Miracle-dz/UniFAR-FTUs huggingface dataset:
Resource constrained distribution network modelling under severe weather conditions

Many methodologies exist for predicting electrical MV network reliability, in order to optimise investment. These approaches often assume that while individual assets will age and become less reliable, system operations will in the future be similar to how they are today. However, due to the advent of the smart grid, historic averages could cease to be useful. There exists a need for practical asset management solutions that can be used to predict how robust distribution networks will be in the future. This would need to account for both normal conditions and stressed situations due to severe weather, when scarcity of resources in available staff available to perform repair actions may pose additional challenges. This paper describes a new reliability-based model specifically developed for predicting distribution network risk and resilience under severe weather conditions and in the presence of resource constraints. The presented system is designed to be integrated with existing asset management software, and therefore inform business decision making. Case studies will show that the consequence of faults can increase significantly for some assets, if the required investment is deferred.
Management of Acute Complicated Mastoiditis

Supplemental Digital Content is available in the text. Background: The objective of our study was to evaluate the efficacy of treatment options for the most frequently reported complications of acute mastoiditis in the English literature. PubMed, EMBASE, and The Cochrane Library were searched from database inception through March 29, 2019. Methods: Two independent reviewers (M.R.K., K.S.) evaluated search results for study inclusion. References cited in publications meeting inclusion criteria were reviewed. Twenty-three included studies were published from 1998 through 2018. Treatment efficacy was determined by comparing the change in number of complication subtypes in each treatment subgroup (medical, conservative, or surgical) from admission to discharge (range: 5–30 days) or postdischarge follow-up (range: 1–27.5 months) with a random effects model. Results: Among 733 identified articles, 23 met inclusion criteria. Of the 883 included patients, 203 were managed medically (23%), 300 conservatively (34%) and 380 surgically (43%). Conservative patients had more extracranial complications (ECC, P = 0.04) and intratemporal complications (IT, P = 0.04) at follow-up compared with medical patients. Medical patients had more total number of complications (TNC, P = 0.03), ECC (P = 0.02), and IT (P = 0.01) at discharge compared with surgical patients. Conservative patients had more of all complications except intracranial/extracranial abscess and “other” at discharge and follow-up compared with surgical patients. Conclusions: There were larger reductions in TNC, ECC, and IT at discharge and follow-up among surgical patients compared with medical and conservative patients. There were greater reductions in TNC, ECC, IT, intracranial complications, subperiosteal abscess and lateral sinus thrombosis at discharge and follow-up among surgical patients compared with conservative patients.
Relationships between physical function, body composition and metabolic health in Pacific Island youth

The Pacific Islands Families (PIF) study is a birth cohort study designed to increase knowledge about the growth and development of Pacific children living in Auckland, New Zealand. Adolescence is a critical time of growth and development, yet the roles of physical function and body composition in metabolic health at this life stage are not clear. We aimed to investigate associations between measures of physical function (the 6-minute-walk-test (6MWT)), heart rate changes before and after the 6MWT, handgrip strength, body composition including appendicular skeletal muscle mass (ASMM) measured by dual-energy X-ray absorptiometry and biomarkers of metabolic health from a fasting blood sample.A total of 200 youth (98 girls, 102 boys) aged 14–15 years, from the birth-cohort of children in the Pacific Islands families study were measured. In girls, the proportion of ASMM was lower and fat higher than in boys. Controlling for age, a 1% increase in ASMM predicted a longer walk distance (+6.3, 95%CI 2.2, 10.4 m in girls; +7.1, 95%CI 4.4, 9.1 m in boys) and lower heart rate following the 6MWT. ASMM and fat mass were independently predictive of maximal handgrip strength which was increased by 1.4 (1.0,1.8) kg in girls and 1.7 (1.3, 2.0) kg in boys for each kg increase in ASMM and reduced by 0.23 (0.08, 0.38) kg in girls and 0.26 (0.14, 0.37) kg in boys for each kg increase in fat mass. Lower total cholesterol and LDL were associated with an increase in distance walked in boys only. For each year of age, distance walked was reduced by 34 (15, 53) m in girls and 59 (36,84) m in boys. These findings should be explored further in the context of other influences such as food security, opportunities for physical activity and cultural expectations.
A cross-sectional analysis of psychological distress among higher education students in Ireland.

