Efficient load balancing on biswapped networks

This paper focuses on devising an efficient algorithm for load balancing on the promising biswapped interconnection networks which were recently proposed as a better architecture over the well-known OTIS networks. The proposed algorithm is called GPM which reduces the number of load balancing steps of the existed algorithms obviously. GPM algorithm first schedules load flows on inter-groups links to achieve the balanced status among groups. Then a general load balancing strategy is executed in each of all groups to balance processor loads. The analytical model proves that GPM algorithm is efficient and results of computer simulation experiment indicate that GPM can implement load balancing in biswapped network interconnected environments efficiently, in terms of various parameters.     

Asymmetrical topology and entropy-based heterogeneous link for many-core massive data communication

As the need for data processing and communication increases, and likewise, as the number of processing cores placed on a given single chip increases, improving the performance of interconnection networks is vital. In the present work, traditional topologies are re-examined. Torus is shown to be a good structure in terms of average latency and symmetry. When using torus in combination with high process levels, it is possible to design new, yet asymmetrical topologies that can meet the high communication performance requirements of many-core processors and also suit a large variety of traffic patterns. Firstly, this paper presents two novel and torus-like topologies called xtorus and xxtorus, which are evaluated by using both theoretical analysis and experimental simulation methods. For theoretical analysis, an algorithm for computing link path diversity and link entropy is given. The analysis shows that, compared with mesh, xmesh and torus, the proposed topologies have better properties in terms of diameter, average latency, throughput, and path diversity. Although more links are added, the number of links is of the same order of magnitude with that of mesh, xmesh, and torus. Proposed topologies also take advantage of increasingly higher levels of the VLSI process. Simulations on GEM5 reveal that xtorus has better scalability, and that its average latency is less than that of mesh, xmesh and torus by significant proportions respectively, particularly when the network scale is larger. Moreover, for different traffic patterns, its performance swing is less than that of mesh. Furthermore, in the present work, the proposed topologies are both asymmetrical and based on the entropy difference of the links in the topology. A strategy for heterogeneous link design is presented, which enables designers to trade off between delay, power and area according to a concrete integrated circuit design scene.     

单孔和四孔腹腔镜胆囊切除术的临床疗效对比分析

摘要 目的：探讨单孔和四孔腹腔镜胆囊切除术的疗效差异。方法：回顾性分析上海交通大学医学院附属仁济医院胆胰外科2018年6月至2019年8月期间施行单孔（单孔组）和四孔腹腔镜胆囊切除术（四孔组）的临床资料,包括手术时间、腹腔引流管留置率、手术方案转变率、手术出血量、术后并发症率（胆漏、出血、伤口感染）、住院时间、住院费用、术后24 h镇痛药物使用率和术后满意度等。结果：单孔组手术时间显著长于四孔组[(42.48±6.66)min Vs (32.18±7.08)min],单孔组腹腔引流管留置率显著低于四孔组（1.67% Vs 21.67%）,差异均有统计学意义（P<0.05）;单孔组的住院时间短于四孔组[(2.22±0.65)天 Vs (2.71±0.57)天],单孔组住院费用高于四孔组[(2.19±0.17)万元Vs (1.81±0.14)万元],单孔组术后24 h镇痛药物使用率低于四孔组（4.17% Vs 16.67%）,术后满意度评分单孔组较四孔组更高[(4.68±0.64)分 Vs (4.47±0.68)分],差异均有统计学意义（P<0.05）;单孔组的手术出血量、手术方案转变率以及术后并发症与四孔组比较没有差异（P>0.05）。结论：单孔腹腔镜胆囊切除术的术后疼痛轻,恢复快,手术安全性与传统四孔腹腔镜胆囊切除术相比无明显差异,同时单孔腹腔镜胆囊切除术满意度更高,值得临床推广。     

Power consumption evaluation of all-optical data center networks

Cloud computing and web emerging applications have created the need for more powerful data centers. These data centers need high bandwidth interconnects that can sustain the high interaction between the web-, application- and database-servers. Data center networks based on electronic packet switches will have to consume excessive power in order to satisfy the required communication bandwidth of future data centers. Optical interconnects have gained attention recently as a promising energy efficient solution offering high throughput, low latency and reduced energy consumption compared to current networks based on commodity switches. This paper presents a comparison on the power consumption of several optical interconnection schemes based on AWGRs, Wavelength Selective Switches (WSS) or Semiconductor Optical Amplifiers (SOAs). Based on a thorough analysis of each architecture, it is shown that optical interconnects can achieve at least an order of magnitude higher energy efficiency compared to current data center networks based on electrical packet based switches and they could contribute to greener IT network infrastructures.     

