Modeling of Observed Permanent Deformation at La Villita Dam

The observed behavior of La Villita dam in Mexico during five different earthquakes which have occurred in the period 1975-1985 is analyzed. Asymmetry observed in the recorded crest acceleration time histories is interpreted to be due to localized stick-slip behavior below the recording instrument. Yield acceleration associated with each stick-slip event can be inferred directly from these crest records. Values of observed average yield accelerations for the November 15, 1975 and September 19, 1985 earthquakes are used to predict the observed horizontal displacements during these earthquakes. Response of other soil systems involving stick-slip deformations during dynamic loading is also briefly discussed

Computation of Dynamic Large Displacements in Earth Systems

A model for the computation of seismically induced permanent displacements is earth structures are proposed. This model allows relative sliding between different zones of the structure under investigation. Large displacements are allowed between these zones. Elasto-plastic constitutive soil behavior is accounted for. An updated Lagrangian Jaumann Finite Element formulation is used. The proposed model is used to predict the observed behavior of LaVillita Dam during the November 15, 1975 earthquake

A Framework for Profit Maximization in a Grid-Connected Microgrid with Hybrid Resources Using a Novel Rule Base-BAT Algorithm

In this paper, an energy management system (EMS) is proposed for optimal operation of a microgrid (MG). Dispersed photovoltaic arrays (PVs) and wind turbine generators (WTs) as renewable energy sources (RES) supply a major part of the network demanded energy. Also, an energy storage system (ESS), a micro-turbine unit (MT), and a fuel cell unit (FC) are integrated. The uncertainty and stochastic nature of the network load and RES data are treated via probabilistic modeling and scenario-selection approach. The predicted day-ahead data of the most diverse hourly scenarios are entered into the proposed EMS to determine the active and reactive power (P-Q) participations of local distributed resources. Likewise, it specifies the discharging/charging power and state of the ESS in addition to the exchanged active/reactive power amounts with the main network. The main goal is to maximize the profit of the secondary grid while satisfying all technical constraints. In the proposed EMS, the day-ahead energy management is developed as a comprehensive optimization problem. Moreover, the paper proposes novel modifications to improve the BAT optimization technique. The optimization problem of the energy management in the microgrid is implemented using a new integrated rule base-improved BAT method. Furthermore, the proposed EMS competence is proven by comparing its performance to recent literature. © 2013 IEEE.Ministry of Higher Education, Egypt, MHEThis work was supported by the Ministry of Higher Education, Egypt

The Expression of TBC1 Domain Family, Member 4 (TBC1D4) in Skeletal Muscles of Insulin-Resistant Mice in Response to Sulforaphane

