Network Contraction Research Articles

Ostrom’s Design Principles as Steering Principles for Contractual Governance in “Hotbeds”

The sustainability of complex contractual governance in “hotbeds” depends on steering principles. Ostrom’s design principles provide an analytical framework for robust institutions that enable collective action and cooperative behaviour. The success of Ostrom’s design principles depends on the capacity of social entities to self-govern. This article explores the potential of Ostrom’s design principles as such steering principles for contractual governance in “hotbeds”. We find that the preconditions for successful contractual networks in “hotbeds” and the empirical situations underlying Ostrom’s design principles are comparable. Building on this comparability, we apply Ostrom’s design principles to contractual networks in “hotbeds” area theoretically, and then go on to demonstrate its applied value to three situations in West Papua, Indonesia.

An Ethereum-based wind power energy network contract management solution

An Ethereum-based wind power energy network contract management solution

An Ethereum-based wind power energy network contract management solution

An Ethereum-based wind power energy network contract management solution

Contratto di rete e codatorialità: il lavoro come fattore di aggregazione e crescita delle medie, piccole e microimprese

The essay examines the spread in Italy of the phenomenon of aggregation between small and medium-sized enterprises and the importance that the co-employment relationships can have as a stimulating factor. From the perspective indicated, the data relating to the use of the network contract are discussed in the first part. In the second part, the technical methods with which co-employment relationships can be established are explored. The conclusions discuss the function that can be performed by the certification of employment contracts.

Some Results on Colored Network Contraction

Networks are pervasive in computer science and in real world applications. It is often useful to leverage distinctive node features to regroup such data in clusters, by making use of a single representative node per cluster. Such contracted graphs can help identify features of the original networks that were not visible before. As an example, we can identify contiguous nodes having the same discrete property in a social network. Contracting a graph allows a more scalable analysis of the interactions and structure of the network nodes. This paper delves into the problem of contracting possibly large colored networks into smaller and more easily manageable representatives. It also describes a simple but effective algorithm to perform this task. Extended performance plots are given for a range of graphs and results are detailed and discussed with the aim of providing useful use cases and application scenarios for the approach

The network contract: an instrument to contrast labour exploitation in agriculture. The Italian case

The network contract: an instrument to contrast labour exploitation in agriculture. The Italian case

The classical two-dimensional Heisenberg model revisited: An $SU(2)$-symmetric tensor network study

The classical Heisenberg model in two spatial dimensions constitutes one of the most paradigmatic spin models, taking an important role in statistical and condensed matter physics to understand magnetism. Still, despite its paradigmatic character and the widely accepted ban of a (continuous) spontaneous symmetry breaking, controversies remain whether the model exhibits a phase transition at finite temperature. Importantly, the model can be interpreted as a lattice discretization of the O(3)O(3) non-linear sigma model in 1+11+1 dimensions, one of the simplest quantum field theories encompassing crucial features of celebrated higher-dimensional ones (like quantum chromodynamics in 3+13+1 dimensions), namely the phenomenon of asymptotic freedom. This should also exclude finite-temperature transitions, but lattice effects might play a significant role in correcting the mainstream picture. In this work, we make use of state-of-the-art tensor network approaches, representing the classical partition function in the thermodynamic limit over a large range of temperatures, to comprehensively explore the correlation structure for Gibbs states. By implementing an SU(2)SU(2) symmetry in our two-dimensional tensor network contraction scheme, we are able to handle very large effective bond dimensions of the environment up to \chi_E^\text{eff} \sim 1500χEeff∼1500, a feature that is crucial in detecting phase transitions. With decreasing temperatures, we find a rapidly diverging correlation length, whose behaviour is apparently compatible with the two main contradictory hypotheses known in the literature, namely a finite-TT transition and asymptotic freedom, though with a slight preference for the second.

Networks and family firm performance: some evidence from Italy

ABSTRACT Using a large sample of Italian small-medium sized firms, this study analyses the effects of formal inter-firm cooperation on the performance of family firms (FFs). The study is based on the network contract (‘Contratto di rete’) implemented in Italy in 2009. The results show that networks have a positive effect on FFs’ performance, while no conclusive evidence is found for non-FFs. Additionally, the advantages for southern family firms and for small firms are considerable.

