Miracle-dz/UniFAR-FTUs huggingface dataset:
Operational and Infrastructure Readiness for Semi-Automated Truck Platoons on Rural Roads

On highways, truck platooning may reduce fuel consumption, improve road safety and streamline trucking operations. However, most roads worldwide are two-way, two-lane rural roads, i.e., conditions for which truck platooning should be tested to explore the extent of those advantages. This paper reports findings from a field study undertaken in Northern Norway, testing a platoon of three semi-automated trucks on rural roads with tunnels, mountain passes and adverse geometries. Fleet management and distance data, videos, interviews and conversations between participants were used to assess whether platooning was feasible on such roads. The platooning system was used without interventions through most road conditions, and worked well on flat and wide roads with 90 km/h speed limits. However, it struggled in sharp horizontal curves, where the following trucks would speed up before regaining connection to their preceding truck and then brake abruptly to regain the prescribed distance. Moreover, steep uphills were problematic due to inconsistent gear shifting between the trucks. Seemingly, no fuel savings were achieved, due to excessive following distances and suboptimal speed profiles on crest curves. To obtain further insights into the benefits of truck platooning on rural roads, we suggest redoing the field study with V2V-communication, allowing for shorter following distances, and also performing a manual-driven baseline first.
Fuel and Energy Complex of Kazakhstan: Geological and Economic Assessment of Enterprises in the Context of Digital Transformation

The relevance of the study is dictated by the growing role of the fuel and energy complex of developing countries in the decarbonization of the economy. The article discusses the digital transformation of mining enterprises in Kazakhstan, taking into account the transition to CRIRSCO international standards and growing competition in the global mineral market. The purpose of the study is to assess the current level of digitalization of the mining industry in Kazakhstan and to deepen the methodological apparatus of the geological and economic assessment of the enterprise based on the factual base of deposits. The role of the transformation of the mining sector in achieving the sustainability of the poorly diversified economy of Kazakhstan is shown. The importance of digitalization of the industry to complete the transition to CRIRSCO international standards and improve the assessment of the digital provision of enterprises in order to optimize their financial and economic policies is argued. It has been established that, at present, most of the enterprises in the investment-attractive mining sector have a low potential for the transition to a new technological paradigm. A methodological approach to the geological and economic assessment of these enterprises has been developed. To maintain high standards of management transparency through the digitalization of key business processes, along with well-known practices of economic analysis, the IDEF1 methodology was used. In order to expand the software ecosystem, the formats of electronic geological and economic databases are integrated into the digital infrastructure of the enterprise. It is substantiated that the introduction of high technologies in the mining industry requires institutional changes and coordinated interaction between the state, business, and universities as equal partners.
Stakeholders’ experiences of ethical challenges in cluster randomized trials in a limited resource setting: a qualitative analysis

Although the use of the cluster randomized trial (CRT) design to evaluate vaccines, public health interventions or health systems is increasing, the ethical issues posed by the design are not adequately addressed, especially in low- and middle-income country settings (LMICs). To help reveal ethical challenges, qualitative interviews were conducted with key stakeholders experienced in designing and conducting two selected CRTs in Malawi. The 18 interviewed stakeholders included investigators, clinicians, nurses, data management personnel and community workers who were invited to share their experiences related to implementation of CRTs. Data analysis revealed five major themes with ethical implications: (1) The moral obligation for health care providers to participate in health research and its compensation; (2) Suboptimal care services compromising the integrity of CRT; (3) Ensuring scientific validity and withholding care service; (4) Obtaining valid consent and permission for waiver of consent; and (5) Inadequate risk assessment for trial participation. Understanding key ethical issues posed by CRTs in Malawi could improve ethical review and research oversight of this particular study design.
Computation of Core Losses in Electrical Steel Laminations With Impacts of Normal Flux and PWM Switching Considered