OBJECTIVES To examine levels of psychological distress among higher education students in Ireland overall and across a range of personal, higher education, and socioeconomic characteristics, prior to the COVID-19 pandemic. METHODS A cross-sectional online survey of college students in Ireland was undertaken in 2018. Data on 5201 students from 13 higher education institutions (HEIs) were analyzed. Stress, anxiety, and depression symptom scores based on the Depression, Anxiety and Stress Scale (DASS-21) were calculated and reported, with statistical testing used to compare across groups. RESULTS Overall, 29.6% and 19.1% of respondents were classified in the mild to moderate and severe to extremely severe range for depression respectively. The corresponding proportions were 25.9% and 20.7% for anxiety, and 24.5% and 14.8% for stress. Differences across groups included higher levels of psychological distress for transgender and female students compared to males (p < 0.01), for gay/lesbian/bisexual students compared to heterosexuals (p < 0.01), for undergraduates compared to postgraduates (p < 0.01), for students from intermediate/technical/service/unskilled social classes compared to professional/self-employed social classes (p < 0.01), and for those with financial difficulties compared to those without financial difficulties (p < 0.01). CONCLUSIONS Rates of psychological distress were high amongst college students in Ireland prior to the COVID-19 pandemic, with substantial differences across groups. Due to study limitations, such as possible selection bias, the findings need replication. Further research is needed to determine the impact of the pandemic on the prevalence of mental illness in this population.
Multi-strategy evolutionary games: A Markov chain approach

Interacting strategies in evolutionary games is studied analytically in a well-mixed population using a Markov chain method. By establishing a correspondence between an evolutionary game and Markov chain dynamics, we show that results obtained from the fundamental matrix method in Markov chain dynamics are equivalent to corresponding ones in the evolutionary game. In the conventional fundamental matrix method, quantities like fixation probability and fixation time are calculable. Using a theorem in the fundamental matrix method, conditional fixation time in the absorbing Markov chain is calculable. Also, in the ergodic Markov chain, the stationary probability distribution that describes the Markov chain’s stationary state is calculable analytically. Finally, the Rock, scissor, paper evolutionary game are evaluated as an example, and the results of the analytical method and simulations are compared. Using this analytical method saves time and computational facility compared to prevalent simulation methods.
Downregulated RRS1 inhibits invasion and metastasis of BT549 through RPL11-c-Myc-SNAIL axis

Regulator of ribosome synthesis 1 (RRS1) is a key factor in ribosome biosynthesis and other cellular functions. High level of RRS1 in breast cancer cell lines is associated with increased cell proliferation, invasion and migration. RRS1 controls the assembly of the 60s subunit and maturation of 25S rRNA during ribosome biosynthesis. In this study, lentiviral transfection of sh-RNA was used to knock down the level of RRS1, to detect the effect of RRS1 on cell function and to explore the specific mechanism of RRS1 affecting cell invasion and metastasis by COIP and dual-luciferase reporter gene assays. The present study found that RRS1 knockdown reduced the accumulation of ribosome protein L11 (RPL11) in the nucleolus, which then migrated to the nucleoplasm and bound to c-Myc. This inhibited trans-activation of SNAIL by c-Myc and eventually decreased the invasion and metastasis capacity of the human breast cancer cell line BT549. Taken together, RRS1 regulates invasion and metastasis of human breast cancer cells through the RPL11-c-Myc-SNAIL axis. The findings are of great significance for exploring the mechanism of breast cancer invasion and metastasis and the corresponding regulatory factors.
Adolescent girls trapped in early marriage social norm in rural Ethiopia: A vignette-based qualitative exploration

