Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical layer security and energy efficiency over different error correcting codes in wireless sensor networks

Despite the rapid growth in the market demanding for wireless sensor networks (WSNs), they are far from being secured or efficient. WSNs are vulnerable to malicious attacks and utilize too much power. At the same time, there is a significant increment of the security threats due to the growth of the several applications that employ wireless sensor networks. Therefore, introducing physical layer security is considered to be a promising solution to mitigate the threats. This paper evaluates popular coding techniques like Reed solomon (RS) techniques and scrambled error correcting codes specifically in terms of security gap. The difference between the signal to nose ratio (SNR) of the eavesdropper and the legitimate receiver nodes is defined as the security gap. We investigate the security gap, energy efficiency, and bit error rate between RS and scrambled t-error correcting codes for wireless sensor networks. Lastly, energy efficiency in RS and Bose-Chaudhuri-Hocquenghem (BCH) is also studied. The results of the simulation emphasize that RS technique achieves similar security gap as scrambled error correcting codes. However, the analysis concludes that the computational complexities of the RS is less compared to the scrambled error correcting codes. We also found that BCH code is more energy-efficient than RS.
Automated pavement crack detection and segmentation based on two‐step convolutional neural network

Cracking is a common pavement distress that would cause further severe problems if not repaired timely, which means that it is important to accurately extract the information of pavement cracks through detection and segmentation. Automated pavement crack detection and segmentation using deep learning are more efficient and accurate than conventional methods, which could be further improved. While many existing studies have utilized deep learning in pavement crack segmentation, which segments cracks from non‐crack regions, few studies have taken the exact pavement crack detection into account, which identifies cracks in the images from other objects. A two‐step pavement crack detection and segmentation method based on convolutional neural network was proposed in this paper. An automated pavement crack detection algorithm was developed using the modified You Only Look Once 3rd version in the first step. The proposed crack segmentation method in the second step was based on the modified U‐Net, whose encoder was replaced with a pre‐trained ResNet‐34 and the up‐sample part was added with spatial and channel squeeze and excitation (SCSE) modules. Proposed method combines pavement crack detection and segmentation together, so that the detected cracks from the first step are segmented in the second step to improve the accuracy. A dataset of pavement crack images in different circumstances were also built for the study. The F1 score of proposed crack detection and segmentation methods are 90.58% and 95.75%, respectively, which are higher than other state‐of‐the‐art methods. Compared with existing one‐step pavement crack detection or segmentation methods, proposed two‐step method showed advantages of accuracy.
An Approach for Handling Uncertainties Related to Behaviour and Vehicle Mixes in Traffic Simulation Experiments with Automated Vehicles

The introduction of automated vehicles is expected to affect traffic performance. Microscopic traffic simulation offers good possibilities to investigate the potential effects of the introduction of automated vehicles. However, current microscopic traffic simulation models are designed for modelling human-driven vehicles. Thus, modelling the behaviour of automated vehicles requires further development. There are several possible ways to extend the models, but independent of approach a large problem is that the information available on how automated vehicles will behave is limited to today’s partly automated vehicles. How future generations of automated vehicles will behave will be unknown for some time. There are also large uncertainties related to what automation functions are technically feasible, allowed, and actually activated by the users, for different road environments and at different stages of the transition from 0 to 100% of automated vehicles. This article presents an approach for handling several of these uncertainties by introducing conceptual descriptions of four different types of driving behaviour of automated vehicles (Rail-safe, Cautious, Normal, and All-knowing) and presents how these driving logics can be implemented in a commonly used traffic simulation program. The driving logics are also linked to assumptions on which logic that could operate in which environment at which part of the transition period. Simulation results for four different types of road facilities are also presented to illustrate potential effects on traffic performance of the driving logics. The simulation results show large variations in throughput, from large decreases to large increases, depending on driving logic and penetration rate.
High Yielding Mungbean [Vigna radiata (L.) Wilczek] Variety “NIFA Mung-2017”

