Miracle-dz/UniFAR-FTUs huggingface dataset:
Residual Tensor Train: A Quantum-Inspired Approach for Learning Multiple Multilinear Correlations

States of quantum many-body systems are defined in a high-dimensional Hilbert space, where rich and complex interactions among subsystems can be modeled. In machine learning, complex multiple multilinear correlations may also exist within input features. In this article, we present a quantum-inspired multilinear model, named residual tensor train (ResTT), to capture the multiple multilinear correlations of features, from low to high orders, within a single model. ResTT is able to build a robust decision boundary in a high-dimensional space for solving fitting and classification tasks. In particular, we prove that the fully connected layer and the Volterra series can be taken as special cases of ResTT. Furthermore, we derive the rule for weight initialization that stabilizes the training of ResTT based on a mean-field analysis. We prove that such a rule is much more relaxed than that of tensor train (TT), which means that ResTT can easily address the vanishing and exploding gradient problem that exists in the existing TT models. Numerical experiments demonstrate that ResTT outperforms the state-of-the-art tensor network and benchmark deep learning models on MNIST and Fashion-MNIST datasets. Moreover, ResTT achieves better performance than other statistical methods on two practical examples with limited data, which are known to have complex feature interactions.
Comparative Evaluation of Different Multi-Agent Reinforcement Learning Mechanisms in Condenser Water System Control

Model-free reinforcement learning (RL) techniques are currently drawing attention in the control of heating, ventilation, and air-conditioning (HVAC) systems due to their minor pre-conditions and fast online optimization. The simultaneous optimal control of multiple HVAC appliances is a high-dimensional optimization problem, which single-agent RL schemes can barely handle. Hence, it is necessary to investigate how to address high-dimensional control problems with multiple agents. To realize this, different multi-agent reinforcement learning (MARL) mechanisms are available. This study intends to compare and evaluate three MARL mechanisms: Division, Multiplication, and Interaction. For comparison, quantitative simulations are conducted based on a virtual environment established using measured data of a real condenser water system. The system operation simulation results indicate that (1) Multiplication is not effective for high-dimensional RL-based control problems in HVAC systems due to its low learning speed and high training cost; (2) the performance of Division is close to that of the Interaction mechanism during the initial stage, while Division’s neglect of agent mutual inference limits its performance upper bound; (3) compared to the other two, Interaction is more suitable for multi-equipment HVAC control problems given its performance in both short-term (10% annual energy conservation compared to baseline) and long-term scenarios (over 11% energy conservation).
Cost-Aware Placement Optimization of Edge Servers for IoT Services in Wireless Metropolitan Area Networks

Edge computing migrates cloud computing capacity to the edge of the network to reduce latency caused by congestion and long propagation distance of the core network. And the Internet of things (IoT) service requests with large data traffic submitted by users need to be processed quickly by corresponding edge servers. The closer the edge computing resources are to the user network access point, the better the user experience can be improved. On the other hand, the closer the edge server is to users, the fewer users will access simultaneously, and the utilization efficiency of nodes will be reduced. The capital investment cost is limited for edge resource providers, so the deployment of edge servers needs to consider the trade-off between user experience and capital investment cost. In our study, for edge server deployment problems, we summarize three critical issues: edge location, user association, and capacity at edge locations through the research and analysis of edge resource allocation in a real edge computing environment. For these issues, this study considers the user distribution density (load density), determines a reasonable deployment location of edge servers, and deploys an appropriate number of edge computing nodes in this location to improve resource utilization and minimize the deployment cost of edge servers. Based on the objective minimization function of construction cost and total access delay cost, we formulate the edge server placement as a mixed-integer nonlinear programming problem (MINP) and then propose an edge server deployment optimization algorithm to seek the optimal solution (named Benders_SD). Extensive simulations and comparisons with the other three existing deployment methods show that our proposed method achieved an intended performance. It not only meets the low latency requirements of users but also reduces the deployment cost.
Sustainable Operations in IoT by Combining Spatiotemporal Data Correlation With Silent Symbol Based Communication Strategy