Background Early marriage is not uncommon in Ethiopia, particularly for adolescent girls in rural settings. Social norms are among the factors believed to perpetuate early marriage practices. This qualitative study explores social norms surrounding adolescent girls’ marriage practices in West Hararghe, Ethiopia. Methods This study used the qualitative inquiry method to explore social norms in rural Ethiopia. Focus group discussions were conducted with purposively sampled married and unmarried adolescent girls, adolescent boys, and parents. A total of 158 individuals participated in the study, comprising 95 adolescents and 63 parents. Data were collected using locally developed vignettes. A thematic framework analysis approach using the Social Norms Analysis Plot (SNAP) was employed to diagnose and understand social norms. Results Adolescent girls’ marriage was found to be mainly influenced by their peers who conform to prevailing social norms. Marrying one’s first suitor was considered an opportunity not to be missed and a symbol of good luck. Relatives, neighbors, and marriage brokers facilitate adolescent girls’ marriage in accordance with the local social norms. Girls usually accept the first marriage proposal regardless of their age, and they are highly expected to do so by their peers, parents, and influential others. Exceptions from the early marriage social norm include adolescent girls determined to continue their education and those having supportive teachers. Conclusions In this study context, social norms strongly encourage early marriage and are mainly perpetuated by peers of adolescent girls and influential adults. A strong determination to continue education on the part of girls, strong school performance, and supportive schoolteachers are important conditions for circumventing social norms on early marriage. As social norms evolve slowly, we recommend periodical assessment in order to develop locally appropriate interventions against early marriage.
Compromised Blood Flow in the Optic Nerve Head after Systemic Administration of Aldosterone in Rats: A Possible Rat Model of Retinal Ganglion Cell Loss

Abstract Purpose To investigate the optic nerve head (ONH) blood flow, retinal vessel diameters, and retinal ganglion cell (RGC) loss after systemic administration of aldosterone in rats. Methods Aldosterone (80 µg/kg/day) or vehicle was administered using an osmotic minipump in Brown Norway rats. The mean blur rate in the vessel (MV) and tissue (MT) regions and retinal vessel diameters in the ONH were measured by laser speckle flowgraphy before and 1, 2, and 4 weeks after administration of aldosterone or vehicle. Intraocular pressure (IOP), blood pressure, and heart rate were recorded. The retrogradely labeled RGCs were counted in the retinal flatmounts prepared 5 weeks after treatment. Results The MV and MT in the aldosterone group significantly decreased at 2 and 4 weeks (MV: 2 weeks, p = 0.001, 4 weeks, p < 0.001; MT: 2 weeks, p = 0.02, 4 weeks, p = 0.03). The artery and vein diameters significantly decreased at 1, 2, and 4 weeks in the aldosterone group (all p < 0.001). The MV, MT, and vessel diameters remained unchanged in the vehicle group. Other parameters did not change over time in either group. RGC counts were significantly lower in the aldosterone group than in the vehicle group (p < 0.001). Conclusions ONH blood flow decreased following retinal vessel constriction without changes in IOP or blood pressure in a possible rat model of RGC loss by systemic administration of aldosterone.
A KPI Set for Steering the IoT Business in Product Companies

Overview: The Internet of Things (IoT) offers product companies the opportunity to develop an IoT business. Existing performance measurement systems (PMS) are unsuitable for measuring and managing the business logic of IoT business. Based on research conducted with 31 product companies, we present three measurement traps, a key performance indicators (KPI) set suited for steering IoT business in product companies, and three recommendations for implementing the KPI set. Companies can use the KPI set to manage their IoT businesses more effectively and avoid the measurement traps.
High Frequency/Low Voltage CMOS Adder