National yield of mungbean is low as compared to other countries, mainly due to shortage of commercial mungbean varieties. To address this issue, an exotic Mungbean Yellow Mosaic Virus (MYMV) susceptible accession VC 1973A and a local MYMV resistant genotype NM 92 were crossed (VC 1973A x NM 92) at the experimental field of the Nuclear Institute for Food and Agriculture (NIFA), Peshawar during kharif 2004. Selection for best recombinant lines based on high yield (more pods per plant), resistance to MYMV, semi erect plant type in early segregating populations, and genetic stability in F2 F5 generations for the desired traits was carried-out from 2005 to 2010. The high yielding recombinant “NFM-6-5” along with other advanced lines and local standard variety “Ramzan” were screened for MYMV resistance, and tested for seed yield and other related components in various yield trials i.e. preliminary, advanced, multi-locations and National Uniform Yield trials from 2011-2015. Results revealed that recombinant “NFM-6-5” produced up to 2283 kg ha -1 seed yield in replicated yield trials with 25-30% higher seed yield compared to the check variety “Ramzan” in various yield trials. More number of pods per plant and large seed size are the main primary yield contributing components in NIFA Mung-2017 (recombinant “NFM-6-5”). NIFA Mung 2017 is a promising variety with different genetic background from earlier mungbean varieties. Khyber Pakhtunkhwa Provincial Seed Council approved the recombinant “NFM-6-5” as a commercial variety with name “NIFA Mung-2017” for general cultivation in Khyber Pakhtunkhwa (KP) on 19 th September 2017.
Disparity among Endocrinologists and Gynaecologists in the Diagnosis of Polycystic Ovarian Syndrome

Objectives This study aimed to compare endocrinologists’ versus gynaecologists’ approaches in using the Rotterdam criteria to diagnose polycystic ovarian syndrome (PCOS). Methods This cross-sectional study was conducted at Physiology Department, King Saud University, Riyadh, Saudi Arabia, between December 2017 and April 2018. A validated self-administered questionnaire in English was used to obtain information from endocrinologists and gynaecologists regarding their approaches to diagnosing PCOS. Each group’s diagnostic use of the Rotterdam criteria, association between years of experience and clinical decision-making, clinical features leading to diagnosis and considerations in the diagnosis of biochemical parameters that define hyperandrogenism were evaluated. Results A total of 132 physicians were included in this study (response rate: 27%); 77 (58.3%) were endocrinologists and 55 (41.7%) were gynaecologists. Most of the respondents (79.5%) had ≤20 years of experience. A statistically significant difference was detected between the endocrinologists and gynaecologists (98.7% versus 81.8%; P = 0.001) in their consideration of hyperandrogenism in the diagnosis. The gynaecologists relied more on ovarian morphology than the endocrinologists did (76.4% versus 45.5%, P <0.0001). Physicians with more experience used ovarian ultrasonography more compared to those with less experience (P = 0.006). Conclusion There was disparity in the diagnostic approaches of endocrinologists, who rely more on androgen levels for diagnosis of PCOS versus gynaecologists, who more frequently use an ovarian morphology assessment. Increased years of experience increased the rate of ultrasonography use for PCOS diagnosis in both groups.
Developing Mixed EWMA-CUSUM and CUSUM-EWMA control charts based on MRSS and DRSS procedures

The mixed EWMA-CUSUM and CUSUM-EWMA control charts are among the control charts provided in recent years by combining two exponentially weighted moving average and cumulative sum charts for efficient monitoring of the process mean. In this paper, we extended these mixed control charts by using new median ranked set sampling and double ranked set sampling procedures. The performance of the proposed mixed control charts is evaluated through extensive Monte Carlo simulations in terms of average run length criterion and the results show the proposed charts outperform the similar charts for detecting different shifts in process mean. Furthermore, a real data-set is also presented for explaining the implementation of the proposed control charts.
The dynamic trophic niche of an island bird of prey

Abstract Optimal foraging theory predicts an inverse relationship between the availability of preferred prey and niche width in animals. Moreover, when individuals within a population have identical prey preferences and preferred prey is scarce, a nested pattern of trophic niche is expected if opportunistic and selective individuals can be identified. Here, we examined intraspecific variation in the trophic niche of a resident population of striated caracara (Phalcoboenus australis) on Isla de los Estados (Staten Island), Argentina, using pellet and stable isotope analyses. While this raptor specializes on seabird prey, we assessed this population's potential to forage on terrestrial prey, especially invasive herbivores as carrion, when seabirds are less accessible. We found that the isotopic niche of this species varies with season, age, breeding status, and, to a lesser extent, year. Our results were in general consistent with classic predictions of the optimal foraging theory, but we also explore other possible explanations for the observed pattern. Isotopic niche was broader for groups identified a priori as opportunistic (i.e., nonbreeding adults during the breeding season and the whole population during the nonbreeding season) than it was for individuals identified a priori as selective. Results suggested that terrestrial input was relatively low, and invasive mammals accounted for no more than 5% of the input. The seasonal pulse of rockhopper penguins likely interacts with caracara's reproductive status by constraining the spatial scale on which individuals forage. Niche expansion in spatially flexible individuals did not reflect an increase in terrestrial prey input; rather, it may be driven by a greater variation in the types of marine prey items consumed.
Molecular typing of canine parvovirus from Sulaimani, Iraq and phylogenetic analysis using partial VP2 gene

