Miracle-dz/UniFAR-FTUs huggingface dataset:
Global estimation of areas with suitable environmental conditions for mariculture species

Aquaculture has grown rapidly over the last three decades expanding at an average annual growth rate of 5.8% (2005–2014), down from 8.8% achieved between 1980 and 2010. The sector now produces 44% of total food fish production. Increasing demand and consumption from a growing global population are driving further expansion of both inland and marine aquaculture (i.e., mariculture, including marine species farmed on land). However, the growth of mariculture is dependent on the availability of suitable farming areas for new facilities, particularly for open farming practices that rely on the natural oceanic environmental parameters such as temperature, oxygen, chlorophyll etc. In this study, we estimated the marine areas within the exclusive economic zones of all countries that were suitable for potential open ocean mariculture activities. To this end, we quantify the environmental niche and inferred the global habitat suitability index (HSI) of the 102 most farmed marine species using four species distribution models. The average weighted HSI across the four models suggests that 72,000,000 km2 of ocean are to be environmentally suitable to farm one or more species. About 92% of the predicted area (66,000,000 km2) is environmentally suitable for farming finfish, 43% (31,000,000 km2) for molluscs and 54% (39,000,000 km2) for crustaceans. These predictions do not consider technological feasibility that can limit crustaceans farming in open waters. Suitable mariculture areas along the Atlantic coast of South America and West Africa appear to be most under-utilized for farming. Our results suggest that factors other than environmental considerations such as the lack of socio-economic and technological capacity, as well as aqua feed supply are currently limiting the potential for mariculture expansion in many areas.
DRL-cloud: Deep reinforcement learning-based resource provisioning and task scheduling for cloud service providers

Cloud computing has become an attractive computing paradigm in both academia and industry. Through virtualization technology, Cloud Service Providers (CSPs) that own data centers can structure physical servers into Virtual Machines (VMs) to provide services, resources, and infrastructures to users. Profit-driven CSPs charge users for service access and VM rental, and reduce power consumption and electric bills so as to increase profit margin. The key challenge faced by CSPs is data center energy cost minimization. Prior works proposed various algorithms to reduce energy cost through Resource Provisioning (RP) and/or Task Scheduling (TS). However, they have scalability issues or do not consider TS with task dependencies, which is a crucial factor that ensures correct parallel execution of tasks. This paper presents DRL-Cloud, a novel Deep Reinforcement Learning (DRL)-based RP and TS system, to minimize energy cost for large-scale CSPs with very large number of servers that receive enormous numbers of user requests per day. A deep Q-learning-based two-stage RP-TS processor is designed to automatically generate the best long-term decisions by learning from the changing environment such as user request patterns and realistic electric price. With training techniques such as target network, experience replay, and exploration and exploitation, the proposed DRL-Cloud achieves remarkably high energy cost efficiency, low reject rate as well as low runtime with fast convergence. Compared with one of the state-of-the-art energy efficient algorithms, the proposed DRL-Cloud achieves up to 320% energy cost efficiency improvement while maintaining lower reject rate on average. For an example CSP setup with 5,000 servers and 200,000 tasks, compared to a fast round-robin baseline, the proposed DRL-Cloud achieves up to 144% runtime reduction.
Interactive Effects of Physical Fitness and Body Mass Index on the Risk of Hypertension.

IMPORTANCE High body mass index (BMI) and low physical fitness are risk factors for hypertension, but their interactive effects are unknown. Elucidation of interactions between these modifiable risk factors may help inform more effective interventions in susceptible subgroups. OBJECTIVE To determine the interactive effects of BMI and physical fitness on the risk of hypertension in a large national cohort. DESIGN, SETTING, AND PARTICIPANTS This cohort study included all 1,547,189 military conscripts in Sweden from January 1, 1969, through December 31, 1997 (97%-98% of all 18-year-old men nationwide each year), who were followed up through December 31, 2012 (maximum age, 62 years). Data analysis was conducted August 1 through August 15, 2015. EXPOSURES Standardized aerobic capacity, muscular strength, and BMI measurements obtained at a military conscription examination. MAIN OUTCOMES AND MEASURES Hypertension identified from outpatient and inpatient diagnoses. RESULTS A total of 93,035 men (6.0%) were diagnosed with hypertension in 39.7 million person-years of follow-up. High BMI and low aerobic capacity (but not muscular strength) were associated with increased risk of hypertension, independent of family history and socioeconomic factors (BMI, overweight or obese vs normal: incidence rate ratio, 2.51; 95% CI, 2.46-2.55; P < .001; aerobic capacity, lowest vs highest tertile: incidence rate ratio, 1.50; 95% CI, 1.47-1.54; P < .001). Aerobic capacity was inversely associated with hypertension across its full distribution (incidence rate ratio per 100 W, 0.70; 95% CI, 0.69-0.71; P < .001). A combination of high BMI (overweight or obese vs normal) and low aerobic capacity (lowest vs highest tertile) was associated with the highest risk of hypertension (incidence rate ratio, 3.53; 95% CI, 3.41-3.66; P < .001) and had a negative additive and multiplicative interaction (P < .001). Although high BMI was a significant risk factor for hypertension, low aerobic capacity also was a significant risk factor among those with normal BMI. CONCLUSIONS AND RELEVANCE In this large national cohort study, high BMI and low aerobic capacity in late adolescence were associated with higher risk of hypertension in adulthood. If confirmed, our findings suggest that interventions to prevent hypertension should begin early in life and include not only weight control but aerobic fitness, even among persons with normal BMI.
Searching for Maximum Out-Degree Vertices in Tournaments