We exploit spatiotemporal correlation in sensor data and redundant binary number system based representation for encoding data, where the number of 0 s in the encoded data is significantly larger than the other symbols. Next, using a hybrid FSK-ASK modulation/demodulation technique with a non-coherent receiver, we have designed an energy-efficient communication scheme where the transmitter is kept silent during the transmission of the dominant symbol in the encoded messages. In contrast to the conventional techniques of data reduction and aggregation which exploit temporal and spatial correlation, our technique does not require dropping any data value while generating significantly more transmission energy savings. Our approach is particularly useful for sustainable energy-efficient communications in IoT applications like environment monitoring, agriculture, etc., where dropping any data value may not be desirable. Simulation results on different real-life sensor data sets using several popular low-cost, low data-rate transceivers like the RFM TR 1,000 show about <inline-formula><tex-math notation="LaTeX">$90.06\% - 90.86\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>90</mml:mn><mml:mo>. </mml:mo><mml:mn>06</mml:mn><mml:mo>%</mml:mo><mml:mo>-</mml:mo><mml:mn>90</mml:mn><mml:mo>. </mml:mo><mml:mn>86</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="sinha-ieq1-3194506.gif"/></alternatives></inline-formula> savings in transmitter energy expenditure over conventional BFSK, and <inline-formula><tex-math notation="LaTeX">$15\% - 20\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>15</mml:mn><mml:mo>%</mml:mo><mml:mo>-</mml:mo><mml:mn>20</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="sinha-ieq2-3194506.gif"/></alternatives></inline-formula> savings at receiver. Simulation results also demonstrate a proportionately reduced <inline-formula><tex-math notation="LaTeX">$CO_{2}$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>C</mml:mi><mml:msub><mml:mi>O</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:math><inline-graphic xlink:href="sinha-ieq3-3194506.gif"/></alternatives></inline-formula> footprint generation of <inline-formula><tex-math notation="LaTeX">$0.12 - 0.14$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>0</mml:mn><mml:mo>. </mml:mo><mml:mn>12</mml:mn><mml:mo>-</mml:mo><mml:mn>0</mml:mn><mml:mo>. </mml:mo><mml:mn>14</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="sinha-ieq4-3194506.gif"/></alternatives></inline-formula> mg/day only, when using the RFM TR 1,000 radio. These savings are considerably higher than those generated with the existing techniques.
Experimental Measurements and Numerical Simulation of H2S Generation during Cyclic Steam Stimulation Process of Offshore Heavy Oil from Bohai Bay, China

Cyclic steam stimulation (CSS) is successfully applied to increase heavy oil recovery in heavy oil reservoirs in Bohai Bay, China. However, during the CSS processes, hydrogen sulfide (H2S) was detected in some heavy oil reservoirs. The existing literature mainly focused on the H2S generation of onshore heavy oil. There is no concrete experimental data available, especially about the level of H2S generation during CSS of offshore heavy oil. In addition, there is still a lack of effective reaction kinetic models and numerical simulation methods to simulate H2S generation during the CSS of offshore heavy oil. Therefore, this paper presents a case study from Bohai Bay, China. First, the laboratory aquathermolysis tests were conducted to simulate the gases that are produced during the CSS processes of heavy oil. The effects of the reaction temperature and time on the H2S generation were studied. Then, a one-dimensional CSS experiment was performed to predict H2S generation under reservoir conditions. A kinetic model for the prediction of H2S generation during the CSS of heavy oil was presented. The developed model was calibrated with the experimental data of the one-dimensional CSS experiment at a temperature of 300 °C. Finally, a reservoir model was developed to predict H2S generation and investigate the effects of soaking time, steam quality, and steam injection volume on H2S generation during CSS processes. The results show that the H2S concentration increased from 0.77 ppm in the first cycle to 1.94 ppm in the eighth cycle during the one-dimensional CSS experiment. The average absolute error between the measured and simulated H2S production was 12.46%, indicating that the developed model can accurately predict H2S production. The H2S production increase with soaking time, steam quality, and steam injection volume due to the strengthened aquathermolysis reaction. Based on the reservoir simulation, the H2S production was predicted in the range of 228 m3 to 2895 m3 within the parameters of this study.
Cloud-cloud collision which triggered formation of the super star cluster RCW38

We have found two molecular clouds having velocities of 2 km s$^{-1}$ and 14 km s$^{-1}$ toward the super star cluster RCW38 by observations of CO ($J=$1--0 and 3--2) transitions. The two clouds are likely physically associated with the cluster as verified by the high intensity ratio of the $J$=3--2 emission to the $J$=1--0 emission, the bridging feature connecting the two clouds in velocity and the morphological correspondence with the infrared dust emission. Since the total mass of the clouds and the cluster is too small to gravitationally bind the velocity, we suggest that a collision happened by chance between the two clouds. We present a scenario that the collision triggered formation of the $\sim$20 candidate O stars which are localized, within $\sim$0.5 pc of the cluster center in the 2 km s$^{-1}$ cloud, just toward the northern tip of the 14 km s$^{-1}$ cloud. The other member low-mass stars are likely pre-existent prior to the collision since they are distributed outside the 14 km s$^{-1}$ cloud. The formation timescale of the O stars is estimated to be $\sim3\times10^4$ yrs ($=\sim$0.5 pc/16 km s$^{-1}$), implying a mass accretion rate $\sim10^{-3}$ $M_\odot$ yr$^{-1}$ for a 20 $M_\odot$ star. This is the third super star cluster alongside of Westerlund 2 and NGC3603 where cloud-cloud collision triggered the cluster formation among the few youngest super star clusters that are associated with dusty nebulae.
Stochastic Dominance Efficiency Tests under Diversification