M. O. BABA SHEIKH, P. M. A. RASHID, A. S. MAROUF, Z. H. RAHEEM, S. MANJUNATH & S. C. JANGA School of Informatics and Computing, Indiana University, Purdue University, Indianapolis, Indiana, USA; Department of Molecular Biology – Veterinary Laboratory Venter, Sulaimani Veterinary Directorate, Iraq; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
Sparse reduced-rank regression for exploratory visualization of multimodal data sets

In genomics, transcriptomics, and related biological fields (collectively known as ‘omics’), it is common to work with n ≪ p data sets with the dimensionality much larger than the sample size. In recent years, combinations of experimental techniques began to yield multiple sets of features for the same set of biological replicates. One example is Patch-seq, a method combining single-cell RNA sequencing with electrophysiological recordings from the same cells. Here we present a framework based on sparse reduced-rank regression for obtaining an interpretable visualization of the relationship between the transcriptomic and the electrophysiological data. We use an elastic net regularization penalty that yields sparse solutions and allows for an efficient computational implementation. Using several publicly available Patch-seq data sets, we show that sparse reduced-rank regression outperforms both sparse full-rank regression and non-sparse reduced-rank regression in terms of predictive performance, and can outperform existing methods for sparse partial least squares and sparse canonical correlation analysis in terms of out-of-sample correlations. We introduce a ‘bibiplot’ visualization in order to display the dominant factors determining the relationship between transcriptomic and electrophysiological properties of neurons. We believe that sparse reduced-rank regression can provide a valuable tool for the exploration and visualization of multimodal data sets, including Patch-seq.
Evaluation of grain size and content of nonplastic fines on undrained behavior of sandy soils

Abstract Marine sandy soils may liquefy under wave loading and/or seismic loading. Current research shows that the presence of fines can significantly affect the liquefaction potential of sandy soils. Thus, a quantitative evaluation of the effect of fines on the undrained behavior of sandy soils can provide useful information on soil liquefaction that can advance the design of foundations of coastal structures. However, little is known about how the grain size of nonplastic fines affects the mechanical behavior of sandy soils. In this study, a series of strain-controlled monotonic undrained triaxial compression tests and critical-state constitutive modeling are carried out on a medium dense saturated sandy soil for various fines contents (FCs), mean grain sizes ( s) of nonplastic fines, and initial effective confining pressures. The results show that the peak deviatoric stress decreases significantly with decreasing especially for high FCs. The equivalent granular state parameter (ψ*) at the phase transformation can be used to characterize the effect of fines on the dilatancy of sandy soils in constitutive modeling. Additionally, the initial value of ψ*( ) serves as physical index for characterizing the influence of fines on the undrained instability state of sandy soils.
The t haplotype, a selfish genetic element, manipulates migration propensity in free-living wild house mice Mus musculus domesticus

Life is built on cooperation between genes, which makes it vulnerable to parasitism. However, selfish genetic elements that exploit this cooperation can achieve large fitness gains by increasing their transmission unfairly relative to the rest of the genome. This leads to counter-adaptations that generate unique selection pressures on the selfish genetic element. This arms race is similar to host-parasite co-evolution. Some multi-host parasites alter the host’s behaviour to increase the chance of transmission to the next host. Here we ask if, similarly to these parasites, a selfish genetic element in house mice, the t haplotype, also manipulates host behaviour, specifically the host’s migration propensity. Variants of the t that manipulate migration propensity could increase in fitness in a meta-population. We show that juvenile mice carrying the t haplotype were more likely to emigrate from and were more often found as migrants within a long-term free-living house mouse population. This result may have applied relevance as the t has been proposed as a basis for artificial gene drive systems for use in population control.
Structural and functional influences of urban and rural childhoods on the medial prefrontal cortex

Urbanization has been implicated as having an important influence on brain development and risk for psychiatric disorders but the mechanisms in brain and the role of genetic background have been unresolved. Here we explored major urbanization changes in recent history in China, and its correlates with brain structure and function in a genetically controlled sample with similar current education and socioeconomic status. Principal component analyses showed no global genomic differences across urban and rural groups. Subjects with rural childhoods had relatively increased medial prefrontal cortex (mPFC) gray matter volumes. The engagement of medial prefrontal cortex during working memory was relatively reduced under increased interpersonal stress. Further, increased trait anxiety and depression was associated with reduced stress-related mPFC engagement but only in subjects with urban childhoods. This is the first study to examine the impact of childhood urbanicity on brain development and function controlling for genetic and socioeconomic variation. We find that urbanicity during childhood is associated with changes in mPFC structure and function that are consistent with conceptualizations of how urbanicity might increase the influence by which interpersonal stressors are neurally processed.
Performance increasing researches in the value chain stages within the petroleum industry