Normal flux (perpendicular to the lamination plane) and pulsewidth modulation (PWM) can have significant impacts on the losses of steel laminations, e.g., in converter-fed synchronous machines or transformers. This article proposes a model for computing the losses of steel laminations with the impacts of normal flux and PWM switching considered. The total core losses are computed by modifying the core losses of a reference sinusoidal case with the global statistics about supply voltage. A dedicated test setup was developed to validate the loss model. The measurement shows that the proposed model can compute core losses with acceptable accuracy, reasonable computing time, and moderate demand for computing resources.
The State-of-the-Art in Ship Detection in Synthetic Aperture Radar Imagery

Abstract : This report is a review of the publicly available literature on algorithms for detecting ships in Synthetic Aperture Radar (SAR) imagery, with the aim of recommending algorithms for inclusion in the Analysts' Detection Support System (ADSS). The ADSS is a software system being developed at DSTO for the automatic detection of targets in SAR imagery. We outline the motivations, theory and justifications of the various approaches so that educated comparisons and evaluations can be made. Most current research on ship detection is based on detecting the ship itself rather than its wake. Detection of ship wakes is not addressed in any depth. Ship detection systems generally consist of several stages: land masking; preprocessing; prescreening; and discrimination. We consider each of these stages in turn and discuss the various algorithms which have been used. A basic system for low to medium resolution single channel SAR imagery is recommended and suggestions for improvements and alternatives are made.
Divergent Survival Outcomes Associated with Elevated Branched-Chain Amino Acid Levels among Older Adults with or without Hypertension and Diabetes: A Validated, Prospective, Longitudinal Follow-Up Study

Branched-chain amino acids are critical metabolic intermediates that can indicate increased risk of cardiometabolic disease when levels are elevated or, alternatively, suggest sufficient mitochondrial energy metabolism and reserve in old age. The interpretation of BCAA levels can be context-dependent, and it remains unclear whether abnormal levels can inform prognosis. This prospective longitudinal study aimed to determine the interrelationship between mortality hazard and fasting serum BCAA levels among older men and women aged ≥65 years with or without hypertension and diabetes mellitus. At baseline (0Y), fasting serum BCAA concentration in 2997 community-living older men and women were measured. Approximately 14 years later (14Y), 860 study participants returned for repeat measurements. Deaths were analysed and classified into cardiovascular and non-cardiovascular causes using International Classification of Diseases codes. Survival analysis and multivariable Cox regression were performed. During a median follow-up of 17Y, 971 (78.6%) non-cardiovascular and 263 (21.4%) cardiovascular deaths occurred among 1235 (41.2%) deceased (median age, 85.8 years [IQR 81.7–89.7]). From 0Y to 14Y, BCAA levels declined in both sexes, whereas serum creatinine concentration increased (both p < 0.0001). In older adults without hypertension or diabetes mellitus, the relationship between mortality hazard and BCAA level was linear and above-median BCAA levels were associated with improved survival, whereas in the presence of cardiometabolic disease the relationship was U-shaped. Overall, adjusted Cox regression determined that each 10% increment in BCAA concentration was associated with a 7% (p = 0.0002) and 16% (p = 0.0057) reduction in mortality hazard estimated at 0Y and 14Y, respectively. Our findings suggested that abnormally high or low (dyshomeostatic) BCAA levels among older adults with hypertension and/or diabetes mellitus were associated with increased mortality, whereas in those with neither disease, increased BCAA levels was associated with improved survival, particularly in the oldest-old.
Towards High-Power and -Efficiency ∼2.8 μm Lasing: Lightly-Erbium-Doped ZrF Fiber Laser Pumped at ∼1.7 μm

