Miracle-dz/UniFAR-FTUs huggingface dataset:
Earnings Announcement Timing, Uncertainty, and Volatility Risk Premiums

We examine the relationship between firms’ quarterly earnings report timing and uncertainty before quarterly earnings announcements. Prior research provides conflicting predictions on how investor uncertainty and report timing are related. Using implied volatilities from equity options and the realized returns to straddle positions, we find evidence that uncertainty and volatility risk premiums are higher for firms that report later in the quarter. Further tests show the increase in option premiums is unexplained by risk factors suggesting a mispricing by investors. These results are not associated with static firm-level factors and our findings are concentrated in high growth firms.
Multitask Learning by Multiwave Optical Diffractive Network

Recently, there has been tremendous research studies in optical neural networks that could complete comparatively complex computation by optical characteristic with much more fewer dissipation than electrical networks. Existed neural networks based on the optical circuit are structured with an optical grating platform with different diffractive phases at different diffractive points (Chen and Zhu, 2019 and Mo et al., 2018). In this study, it proposed a multiwave deep diffractive network with approximately 106 synapses, and it is easy to make hardware implementation of neuromorphic networks. In the optical architecture, it can utilize optical diffractive characteristic and different wavelengths to perform different tasks. Different wavelengths and different tasks inputs are independent of each other. Moreover, we can utilize the characteristic of them to inference several tasks, simultaneously. The results of experiments were demonstrated that the network could get a comparable performance to single-wavelength single-task. Compared to the multinetwork, single network can save the cost of fabrication with lithography. We train the network on MNIST and MNIST-FASHION which are two different datasets to perform classification of 32∗32 inputs with 10 classes. Our method achieves competitive results across both of them. In particular, on the complex task MNIST_FASION, our framework obtains an excellent accuracy improvement with 3.2%. In the meanwhile, MNSIT also has the improvement with 1.15%.
Power Combining Techniques for Space-Borne GaN SSPA in Ka-Band

Highly Efficient power combining techniques are mandatory for developing solid state power amplifiers (SSPAs) for high frequency space applications. Indeed, SSPAs are designed starting from medium power components, in the range of few watts, that are combined in such a way that the equipment efficiency is kept as maximum as possible. Planar structures such as branchlines or Wilkinson provide good isolation between ports but their losses become prohibitive when both peak power and frequency are in the range of hundreds of watt and tens of GHz, respectively. In these cases, waveguide structures result to be the most appropriate. On this way, the paper presents the design and experimental characterization of two distinctive structures conceived for spatially combine sixteen 10W Gallium nitride monolithic microwave integrated circuit for realizing a Ka-band (17.3 GHz–20.2 GHz) SSPA with more than 125W of saturated output power.
Cerebral small vessel disease and its impact on the course and outcome of stroke

Cerebral small vessel disease (CSVD) is a common cause of stroke (25 % of all strokes) and has a significant contribution to development dementia, functional loss and increases the risk of death. Validation of methods for assessing the total cerebral small vessel disease burden on CT and MRI makes it possible to more accurately and fully assess the impact of the cumulative effect of cerebrovascular pathology on the development and consequences of stroke after 3 months. The aim of our study was to investigate the prognostic value of the total CSVD burden and its individual features (leukoaraiosis, lacunes, brain atrophy) on the course and outcome of stroke at 90 days. 131 patients with ischemic stroke, diagnosed according to TOAST criteria, were enrolled. All patients underwent computed tomography on a General Electric CT/e device (Italy) with a slice thickness of 3-7 mm. Leukoaraiosis was diagnosed and scored by the visual scale of Fazekas and von Swieten. Brain atrophy was assessed separately in central and cortical regions by validated standard template. Lacunes were defined according to the standard protocol. We calculated the total CSVD burden (composed leukoaraiosis, lacunes, brain atrophy) with and without brain atrophy. We assessed the severity of neurological deficit by the NIHSS scale. The functional outcome and the degree of disability or dependence in the daily activities we measured by modified Rankin scale and Barthel index. MMSE was used to assess cognitive function. Statistical analyses were performed by SPSS 25.0 software (IBM Corp., Armonk, NY, USA). We used Student's t-test or Mann-Whitney U test, Pearson or Spearman correlation and regression analysis. Our data have shown that cerebral small vessel disease is negatively correlated with the consequences of stroke and reflect brain frailty and impair regenerative potential. The degree of cognitive deficit was associated with negative prognostic consequences of stroke. The total cerebral small vessel disease burden is a valuable prognostic marker of stroke prognosis and can be used as a tool for the assessment of effectiveness of preventive and curative measures.
Target Tracking Algorithm Suitable for Fisheye Camera in Vehicle Environment

