is to design a VPN technology based on L2TP & IPSec, to be able to determine the resulting performance after implementing a VPN based on L2TP & Ip Sec. The result is that VPN can connect from HO to branch one and branch two or connect from public connection to local connection. The Ubuntu server used is also running well, so it helps the VPN process properly.

The dimensional reduction of linearized spin-2 theories invariant under transverse diffeomorphisms

Here we perform the Kaluza–Klein dimensional reduction from $$D+1$$ D + 1 to D dimensions of massless Lagrangians described by a symmetric rank-2 tensor and invariant under transverse differmorphisms (TDiff). They include the linearized Einstein–Hilbert theory, linearized unimodular gravity and scalar tensor models. We obtain simple expressions in terms of gauge invariant field combinations and show that unitarity is preserved in all cases. After fixing a gauge, the reduced model becomes a massive scalar tensor theory. We show that the diffeomorphism (Diff) symmetry, instead of TDiff, is a general feature of the massless sector of consistent massive scalar tensor models. We discuss some subtleties when eliminating Stückelberg fields directly at action level as gauge conditions. A non local connection between the massless sector of the scalar tensor theory and the pure tensor TDiff model leads to a parametrization of the non conserved source which naturally separates spin-0 and spin-2 contributions in the pure tensor theory. The case of curved backgrounds is also investigated. If we truncate the non minimal couplings to linear terms in the curvature, vector and scalar constraints require Einstein spaces as in the Diff and WTDiff (Weyl plus Diff) cases. We prove that our linearized massive scalar tensor models admit those curved background extensions.

Lubrication-Contact Boundary Conditions for Lubrication Problems

Under sever conditions, asperity contacts take place, surrounded by fluid lubrication. Mathematical descriptions are needed to describe local connection between fluid lubrication and solid contacts. In order to differentiate them from conventional boundary conditions, these conditions are called lubrication-contact boundary conditions (LCBCs), which have not been sufficiently addressed by previous studies. In this work, a set of LCBCs formulations are constructed based on local flow continuity from the continuum mechanics point of view, together with pressure inequalities. Numerical implementations are developed and tested with problems involving simple geometries, and they are expected to be integrated with mixed/boundary EHL solvers, as well as be applied to deterministic sub-models of stochastic models in order to obtain flow factors that consider solid contacts.

A Bioinspired Neural Network-Based Approach for Cooperative Coverage Planning of UAVs

This paper describes a bioinspired neural-network-based approach to solve a coverage planning problem for a fleet of unmanned aerial vehicles exploring critical areas. The main goal is to fully cover the map, maintaining a uniform distribution of the fleet on the map, and avoiding collisions between vehicles and other obstacles. This specific task is suitable for surveillance applications, where the uniform distribution of the fleet in the map permits them to reach any position on the map as fast as possible in emergency scenarios. To solve this problem, a bioinspired neural network structure is adopted. Specifically, the neural network consists of a grid of neurons, where each neuron has a local cost and has a local connection only with neighbor neurons. The cost of each neuron influences the cost of its neighbors, generating an attractive contribution to unvisited neurons. We introduce several controls and precautions to minimize the risk of collisions and optimize coverage planning. Then, preliminary simulations are performed in different scenarios by testing the algorithm in four maps and with fleets consisting of 3 to 10 vehicles. Results confirm the ability of the proposed approach to manage and coordinate the fleet providing the full coverage of the map in every tested scenario, avoiding collisions between vehicles, and uniformly distributing the fleet on the map.