Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloud Versus Edge Deployment Strategies of Real-Time Face Recognition Inference

Choosing the appropriate deployment strategy for any Deep Learning (DL) project in a production environment has always been the most challenging problem for industrial practitioners. There are several conflicting constraints and controversial approaches when it comes to deployment. Among these problems, the deployment on cloud versus the deployment on edge represents a common dilemma. In a nutshell, each approach provides benefits where the other would have limitations. This paper presents a real-world case study on deploying a face recognition application using MTCNN detector and FaceNet recognizer. We report the challenges faced to decide on the best deployment strategy. We propose three inference architectures for the deployment, including cloud-based, edge-based, and hybrid. Furthermore, we evaluate the performance of face recognition inference on different cloud-based and edge-based GPU platforms. We consider different models of Jetson boards for the edge (Nano, TX2, Xavier NX, Xavier AGX) and various GPUs for the cloud (GTX 1080, RTX 2080Ti, RTX 2070, and RTX 8000). We also investigate the effect of deep learning model optimization using TensorRT and TFLite compared to a standard Tensorflow GPU model, and the effect of input resolution. We provide a benchmarking study for all these devices in terms of frames per second, execution times, energy and memory usages. After conducting a total of 294 experiments, the results demonstrate that the TensorRT optimization provides the fastest execution on all cloud and edge devices, at the expense of significantly larger energy consumption (up to +40% and +35% for edge and cloud devices, respectively, compared to Tensorflow). Whereas TFLite is the most efficient framework in terms of memory and power consumption, while providing significantly less (-4% to -62%) processing acceleration than TensorRT. Practitioners Note: The study reported in this paper presents the real-challenges that we faced during our development and deployment of a face-recognition application both on the edge and on the cloud, and the solutions we have developed to solve these problems. The code, results, and interactive analytic dashboards of this paper will be put public upon publication.
Robotic biomimicry demonstrates behavioral control of planktonic dispersal in the sea

Plankton are widely considered to be at the mercy of ocean currents, even after decades of research revealing that plankton regulate dispersal by positioning themselves in surface and bottom currents flowing in different directions. The degree of effectiveness of these behaviors remains controversial, because tiny plankters cannot be tracked at sea. Here, we experimentally tested the effectiveness of 3 vertical positioning behaviors in nature by developing a biomimetic robot that emulates them. We conducted a challenging test by deploying them in complex circulation during strong upwelling winds and wind relaxation and reversal events. Behavior alone dramatically affected transport. Transport trajectories of robots with 3 different behaviors diverged markedly while those sharing the same behavior were very similar. Moreover, all 3 be haviors produced trajectories that matched previously modeled projections during both upwelling and relaxation conditions at the study site: shallow plankton disperse far, deep plankton move little, and plankton migrating from depth during the day to the surface at night travel an inter mediate distance. The ability of weakly swimming plankton to control their fate and replenish populations in a dynamic ocean is of central importance to the ecology and evolution of marine life and to the management of resources in a changing climate.
EFFECT OF WHOLE-BODY VIBRATION ON SPASTIC DIPLEGIC CHILDREN

1 Assistant Professor, Department of Physical Therapy for Pediatrics, Faculty of Physical Therapy, Cairo University, Egypt 2 Assistant Professor Basic Sciences Department -Faculty of Physical Therapy– Cairo University and Heliopolis University for sustainable development, Egypt. 3 lecturer of Physical Therapy, Department of Physical Therapy for internal medicine and neurology, Faculty of Physical Therapy Heliopolis University for sustainable development, Egypt. 4 lecturer of Physical Therapy department for integumentary, Faculty of Physical Therapy Deraya University, Egypt. 5 Assistant Professor Department of Physical Therapy for Pediatrics – Faculty of Physical Therapy – Cairo University and department of Physical Therapy and Health Rehabilitation, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
Effects of Direct Thermal Method Processing Parameters on Mechanical Properties of Semisolid A6061 Feedstock