Moving target tracking is one of the core issues in the fields of automobile assisted driving and autonomous driving. This algorithm proposes a target tracking algorithm suitable for fisheye cameras in vehicle environment. A background point removal method based on median ordering is proposed to optimize the optical flow method to solve the problem of target scale change in fisheye camera videos. Multi-scale scaling processing for frames, tracking algorithm based on cyclic matrix structure (CSK), target tracking for multiple images after zooming, using fitting to determine the maximum corresponding value, reducing the error caused by target deformation on tracking results. The tracking test results of multiple fisheye camera videos in the vehicle environment show that the algorithm has high real-time tracking accuracy.
Work Readiness across Various Specializations

The employability of locals in the United Arab Emirates is a national priority and an integral part of Emiratisation, which is an affirmative action policy of the United Arab Emirates Government that promotes preferential hiring status to Emiratis. The latter safeguards national identity, economic sustainability, and political stability (Modarress, Ansari and Lockwood, 2013). The purpose of this research is to study the work readiness of Emirati graduating students across various specializations. The theoretical framework for this study is the four-factor model by Caballero, Walker and Fuller-Tyszkiewicz (2011). The four factors are personal work characteristics, organizational acumen, work competence and social intelligence. The research conducted so far on work readiness of graduates has been limited to particular disciplines (Walker, Storey, Costa, Leung, 2015; Dermott, 2007; Jollands, Jolly and Molyneaux, 2012; Haigh, Ell and Mackisack, 2013; Dermott and Ortiz, 2017). This study contributes to the existing body of knowledge as it does not focus on a single specialization and takes a broad exploratory look at work readiness across five specializations, namely business, information technology, health sciences, applied communication and engineering. 302 graduating Emirati students chosen randomly from various disciplines in different institutions participated in this quantitative research study by filling in a 60-item work readiness questionnaire. The main findings of this study is that specializations in tertiary education vary not only in terms of curriculum, technical knowledge, skills and abilities taught, but also in the preparation for employment which influences the perceptions of graduating students of their work readiness; graduating students in a health specialization perceiving to be the most work ready and graduating students in a business specialization perceiving to be the least work ready.
Comparative Analysis of Vehicle-to-Vehicle (V2V) Power Transfer Configurations without Additional Power Converters

This paper presents a comparative analysis of power transfer configurations towards vehicle-to-vehicle (V2V) battery charging operation without using additional power converters, i.e., using just the on-board battery chargers of two electric vehicles (EVs). Three access interfaces were considered, namely the ac power grid interface, the dc-link interface and the dc battery interface, which allow the establishment of eight V2V configurations. The defined configurations are described and verified through computational simulations. A comparison is performed based on quantitative data, i.e., power transfer efficiency for a given output power range, and qualitative data, i.e., flexibility and safety. According to the obtained results, it can be concluded that each V2V configuration has its pros and cons regarding efficiency, number of possible quadrant operation and need for additional equipment.
The impact of differences in soil texture within a vineyard on vine vigour, vine earliness and juice composition

Aims: The young alluvial soils of the Wairau Plains, Marlborough, New Zealand, are considered to play an important role in determining this unique wine style. The aim of this experiment was to investigate, within a single vineyard, the impact of soil texture on vine vigour, vine earliness and fruit composition.Methods and results: Trunk circumference and pruning weights, were greater as the depth to gravel increased. Soil conductivity measurements, using an electromagnetic sensor (EM38) in conjunction with global positioning related well to vine trunk circumference. Where gravels came to the surface, soil temperatures measured at 30 cm depth were consistently higher by 1 to 2 °C (air temperature was unaffected) and vine phenology was more advanced, when compared to the deep silt soils. At harvest, fruit soluble solids and pH were higher and titratable acidity lower when vines grown on shallow soils, but soil type had no significant effect on fruit yield.Conclusions and significance of the study: Vine phenology during the growing season and fruit composition at harvest but not yield, reflect changes in soil texture over quite short distances within vineyards on the Wairau Plains. Within a vineyard, the higher the proportion of gravelly soils, the more advanced the vine phenology and the riper the fruit and wine style will exhibit riper (more tropical) and lower unripe (herbaceous) characteristics on a particular date.
Integration of affine ICP into the precise localization problem of smart-AGVs: Procedures, enhancements and challenges