单孔与三孔胸腔镜肺癌根治术对患者T淋巴细胞亚群、应激反应及生活质量的影响

目的:探讨单孔与三孔胸腔镜肺癌根治术对患者T淋巴细胞亚群、应激反应及生活质量的影响。方法:选择2016年2月～2018年9月期间我院收治的肺癌根治术患者127例为研究对象,依据随机数字表法将其分成单孔组(n=63,采用单孔胸腔镜肺癌根治术治疗)和三孔组(n=64,采用三孔胸腔镜肺癌根治术治疗),比较两组患者手术及临床指标、T淋巴细胞亚群、应激反应指标及生活质量评分,并观察两组患者术后并发症发生情况。结果:单孔组术中出血量少于三孔组,住院时间短于三孔组,而手术时间长于三孔组(P0.05),而两组淋巴结清扫个数、术后引流时间、术后引流量比较差异无统计学意义(P0.05)。术后1d、术后7d单孔组皮质醇、生长激素、PGE_2均低于三孔组(P0.05)。术后3d单孔组CD3~+、CD4~+以及CD4~+/CD8~+高于三孔组(P0.05)。术后3个月单孔组躯体疼痛、社会功能、情感职能、平均分数高于三孔组(P0.05)。两组患者术后并发症总发生率比较无差异(P0.05)。结论:与三孔胸腔镜肺癌根治术相比,单孔胸腔镜肺癌根治术可减少患者术中出血量,缩短住院时间,减轻机体应激反应,对免疫功能损害较轻,且可有效改善患者生活质量。     

Improving the efficiency of evolutionary de novo peptide design: strategies for probing configuration and parameter settings

Evolutionary molecular design based on genetic algorithms (GAs) has been demonstrated to be a flexible and efficient optimization approach with potential for locating global optima. Its efficacy and efficiency are largely dependent on the operations and control parameters of the GAs. Accordingly, we have explored new operations and probed good parameter setting through simulations. The findings have been evaluated in a helical peptide design according to "Parameter setting by analogy" strategy; highly helical peptides have been successfully obtained with a population of only 16 peptides and 5 iterative cycles. The results indicate that new operations such as multi-step crossover-mutation are able to improve the explorative efficiency and to reduce the sensitivity to crossover and mutation rates (CR-MR). The efficiency of the peptide design has been furthermore improved by setting the GAs at the good CR-MR setting determined through simulation. These results suggest that probing the operations and parameter settings through simulation in combination with "Parameter setting by analogy" strategy provides an effective framework for improving the efficiency of the approach. Consequently, we conclude that this framework will be useful for contributing to practical peptide design, and gaining a better understanding of evolutionary molecular design.     

Predictive current control of a switched reluctance machine in the direct-drive manipulator of cloud robotics

Cloud robotics has undergone rapid development. As an important candidate for direct-drive manipulator, switched reluctance machines (SRMs) face significant challenge in terms of control used in cloud robotics because of latency and package losses in network communication. In this paper, predictive current control of SRMs is extended to use in controller upon cloud in the face of latency and package losses. The starting point of predictive model is modified to eliminate errors caused by latency in sensor-controller communication, and the execution of control command sequence is dynamically regulated according to the arrival time of the following sequence to adapt for latency and package losses in controller-actuator communication. The proposed control method is evaluated in a 1.5 kW SRM test platform and comparison with a conventional control method is performed; the results show that the proposed control method has better tracking performance in face of time delay and package losses in transmission.     

Performance analysis of MPI collective operations

Previous studies of application usage show that the performance of collective communications are critical for high-performance computing. Despite active research in the field, both general and feasible solution to the optimization of collective communication problem is still missing. In this paper, we analyze and attempt to improve intra-cluster collective communication in the context of the widely deployed MPI programming paradigm by extending accepted models of point-to-point communication, such as Hockney, LogP/LogGP, and PLogP, to collective operations. We compare the predictions from models against the experimentally gathered data and using these results, construct optimal decision function for broadcast collective. We quantitatively compare the quality of the model-based decision functions to the experimentally-optimal one. Additionally, in this work, we also introduce a new form of an optimized tree-based broadcast algorithm, splitted-binary. Our results show that all of the models can provide useful insights into various aspects of the different algorithms as well as their relative performance. Still, based on our findings, we believe that the complete reliance on models would not yield optimal results. In addition, our experimental results have identified the gap parameter as being the most critical for accurate modeling of both the classical point-to-point-based pipeline and our extensions to fan-out topologies.