This paper highlights the effects of pouring temperature and holding time on the mechanical properties of aluminium 6061 semisolid feedstock billets. The semisolid metal feedstock billets were prepared by a direct thermal method (DTM), in which the molten metal was poured into a cylindrical copper mould with a different combination of pouring temperature and holding time before it was solidified in room temperature water. The results show that the sample with pouring temperature slightly above aluminium 6061 liquidus temperature has the lowest porosity, thereby the highest mechanical properties value. The sample with a pouring temperature of 660 °C and holding time of 60 s has the density, tensile strength and hardness properties of 2.701 g/cm3, 146.797 MPa, and 86.5 HV, respectively. Meanwhile, the sample at a pouring temperature of 640 °C and holding time of 20 s has density, tensile strength and hardness properties of 2.527 g/cm3, 65.39 MPa, and 71.79 HV, respectively. The density and fractography tests were conducted to confirm the existence of porosity within the samples. The results from these experimental works suggested that the mechanical properties of DTM semisolid feedstock billet merely depended on processing parameters, which influenced the porosity level within the feedstock billet, thus directly affected their mechanical properties.
Multi-Criterional Choice of An Alternative under the Rules of Fuzzy Products with Some Reliability Degree

One of the main problems of decision-making tasks is the need to take into account subjective expert assessments, the complete consistency of which is rare, and the choice of the best alternative. The complexity of the connections between the many-sided aspects of the decision-making situation and the lack of an accurate forecast of the consequences leads to the fact that when assessing and choosing alternatives, it is possible, and often necessary, to use and process qualitatively fuzzy estimates. In decision-making situations, when at least one of the elements (outcomes, criteria, preferences, expert opinions, etc.) is described qualitatively, indistinctly, there are problems of multi-criteria decision-making with fuzzy initial information. <br><br>Let’s consider the solution to the problem of multi-criteria choice based on the rules of fuzzy conditional inference, which have the form of fuzzy statements, the conditions and conclusions of which, along with expert assessments of the criteria, are presented in the form of interval fuzzy numbers of the second type (IT2FN). The convolution of private implications in each statement is made according to Lukasiewicz's rule. To reduce the type and defuzzify the resulting IT2FN, the Karrnik-Mendel algorithm was used to construct the minimum and maximum centroids of nested fuzzy sets of the first type, which give an estimate of the utility interval for each alternative. To refine the obtained utility estimates, under conditions of incomplete definiteness of statements, using the generalized Bayesian inference mechanism, adjusted estimates of the utility intervals of alternatives are constructed. By comparing these intervals, a larger interval is determined and the corresponding alternative is taken as a solution to the problem under consideration. <br><br>The application of the proposed approach to solving the problem of multicriteria selection of the most corroded section of a gas pipeline with ambiguous expert opinions is shown. To date, specific practical and theoretical results have been obtained for decision-making problems with fuzzy initial information.
Water on the Fen Mire as a Problemin the Protection of Globally ThreatenedSpecies: Long-Term Changesin Aquatic Warbler Numbers

This paper presents the results of 11 years study of aquatic warblers in the Roskosz Nature Reserve in eastern Poland. The study was carried out in fen mires near Chełm, in the proximity of the Polish-Ukrainian boundary. The number of aquatic warblers was correlated with the mean water level and with the mean groundwater level. We found that the higher the surface water level, the smaller the number of singing males. The largest number of males (density 10.9 singing males per 10 ha) was found when the mean water level was 23.7 cm, and the smallest number (density 2.1 singing males per 10 ha) when the mean water level was 35.7 cm. These results can be useful in studies that focus on the optimal habitat conditions for breeding of aquatic warblers. This is the first systematic study in calcareous Cladium mariscus fen mires.
Simultaneous Learning of Moving and Active Perceptual Policies for Autonomous Robot