The performance increasing in different stages of the value chain represents an important domain of study for both academic researchers and business experts. In the light of globalization, this topic enjoys a major interest from experts in various fields of activity and from the company's management, as well. From the research perspectives, it is desired to analyze the elements that determine and influence the oil companies’ performances. For this scope, we have made an analysis of the value chain stages, and we have identified the relevant performance indicators for each working stage. By questioning some key people, managers, and experts situated on different stages of the value chain in a petroleum company, important information and data were obtained regarding their perception of the importance of the chain elements’ value. Using a statistical methodology, we intend to obtain a unitary image regarding the importance of the performance in different stages of the value chain within the oil companies.
Refining genetic boundaries for Agassiz’s desert tortoise (Gopherus agassizii) in the western Sonoran Desert: the influence of the Coachella Valley on gene flow among populations in southern California

Understanding the influence of geographic features on the evolutionary history and population structure of a species can assist wildlife managers in delimiting genetic units (GUs) for conservation and management. Landscape features including mountains, low elevation depressions, and even roads can influence connectivity and gene flow among Agassiz’s desert tortoise (Gopherus agassizii) populations. Substantial changes in the landscape of the American Southwest occurred during the last six million years (including the formation of the Gulf of California and the lower Colorado River), which shaped the distribution and genetic structuring of tortoise populations. The area northwest of the Gulf of California is occupied by the Salton Trough, including the Coachella Valley at its northern end. Much of this area is below sea level and unsuitable as tortoise habitat, thus forming a potential barrier for gene flow. We assessed genetic relationships among three tortoise populations separated by the Coachella Valley. Two adjacent populations were on the east side of the valley in the foothills of the Cottonwood and Orocopia mountains separated by Interstate 10. The third population, Mesa, was located about 87 km away in the foothills of the San Bernardino Mountains at the far northwestern tip of the valley. The Cottonwood and Orocopia localities showed genetic affiliation with the adjacent Colorado Desert GU immediately to the east, and the Mesa population exhibited affiliation with both the Southern Mojave and Colorado Desert GUs, despite having a greater geographic distance (0.5x–1.5x greater) to the Colorado Desert GU. The genetic affiliation with the Colorado Desert GU suggests that the boundary for that GU needs to be substantially extended to the west to include the desert tortoise populations around the Coachella Valley. Their inclusion in the Colorado Desert GU may benefit these often overlooked populations when recovery actions are considered.
Performance of PV integrated multilevel inverter for PQ enhancement

ABSTRACT Three phase shunt active power filter (SAPF) using multilevel inverter (MLI) is implemented in this paper for a grid integrated solar photovoltaic (PV) system for eliminating the harmonics. The objective in this work is to develop and regulate the grid integrated PV system for mitigation of harmonics with incorporation of SAPF. The PV integrated SAPF delivers the active/reactive power to the grid to reduce the harmonic contents. Harmonic compensation ability of SAPF is mainly achieved by employing suitable control technique to estimate the reference current signal. Here, adaptive artificial neural networks (AANNs) like adaptive neuro-fuzzy interference system (ANFIS), Widrow–Hoff adaptive linear neuron (WH ADALINE) and Modified Widrow–Hoff adaptive linear neuron (MWH ADALINE) are employed for generating the reference current of VSI in the MLI. The control techniques are tested in MATLAB/SIMULINK as well as real-time OPAL-RT environments. It is noticed that proposed MWH ADALINE-based SAPF design shows enhanced performance to maintain the power quality (PQ) by restricting the distortion level below 5% as per the IEEE/IEC standard.
The effect of RFRP-3 on the gonadotrophic axis of the Syrian hamster : sex-dependent differences and modes of action

RFRP-3 has been shown to play a role in the regulation of the mammalian hypothalamic-pituitary-gonadal axis. The aim of this work was to determine the involvement of RFRP-3 in the regulation of the Syrian hamster reproductive axis. We report unprecedented results indicating that RFRP-3 stimulates the male Syrian hamster gonadotrophic axis, whereas it has variable effects in female Syrian hamsters. Indeed, in females the peptide inhibits the reproductive axis at the time of the LH surge on the day of proestrus, and has no effect during diestrus. We went on to characterize RFRP-3 sites of action in the Syrian hamster brain, and show that the effect of the peptide on the gonadotrophic axis is mediated directly or indirectly via GnRH neurons. Moreover, we clearly rule out the possibility of a hypophysiotrophic effect of RFRP-3 in this species. Taken together, the present data raise interesting questions regarding species- and sex-dependent effects of RFRP-3 on the mammalian gonadotrophic axis.