Scaling-Laws of Human Broadcast Communication Enable Distinction between Human,Corporate and Robot Twitter Users

Human behaviour is highly individual by nature, yet statistical structures are emerging which seem to govern the actions of human beings collectively. Here we search for universal statistical laws dictating the timing of human actions in communication decisions. We focus on the distribution of the time interval between messages in human broadcast communication, as documented in Twitter, and study a collection of over 160,000 tweets for three user categories: personal (controlled by one person), managed (typically PR agency controlled) and bot-controlled (automated system). To test our hypothesis, we investigate whether it is possible to differentiate between user types based on tweet timing behaviour, independently of the content in messages. For this purpose, we developed a system to process a large amount of tweets for reality mining and implemented two simple probabilistic inference algorithms: 1. a naive Bayes classifier, which distinguishes between two and three account categories with classification performance of 84.6% and 75.8%, respectively and 2. a prediction algorithm to estimate the time of a user''s next tweet with an . Our results show that we can reliably distinguish between the three user categories as well as predict the distribution of a user''s inter-message time with reasonable accuracy. More importantly, we identify a characteristic power-law decrease in the tail of inter-message time distribution by human users which is different from that obtained for managed and automated accounts. This result is evidence of a universal law that permeates the timing of human decisions in broadcast communication and extends the findings of several previous studies of peer-to-peer communication.     

No need to shout: Effect of signal loudness on sibling communication in barn owls Tyto alba

In animal communication, signal loudness is often ignored and seldom measured. We used a playback experiment to examine the role of vocal loudness (i.e., sound pressure level) in sibling to sibling communication of nestling barn owls Tyto alba. In this species, siblings vocally negotiate among each other for priority access to parental food resources. Call rate and call duration play key roles in this vocal communication system, with the most vocal nestlings deterring their siblings from competing for access to the food item next delivered by parents. Here, we broadcast calls at different loudness levels and call rate to live nestlings. The loudness of playback calls did not affect owlets' investment in call rate, call duration or call loudness. The rate at which playback calls were broadcast affected owlets' call rate but did not influence their response in terms of loudness. This suggests that selection for producing loud signals may be weak in this species, as loud calls may attract predators. Moreover, given that owlets do not overlap their calls and that they communicate to nearby siblings in the silence of the night, loud signals may not be necessary to convey reliable information about food need.     

微藻在CO2生物捕集及废水生态修复领域的研究进展

温室效应、水资源短缺和能源危机是21世纪人类面临的三大挑战。微藻是一种水生植物,在CO₂减排、废水生态修复及生物能源领域已成为全球研究热点。综述了微藻在CO₂生物捕集和废水生态修复的应用研究进展。微藻生物柴油现已成为全球研发热点,但研究主要集中在某个单元的最优化设计,而对各单元之间相互作用和耦合的重要性缺乏充分认知,提出了将CO₂生物捕集、废水生态修复、生物柴油制备、藻渣替代水煤浆与煤共气化的理念,这对微藻生物过程的高效全局优化和环境综合治理具有重要意义,是未来我国发展低碳经济的有效途径,并在此基础上对微藻产业规模化的未来核心研究方向进行了展望。     

A queueing model for predicting message latency in uni-directional <Emphasis Type="Italic">k</Emphasis>-ary <Emphasis Type="Italic">n</Emphasis>-cubes with deterministic routing and non-uniform traffic

The interconnection network is one of the key architectural components in any parallel computer. The distribution of the traffic injected into the network is among the factors that greatly influences network performance. The uniform traffic pattern has been adopted in many existing network performance evaluation studies due to the tractability of the resulting analytical modelling approach. However, many real applications exhibit non-uniform traffic patterns such as hot-spot traffic. K-ary n-cubes have been the mostly widely used in the implementation of practical parallel systems. Extensive research studies have been conducted on the performance modelling and evaluation of these networks. Nonetheless, most of these studies have been confined to uniform traffic distributions and have been based on software simulation. The present paper proposes a new stochastic model to predict message latency in k-ary n-cubes with deterministic routing in the presence of hot-spot traffic. The model has been validated through simulation experiments and has shown a close agreement with simulation results.

Priority Based Messaging for Software Distributed Shared Memory

Software Distributed Shared Memory (DSM) systems can be used to provide a coherent shared address space on multicomputers and other parallel systems without support for shared memory in hardware. The coherency software automatically translates shared memory accesses to explicit messages exchanged among the nodes in the system. Many applications exhibit a good performance on such systems but it has been shown that, for some applications, performance critical messages can be delayed behind less important messages because of the enqueuing behavior in the communication libraries used in current systems. We present in this paper a new portable communication library that supports priorities to remedy this situation. We describe an implementation of the communication library and a quantitative model that is used to estimate the performance impact of priorities for a typical situation. Using the model, we show that the use of high-priority communication reduces the latency of performance critical messages substantially over a wide range of network design parameters. The latency is reduced with up to 10–25% for each delaying low priority message in the queue ahead.     

