Coordination and P2P computing

Peer-to-Peer (P2P) refers to a class of systems and/or applications that use distributed resources in a decentralized and autonomous manner to achieve a goal. A number of successful applications, like BitTorrent (for file and content sharing) and SETI@Home (for distributed computing) have demonstrated the feasibility of this approach. As a new form of distributed computing, P2P computing has the same coordination problems as other forms of distributed computing. Coordination has been considered an important issue in distributed computing for a long time and many coordination models and languages have been developed. This research focuses on how to solve coordination problems in P2P computing. In particular, it is to provide a seamless P2P computing environment so that the migration of computation components is transparent. This research extends Manifold, an event-driven coordination model, to meet P2P computing requirements and integrates the P2P-Manifold model into an existing platform. The integration hides the complexity of the coordination model and makes the model easy to use

UC Secure Private Branching Program and Decision Tree Evaluation

Branching program (BP) is a DAG-based non-uniform computational model for L/poly class. It has been widely used in formal verification, logic synthesis, and data analysis. As a special BP, a decision tree is a popular machine learning classifier for its effectiveness and simplicity. In this work, we propose a UC-secure efficient 3-party computation platform for outsourced branching program and/or decision tree evaluation. We construct a constant-round protocol and a linear-round protocol. In particular, the overall (online + offline) communication cost of our linear-round protocol is $O(d(\ell + \log m+\log n))$ and its round complexity is $2d-1$, where $m$ is the DAG size, $n$ is the number of features, $\ell$ is the feature length, and $d$ is the longest path length. To enable efficient oblivious hopping among the DAG nodes, we propose a lightweight $1$-out-of-$N$ shared OT protocol with logarithmic communication in both online and offline phase. This partial result may be of independent interest to some other cryptographic protocols. Our benchmark shows, compared with the state-of-the-arts, the proposed constant-round protocol is up to 10X faster in the WAN setting, while the proposed linear-round protocol is up to 15X faster in the LAN setting

The role of rock joint frictional strength in the containment of fracture propagation

The fracturing phenomenon within the reservoir environment is a complex process that is controlled by several factors and may occur either naturally or by artificial drivers. Even when deliberately induced, the fracturing behaviour is greatly influenced by the subsurface architecture and existing features. The presence of discontinuities such as joints, artificial and naturally occurring faults and interfaces between rock layers and microfractures plays an important role in the fracturing process and has been known to significantly alter the course of fracture growth. In this paper, an important property (joint friction) that governs the shear behaviour of discontinuities is considered. The applied numerical procedure entails the implementation of the discrete element method to enable a more dynamic monitoring of the fracturing process, where the joint frictional property is considered in isolation. Whereas fracture propagation is constrained by joints of low frictional resistance, in non-frictional joints, the unrestricted sliding of the joint plane increases the tendency for reinitiation and proliferation of fractures at other locations. The ability of a frictional joint to suppress fracture growth decreases as the frictional resistance increases; however, this phenomenon exacerbates the influence of other factors including in situ stresses and overburden conditions. The effect of the joint frictional property is not limited to the strength of rock formations; it also impacts on fracturing processes, which could be particularly evident in jointed rock masses or formations with prominent faults and/or discontinuities

Computation in Peer-to-Peer Networks

Peer-to-Peer (P2P) networks are the latest addition to the universe of distributed systems. Emphasizing decentralization and selforganization the P2P networks tend to be more robust and scalable than other forms of distributed systems. Especially in the domain of file-swapping P2P networks seem to outperform other approaches largely due to the anonymity of t he participants in the peer-network, low network costs and the inexpensive disk-space. Trying to apply P2P principles in the area of distributed computation was significantly less successful. The much referred SETI@home system and its look-alikes have a far smaller reach and seem to be very limited to single-process multiple data problems

ACKNOWLEDGMENTS

support. Without his help, this work would not be possible. I would also like to thank the members of my committee who attended my defense: Professor JulitaVassileva, Professor Dwight Makaroff and Professor Chris Zhang. Their advice and patience is appreciated. Special thanks go to Professor Dwight Makaroff for his invaluable advice on system evaluation and simulation. I would also like to thank all graduate students of MADMUC labs for their helps. I dedicate this thesis to my parents. Peer-to-Peer (P2P) refers to a class of systems and/or applications that use distributed resources in a decentralized and autonomous manner to achieve a goal. A number of successful applications, like BitTorrent (for file and content sharing) an

