Miracle-dz/UniFAR-FTUs huggingface dataset:
Increasing compliance with domestic violence protection orders: investing in perpetrator education and support as an investment in victim and family safety

ABSTRACT Domestic Violence (DV) is a persistent public health issue of global proportions affecting an estimated one in four women worldwide. Civil protection orders or domestic violence orders (DVO) are a legal tool used in many jurisdictions, including Australia, to hold the alleged perpetrators accountable and improve the safety of victims. However, the research on the effectiveness of these orders are mixed and perpetrator non-compliance with such orders continues to be a concern. Few studies examine the situational factors that impact compliance with orders, especially in relation to service engagement and support needs of perpetrators of DV during and beyond the protection order court process. Our study uses focus group data to explore the perceptions of police officers (n = 16) and prosecutors (n = 3) involved in policing and prosecuting DV and the compliance with relevant protection orders in two court districts in Queensland, Australia. Alleged perpetrators’ comprehension of their order conditions and intersecting experiences of social disadvantage and complex needs emerged as key factors influencing compliance, along with the role of timely engagement with alleged perpetrators during the court process to maximise respondent comprehension of order conditions and engagement with available and relevant support services. In concluding, we highlight the importance of protective and preventive aspects of the DVO process that combine holistic wraparound support with perpetrator accountability in order to maximise perpetrator compliance and thus victim and family safety.
Simple and Accurate Approximation of Rough Conductor Surface Impedance

This article presents a simple but accurate approximation of the surface impedance of rough conductors. The approximation uses insights about properties of magnetic field and surface impedance observed from the finite-difference numerical solution of gradient model. The key insight is that surface impedance calculated by the gradient model is essentially only a function of frequency. This property allows the design of approximating function that depends only on frequency but can be used to calculate the surface impedance of conductors with any conductance and roughness. Coefficients for Gauss and Rayleigh distribution of position-dependent conductance are given, and approximations are compared to numerical solutions. The relative error of both approximations is below 0.1% at all frequencies of interest. Approximating function is causal by design and is simple enough that it could be evaluated with a scientific calculator.
In-situ damage localization for a wind turbine blade through outlier analysis of stochastic dynamic damage location vector-induced stress resultants

Today, structural integrity inspections of wind turbine blades are typically carried out by the use of rope or platform access. Since these inspection approaches are both tedious and extremely costly, a need for a method facilitating reliable, remote monitoring of the blades has been identified. In this article, it is examined whether a vibration-based damage localization approach proposed by the authors can provide such reliable monitoring of the location of a structural damage in a wind turbine blade. The blade, which is analyzed in idle condition, is subjected to unmeasured hits from a mounted actuator, yielding vibrations that are measured with a total of 12 accelerometers; of which 11 are used for damage localization. The employed damage localization method is an extended version of the stochastic dynamic damage location vector method, which, in its origin, is a model-based method that interrogates damage-induced changes in a surrogate of the transfer matrix. The surrogate’s quasi-null vector associated with the lowest singular value is converted into a pseudo-load vector and applied to a numerical model of the healthy structure in question, hereby, theoretically, yielding characteristic stress resultants approaching zero in the damaged elements. The proposed extension is based on outlier analysis of the characteristic stress resultants to discriminate between damaged elements and healthy ones; a procedure that previously, in the context of experiments with a small-scale blade, has proved to mitigate noise-induced anomalies and systematic, non-damage-associated adverse effects.
How do French agri-tech start-ups contribute to the sustainability of food value chains?

ABSTRACT The development of digital technologies is one of the solutions being implemented to empower the food industry, especially now, when the sector is struggling to meet sustainable development goals by 2030. The attention of digital solutions has been widely given to its use at the production segment of the food value chains; that is, on-farm activities. We argue that digital technologies can enhance productivity and resilience along the entire food value chain, while increasing sustainability in this domain. Our results show complete digitalization of food value chains in France, driven by innovative start-ups, with some stages more digitalized than others. Indeed, digital technologies are shown to support the three dimensions of sustainable development goals: economic, social, and environmental. However, their benefits should be equally accessible to all actors in this field, and we therefore suggest further research.
Integral State Feedback Control Using Linear Quadratic Gaussian in DC-drive System