A high frequency/low voltage CMOS adder is presented. Two main components in the proposed adder are i) the V to I circuit which uses two MOSs and two constant current sources and ii) the I to V circuit which uses two MOSs. The proposed adder uses two V to I circuits and one I to V circuit for the first adder function. The next adder functions can be obtained by increasing one V to I circuit per one n€xt adder function. The theory of operation is described and simulated results obtained from PSPICE program are used to verif,i the theoretical prediction. Simulated adder performance with 0.8 p m MOS technology shows that the output operating voltage range given an error voltage less than I 0/o is 775 mV when using the power supplies of t I . 5 VDC and a frequency response up to 125 MHz. l. Introduction Analog CMOS signal processing circuits have received significant attention. One of them is an analog adder that is used as an important building block in analog computation [1-2] and in fuzzy control [3]. A well-known adder is an opamp adder. One advantage of the opamp adder is, it has a wide operating voltage range. However it also has disadvantages, using many transistors and using passive devices, which are the cause of the use of the large chip area. One way to avoid these drawbacks is the use of CMOS adders [4-6]. The operations of these adders are performed in current mode since the currents can be directly summed using Kirchhoff s law. This paper proposes a CMOS voltage adder operating in current mode, the same as CMOS adders [4-6], namely it uses the V to Is to convert input voltages into input currents and the I to V to convert the sum of input currents into the output voltage. Nevertheless the proposed adder uses the supply voltages lower than [4-5]. Additionally, owing to the proposed adder using 0.8 pm MOS technology, it has an operating frequency higher than [4-6]. 2. Circuit Description The proposed V to I circuit is shown in Fig. I a. All MOSs are biased in saturation region. The source current of M,, can be expressed as where W^, 0" = K"----::t ' a f " t M o and the drain current of M r can be expressed AS I , t ( , , ) = F r (v , , -Vr , -vr r ) ' Q) where W^, B^, =K^ , : " 2Lu, Let B, = Fu = B byadjustinEWrof Lr,, and W, , I Lr, , and assume that Vrr = Vr, = V7 , the output current of the V to I circuit can be obtained as I out(L' ut t1 = 1.s1,l.lu ) I ,,,(, ,, =((v,,,, -vl -v,,)t -(v,, -vr, -v,) ')B I ,(, ,) = 0 ,(v ,, -lvrrl v,,)' ( I )
FPGA-based hardware acceleration of electromagnetic wave reverse time migration imaging

Electromagnetic wave reverse time migration (RTM) imaging based on finite difference time domain (FDTD) method is widely used in geological exploration. It can accurately attribute the wavefield to its true subsurface spatial location when dealing with steeply dipping structures and complex velocity models. However, the forward and backward propagation processes of RTM imaging require recording wavefield information at each time step, which causes a large number of buffer accesses to degrade the overall calculation speed. This computationally and data intensive features limits its application in more scenarios. Therefore, this paper develops the FDTD prototype accelerator based on FPGA to accelerate the forward and backward propagation process of reverse time migration imaging, and realize the hardware circuit of cross-correlation imaging conditions. The experimental results show that the forward propagation process of FPGA at a clock frequency of 100MHz is 17.384 times faster than the PC using 3.6GHz CPU, and the backward propagation process is 18.371 times faster in comparison.
Cooperative formation control of fixed-wing UAVs based on deep reinforcement learning

In recent years, artificial intelligence has attracted research interest and developed rapidly. As one of its representative technologies, deep reinforcement learning methods have gradually combined with various fields to develop numerous research results. Aiming at the motion constraints of fixed-wing aircraft and the existence of disturbances, model uncertainties, etc., this paper designs a fixed-wing aircraft formation controller based on the PID control structure and using the Proximal Policy Optimization algorithm (PPO). The simulation results show that the PID parameters change adaptively with the state of the system, and the system can quickly form the desired formation.
A novel 3D clutter removal for GPR pipe detection via tensor RPCA