Humans can move their bodies and eyes actively to perceive the state of the environment they are surrounded by. Autonomous robots are needed to learn this ability, so called active perception, to behave as humans do. In this paper, we propose a reinforcement learning algorithm to make the robots have the perceptual ability. In our algorithm, we simultaneously train two agents which control the robot and its sensor on the robot to achieve a task. We conducted experiments on navigation tasks in a 3D environment where useful information for the task achievement is partially occluded. The experimental results show that our algorithm can obtain better perceptual behavior and achieve higher success rates than conventional reinforcement learning algorithms.
Examining the effect of reduced crew sizes on submarine command team workload

The Command Team Experimental Test-Bed (ComTET) is a body of work that aims to understand the current functionality of submarine command teams and future ways of working. To facilitate their research, the ComTET team built a submarine control room simulator for testing purposes. Previous research from the ComTET research program ran baseline testing to understand current functionalities in the control room. This generated a number of recommendations that informed the design of a new control room configuration, whereby the crew size was reduced by removing one Sonar Operator and one Target Motion Analyst Operator. This study tested 70 participants (ten teams of seven individuals), all of which received general maritime and role-specific training using the ComTET tutorial package. Each team was required to complete high and low demand versions of three scenario types: Return to Periscope Depth, Inshore Operations, and Dived Tracking. Following the completion of each scenario, the participants’ subjective workload was self-reported using an electronic version of the Bedford Workload scale. The results provided in this paper show a preliminary analysis of workload scores from a subset of four teams. Teams were taken from both the baseline and reduced crew size configuration. Results suggested that the subjective workload of operators was affected by scenario demand and type. Additionally, the results indicate that the reduction of crew size increased the workload placed on operators in the command team. Therefore, submarine command teams with reduced crew sizes are more likely to be faced with higher workload levels during submarine operations.
Osteolytic effects of tumoral estrogen signaling in an estrogen receptor-positive breast cancer bone metastasis model

Aim: Estrogen receptor α-positive (ER+) subtypes of breast cancer have the greatest predilection for forming osteolytic bone metastases (BMETs). Because tumor-derived factors mediate osteolysis, a possible role for tumoral ERα signaling in driving ER+ BMET osteolysis was queried using an estrogen (E2)-dependent ER+ breast cancer BMET model. Methods: Female athymic Foxn1nu mice were inoculated with human ER+ MCF-7 breast cancer cells via the left cardiac ventricle post-E2 pellet placement, and age- and dose-dependent E2 effects on osteolytic ER+ BMET progression, as well as direct bone effects of E2, were determined. Results: Osteolytic BMETs, which did not form in the absence of E2 supplementation, occurred with the same frequency in young (5-week-old) vs. skeletally mature (16-week-old) E2 (0.72 mg)-treated mice, but were larger in young mice where anabolic bone effects of E2 were greater. However, in mice of a single age and across a range of E2 doses, anabolic E2 bone effects were constant, while osteolytic ER+ BMET lesion incidence and size increased in an E2-dose-dependent fashion. Osteoclasts in ER+ tumor-bearing (but not tumor-naive) mice increased in an E2-dose dependent fashion at the bone-tumor interface, while histologic tumor size and proliferation did not vary with E2 dose. E2-inducible tumoral secretion of the osteolytic factor parathyroid hormone-related protein (PTHrP) was dose-dependent and mediated by ERα, with significantly greater levels of secretion from ER+ BMET-derived tumor cells. Conclusion: These results suggest that tumoral ERα signaling may contribute to ER+ BMET-associated osteolysis, potentially explaining the greater predilection for ER+ tumors to form clinically-evident osteolytic BMETs.
Prevalence of substance abuse and use among Australian youth: A literature review