Electric Vehicle Peer-to-Peer Energy Trading Model Based on SMES and Blockchain

As the energy internet develops, it will become possible to carry out peer-to-peer energy trading among prosumers. Different from traditional commodity trading, the process of P2P electricity trading will be affected by physical constraints such as network congestion. To avoid transaction failure, a superconducting energy storage unit is introduced. First, we established the overall structure of the electric vehicle P2P energy trading, and designed the blockchain network and smart contracts; then analyze the benefits of each user entity in the system, and optimize the user matching in the transaction process; After that, we used the co-operative game algorithm to realize P2P electricity transaction pricing model. Finally, the simulation and analysis results show that the use of superconducting energy storage has effectively improved the success rate and demand consumption rate of electric vehicle P2P energy trading.

The enabling role of formalized corporate networks to drive small and medium‐sized enterprises toward sustainability

AbstractThe global economy's transition toward more sustainable development models is undoubtedly grounded on small and medium‐sized enterprises (SMEs). However, SMEs, individual entrepreneurs, and microenterprises have always encountered barriers to implementing social responsibility and sustainability concepts. The paper investigates the enabling role of formalized corporate networks to drive SMEs toward sustainable behaviors. A quantitative nonlinear regression approach is applied to a content analysis of a sample of network contracts coded. The content analysis is applied to analyze the declared objectives, the purpose of the contract, and sustainability areas. An ordered logistic regression is applied on variables related to the behavior of SMEs before entering in the contract and post‐adhesion phases. Data demonstrates how networks of SMEs can be used as enabling factors to boost sustainability among them. Specifically, the study is based on a sample of 96 formalized network contracts (FNCs), including 1486 Italian SMEs in that sustainability‐oriented networks. It offers an evidence‐based perspective on how networks of companies can play a fundamental role in the development of policies aimed at bringing small companies closer to the concept of sustainability (such as eco‐innovations, eco‐efficiency, environmental performance, and social innovations, among others) and its practical implementation. This paper has two significant strengths. The first is that it uses as a sample a set of 1486 companies, including individual entrepreneurs and microenterprises, whose data are usually difficult to collect. The second is that it demonstrates the efficacy of a contractual form that could be scalable to different countries.

Salmonid thermal habitat contraction in a hydrogeologically complex setting

AbstractBroadening our understanding of river thermal variability is of paramount importance considering the role temperature plays in aquatic ecosystem health. At the catchment scale, spatial statistical river network models (SSN) are popular for analyses of river temperature, as these are less “data hungry” than other modeling methods, and have offered invaluable insights into how thermal habitats of salmonids may change with climate warming. However, recent work has demonstrated that hydrogeological complexity can disrupt river temperature spatial autocorrelation. We test the prediction that the non‐linearity of hydrological processes inherent in a hydrogeologically complex setting, such as the Miramichi River, invalidates the SSN approach, and a Random Forest (RF) model can overcome these complexities. In all instances, RFs outperformed SSNs when predicting average (TwA) and maximum (TwM) August river temperature during 2017, and were quite robust (TwA and TwM: R2 = 0.93; RMSE = 0.6°C; R2 = 0.91; RMSE = 1.0°C, respectively). We conclude that RF models can capture the inherent non‐linearity of hydrological processes in complex hydrogeologic settings. We examined thermal habitat change for adult and 1+/2+ Atlantic salmon—AS—(Salmo salar), and all age classes of brook trout—BKT—(Salvelinus fontinalis), during August 2017, with thresholds of behavioral thermoregulation specific to the catchment. We assumed a baseline = TwA and investigated river network contraction (km) for TwM. During TwA, all habitat was suggested to be thermally suitable for 1+/2+ AS (<23°C), but 4.2% was unsuitable for adult AS and BKT of all ages (>20°C). For TwM, ~80% of the catchment was predicted to be unsuitable for adult AS and BKT. We examined two boundaries for behavorial thermoregulation in 1+/2+ AS: >23°C and >27°C. For the >23°C boundary, ~27.7% of the catchment is thermally unsuitable during TwM, and 4.9% is thermally unsuitable for the >27°C boundary. TwA in August 2017 was identical to long‐term (1970–1999) July–August TwA, as such these thermal maps will be useful for resource managers.

‘Vertical mobility’. Migrants’ trajectories within/between the western Alps and southern Italy

ABSTRACT In the past twenty years a renewed trend of migration has flown into the Italian Alps, inverting the out-migration trend. New mountain dwellers, a heterogeneous population ranging from former urban residents who chose to inhabit highlands, to asylum seekers forced into a highland life while waiting for their documents, have adjusted to the socio-ecological environment which imposes mobility. The contribution analyses in the first place the twofold mobility of the mountain dwellers, vertical in altitude and latitude, and stresses, on the side, the inequalities and exploitation at the basis of the latitudinal mobility and, on the other hand, the mobility power and capital migrants agentively play in such regime of mobility. Questioning the extent to which mobility can affect the multiple and varying migration projects, the contribution argues that juridical tools, such as the network contract within the Alpine farming system, can emplace migrants and enhance their social mobility.