The localization problem in robotics has been widely studied both for indoor and outdoor applications, but is still open for improvements. In indoor environments, GPS-based methods are not preferred due to reflections, and the pose of the robot is determined according to the measurements taken around with its sensors. One of them is iterative closest point (ICP)-based localization method. ICP is a point set registration method, the essence of which is to iteratively compute the transformation between two point sets. However, it is also utilized to solve the localization problem thanks to its high precision in registration. Precise localization is important for applications that require highly accurate pose estimation, such as for smart-AGVs to be used in smart factories to reach a station at industrial standards. Traditional ICP finds transformation in terms of a rotation and translation, and thus can be directly applied to the localization problem. On the other hand, the affine variant of ICP is not adapted to solve the localization problem. In this study, the necessary arrangements to make affine ICP suitable for precise localization are given as a procedure such that the transformation between point sets is found by affine ICP, the resulting transformation is projected to rotation plane by polar decomposition and then the pose is estimated. The enhancements achieved with the usage of affine ICP in precise localization problems are demonstrated in simulation by comparing localization performance of affine ICP with that of traditional ICP. For this purpose, in a factory environment, a scenario where a smart-AGV approaching the target autonomously to carry out an operation has been prepared. The performances of the algorithms have been evaluated for five different docking stations with 30 separate experiments. Moreover, the challenges related to the affine ICP-based fine localization, in particular about finding projection of affine transformation to rotation plane, are highlighted in this study.
Certificates of confidentiality and unexpected complications for pragmatic clinical trials

The need to protect the confidentiality of research data has long been recognized. One means to help protect research data from use in civil or criminal matters in the United States is a Certificate of Confidentiality (CoC). Until recently, investigators applied for a CoC when conducting research that was sensitive, stigmatizing or where the disclosure of private information could possibly result in civil or criminal liability. However, effective October 1, 2017, CoCs are automatically issued for much research supported by the National Institutes of Health (NIH). While automatic issuance reduces administrative burden, it also poses some surprising unanticipated challenges for research in general and pragmatic clinical trials (PCTs) in particular, which are key elements of learning health systems.
Factors Related to Coastal Communities’ Water-Related Natural Disaster Awareness, Preparedness, Resilience and Recovery in Three Cyclone Nargis Affected Areas in the Ayeyarwaddy Delta Region, Myanmar

Received: 15 Jan 2020 Received in revised: 12 May 2020 Accepted: 26 May 2020 Published online: 12 Jun 2020 DOI: 10.32526/ennrj.18. 3.2020. 29 Natural disasters have a negative impact on the socio-economy of a country. This cross-sectional analytical study determined the factors that influence coastal communities’ water-related disaster awareness, preparedness, resilience and recovery in Cyclone Nargis affected areas in Myanmar. A total of 390 respondents from the three townships most affected by Cyclone Nargis in the Ayeyarwaddy Delta Region were purposively selected. Data were analyzed using SPSS Version 22.0. Associations between variables were analyzed by using binary logistic regression with p<0.05. Multivariate analysis was performed for the final model and interpreted with adjusted odds ratio and 95% confidence interval. Among respondents, more than 75% were not only aware and prepared before the disaster but had recovered and demonstrated resilience following the disaster. The respondents who had problems recovering on the “financial” index were 0.5 times less likely to exhibit recovery (OR=0.558, 95% CI=0.346-0.899, p=0.016) in binary analysis. The respondents who had problems recovering on the “health” index were 0.3 times less likely to demonstrate recovery (OR=0.387, 95% CI=0.194-0.772, p=0.007) in multivariate analysis. It is recommended that awareness and disaster management education programs that shape behavioral change are initiated which target both rural and urban areas in Myanmar.
A Synthesis of the Biology and Ecology of Sculpin Species in the Laurentian Great Lakes and Implications for the Adaptive Capacity of the Benthic Ecosystem

Abstract The Laurentian Great Lakes have experienced recent ecosystem changes that could lead to reductions in adaptive capacity and ultimately a loss of biodiversity and production throughout the food web. Observed changes in Great Lakes benthic communities include declines of native species and widespread success of invasive species like dreissenid mussels in all but Lake Superior. Understanding the ecology of native benthic deepwater preyfish and the reasons for their declines is important for predicting future losses in adaptive capacity and diversity, as well as managing the Great Lakes ecosystem to avoid such losses. Native sculpin species (Cottus bairdii, C. cognatus, C. ricei, Myoxocephalus thompsonii) historically were among the most abundant of the Great Lakes native deepwater benthic preyfish community and are an important link between offshore benthic and pelagic food webs. With one exception, these species have declined in abundance throughout the Great Lakes in recent years, but relatively little is known about their biology and ecology. This review synthesizes the available knowledge for the Great Lakes sculpin species and provides suggestions for future research efforts, which include understanding reproductive ecology and spawning behavior, connectivity and dispersal of populations, early life history, and influences of interactions with native and non-native species.
Data-Augmentation-Based Cellular Traffic Prediction in Edge-Computing-Enabled Smart City