The frequency of abusing substance and its use is a pervasive one. The study sought to ascertain the burden of using substance and abuse among the Australian youth. Secondary sources were employed, offering a vivid representation of the non-ending problem of using substance and abuse among the Australian youth. A literature review was conducted using the preferred reporting items for systematic reviews and meta-analyses guidelines to produce evidence from relevant referred publications, and other papers that focus on using substance and abuse among the Australian youth. The method used in looking for literature includes: Websites, databases, and keywords. A final list of six unique articles that satisfied the conditions was reviewed. Evidence suggests that substance used and abused is very prevalent among the youth of Australians and that there has been increase in use. Additional research is needed to comprehend the trends in the various substance uptakes and use pattern among Australian youth. Pragmatic interventions may have to be established and be made accessible to the youth group who are heavily using these substances. Key words: Youth, substance use, substance abuse, prescription drug abuse, drug abuse treatment, substance abuse treatment.
Local and regional patterns of fish assemblages in coastal lagoons surrounded by mangroves, Gulf of Tehuantepec in the south Pacific of Mexico

We analyzed the local variation of fish assemblages in four coastal lagoon systems surrounded by mangroves, draining into the Gulf of Tehuantepec (Pacific versant of Mexico), and determined the spatial patterns of alpha, beta, and gamma diversity. Fish were sampled between 2004 and 2016 at 63 sites using cast nets. The collected data were supplemented with information obtained from published works for three other coastal lagoons for the regional analysis. Local richness was high (89 species in a total of 19,017 specimens in four systems). Locally, dissolved oxygen, depth, and distance to mangrove were variables that significantly affected richness and abundance of fish in one or more systems. The Chantuto-Panzacola system showed the highest richness, significantly different from the other systems, although the trophic groups were similar. Regionally, two, Istmo and Soconusco complexes were identified, whose turnover rate (0.36) and gamma diversity (176) increased from north to south. Fish species richness and abundance increased with growing mangrove area, both locally and regionally, making this a highly explanatory variable. The Gulf of Tehuantepec is an environmentally heterogeneous region, with ecological patterns defined according to the spatiotemporal scale, which should be considered in the delineation of ecoregions and coastal management planning.
An Empirical Investigation Between CO2 emission, Energy Consumption, Export and Economic growth: A Case of China

The purpose of this study is to examine the long-run and short-run relationship between environmental degradation (proxied by C02 emission), gross domestic product, energy consumption and exports in China over the period from 1971 to 2014, using time-series analysis. The study used the annual data which was obtained from a World Development Indicator of the World Bank. The Augmented Dickey-Fuller and Phillips-perron test is applied in this study to establish the stationarity among datasets. Their results show that all variables were non-stationary at level (I(0)). However, they became stationary at the first difference (I(1)). Base on the findings, a well-defined Autoregressive Distributed Lag Model (ARDL) was applied to the datasets, and the results were in support of the long-run and short-run relationships among the variables. C02 emission and exports accelerate economic growth, however, energy consumption has an inverse impact on economic growth; economic growth and energy consumption also play a significant impact on C02 emission whereas export has a significant negative impact. Furthermore, the granger causality test shows the existence of bi-directional causality between exports and economic growth. A unidirectional causality is running from energy consumption and C02 emission to economic growth as well as energy consumption and C02 emission to exports. The findings support that C02 emission and exports have a substantial impact on the economic growth of China. Furthermore, energy use and economic growth accelerate C02 emission. This study concludes with an examination of the policy implications of the findings. -----------------------------------------------------------------------* Corresponding author. International Journal of Sciences: Basic and Applied Research (IJSBAR) (2020) Volume 54, No 4, pp 151-169 152
Can the Business Outlook Survey Help Improve Estimates of the Canadian Output Gap?

central bank policy, produced independently from the Bank’s Governing Council. This work may support or challenge prevailing policy orthodoxy. Therefore, the views expressed in this note are solely those of the authors and may differ from official Bank of Canada views. No responsibility for them should be attributed to the Bank. ISSN 1914-0568 ©2020 Bank of Canada Staff Discussion Paper/Document d’analyse du personnel — 2020-14
THE VALUE OF DIFFERENT ANTHROPOMETRIC VARIABLES IN ASSESSING CARDIOMETABOLIC RISK