A novel truncated variant in SPAST results in spastin accumulation and defects in microtubule dynamics

Abstract Objective Haploinsufficiency is widely accepted as the pathogenic mechanism of hereditary spastic paraplegias type 4 (SPG4). However, there are some cases that cannot be explained by reduced function of the spastin protein encoded by SPAST. The aim of this study was to identify the causative variant of SPG4 in a large Chinese family and explore its pathological mechanism. Materials and methods A five-generation family with 49 members including nine affected (4 males and 5 females) and 40 unaffected individuals in Mongolian nationality was recruited. Whole exome sequencing was employed to investigate the genetic etiology. Western blotting and immunofluorescence were used to analyze the effects of the mutant proteins in vitro. Results A novel frameshift variant NM_014946.4: c.483_484delinsC (p.Val162Leufs*2) was identified in SPAST from a pedigree with SPG4. The variant segregated with the disease in the family and thus determined as the disease-causing variant. The c.483_484delinsC variant produced two truncated mutants (mutant M1 and M87 isoforms). They accumulated to a higher level and presented increased stability than their wild-type counterparts and may lost the microtubule severing activity. Conclusion SPAST mutations leading to premature stop codons do not always act through haploinsufficiency. The potential toxicity to the corticospinal tract caused by the intracellular accumulation of truncated spastin should be considered as the pathological mechanism of SPG4

Image_3_Identification of natural compounds as SARS-CoV-2 inhibitors via molecular docking and molecular dynamic simulation.TIF

BackgroundBase mutations increase the contagiousness and transmissibility of the Delta and Lambda strains and lead to the severity of the COVID-19 pandemic. Molecular docking and molecular dynamics (MD) simulations are frequently used for drug discovery and relocation. Small molecular compounds from Chinese herbs have an inhibitory effect on the virus. Therefore, this study used computational simulations to investigate the effects of small molecular compounds on the spike (S) protein and the binding between them and angiotensin-converting enzyme 2 (ACE2) receptors.MethodsIn this study, molecular docking, MD simulation, and protein–protein analysis were used to explore the medicinal target inhibition of Chinese herbal medicinal plant chemicals on SARS-CoV-2. 12,978 phytochemicals were screened against S proteins of SARS-CoV-2 Lambda and Delta mutants.ResultsMolecular docking showed that 65.61% and 65.28% of the compounds had the relatively stable binding ability to the S protein of Lambda and Delta mutants (docking score ≤ −6). The top five compounds with binding energy with Lambda and Delta mutants were clematichinenoside AR2 (−9.7), atratoglaucoside,b (−9.5), physalin b (−9.5), atratoglaucoside, a (−9.4), Ochnaflavone (−9.3) and neo-przewaquinone a (−10), Wikstrosin (−9.7), xilingsaponin A (−9.6), ardisianoside G (−9.6), and 23-epi-26-deoxyactein (−9.6), respectively. Four compounds (Casuarictin, Heterophylliin D, Protohypericin, and Glansrin B) could interact with S protein mutation sites of Lambda and Delta mutants, respectively, and MD simulation results showed that four plant chemicals and spike protein have good energy stable complex formation ability. In addition, protein–protein docking was carried out to evaluate the changes in ACE2 binding ability caused by the formation of four plant chemicals and S protein complexes. The analysis showed that the binding of four plant chemicals to the S protein could reduce the stability of the binding to ACE2, thereby reducing the replication ability of the virus.ConclusionTo sum up, the study concluded that four phytochemicals (Casuarictin, Heterophylliin D, Protohypericin, and Glansrin B) had significant effects on the binding sites of the SARS-CoV-2 S protein. This study needs further in vitro and in vivo experimental validation of these major phytochemicals to assess their potential anti-SARS-CoV-2.Graphical abstract</p

Table_1_Identification of natural compounds as SARS-CoV-2 inhibitors via molecular docking and molecular dynamic simulation.xlsx