With the massive deployment of 5G cellular infrastructures, traffic prediction has become an indispensable part of the cellular resource management system in order to provide reliable and fast communication services that can meet the increasing quality-of-service requirements of smart city. A promising approach for handling this problem is to introduce intelligent methods to implement a highly effective and efficient cellular traffic prediction model. Meanwhile, integrating the multiaccess edge computing framework in 5G cellular networks facilitates the application of intelligent traffic prediction models by enabling their implementation at the network edge. However, the data shortage and privacy issues may still be obstacles for training a robust and accurate prediction model at the edge. To address these issues, we propose a data-augmentation-based cellular traffic prediction model (ctGAN-S2S), where an effective data augmentation submodel based on generative adversarial networks is proposed to improve the prediction performance while protecting data privacy, and a long-short-term-memory-based sequence-to-sequence submodel is used to achieve the flexible multistep cellular traffic prediction. The experimental results on a real-world city-scale cellular traffic dataset reveal that our ctGAN-S2S model achieves up to 48.49% improvement of the prediction accuracy compared to four typical reference models.
Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends

The growing trend in electrical vehicle (EV) deployment has transformed independent power network and transportation network studies into highly congested interdependent network performance evaluations assessing their impact on power and transportation systems. Electrified transportation is highly capable of intensifying the interdependent correlations across charging service, transportation, and power networks. However, the evaluation of the complex coupled relationship across charging services, transportation, and power networks poses several challenges, including an impact on charging scheduling, traffic congestion, charging loads on the power grid, and high costs. Therefore, this article presents comparative survey analytics of large-scale EV integration’s impact on charging service network scheduling, transportation networks, and power networks. Moreover, price mechanism strategies to determine the charging fares, minimize investment profits, diminish traffic congestion, and reduce power distribution constraints under the influence of various factors were carried out. Additionally, the survey analysis stipulates the interdependent network performance index, ascertaining travel distance, route selection, long-term and short-term planning, and different infrastructure strategies. Finally, the limitations of the proposed study, potential research trends, and critical technologies are demonstrated for future inquiries.
Preparation of Polymeric Composites from Polypropylene and Palm Fronds and the Study of Some of Their Physical Properties

تم في هذا البحث تحضير نوع من المتراكبات البوليمرية من البولي بروبلين المنصهر كمادة أساس مع مسحوق سعف النخيل كمواد مدعمة وقد تم تقييم المواد المتراكبة من خلال دراسة بعض خواصها الميكانيكية والتي شملت مقاومة الصدمة (I.S) ومعامل يونك(E) ومقاومة الانضغاط (C·S) ومعامل المرونة وصلادة برينيل (B.H) وقد تمت المقارنة بين المتراكبات البوليمرية قبل وبعد التدعيم. ولوحظ زيادة مقاومة الصدمة وصلادة برينيل ومقاومة الانضغاطية وتمت دراسة تأثير بعض الحوامض HNO3) وH2SO4 وHCl) وبتراكيز 1.5N)و 1Nو1. 5 N) وتمت دراسة بعض الخصائص الفيزيائية كالامتصاصية ومعامل الانتشار للبولي بروبلين قبل وبعد التدعيم وقد أظهرت النتائج زيادة واضحة في قيم هذه الخصائص بزيادة تركيز الحامض وزمن غمر البوليمر في المحلول الحامضي.
Plasma processing of poly(ethylene terephthalate) (PET) in an oxygen decoupled plasma source

Plasma Processing of Poly(ethylene terepthalate) (PET) in an Oxygen Decoupled Plasma Source . In a novel use of a decoupled plasma system (DPS), polymer samples were exposed to an energetic oxygen discharge in order to modify the local surface properties of poly(ethylene terepthalate) (PET) samples. Samples were placed at differing distances (13 cm and 20 cm) from the center of the discharge coil to assess the change in interaction between the sample and the DPS discharge resulting from an increase in sample distance from the center of the discharge coil. Radio frequency discharge generated at 13.56 MHz was used to modify the surface of 200 mm samples. The discharge was generated in a pure oxygen atmosphere at varying pressures of 100, 300, 500, and 1000 mtorr at applied power levels of 250, 500, 750, and 1000 watts. Optical emission spectroscopy (OES), used as a diagnostic tool, allowed non-invasive monitoring of spectra enabling the characterization of the interaction between the oxygen discharge and the samples during processing. Spectra were acquired between 250 nm and 900 nm. The spectra showed increased overall intensity related to the increase in power. Additionally, the spectra showed a decrease in intensity at pressures above 300 mtorr attributable to increased recombination of oxygen. Increased intensities of CO, OH and atomic OI, andHα, as well as a continuum attributed to chemiluminescent recombination of CO, were also seen as applied power levels increased. Surface energy (γ) of the PET samples was monitored using the sessile drop method equating the change in the contact angle to the degree of change in the surface energy of the sample as a result of processing. The samples showed a reduction in contact angle of ii 48 degrees, indicating a change from the initial hydrophobic (78◦) to an average value of 30◦ after processing. Additionally, visible changes were seen in the samples ranging from a light roughening of the surfaces at lower applied power levels to distortion and melting of the samples at applied power levels of 750 and 1000 watts.