In this article, we demonstrate great potential of lightly-erbium(Er<sup>3+</sup>)-doped ZrF<sub>4</sub> fiber in efficient power scaling at ∼2.8 μm, when excited at ∼1.7 μm. Core-pumped by a random Raman fiber laser at 1.69 μm, the 1.5 mol. % Er<sup>3+</sup>-doped ZrF<sub>4</sub> fiber in a F-P cavity has experimentally yielded an output power of >6 W at 2.783 μm with a slope efficiency of up to 58.4% (with respect to the absorbed pump), close to its Stokes limit of 60.7% (1.69/2.783). To our knowledge, this is the highest efficiency of Er<sup>3+</sup>-doped ZrF<sub>4</sub> fiber lasers in the mid-infrared. Further power scaling is only limited by the current pump power. Based on the validated numerical model, the dominant role of the excited state absorption (ESA) process (i.e., <inline-formula><tex-math notation="LaTeX">$^4{\mathrm{I}}_{13/2}{ \to }^4{\mathrm{I}}_{9/2}$</tex-math></inline-formula>) in exciting efficient ∼2.8 μm laser has been highlighted, and the resonant ground state absorption process (i.e., <inline-formula><tex-math notation="LaTeX">$^4{\mathrm{I}}_{15/2}{ \to }^4{\mathrm{I}}_{13/2}$</tex-math></inline-formula>) is also essential. The simulation results indicate that the pump wavelength closer to the ESA peak can yield a higher slope efficiency. In addition, heat load analyses via numerical modeling reveals that the <inline-formula><tex-math notation="LaTeX">$^4{\mathrm{I}}_{9/2}{ \to }^4{\mathrm{I}}_{11/2}$</tex-math></inline-formula> multiphonon relaxation is the main heat source of the system. By taking fiber optical damage limit into account simultaneously, a high-power lightly-Er<sup>3+</sup>-doped ZrF<sub>4</sub> fiber laser arrangement has been proposed, which theoretically enables 100-W-class output under a slope efficiency of >50% and a relatively low heat load.
Experiential Learning Student Surveys: Indirect Measures of Student Growth

Kolb’s experiential learning cycle theorizes the process of learning through a hands-on experience. Although the Association of American Colleges and Universities (AAC&U) Valid Assessment of Learning in Undergraduate Education (VALUE) rubrics provide a direct measure of the qualities of this learning cycle, few indirect measures have been developed to accompany the rubrics and the learning cycle. This paper aims to demonstrate construct validity and measurement invariance of pre-experience and post-experience surveys intended to measure undergraduate students’ perception of learning in an experiential learning context. Construct validity and longitudinal measurement invariance were examined through a confirmatory factor analysis. Findings suggest the instruments provide an adequate measure of students’ perceptions of learning. In addition, partial scalar measurement invariance was achieved supporting the ability to compare growth between surveys. The survey instruments serve as strong indirect measures of Experience Learning Student Learning Outcomes. These indirect measures, coupled with direct measures, provide evidence of learning through hands-on experiences, however evidence of growth is less robust.
Extending and Intensifying the FIA Inventory of Down Forest Fuels: Boundary Waters Canoe Area and Pictured Rocks National Lakeshore

The sampling design for the Forest Inventory and Analysis (FIA) program of the U.S. Department of Agriculture Forest Service allows intensification of fuel inventory sampling in areas of ? special interest? and implementation of fuel sampling protocol by non-FIA personnel. The objective of this study is to evaluate the contribution of sampling intensification/extension toward furthering multiscale fire science investigations in two case study areas. In the Pictured Rocks National Lakeshore in Michigan, adoption of FIA? s fuel sampling protocols increased inventory efficiencies while linking local fuel estimates to the system of FIA plots. In Minnesota's Boundary Waters Canoe Area, results indicate that 100- and 1,000-hr fuel loadings in wilderness blowdown areas may be twice those of the surrounding forest ecosystem. Both case studies illustrate the potential for the FIA program to provide estimates of fuels and facilitate local fire science initiatives and fuel inventories.
u-Help: Supporting Helpful Communities with Information Technology

When people need help with day-to-day tasks they turn to family, friends or neighbours to help them out. Finding someone to help out can be a stressful waste of time. Despite an increasingly networked world, technology falls short in supporting such daily irritations. u-Help provides a platform for building a community of helpful people and supports them in finding help for day-to-day tasks. It relies on a trio of techniques that allow a requester and volunteer to find one another easily, and build up a community around such provision of services. First, we use an ontology to distinguish between the various tasks that u-Help allows people to provide. Second, a computational trust model is used to aggregate feedback from community members and allows people to discover who are good or bad at performing the various tasks. Last, a flooding algorithm, similar to the popular Gnutella algorithm, quickly disseminates requests for help through the community. This paper describes these three techniques in detail. This work is implemented as an iPhone application that we also describe in this paper.
Efficient Compressed Sensing Reconstruction Algorithm for Nonnegative Vectors in Wireless Data Transmission