This paper focuses on Stochastic Dominance (SD) efficiency in a finite empirical panel data. We analytically characterize the sets of unsorted time series that dominate a given evaluated distribution by the First, Second, and Third order SD. Using these insights, we develop simple Linear Programming and 0-1 Mixed Integer Linear Programming tests of SD efficiency. The advantage to the earlier efficiency tests is that the proposed approach explicitly accounts for diversification. Allowing for diversification can both improve the power of the empirical SD tests, and enable SD based portfolio optimization. A simple numerical example illustrates the SD efficiency tests. Discussion on the application potential and the future research directions concludes.
Recommendations for Early Phases of Engaging Communities in Climate Change Adaptation

Communities across the globe have begun planning for and adapting to climate change. Cooperative Extension Service professionals are in a unique position to use the resources available to them to facilitate climate change adaptation in their communities. Adaptation planning is a local activity that must be context specific. However, general recommendations can be made to help facilitate the planning process. In this study, we conducted a systematic review of research about climate change adaptation in communities to explore ideas that contribute to successful adaptation-planning communication. We identified and reviewed 50 peer-reviewed articles that described various outreach efforts to engage communities in planning for adaptation across a range of contexts and settings. Five themes emerged addressing how to facilitate early stages of the climate change adaptation process: establishing positive initial engagement, incorporating participatory methods, using tools to facilitate understanding, addressing trust and uncertainty, and maximizing limited time. Based on the review and emergent themes, we offer practical recommendations for educators and Cooperative Extension Service professionals as they engage communities in climate change adaptation.
Deployment of Source Address Validation by Network Operators: A Randomized Control Trial

IP spoofing, sending IP packets with a false source IP address, continues to be a primary attack vector for large-scale Denial of Service attacks. To combat spoofing, various interventions have been tried to increase the adoption of source address validation (SAV) among network operators. How can SAV deployment be increased? In this work, we conduct the first randomized control trial to measure the effectiveness of various notification mechanisms on SAV deployment. We include new treatments using nudges and channels, previously untested in notification experiments. Our design reveals a painful reality that contrasts with earlier observational studies: none of the notification treatments significantly improved SAV deployment compared to the control group. We explore the reasons for these findings and report on a survey among operators to identify ways forward. A portion of the operators indicate that they do plan to deploy SAV and ask for better notification mechanisms, training, and support materials for SAV implementation.
Probabilistic Flooding Performance Analysis Exploiting Graph Spectra Properties

Probabilistic flooding is an efficient information dissemination policy capable of spreading information to the network nodes by sending information messages according to a fixed forwarding probability in a per-hop manner starting from an initiator node. It is a suitable approach, especially in topologies where the number of information messages sent under traditional approaches is significantly increased. The analysis presented in this paper considers graph spectra properties such as the largest eigenvalue <inline-formula> <tex-math notation="LaTeX">$\lambda _{1}$ </tex-math></inline-formula> of the adjacency matrix, and the eigenvector centrality. Both are analytically investigated and <inline-formula> <tex-math notation="LaTeX">$\frac {4}{\lambda _{1}}$ </tex-math></inline-formula> is derived as a lower bound of the forwarding probability that allows for global coverage, i.e., all network nodes receive the information message, under certain conditions also investigated here (e.g., the condition of the binomial approximation). It is shown that for any value of the forwarding probability equal to or larger than <inline-formula> <tex-math notation="LaTeX">$\frac {4}{\lambda _{1}}$ </tex-math></inline-formula>: (i) coverage is proportional to the initiator node’s eigenvector centrality; (ii) the probability a node receives the information message is proportional to the node’s eigenvector centrality; (iii) termination time decreases as the initiator node’s eigenvector centrality increases. If knowledge of <inline-formula> <tex-math notation="LaTeX">$\lambda _{1}$ </tex-math></inline-formula> is not available, then the average node degree <inline-formula> <tex-math notation="LaTeX">$\bar {d}$ </tex-math></inline-formula> can be used for ensuring global coverage. If knowledge of both <inline-formula> <tex-math notation="LaTeX">$\lambda _{1}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\bar {d}$ </tex-math></inline-formula> is not available, a dissemination policy is proposed that forwards messages to <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> (randomly selected) neighbor nodes. It is analytically shown that any value of <inline-formula> <tex-math notation="LaTeX">$m \geq 4$ </tex-math></inline-formula> allows for global coverage. Simulation results demonstrate the effectiveness of the considered analytical approach and the introduced policy.
Planck’s constant measurement by Landauer quantization for student laboratories