The electric motor is one of the technological developments which can support the production process. DC motor has some advantages compared to AC motor especially on the easier way to control its speed or position as well as its widely adjustable range. The main issue in the DC motor is controlling the angular speed with uncertainty and disturbance. The alternative solution of a control method with simple, easy to design, and implementable in a multi-input multi-output system is integral state feedback such as linear quadratic Gaussian (LQG). It is a combination between linear quadratic regulator and Kalman filter. One of the advantages of this method is the usage of fewer sensors compared with the original linear quadratic regulator method which uses sensors as many as the state in the system model. The design, simulation, and experimental study of the application of LQG as state feedback control in a DC-drive system have been done. Both performance and energy were analyzed and compared with conventional proportional integral derivative (PID). The gain of LQG was determined by trial whereas the PID gain is determined from MATLAB autotuning without fine-tuning. The load test and tracking test were carried out in the experiment. Both simulation and hardware tests showed the same result which LQG is superior in integral absolute error (IAE) by up to 74.37 % in loading test compared to PID. On the other side, LQG needs more energy, it consumes higher energy by 6.34 % in the load test.
Design methodology for wearable antenna on artificial magnetic conductor using stretch conductive fabric

The current practice for designing antennas over artificial magnetic conductor (AMC) is time and labour intensive. A novel methodology is described for saving time and effort in designing such antennas. The proposed method is based on using conductive fabric as a radiating element. The method is validated via the design of a textile dual-band monopole antenna on AMC covering both WiFi and the 4G long term evolution (LTE) frequency bands.
A Literature Review on Automatic Generation of Examinations

The examination is a key activity in determining what the learner has gained from the study. Institutions of higher learning (IHL) perform this activity through various assessment methods (test/examination, practical, etc.). The world today is focused on automation of exam generation which is ongoing with dire need during this period of the COVID-19 pandemic when education is greatly affected, leading to embracing online learning and examination. A text/exam comprises questions and answers that focus on evaluation to determine the student’s conversant level in the area of study. Each question has a cognitive level as described by (Armstrong, 2016) in the revised Bloom’s taxonomy. Questions chosen have cognitive levels based on the level of study and standardization of the exam. There is, therefore, a need to consider the question’s cognitive level along with other factors when generating an examination by incorporating deep learning algorithms.
Flowpath influence on stream acid events in tropical urban streams in Singapore

We investigated processes contributing to periodic acidification events in headwater streams of Nee Soon Forest Catchment (NSFC) in Singapore by monitoring hydrochemical changes in response to rainfall inputs. Stream chemistry response to most rainfall events was characterized by decreases in pH from means ranging from 5.1 to 5.3 to below 4.8–5.0 and corresponding increases in specific electrical conductivity from baseflow values of 15–30 to 50–80 μS cm−1, indicative of low‐total dissolved solids in stormflow. The decreases in pH in the streams, which are typically acidic year‐round, were related to occasional highly acidic rainfall inputs (pH ~4.05) and likely the flushing of organic acids into the stream by shallow subsurface flow interacting with surface litter and/or organic‐rich soil horizons. The interaction of rainwater runoff with organic matter in the soil matrix possibly alters the chemical composition of stormflow, influencing pH. Decomposition of instream organic matter also reduces stream water pH. Leaching experiments revealed that the overland flow passing through organic matter and A horizon material has the potential to lower stream water pH by approximately a half unit or more, in part, by flushing nitrates that were produced by microbial decomposition of organic matter and/or precipitated sulphur that enterred the forest by wet or dry atmospheric deposition. The observed periodic acid events are a natural phenomenon in the stream system in this urban environment because of naturally acidic rainfall and granitic soils with low buffering potential. However, acid events are likely amplified in frequency and magnitude by anthropogenic pollution emissions of sulphur and nitrogen species (e.g., SO2 and NOx) from local and regional sources that lower rainfall pH. Although, acid runoff events are typically short‐lived (<12–24 h), further longitudinal monitoring and experimental studies are needed to investigate the long‐term implications on sensitive taxa in the NSFC streams. Finally, understanding the flow pathways of stormflow water in the nested system was critical for deciphering the mechanisms driving stream acid events at the site.
Power Allocation and Energy Cooperation for UAV-Enabled MmWave Networks: A Multi-Agent Deep Reinforcement Learning Approach

Unmanned Aerial Vehicle (UAV)-assisted cellular networks over the millimeter-wave (mmWave) frequency band can meet the requirements of a high data rate and flexible coverage in next-generation communication networks. However, higher propagation loss and the use of a large number of antennas in mmWave networks give rise to high energy consumption and UAVs are constrained by their low-capacity onboard battery. Energy harvesting (EH) is a viable solution to reduce the energy cost of UAV-enabled mmWave networks. However, the random nature of renewable energy makes it challenging to maintain robust connectivity in UAV-assisted terrestrial cellular networks. Energy cooperation allows UAVs to send their excessive energy to other UAVs with reduced energy. In this paper, we propose a power allocation algorithm based on energy harvesting and energy cooperation to maximize the throughput of a UAV-assisted mmWave cellular network. Since there is channel-state uncertainty and the amount of harvested energy can be treated as a stochastic process, we propose an optimal multi-agent deep reinforcement learning algorithm (DRL) named Multi-Agent Deep Deterministic Policy Gradient (MADDPG) to solve the renewable energy resource allocation problem for throughput maximization. The simulation results show that the proposed algorithm outperforms the Random Power (RP), Maximal Power (MP) and value-based Deep Q-Learning (DQL) algorithms in terms of network throughput.
Coupled Fluid-Thermal Investigation on Drag and Heat Reduction of a Hypersonic Spiked Blunt Body with an Aerodisk