With the rapid development of 5G communication and wireless Internet of Things technology, the application of intelligent wearable devices based on wireless data transmission technology is becoming more and more popular. However, due to the bandwidth of wireless data transmission nodes and the power consumption of the device system, the use time and data storage of wearable devices are severely restricted. The compressed sensing (CS) technology has become an effective method to tackle this problem. CS technology includes data compressive sensing at the transmission end and data reconstruction at the receiving end. In this paper, we consider the reconstruction of nonnegative sparse vectors, an important problem in the area of CS for wireless data transmission. It is known that the interval-passing (IP) algorithm is a low-complexity message-passing type method for the problem. However, the reconstruction performance of the IP algorithm is inferior to that of the other state-of-the-art CS reconstruction algorithms such as the orthogonal matching pursuit (OMP) algorithm. In order to address the problem, we propose a two-stage reconstruction algorithm in this paper. The proposed algorithm applies the IP algorithm for the first stage of reconstruction. If the reconstruction fails, the OMP algorithm is then used on the basis of the results in the first stage. The proposed algorithm is evaluated and compared with other state-of-the-art algorithms by the probability of perfect reconstruction under the given sparsity order value. Simulation results suggest that the proposed two-stage algorithm can greatly improve the reconstruction performance of the IP algorithm and can even outperform the OMP algorithm. In addition, the low-complexity advantages of the IP algorithm are maintained in the proposed algorithm.
Finite-sample Guarantees for Nash Q-learning with Linear Function Approximation

Lemma A.1 (Concentration bound for self-normalized processes – Lemma D.4 in (Jin et al., 2020)). Let {Fτ}τ=0 be a filtration. Let {xτ}τ=1 be a stochastic process on S such that xτ ∈ Fτ , and let {φτ}τ=1 be an R-valued stochastic process such that φτ ∈ Fτ−1 and ∥φτ∥ ≤ 1. Let G be a function class of real-valued functions such that supx∈S |g(x)| ≤ H for any g ∈ G, and with ε-covering number Nε with respect to the distance dist(g, g′) = supx∈S |g(x) − g′(x)|. Let ΛA = λId + ∑A τ=1 φτφ ⊤ τ . Then for every A ∈ Z≥1, every g ∈ G, and any δ ∈ (0, 1], we have that with probability at least 1− δ, ∥∥∥∥ A ∑
Numerical Simulation of Multiphase Flow in Nanoporous Organic Matter With Application to Coal and Gas Shale Systems

Fluid flow in nanoscale organic pores is known to be affected by fluid transport mechanisms and properties within confined pore space. The flow of gas and water shows notably different characteristics compared with conventional continuum modeling approach. A pore network flow model is developed and implemented in this work. A 3‐D organic pore network model is constructed from 3‐D image that is reconstructed from 2‐D shale SEM image of organic‐rich sample. The 3‐D pore network model is assumed to be gas‐wet and to contain initially gas‐filled pores only, and the flow model is concerned with drainage process. Gas flow considers a full range of gas transport mechanisms, including viscous flow, Knudsen diffusion, surface diffusion, ad/desorption, and gas PVT and viscosity using a modified van der Waals' EoS and a correlation for natural gas, respectively. The influences of slip length, contact angle, and gas adsorption layer on water flow are considered. Surface tension considers the pore size and temperature effects. Invasion percolation is applied to calculate gas‐water relative permeability. The results indicate that the influences of pore pressure and temperature on water phase relative permeabilities are negligible while gas phase relative permeabilities are relatively larger in higher temperatures and lower pore pressures. Gas phase relative permeability increases while water phase relative permeability decreases with the shrinkage of pore size. This can be attributed to the fact that gas adsorption layer decreases the effective flow area of the water phase and surface diffusion capacity for adsorbed gas is enhanced in small pore size.
Sex- and age-dependent contribution of System xc– to cognitive, sensory, and social behaviors revealed by comprehensive behavioral analyses of System xc– null mice