The Expression of TBC1 Domain Family, member 4 (TBC1D4) in Skeletal Muscles of Insulin-Resistant Mice in Response to Sulforaphane. Background: Obesity is commonly accompanied by impaired glucose homeostasis. Decreased glucose transport to the peripheral tissues, mainly skeletal muscle, leads to reduced total glucose disposal and hyperglycemia. TBC1D4 gene is involved in the trafficking of GLUT4 to the outer cell membrane in skeletal muscle. Sulforaphane (SFN) has been suggested as a new potential anti-diabetic compound acting by reducing blood glucose levels through mechanisms not fully understood (1). The aim of this study is to investigate the effects SFN on TBC1D4 and GLUT4 gene expression in skeletal muscles of DIO mice, in order to elucidate the mechanism(s) through which SFN improves glucose homeostasis. Methodology: C57BL/6 mice (n=20) were fed with a high fat diet (60%) for 16 weeks to generate diet induced obese (DIO) mice with body weights between 45–50 gm. Thereafter, DIO mice received either SFN (5mg/kg BW) (n=10) or vehicle (n=10) as controls daily by intraperitoneal injections for four weeks. Glucose tolerance test (1g/kg BW, IP) and insulin sensitivity test (ITT) were conducted (1 IU insulin/ g BW, IP route) at the beginning and end of the third week of the injection. At the end of 4 weeks of the injection, samples of blood and skeletal muscles of both hindlimbs were collected. The expression levels of GLUT4 and TBC1D4 genes were analyzed by qRT-PCR. Blood was also used for glucose, adiponectin and insulin measurements. Results: SFN-treated DIO mice had significantly lower non-fasting blood glucose levels than vehicle-treated mice (194.16 ± 14.12 vs. 147.44 ± 20.31 mg/dL, vehicle vs. SFN, p value=0.0003). Furthermore, GTT results indicate that the blood glucose levels at 120 minutes after glucose infusion in was (199.83±34.53 mg/dl vs. 138.55±221.78 mg/dl) for vehicle vs. SFN with p=0.0011 respectively. ITT showed that SFN treatment did not enhance insulin sensitivity in DIO mice. Additionally, SFN treatment did not significantly change the expression of TBC1D4, and GLUT4 genes in skeletal muscles compared to vehicle treatment (p values >0.05). Furthermore, SFN treatment did not significantly affect the systemic insulin (1.84±0.74 vs 1.54±0.55 ng/ml, p=0.436), or adiponectin (11.96 ±2.29 vs 14.4±3.33 ug/ml, p=0.551) levels in SFN vs. vehicle-treated DIO mice, respectively. Conclusion: SFN treatment improves glucose disposal in DIO mice, which is not linked to the gene expression of GLUT4 and TBC1D4 and its mechanism of glucose disposal in skeletal muscles. Furthermore, SFN treatment did not improve insulin level, and the insulin sensitizer hormone adiponectin as potential players for enhancing insulin sensitivity.QNRF-NPR

Encrypted Shared Data Spaces

The deployment of Share Data Spaces in open, possibly hostile, environments arises the need of protecting the confidentiality of the data space content. Existing approaches focus on access control mechanisms that protect the data space from untrusted agents. The basic assumption is that the hosts (and their administrators) where the data space is deployed have to be trusted. Encryption schemes can be used to protect the data space content from malicious hosts. However, these schemes do not allow searching on encrypted data. In this paper we present a novel encryption scheme that allows tuple matching on completely encrypted tuples. Since the data space does not need to decrypt tuples to perform the search, tuple confidentiality can be guaranteed even when the data space is deployed on malicious hosts (or an adversary gains access to the host). Our scheme does not require authorised agents to share keys for inserting and retrieving tuples. Each authorised agent can encrypt, decrypt, and search encrypted tuples without having to know other agents’ keys. This is beneficial inasmuch as it simplifies the task of key management. An implementation of an encrypted data space based on this scheme is described and some preliminary performance results are given

Human Multipotent Stromal Cell Secreted Effectors Accelerate Islet Regeneration

Human multipotent stromal cells (hMSC) can induce islet regeneration after transplantation via the secretion of proteins that establish an islet regenerative niche. However, the identity of hMSC-secreted signals and the mechanisms by which pancreatic islet regeneration is induced remain unknown. Recently, mammalian pancreatic α-cells have been shown to possess considerable plasticity, and differentiate into β-like cells after near complete β-cell loss or overexpression of key transcriptional regulators. These studies have generated new excitement that islet regeneration during diabetes may be possible if we can identify clinically applicable stimuli to modulate these key regulatory pathways. Herein, we demonstrate that intrapancreatic-injection of concentrated hMSC-conditioned media (CM) stimulated islet regeneration without requiring cell transfer. hMSC CM-injection significantly reduced hyperglycemia, increased circulating serum insulin concentration, and improved glucose tolerance in streptozotocin-treated mice. The rate and extent of endogenous β-cell mass recovery was dependent on total protein dose administered and was further augmented by the activation of Wnt-signaling using GSK3-inhibition during CM generation. Intrapancreatic hMSC CM-injection immediately set in motion a cascade of regenerative events that included the emergence of proliferating insulin + clusters adjacent to ducts, NKX6.1 expression in glucagon + cells at days 1–4 suggesting the acquisition of β-cell phenotype by α-cells, and accelerated β-cell maturation with increased MAFA-expression for \u3e1 month postinjection. Discovery and validation of islet regenerative hMSC-secreted protein may lead to the development of cell-free regenerative therapies able to tip the balance in favor of β-cell regeneration versus destruction during diabetes. Stem Cells 2019;37:516–528