In the traditional investigations on the drag and heat reduction of hypersonic spiked models, only the aerodynamic calculation is performed, and the structural temperature cannot be obtained. This paper adopted the loosely coupled method to study its efficiency of drag and heat reduction, in which the feedback effect of wall temperature rise on aeroheating is considered. The aeroheating and structural temperature were obtained by the CFD and ABAQUS software respectively. The coupling analysis of the hypersonic circular tube was carried out to verify the accuracy of the fluid field, the structural temperature, and the coupled method. Compared with experimental results, the calculated results showed that the relative errors of stagnation heat flux and stagnation temperature were 1.34% and 4.95% respectively, and thus the effectiveness of the coupled method was verified. Installing a spike reduced the total drag of the forebody. The spiked model with an aerodisk reduced the aeroheating of the forebody, while the model without an aerodisk intensified the aeroheating. The spiked model with a planar aerodisk had the best performance on drag and heat reduction among all the models. In addition, increasing the length of the spike reduced the drag and temperature of the forebody. With the increase of the length, the change rates of drag, pressure, heat flux, and temperature decreased gradually. Increasing the diameter of the aerodisk also reduced the temperature of the forebody, while the efficiency of forebody drag reduction first increased and then decreased. In conclusion, the heat and drag reduction must be considered comprehensively for the optimal design of the spike.
Synchronization of Public Transport Timetabling with Multiple Vehicle Types

Public transport (PT) timetables play an important role in creating a bridge between the PT agency, the community–municipality, or both and the passengers who seek a reliable, comfortable, and attractive PT service. Inadequate–inaccurate PT timetables not only confuse passengers but also reinforce the unfavorable image of PT service as a whole. Therefore, a prudent timetable strategy can improve these conditions economically and imagewise. This work addresses the problem of PT timetable synchronization while taking into consideration fluctuating passenger demand and multisize vehicle types for better matching of supply and demand. This problem was formulated as an integer programming, two-objective optimization problem. A decomposition method that integrated the route’s headway, vehicle trip offset time, and vehicle type selection and assignment was developed to synchronize timetables of PT routes. The goal was to develop a maximally synchronized timetable that used a mixed-size fleet for a given PT network. The two-objective function was to minimize both the expected total passenger waiting time and the observed passenger load discrepancy at a desired occupancy level on vehicles at the maximum load points. The elaborated methodology was applied to a numerical PT network example and to a real-life PT network in Auckland, New Zealand. The results show that, compared with those of the current timetables, the total passenger waiting time and vehicle load discrepancy can be reduced by 68% to 72% and by 59% to 65%, respectively, by adopting the new timetabling strategy that synchronizes multiple types of vehicles.
Memristor ratioed logic crossbar‐based delay and jump‐key flip‐flops design

Memristor has been widely explored in digital logic circuits where most of the works are focused on basic gate circuits, such as OR and AND logic gates or full adders while few involve flip‐flops. In fact, flip‐flops are also basic logic units with memory function for various digital systems. In this paper, we present circuit designs for Delay (D) and Jump‐Key (JK) flip‐flops based on memristor ratioed logic (MRL). The proposed circuit for D flip‐flop only needs five memristors and one NMOS transistor, and circuit for JK flip‐flop needs seven memristors and two NMOS transistors. Furthermore, the proposed circuits have been mapped into a hybrid memristor‐CMOS crossbar array. Compared with previous approaches, the quantity of MOSFET for each proposed circuit has been greatly reduced. Thus, the proposed designs have achieved simpler structure, smaller area, and lower power consumption benefiting from the memristor's nanoscale size and low power consumption. The circuit verification based on PSpice simulation is also provided.
Long-run asymmetric association between FDI and productivity in Turkey