Simulation of quantum computing on classical supercomputers with tensor-network edge cutting

Simulation of quantum computing on supercomputers is a significant research topic, which plays a vital role in quantum algorithm verification, error-tolerant verification and other applications. Tensor network contraction based on density matrix is an important single-amplitude simulation strategy, but it is hard to execute on the distributed computing systems currently. In this paper, we dive deep into this problem, and propose a scheme based on cutting edges of undirected graphs. This scheme cuts edges of undirected graphs with large tree width to obtain many undirected subgraphs with small tree width, and these subgraphs contracted on different computing cores. The contraction results of slave cores are summarized in the master node, which is consistent with the original tensor network contraction. Thus, we can simulate the larger scale quantum circuit than single core. Moreover, it's an NP-hard problem to find the global optimum cutting edges, and we propose a search strategy based on a heuristic algorithm to approach it. In order to verify the effectiveness of our scheme, we conduct tests based on QAOA algorithm, and it can simulate 120-qubit 3-regular QAOA algorithm on 4096-core supercomputer, which greatly exceeds the simulation scale on a single core of 100-qubit.

Efficient parallelization of tensor network contraction for simulating quantum computation

We develop an algorithmic framework for contracting tensor networks and demonstrate its power by classically simulating quantum computation of sizes previously deemed out of reach. Our main contribution, index slicing, is a method that efficiently parallelizes the contraction by breaking it down into much smaller and identically structured subtasks, which can then be executed in parallel without dependencies. We benchmark our algorithm on a class of random quantum circuits, achieving greater than 105 times acceleration over the original estimate of the simulation cost. We then demonstrate applications of the simulation framework for aiding the development of quantum algorithms and quantum error correction. As tensor networks are widely used in computational science, our simulation framework may find further applications.

Boltzmann machines as two-dimensional tensor networks

Restricted Boltzmann machines (RBM) and deep Boltzmann machines (DBM) are important models in machine learning, and recently found numerous applications in quantum many-body physics. We show that there are fundamental connections between them and tensor networks. In particular, we demonstrate that any RBM and DBM can be exactly represented as a two-dimensional tensor network. This representation gives an understanding of the expressive power of RBM and DBM using entanglement structures of the tensor networks, also provides an efficient tensor network contraction algorithm for the computing partition function of RBM and DBM. Using numerical experiments, we demonstrate that the proposed algorithm is much more accurate than the state-of-the-art machine learning methods in estimating the partition function of restricted Boltzmann machines and deep Boltzmann machines, and have potential applications in training deep Boltzmann machines for general machine learning tasks.

Contractual networks and their Impact upon consumer well-being: legal regulation and prospects

The subject of this research is the contractual (business) networks and their impact upon consumer well-being from the perspective of current legal regulation and prospects. As an example, the author chose an Italian model il contratto di rete. Attention is focused on such questions associated with the activity of contractual networks as the advantages for the companies that are part of the network with or without legal capacity; consumers; the so-called “beneficiary members”, who are not the parties to the network creation agreement, but may have benefits or costs from interaction of its members. The novelty of this research consists in determination of the advantages and disadvantages of the activity if contractual networks. It is also noted that the current trend towards creating business networks on a contractual basis (legal entity or contract) is carried out in terms of complementarity and economic autonomy for the purpose of obtaining competitive advantages by increasing productivity, innovation potential, profitability, etc., and raises issues on the liability with regards to binding results of network cooperation through creating a special form of their secondary impact upon the beneficiary members.