Background System xc– (Sxc–) is an important heteromeric amino acid cystine/glutamate exchanger that plays a pivotal role in the CNS by importing cystine into cells while exporting glutamate. Although certain behaviors have been identified as altered in Sxc– null mutant mice, our understanding of the comprehensive impact of Sxc– on behavior remains incomplete. Methods To address this gap, we compared motor, sensory and social behaviors of male and female mice in mice null for Sxc– (SLC7A11sut/sut) with wildtype littermates (SLC7A11+/+) in a comprehensive and systematic manner to determine effects of genotype, sex, age, and their potential interactions. Results Motor performance was not affected by loss of Sxc– in both males and females, although it was impacted negatively by age. Motor learning was specifically disrupted in female mice lacking Sxc– at both 2 and 6 months of age. Further, female SLC7A11sut/sut mice at both ages exhibited impaired sociability, but normal spatial and recognition memory, as well as sensorimotor gating. Finally, pronounced open-space anxiety was displayed by female SLC7A11sut/sut when they were young. In contrast, young SLC7A11sut/sut male mice demonstrated normal sociability, delayed spatial learning, increased open-space anxiety and heightened sensitivity to noise. As they aged, anxiety and noise sensitivity abated but hyperactivity emerged. Discussion We find that the behavioral phenotypes of female SLC7A11sut/sut are similar to those observed in mouse models of autism spectrum disorder, while behaviors of male SLC7A11sut/sut resemble those seen in mouse models of attention deficit hyperactivity disorder. These results underscore the need for further investigation of SLC7A11 in neurodevelopment. By expanding our understanding of the potential involvement of Sxc–, we may gain additional insights into the mechanisms underlying complex neurodevelopmental conditions.
Optimizing Performance for Coalition Structure Generation Problems ’ IDP Algorithm

The Coalition Structure Generation (CSG) problem is well-known in the area of Multi-Agent Systems. Its goal is establishing coalitions between agents while maximizing the global welfare. Between the existing different algorithms designed to solve the CSG problem, DP and IDP are the ones with smaller temporal complexity. After analyzing the performance of the DP and IDP algorithms, we identify which is the most frequent operation and propose an optimized method. Then, we analyze the memory access pattern and find that its irregular behavior represents a potential performance bottleneck. In addition, we study and implement a method for dividing the work in different threads. We show that selecting the best algorithmic options can improve performance by 10x or more. Furthermore, the execution in a dual-socket, six-core processor computer may increase performance by an additional 5x-6x.
A Bi-Level Network-Wide Cooperative Driving Approach Including Deep Reinforcement Learning-Based Routing

Cooperative driving of connected and automated vehicles (CAVs) has attracted extensive attention and researchers have proposed various approaches. However, existing approaches are limited to small-scale isolated scenarios and gaps remain in network-wide cooperative driving, especially in routing. In this article, we decompose the network-level cooperative driving problem into two dominant sub-problems and accordingly propose a bi-level network-wide cooperative driving approach. The dynamic routing problem is considered in the upper level and we propose a multi-agent deep reinforcement learning (DRL) based routing model. The model can promote the equilibrium of network-wide traffic through distributed self-organized routing collaboration among vehicles, thereby improving efficiency for both individual vehicles and global traffic systems. In the lower level, we focus on the right-of-way assignment problem at signal-free intersections and propose an adaptive cooperative driving algorithm. The algorithm can adaptively evaluate priorities of different lanes, and then uses the lane priorities to guide the Monte Carlo tree search (MCTS) for better right-of-way assignments. Essentially, the upper level determines which conflict areas the vehicles will pass through, and the lower level addresses how the vehicles use the limited road resources more efficiently in each conflict area. The experimental results show that the upper and lower levels complement each other and work together to significantly improve the network-wide traffic efficiency and reduce the travel time of individual vehicles. Moreover, the results demonstrate that microscopic and mesoscopic cooperative driving behaviors of vehicles can significantly benefit the macroscopic traffic system.