Ground penetrating radar (GPR) is widely used in underground pipe detection due to its non-destructive and high efficiency characteristics. To improve the accuracy of data interpretation, 3D GPR survey is gradually applied to collect more information to classify pipes and other underground objects. However, its efficiency is often highly deteriorated by strong clutters, especially for nonmetal pipe detection. Recently, low rank and sparse decomposition (LRSD) based methods have been demonstrated their superiority to conventional methods in GPR clutter suppression. However, these methods are suitable for B-scan images, but not effective for 3D GPR data. In this paper, a novel clutter removal method based on Tensor RPCA is proposed for 3D GPR data. Similar to the RPCA, it decomposes the data matrix into a low-rank clutter matrix and a sparse target matrix, but a different cost function is utilized. It minimizes the third-order tensor nuclear norm to achieve global optimization of the clutter and limits the sparsity of the targets by the l-1 norm. Moreover, the randomized singular value decomposition is employed to reduce the computational complexity of the proposed algorithm. Simulation and experimental results show its outstanding performance in clutter removal for 3D data.
Research on signal processing method of linear array scanning infrared detection system

For the linear array scanning infrared detection system, the reasonable design of the system hardware architecture and data processing flow is the key to ensure the system to achieve real-time target detection and fast recognition. Fast and effective target recognition algorithm is the core of the system design. The signal processing of the linear scanning infrared detection system designed in this paper adopts the hardware architecture of FPGA + DSP + GPU, and puts forward the false target discrimination method of sky and earth line based on semantic segmentation based on deep learning, which is different from the traditional threshold detection and segmentation method based on artificial template matching. The deep learning method uses the semantic information and spatial information of infrared image and has certain adaptability. Finally, the algorithm is implemented on the hardware system through the field measured data, and the effectiveness of the algorithm is verified.
Study on fast calibration method of photoelectric sighting

In order to solve the problems of complex operation and insufficient environmental adaptability in the traditional zero calibration process of sight, a fast calibration scheme of photoelectric sight is proposed. A rod insertion calibration device based on collimator is used and the collimator image collected by CCD is processed in this scheme. Through the image processing method of adaptive threshold Canny edge detection and Hough transform fitting, and the feature point acquisition method of point clustering, the center position of the cross image is obtained, and the deflection angle between the optical axis of the sight and the muzzle axis is calculated. Analysis and experimental results show that the average calibration error of this method is within 0.1mil. Compared with the traditional gun calibration process, this calibration method can achieve higher cold chamber calibration efficiency and environmental adaptability.
Dynamic scattering media imaging based on combined modulation

Imaging through dynamic scattering media has very important applications in many fields such as autonomous driving and drones. In this article, we propose an imaging method based on combined modulation of dynamic scattering medium and spatial light modulator. This method is based on the compressed sensing (CS) imaging model, and uses the combined modulation as the modulation mechanism to achieve the target reconstruction. The results of optical experiments show that the combined modulation method can successfully reconstruct the target image. It is also suitable for dynamic scattering media with large changes in concentration. Moreover, the algorithm comparison experiment results show that compared with the orthogonal matching pursuit (OMP) algorithm, the total variation algorithm can improve the quality of the image.
Compressive sensing-based infrared image super-resolution method for rapid NDT of CFRP components

In the field of non-destructive testing (NDT), low-cost uncooled infrared (IR) sensors cannot generate high-speed thermography detection results with low levels of noise and high sensitivity. Hence, this paper proposes a compressive sensing-based postprocessing method for the results of uncooled IR sensors to obtain high-quality and super-resolution NDT imaging results. Super-resolution IR images are generated using low-resolution IR images and sparse dictionaries generated from randomly sampled raw patches of training images. Super-resolution IR images and pulsed phase thermography (PPT) are combined to improve the NDT results for carbon fiber-reinforced polymer (CFRP) specimens with artificial defects engraved on them. The results of the PPT experiments show that the compressive sensing-based super-resolution algorithm can be used to double the resolution of PPT phase images. The reconstructed PPT phase images further show that the proposed method can produce sharp defect edges while preserving the original texture, which will enable the use of uncooled IR sensors in a wider range of NDT applications.