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  1. Abstract The increase in the resistivity with decreasing temperature followed by a drop by more than one order of magnitude is observed on the metallic side near the zero-magnetic-field metal-insulator transition in a strongly interacting two-dimensional electron system in ultra-clean SiGe/Si/SiGe quantum wells. We find that the temperature $$T_{\text {max}}$$ T max , at which the resistivity exhibits a maximum, is close to the renormalized Fermi temperature. However, rather than increasing along with the Fermi temperature, the value $$T_{\text {max}}$$ T max decreases appreciably for spinless electrons in spin-polarizing (parallel) magnetic fields. The observed behaviour of $$T_{\text {max}}$$ T max cannot be described by existing theories. The results indicate the spin-related origin of the effect.
    Free, publicly-accessible full text available December 1, 2023
  2. During International Ocean Discovery Program (IODP) Expedition 359, Site U1471 was cored in the Maldives Inner Sea, where the sediments consist of hemipelagic carbonate drifts containing a mixture of components exported from the atolls and pelagic origin (periplatform ooze). The cores from this site provide a complete and uninterrupted record of the sedimentary and paleoceanographic changes in the Maldives Inner Sea from the Miocene through the Pleistocene. Here, we present the bulk sediment total organic carbon, total nitrogen, and calcium carbonate contents for the uppermost 21 m of the composite splice of Site U1471.
    Free, publicly-accessible full text available August 31, 2023
  3. Irfan Awan ; Muhammad Younas ; Jamal Bentahar ; Salima Benbernou (Ed.)
    Multi-site clinical trial systems face security challenges when streamlining information sharing while protecting patient privacy. In addition, patient enrollment, transparency, traceability, data integrity, and reporting in clinical trial systems are all critical aspects of maintaining data compliance. A Blockchain-based clinical trial framework has been proposed by lots of researchers and industrial companies recently, but its limitations of lack of data governance, limited confidentiality, and high communication overhead made data-sharing systems insecure and not efficient. We propose π–²π—ˆπ—π–Ύπ—‹π—‚π–Ί, a privacy-preserving smart contracts framework, to manage, share and analyze clinical trial data on fabric private chaincode (FPC). Compared to public Blockchain, fabric has fewer participants with an efficient consensus protocol. π–²π—ˆπ—π–Ύπ—‹π—‚π–Ί consists of several modules: patient consent and clinical trial approval management chaincode, secure execution for confidential data sharing, API Gateway, and decentralized data governance with adaptive threshold signature (ATS). We implemented two versions of π–²π—ˆπ—π–Ύπ—‹π—‚π–Ί with non-SGX deploys on AWS blockchain and SGX-based on a local data center. We evaluated the response time for all of the access endpoints on AWS Managed Blockchain, and demonstrated the utilization of SGX-based smart contracts for data sharing and analysis.
    Free, publicly-accessible full text available September 1, 2023
  4. Free, publicly-accessible full text available July 1, 2023
  5. Free, publicly-accessible full text available April 1, 2023
  6. Free, publicly-accessible full text available April 1, 2023
  7. Soft robot serial chain manipulators with the capability for growth, stiffness control, and discrete joints have the potential to approach the dexterity of traditional robot arms, while improving safety, lowering cost, and providing an increased workspace, with potential application in home environments. This paper presents an approach for design optimization of such robots to reach specified targets while minimizing the number of discrete joints and thus construction and actuation costs. We define a maximum number of allowable joints, as well as hardware constraints imposed by the materials and actuation available for soft growing robots, and we formulate and solve an optimization problem to output a planar robot design, i.e., the total number of potential joints and their locations along the robot body, which reaches all the desired targets, avoids known obstacles, and maximizes the workspace. We demonstrate a process to rapidly construct the resulting soft growing robot design. Finally, we use our algorithm to evaluate the ability of this design to reach new targets and demonstrate the algorithm's utility as a design tool to explore robot capabilities given various constraints and objectives.
    Free, publicly-accessible full text available May 23, 2023
  8. Vapor loss and molecular absorption make the transmission distance in sub-Terahertz bands a challenge, especially in mobile statues such as UAVs communication. The molecular absorption element is an essential part of the path loss in THz communication channel modeling that cannot be neglected. Along this direction, we investigated the UAV trajectories in sub-THz band. To maximize the secrecy rate of the UAVs communication, an optimization problem has been proposed to jointly optimize the trajectory and transmit power. To enhance the obtained average secrecy rate, MIMO communication and a cooperative UAV jammer strategy were used in this paper. Also, analysis and simulations results were presented to show the performance of UAV-ground communication at THz communications. Finally, Secrecy Outage Probability was obtained for each UAV trajectories in different flight periods to examine the performance of physical layer security added to the UAVground communication at sub-THz communication.
  9. Free, publicly-accessible full text available December 26, 2023
  10. Recently, using credit cards has been considered one of the essential things of our life due to its pros of being easy to use and flexible to pay. The critical impact of the increment of using credit cards is the occurrence of fraudulent transactions, which allow the illegal user to get money and free goods via unauthorized usage. Artificial Intelligence (AI) and Machine Learning (ML) have become effective techniques used in different applications to ensure cybersecurity. This paper proposes our fraud detection system called Man-Ensemble CCFD using an ensemble-learning model with two stages of classification and detection. Stage one, called ML-CCFD, utilizes ten machine learning (ML) algorithms to classify credit card transactions to class 1 as a fraudulent transaction or class 0 as a legitimate transaction. As a result, we compared their classification reports together, precisely precision, recall (sensitivity), and f1-score. Then, we selected the most accurate ML algorithms based on their classification performance and prediction accuracy. The second stage, known Ensemble-learning CCFD, is an ensemble model that applies the Man-Ensemble method on the most effective ML algorithms from stage one. The output of the second stage is to get the final prediction instead of using common types of ensemblemore »learning, such as voting, stacking, boosting, and others. Our framework’s results showed the effectiveness and efficiency of our fraud detection system compared to using ML algorithms individually due to their weakness issues, such as errors, overfitting, bias, prediction accuracy, and even their robustness level.« less