Objective. To investigate which anthropometric parameter best correlates with modifications in blood glucose and blood pressure (BP). Material and method. 135 subjects were included in the study. We measured weight, height, waist circumference (WC), BP and calculated body mass index (BMI) and waist-to-height ratio (WHtR). We determined glycated hemoglobin A1c (HbA1c) and performed an oral glucose tolerance test (OGTT) under standard conditions. Results. HbA1c increased with BMI, WC and WHtR. We found statistically higher values of fasting blood glucose (FBG) in obese (P=0.001), in those with large WC (P=0.028) and in those with WHtR0.5 (P=0.028). Using ROC curves with area under curve (AUC) of BMI, WC and WHtR, WHtR was the best predictor for HbA1c5.7% (AUC=0.665, 95%CI:0.570-0.760), FBG100mg/dl (AUC=0.705, 95%CI:0.617-0.793) and high blood pressure (AUC=0.768, 95%CI:0.689-0.848). Conclusions: WHtR was the best predictor for elevated HbA1c, FBG and blood pressure, hence people with a WHtR0.5 should be included in preventive strategies. keywords: abdominal obesity, waist-to-height ratio, prediabetes, cardiovascular risk
Comprehensive Modelling of Renewable Energy Based Microgrid for System Level Control Studies

Renewable energy will constitute the backbone of the future sustainable energy systems by forming onsite microgrids. This reduces the utility grid burden and outages. Besides, microgrids can address the issues of greenhouse gasses, global warming, fossil fuel evaporations, slow start-up/shutdown times, etc. However, their dependency on geography/climatic conditions lead to the exhibition of intermittent output characteristics. Moreover, a majority of microgrids must be interfaced with the utility grid through power electronic converters, which are static and do not possess any kinetic energy. Due to this nature, these systems are highly sensitive to events, and thereby, creating issues with fast detection of islanding during abnormalities. Furthermore, for superior power quality, stability, energy yield, reliability, and protection, they must be properly coordinated with the utility grid or neighbour microgrids via robust control mechanisms. To study all these factors, lead to a better system, it is desired to have a perfect model of the system. Many literary works have developed microgrid models by focusing on a very particular aspect or component of it with respect to their area of research. But, comprehensive models are much required for many different studies as mentioned above. Further, the comprehensive model helps in detailed system-level studies. So, with this intension, this paper proposes the development of comprehensive model of the microgrid which involves all its key characteristics/elements. Further, system-level control study is presented to persuade the importance of this proposed model. From results, the WJC method is recommended as the best method to design microgrid’s controller.
ANALYTICAL EXPRESSION FOR UNCERTAINTY PROPAGATION OF AERIAL COOPERATIVE NAVIGATION

In this paper, the propagation of uncertainty in a cooperative navigation algorithm (CNA) for a group of flying robots (FRs) is investigated. Each FR is equipped with an inertial measurement unit (IMU) and range-bearing sensors to measure the relative distance and bearing angles between the agents. In this regard, an extended Kalman filter (EKF) is implemented to estimate the position and rotation angles of all the agents. For further studies, a relaxed analytical performance index through a closed-form solution is derived. Moreover, the effects of the sensors noise covariance and the number of FRs on the growth rate of the position error covariance is investigated. Analytically, it is shown that the covariance of position error in the vehicles equipped with the IMU is proportional to the cube of time. However, the growth rate of the navigation error is, considerably more rapid compared to a mobile robot group. Furthermore, the covariance of position error is independent of the path and noise resulting from the relative position measurements. Further, it merely depends on both the size of the group and noise characteristics of the accelerometers. Lastly, the analytical results are validated through comprehensive Guidance, Navigation, and Control (GNC) in-the-loop simulations.