Introgression despite substantial divergence in a broadcast spawning marine invertebrate

Understanding the relationship between reproductive isolation and time since divergence is critical to our understanding of speciation. One group for which we know little about the relationship between hybridization/introgression and time since divergence is the marine broadcast spawners. Here, we investigate the distribution of closely related cryptic species of marine broadcast spawners (Type A and B Ciona intestinalis) in areas of potential sympatry to determine whether these two types occur together and if so, whether they show evidence of hybridization and introgression. Then we combine our data with other studies to investigate general patterns of reproductive isolation versus divergence in marine broadcast spawners. We found that Type A and B C. intestinalis occurred sympatrically in 2007, and that 21 individuals show evidence of introgression in sympatry (out of approximately 500). Type A and B C. intestinalis are 12.4% divergent at mitochondrial COI (mtCOI), and in comparison with other marine broadcast spawning species at mtCOI, these two types may be near the upper limit of the range of divergence values in which introgression is still possible. However, introgression at divergence levels similar to those found in Ciona does exist, prompting questions about the strength of postmating prezygotic reproductive barriers in marine broadcast spawners.     

Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation

Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical modeling.     

Effect of conspecific alarm calls in the parental behaviour of nesting southern house wrens

Alarm calls are usually used to signal the presence of a threat to members of the same species and have been studied broadly in social foraging species. We analysed the effects of conspecific alarm calls on the parental behaviour of a territorial species, the southern house wrens (Troglodytes aedon musculus), during nestling stage. We compared the parental response of adults feeding 9–11-day-old nestlings when faced with conspecific alarm calls and with a control non-sympatric species’ song broadcast from a neighbouring territory. We measured the time required by parents to return to the nest (latency) when exposed to the stimuli and estimated parent’s nest visitation rate and mean visit duration. Parents took longer to resume parental activities when we broadcast a conspecific alarm call, but they did not modify their nest visitation rate or the mean visit duration. Heterospecific songs did not seem to affect parental behaviour. Our results suggest that nesting southern house wrens can use alarm calls uttered from neighbouring territories to assess the presence of a threat and adjust their parental behaviour accordingly.     

Dynamics of Complex Systems Built as Coupled Physical,Communication and Decision Layers

This paper proposes a simple model to capture the complexity of multilayer systems where their constituent layers affect, and are affected by, each other. The physical layer is a circuit composed by a power source and resistors in parallel. Every individual agent aims at maximizing its own delivered power by adding, removing or keeping the resistors it has; the delivered power is in turn a non-linear function that depends on the other agents’ behavior, its own internal state, its global state perception, the information received from its neighbors via the communication network and a randomized selfishness. We develop an agent-based simulation to analyze the effects of number of agents (system size), communication network topology, communication errors and the minimum power gain that triggers a behavioral change on the system dynamic. Our results show that a wave-like behavior at macro-level (caused by individual changes in the decision layer) can only emerge for a specific system size. The ratio between cooperators and defectors depends on the minimum gain assumed—lower minimal gains lead to less cooperation, and vice-versa. Different communication network topologies imply different levels of power utilization and fairness at the physical layer, and a certain level of error in the communication layer induces more cooperation.     

Backpropagation algorithm adaptation parameters using learning automata

Despite of the many successful applications of backpropagation for training multi-layer neural networks, it has many drawbocks. For complex problems it may require a long time to train the networks, and it may not train at all. Long training time can be the result of the non-optimal parameters. It is not easy to choose appropriate value of the parameters for a particular problem. In this paper, by interconnection of fixed structure learning automata (FSLA) to the feedforward neural networks, we apply learning automata (LA) scheme for adjusting these parameters based on the observation of random response of neural networks. The main motivation in using learning automata as an adaptation algorithm is to use its capability of global optimization when dealing with multi-modal surface. The feasibility of proposed method is shown through simulations on three learning problems: exclusive-or, encoding problem, and digit recognition. The simulation results show that the adaptation of these parameters using this method not only increases the convergence rate of learning but it increases the likelihood of escaping from the local minima.     

Differential responses of territorial Tawny Owls Strix aluco to the hooting of neighbours and strangers

Male Tawny Owls Strix aluco have individually distinct hooting calls. A classic play-back experimental design was used to examine the differences in behavioural responses of a known owl to the hooting of a neighbour (familiar) compared with a stranger (unfamiliar) in order to test the hypothesis that such hooting variations are used in calibrating interactions between conspecifics. We tested 12 male Tawny Owls and their mates; the overall intensity of agonistic response was significantly higher when we stimulated birds using playbacks of strangers than when we did so with those of neighbours. The behaviour displayed and the type of voice used by Tawny Owls were stronger toward strange males. Moreover, on the occasions we broadcast a strange male hooting, the singing rate was higher while the latency was lower.