BackgroundBase mutations increase the contagiousness and transmissibility of the Delta and Lambda strains and lead to the severity of the COVID-19 pandemic. Molecular docking and molecular dynamics (MD) simulations are frequently used for drug discovery and relocation. Small molecular compounds from Chinese herbs have an inhibitory effect on the virus. Therefore, this study used computational simulations to investigate the effects of small molecular compounds on the spike (S) protein and the binding between them and angiotensin-converting enzyme 2 (ACE2) receptors.MethodsIn this study, molecular docking, MD simulation, and protein–protein analysis were used to explore the medicinal target inhibition of Chinese herbal medicinal plant chemicals on SARS-CoV-2. 12,978 phytochemicals were screened against S proteins of SARS-CoV-2 Lambda and Delta mutants.ResultsMolecular docking showed that 65.61% and 65.28% of the compounds had the relatively stable binding ability to the S protein of Lambda and Delta mutants (docking score ≤ −6). The top five compounds with binding energy with Lambda and Delta mutants were clematichinenoside AR2 (−9.7), atratoglaucoside,b (−9.5), physalin b (−9.5), atratoglaucoside, a (−9.4), Ochnaflavone (−9.3) and neo-przewaquinone a (−10), Wikstrosin (−9.7), xilingsaponin A (−9.6), ardisianoside G (−9.6), and 23-epi-26-deoxyactein (−9.6), respectively. Four compounds (Casuarictin, Heterophylliin D, Protohypericin, and Glansrin B) could interact with S protein mutation sites of Lambda and Delta mutants, respectively, and MD simulation results showed that four plant chemicals and spike protein have good energy stable complex formation ability. In addition, protein–protein docking was carried out to evaluate the changes in ACE2 binding ability caused by the formation of four plant chemicals and S protein complexes. The analysis showed that the binding of four plant chemicals to the S protein could reduce the stability of the binding to ACE2, thereby reducing the replication ability of the virus.ConclusionTo sum up, the study concluded that four phytochemicals (Casuarictin, Heterophylliin D, Protohypericin, and Glansrin B) had significant effects on the binding sites of the SARS-CoV-2 S protein. This study needs further in vitro and in vivo experimental validation of these major phytochemicals to assess their potential anti-SARS-CoV-2.Graphical abstract</p

Table_2_Identification of natural compounds as SARS-CoV-2 inhibitors via molecular docking and molecular dynamic simulation.xlsx

BackgroundBase mutations increase the contagiousness and transmissibility of the Delta and Lambda strains and lead to the severity of the COVID-19 pandemic. Molecular docking and molecular dynamics (MD) simulations are frequently used for drug discovery and relocation. Small molecular compounds from Chinese herbs have an inhibitory effect on the virus. Therefore, this study used computational simulations to investigate the effects of small molecular compounds on the spike (S) protein and the binding between them and angiotensin-converting enzyme 2 (ACE2) receptors.MethodsIn this study, molecular docking, MD simulation, and protein–protein analysis were used to explore the medicinal target inhibition of Chinese herbal medicinal plant chemicals on SARS-CoV-2. 12,978 phytochemicals were screened against S proteins of SARS-CoV-2 Lambda and Delta mutants.ResultsMolecular docking showed that 65.61% and 65.28% of the compounds had the relatively stable binding ability to the S protein of Lambda and Delta mutants (docking score ≤ −6). The top five compounds with binding energy with Lambda and Delta mutants were clematichinenoside AR2 (−9.7), atratoglaucoside,b (−9.5), physalin b (−9.5), atratoglaucoside, a (−9.4), Ochnaflavone (−9.3) and neo-przewaquinone a (−10), Wikstrosin (−9.7), xilingsaponin A (−9.6), ardisianoside G (−9.6), and 23-epi-26-deoxyactein (−9.6), respectively. Four compounds (Casuarictin, Heterophylliin D, Protohypericin, and Glansrin B) could interact with S protein mutation sites of Lambda and Delta mutants, respectively, and MD simulation results showed that four plant chemicals and spike protein have good energy stable complex formation ability. In addition, protein–protein docking was carried out to evaluate the changes in ACE2 binding ability caused by the formation of four plant chemicals and S protein complexes. The analysis showed that the binding of four plant chemicals to the S protein could reduce the stability of the binding to ACE2, thereby reducing the replication ability of the virus.ConclusionTo sum up, the study concluded that four phytochemicals (Casuarictin, Heterophylliin D, Protohypericin, and Glansrin B) had significant effects on the binding sites of the SARS-CoV-2 S protein. This study needs further in vitro and in vivo experimental validation of these major phytochemicals to assess their potential anti-SARS-CoV-2.Graphical abstract</p