Synthesis and antimicrobial activity of some novel 5- and 6-substituted furocoumarins

662-66

Reinforcement Learning for Resource Allocation in Steerable Laser-based Optical Wireless Systems

Vertical Cavity Surface Emitting Lasers (VCSELs) have demonstrated suitability for data transmission in indoor optical wireless communication (OWC) systems due to the high modulation bandwidth and low manufacturing cost of these sources. Specifically, resource allocation is one of the major challenges that can affect the performance of multi-user optical wireless systems. In this paper, an optimisation problem is formulated to optimally assign each user to an optical access point (AP) composed of multiple VCSELs within a VCSEL array at a certain time to maximise the signal to interference plus noise ratio (SINR). In this context, a mixed-integer linear programming (MILP) model is introduced to solve this optimisation problem. Despite the optimality of the MILP model, it is considered impractical due to its high complexity, high memory and full system information requirements. Therefore, reinforcement Learning (RL) is considered, which recently has been widely investigated as a practical solution for various optimization problems in cellular networks due to its ability to interact with environments with no previous experience. In particular, a Q-learning (QL) algorithm is investigated to perform resource management in a steerable VCSEL-based OWC systems. The results demonstrate the ability of the QL algorithm to achieve optimal solutions close to the MILP model. Moreover, the adoption of beam steering, using holograms implemented by exploiting liquid crystal devices, results in further enhancement in the performance of the network considered

AI-Driven Resource Allocation in Optical Wireless Communication Systems

Visible light communication (VLC) is a promising solution to satisfy the extreme demands of emerging applications. VLC offers bandwidth that is orders of magnitude higher than what is offered by the radio spectrum, hence making best use of the resources is not a trivial matter. There is a growing interest to make next generation communication networks intelligent using AI based tools to automate the resource management and adapt to variations in the network automatically as opposed to conventional handcrafted schemes based on mathematical models assuming prior knowledge of the network. In this article, a reinforcement learning (RL) scheme is developed to intelligently allocate resources of an optical wireless communication (OWC) system in a HetNet environment. The main goal is to maximise the total reward of the system which is the sum rate of all users. The results of the RL scheme are compared with that of an optimization scheme that is based on Mixed Integer Linear Programming (MILP) model.Comment: 6 pages, 2 Figures, Conferenc

Security and Efficiency Analysis of the Hamming Distance Computation Protocol Based on Oblivious Transfer

open access articleBringer et al. proposed two cryptographic protocols for the computation of Hamming distance. Their first scheme uses Oblivious Transfer and provides security in the semi-honest model. The other scheme uses Committed Oblivious Transfer and is claimed to provide full security in the malicious case. The proposed protocols have direct implications to biometric authentication schemes between a prover and a verifier where the verifier has biometric data of the users in plain form. In this paper, we show that their protocol is not actually fully secure against malicious adversaries. More precisely, our attack breaks the soundness property of their protocol where a malicious user can compute a Hamming distance which is different from the actual value. For biometric authentication systems, this attack allows a malicious adversary to pass the authentication without knowledge of the honest user's input with at most $O(n)$ complexity instead of $O(2^n)$, where $n$ is the input length. We propose an enhanced version of their protocol where this attack is eliminated. The security of our modified protocol is proven using the simulation-based paradigm. Furthermore, as for efficiency concerns, the modified protocol utilizes Verifiable Oblivious Transfer which does not require the commitments to outputs which improves its efficiency significantly