Cancer cell migration in collagen-hyaluronan composite extracellular matrices

Hyaluronan (HA) is a key component in the tumor microenvironment (TME) that participates in cancer growth and invasiveness. While the molecular weight (MW) dependent properties of HA can cause tumor-promoting and -repressing effects, the elevated levels of HA in the TME impedes drug delivery. The degradation of HA using hyaluronidases (HYALs), resulting in fragments of HA, is a way to overcome this, but the consequences of changes in HA molecular weight and concentration is currently unknown. Therefore, it is critical to understand the MW-dependent biological effects of HA. Here we examine the influence of HA molecular weight on biophysical properties that regulate cell migration and extracellular matrix (ECM) remodeling. In our study, we used vLMW, LMW and HMW HA at different physiologically relevant concentrations, with a particular interest in correlating the mechanical and structural properties to different cell functions. The elastic modulus, collagen network pore size and collagen fiber diameter increased with increasing HA concentration. Although the collagen network pore size increased, these pores were filled with the bulky HA molecules. Consequently, cell migration decreased with increase in HA concentration due to multiple, long-lived and unproductive protrusions, suggesting the influence of steric factors. Surprisingly, even though elastic modulus increased with HA molecular weight and concentration, gel compaction assays showed an increased degree of ECM compaction among HMW HA gels at high concentrations (2 and 4 mg mL−1 [0.2 and 0.4%]). These results were not seen in collagen gels that lacked HA, but had similar stiffness. HA appears to have the effect of decreasing migration and increasing collagen network contraction, but only at high HA molecular weight. Consequently, changes in HA molecular weight can have relatively large effects on cancer cell behavior. Statement of significanceHyaluronan (HA) is a critical component of the tumor microenvironment (TME). Overproduction of HA in the TME results in poor prognosis and collapse of blood vessels, inhibiting drug delivery. Hyaluronidases have been used to enhance drug delivery. However, they lead to low molecular weight (MW) HA, altering the mechanical and structural properties of the TME and cancer cell behavior. Understanding how HA degradation affects cancer cell behavior is critical for uncovering detrimental effects of this therapy. Very little is known about how HA MW affects cancer cell behavior in tumor-mimicking collagen-HA composite networks. Here we examine how MW and HA content in collagen-HA networks alter structural and mechanical properties to regulate cell migration and matrix remodeling in 3D TME-mimicking environments.

Monitoring and Modeling Drainage Network Contraction and Dry Down in Mediterranean Headwater Catchments.

Understanding the expansion and contraction dynamics of flowing drainage networks is important for many research fields like ecology, hydrology, and biogeochemistry. This study analyzes for the first time the network shrinking and dry down in two seasonally dry hot‐summer Mediterranean catchments (overall area 1.15 km2) using a comprehensive approach based on monitoring and modeling of the flowing network. A field campaign consisting of 19 subweekly visual surveys was carried out in the early summer of 2019. These observations were used to calibrate and validate an integrated model aimed to estimate the time evolution of the total flowing drainage network length based on meteorological drivers and define the position of the stretches with flowing water based on topographic and geological information. We used a statistical model to describe the observed variations in the total flowing length based on the accumulated difference between antecedent precipitation and evapotranspiration. The study emphasizes the relevant role of evapotranspiration in the seasonal network contraction. Then, we modeled spatial patterns of the flowing channels using an empirical approach based on topographic data, achieving satisfactory performances. Nevertheless, the performance further increased when site‐specific geological information was integrated into the model, leading to accuracies up to 92% for cell‐by‐cell comparisons. The proposed methodology, which combines meteorological, topographic, and geological information in a sequential manner, was able to accurately represent the space‐time dynamics of the flowing drainage network in the study area, proving to be an effective and flexible tool for investigating network dynamics in temporary streams.

Partnership Forum: The Role of Research in the Transformation of Veterans Affairs Community Care.

Partnership Forum: The Role of Research in the Transformation of Veterans Affairs Community Care.

Smart contract: from definition to certainty

The purpose of the present article is to gain an understanding of the opportunities and difficulties created by the introduction and development of the practice of network (smart) contracts. Our research methodology is based on a holistic set of principles and methods of scholarly analysis employed by modern legal science. It uses a dialectical method involving both general approaches (structural system method, formal logical method, analysis and synthesis of individual elements, individual features of concepts, abstraction, generalization, etc.) and particular methods (legal technical, systematic, comparative, historical, and grammatical methods, method of the unity of theory and practice, etc.). We analyze the views of lawyers and other specialists from Russia and abroad, legislative innovations in the field of digital technologies, the practice of blockchain-based smart contracts, and the main risks (whether legal, technological, operational, or criminogenic) of smart contracts for economic activities with a study of their causes. In the present-day situation, it is necessary to move from the legal definition of the smart contract and its legal and technological characteristics, advantages and disadvantages to the implementation of startups in a wide range of areas, especially business, public regulation, and social relations. Scholarly and information support for such processes will contribute to the development of industry, public administration and digital technology applications to improve the life of individual citizens and society as a whole. The introduction of smart contracts does not require the adoption of new laws or regulations. Instead, one should adapt and, possibly, modify existing legal principles at the legislative and judicial levels to pave the way for the use of smart contracts and other new technologies. The system of contract law provides a sufficient framework for regulating transactions without the introduction of any new legal categories. We propose approaches to the legal definition of the smart contract and identify a set of problems that must be solved at the legislative and technical legal levels in order to implement smart contracts effectively in different spheres of life.