A simple experimental setup for measuring Planck’s constant, using Landauer quantization of the conductance between touching gold wires, is described. It consists of two gold wires with thickness of 500 &mgr; m ? > and 1.5 cm ? > length, and an operational amplifier. The setup costs less than $30 and can be realized in every teaching laboratory in two weeks. The use of an oscilloscope is required.
Joint Transceiver and Intelligent Reflecting Surface Design for mmWave Massive MIMO Systems

This article aims to maximize the spectral efficiency of an intelligent reflecting surface (IRS)-assisted hybrid millimeter-wave massive multiple-input–multiple-output system by jointly optimizing the hybrid precoding at the base station, hybrid combining at the user equipment, and reflecting beamforming at the IRS, where the reflecting beamforming and analog precoding/combining are implemented with finite-resolution phase shifters. This joint design problem can be decoupled into reflecting beamforming and hybrid precoding/combining design problems. However, such a decoupled approach experiences difficulties in solving the reflecting beamforming design problem. A known solution further reformulates the reflecting beamforming design problem into a more tractable problem addressed by a Riemannian manifold optimization (RMO)-based algorithm. However, the application of the RMO-based algorithm to solve the reformulated problem may lead to performance degradation given that the reformulated problem differs from the original one. Moreover, the RMO-based algorithm is tailored for the IRS with infinite-resolution phase shifters rather than practical finite-resolution phase shifters. Furthermore, the complexity of the RMO-based algorithm remains high. Therefore, we propose two coordinate descent method-based algorithms to tackle these issues. Simulation results demonstrate the effectiveness of the proposed algorithms compared with the state-of-the-art RMO-based algorithm.
Magnetic Properties of Uranium Based Ferromagnetic Superconductors

Ferromagnetism and superconductivity have long been thought to be mutually exclusive. Recently however it was found that the compounds UGe2, URhGe and UIr belong to a class of materials in which ferromagnetisme and superconductivity appear simultaneously. One characteristic property of these compounds is the existence of strong correlations between the magnetic moments of the uranium ions and the conduction electrons. These correlations lead to unusual magnetic properties at low temperatures. By applying external pressure the magnetic correlations can be varied. The fact that superconductivity in these materials is found only for those pressures, at which the magnetic correlations are strongest, indicates that the effective attracting force between the conduction electrons responsible for superconductivity has a magnetic origin. In this research the magnetic correlations of the ferromagnetic superconductors are investigated in order to better understand the unusual coexistence of ferromagnetism and superconductivity. Besides the dilatometry, specific heat, magnetization, and three-dimensional neutron depolarization techniques, the muon spin relaxation (muSR) technique is frequently used in the study of de magnetic properties of the ferromagnetic superconductors. The muon experiments indicate that unusual excitations exist in these materials which are possibly responsible for the superconductivity.
Effects of intra-operative infusion of lidocaine on postoperative pain and quality of recovery in patients undergoing gynecological laparoscopic surgery: A randomized controlled trial

Background and Aims: Early recovery is desirable after day care surgery. Intravenous lidocaine has anti-inflammatory, anti-hyperalgesic, and analgesic effects and by reducing postoperative pain, nausea, vomiting, and duration of postoperative ileus and hospital stay, might be a useful adjuvant to improve recovery after gynecological laparoscopic surgery. Material and Methods: Fifty female patients, aged 18–55 years, undergoing gynecological laparoscopic surgery were randomly allocated to two groups. In Group L, patients received intravenous lidocaine 1.5 mg/kg at induction of anesthesia followed by infusion of 2 mg/kg/hour until the completion of surgery and in Group NS, patients received normal saline infusion. The Global QoR-40 score at 24 hours, pain score in PACU and at 24 hours, nausea/vomiting, PADSS score in PACU and analgesic consumption over 24 hours were assessed and data were analyzed using SPSS version 17 software. Results: Demographic data were comparable in both groups. The mean Global QoR-40 score in Group L was 197.30 ± 2.3 versus 178.74 ± 6.02 in Group NS (P < 0.001). The mean time to attain PADSS ≥9 was 50 min shorter in Group L than in Group NS (P < 0.001). Nausea, vomiting, and anti-emetic requirement were also significantly reduced in Group L as compared to Group NS (P = 0.005) as was the mean pain score over 24 h (P < 0.001) and the total analgesic consumption over the first 24 h after surgery (P < 0.005). Conclusion: Intraoperative intravenous lidocaine infusion resulted in an improved overall Quality of Recovery in patients undergoing ambulatory gynecological surgery.