Incoming foreign direct investments (FDI) may enhance the productivity level of the host country by bringing new advanced technologies. On the other hand, the nexus of FDI and productivity, rather than being linear, might be nonlinear because the effect of increases and decreases in FDI on productivity may not be symmetric. In this sense, this study investigates the asymmetric relationship between FDI and productivity in Turkey by using two different productivity indicators (i.e., PROD1 and PROD2) and employing a Nonlinear ARDL approach. Our hypothesis claims there is an asymmetric association between FDI and productivity in the long run in Turkey. Nonlinear cointegration test findings indicate that selected variables are cointegrated. Hence, they move together in the long run. Our study uses aggregated data at the macro level to analyze the long-term asymmetric relationship between foreign direct investment and labor productivity in Turkey using the NARDL estimation technique. Concerning the estimation results, a long-run nonlinear relationship between incoming FDI and labor productivity was detected, and this finding remained valid across two models constructed by using two distinct labor productivity indicators. As a whole, our results are consistent with the ones found in the literature. Besides, for the first time in the literature, this study addresses the long-run asymmetric nexus between FDI and labor productivity by using macro-level data specific to Turkey and makes various policy recommendations.
MPACT Fast Neutron Multiplicity System Prototype Development

This document serves as both an FY2103 End-of-Year and End-of-Project report on efforts that resulted in the design of a prototype fast neutron multiplicity counter leveraged upon the findings of previous project efforts. The prototype design includes 32 liquid scintillator detectors with cubic volumes 7.62 cm in dimension configured into 4 stacked rings of 8 detectors. Detector signal collection for the system is handled with a pair of Struck Innovative Systeme 16-channel digitizers controlled by in-house developed software with built-in multiplicity analysis algorithms. Initial testing and familiarization of the currently obtained prototype components is underway, however full prototype construction is required for further optimization. Monte Carlo models of the prototype system were performed to estimate die-away and efficiency values. Analysis of these models resulted in the development of a software package capable of determining the effects of nearest-neighbor rejection methods for elimination of detector cross talk. A parameter study was performed using previously developed analytical methods for the estimation of assay mass variance for use as a figure-of-merit for system performance. A software package was developed to automate these calculations and ensure accuracy. The results of the parameter study show that the prototype fast neutron multiplicity counter design is very more » nearly optimized under the restraints of the parameter space. « less
The bromodomain and extra-terminal domain degrader MZ1 exhibits preclinical anti-tumoral activity in diffuse large B-cell lymphoma of the activated B cell-like type

Aim: Bromodomain and extra-terminal domain (BET) proteins are epigenetic readers that play a fundamental role in transcription regulation. Preclinical and early clinical evidence sustain BET targeting as an anti-cancer approach. BET degraders are chimeric compounds comprising of a BET inhibitor, which allows the binding to BET bromodomains, linked to a small molecule, binder for an E3 ubiquitin ligase complex, triggering BET proteins degradation via the proteasome. These degraders, called proteolysis-targeting chimeras (PROTACs), can exhibit greater target specificity compared to BET inhibitors and overcome some of their limitations, such as the upregulation of the BET proteins themselves. Here are presented data on the anti-tumor activity and the mechanism of action of the BET degrader MZ1 in diffuse large B cell lymphoma (DLBCL) of the activated B-cell like (ABC, ABC DLBCL), using a BET inhibitor as a comparison. Methods: Established lymphoma cell lines were exposed for 72 h to increasing doses of the compounds. Cell proliferation was evaluated by using an 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazoliumbromide (MTT) assay. Fluorescent-Activated Cell Sorter (FACS) analysis was performed to measure apoptotic activation and RNA sequencing (RNA-Seq) to study the transcriptional changes induced by the compounds. Results: MZ1, and not its negative control epimer cisMZ1, was very active with a median half maximal inhibitory concentration (IC50) of 49 nmol/L. MZ1 was more in vitro active than the BET inhibitor birabresib (OTX015). Importantly, MZ1 induced cell death in all the ABC DLBCL cell lines, while the BET inhibitor was cytotoxic only in a fraction of them. BET degrader and inhibitor shared partially similar changes at transcriptome level but the MZ1 effect was stronger and overlapped with that caused cyclin-dependent kinase 9 (CDK9) inhibition. Conclusions: The BET degrader MZ1 had strong cytotoxic activity in all the ABC DLBCL cell lines that were tested, and, at least in vitro, it elicited more profound effects than BET inhibitors, and encourages further investigations.
A Newton‐type method for two‐dimensional eigenvalue problems

Two‐dimensional eigenvalue problems (2DEVP) equations in complex Hermitian case contain complex quadratic forms which is non‐holomorphic. In this case, standard Newton method fails to apply. An existing strategy to solve this problem is to transform them into real problems (TRN). However, this method doubles the size of equations and thus is time consuming. On the other hand, the non‐isolation of the solution set in 2DEVP also complicates the analysis. In this article, we propose a Newton type method which solves the problem caused by non‐holomophism and non‐isolation. It has locally quadratic convergence rate and is about at least twice as much efficient as TRN. We hope our ideas can provide insights for solving other problems including non‐holomorphism and non‐isolation. We apply our algorithm to calculate the distance to instability. Numerical experiments show its advantages in efficiency while keeping good convergence compared with the current state of art algorithms.