A vertex $x$ in a tournament $T$ is called a king if for every vertex $y$ of $T$ there is a directed path from $x$ to $y$ of length at most 2. It is not hard to show that every vertex of maximum out-degree in a tournament is a king. However, tournaments may have kings which are not vertices of maximum out-degree. A binary inquiry asks for the orientation of the edge between a pair of vertices and receives the answer. The cost of finding a king in an unknown tournament is the number of binary inquiries required to detect a king. For the cost of finding a king in a tournament, in the worst case, Shen, Sheng and Wu (SIAM J. Comput., 2003) proved a lower and upper bounds of $\Omega(n^{4/3})$ and $O(n^{3/2})$, respectively. In contrast to their result, we prove that the cost of finding a vertex of maximum out-degree is ${n \choose 2} -O(n)$ in the worst case.
Comparison of scrape-off layer profiles in outboard-versus inboard-limited plasmas in Tore Supra

In the Tore Supra tokamak, the scrape-off layer profiles of discharges limited either on the inboard or on the outboard side are compared. Inboard-limited discharges are characterized by substantially longer SOL e-folding lengths of ion and electron temperatures and electron density measured near the top of the plasma, providing strong evidence that the ion and electron energy transport across the SOL is enhanced on the outboard side, similar to the particle transport. The parallel heat flux density extrapolated to the last closed flux surface is found to be inversely proportional to its e-folding length in the SOL. The outboard limiters thus receive higher and more peaked heat loads than the inboard limiters. These results are important for the optimization of the plasma start-up scenario and design of the first wall in ITER.
against frame and collude attacks of third party auditor

Cloud computing has been envisioned as the next generation architecture of the IT enterprise, but there exist many security problems. A significant problem encountered in the context of cloud storage is whether there exists some potential vulnerabilities towards cloud storage system after introducing third parties. Public verification enables a third party auditor (TPA), on behalf of users who lack the resources and expertise, to verify the integrity of the stored data. Many existing auditing schemes always assume TPA is reliable and independent. This work studies the problem what if certain TPAs are semi-trusted or even potentially malicious in some situations. Actually, the authors consider the task of allowing such a TPA to involve in the audit scheme. They propose a feedback-based audit scheme via which users are relaxed from interacting with cloud service provider (CSP) and can check the integrity of stored data by themselves instead of TPA yet. Specifically, TPA generates the feedback through processing the proof from CSP and returns it to user which is yet unforgeable to TPA and checked exclusively by user. Through detailed security and performance analysis, the author's scheme is shown to be more secure and lightweight.
Influence of Pixel Design on Charge Transfer Performances in CMOS Image Sensors

The influence of pixel design on image lag is investigated by focusing on two different aspects which impact the charge transfer. First, it is confirmed that the transfer gate (TG) channel doping profile strongly affects image lag. Introducing a step under the TG in the potential diagram, due to the doping implant differences in the channel, enables very good transfer performances by limiting spillback of the charge to the photodiode. On the other hand, it is demonstrated that the overlap between the two implants used to create the step can produce a potential barrier under the TG which extension increases the image lag. Then, the influence of pixel layout geometrical parameters (e.g., the photodiode size, the TG length, and the floating diffusion area) on the charge transfer efficiency is clarified. The whole study conclusions allow identifying the design parameter limiting the transfer efficiency in a given design and the possible design-based solutions to improve it.
QoE-Based Resource Allocation for Heterogeneous Multi-Radio Communication in Software-Defined Vehicle Networks

Recently, vehicle to everything (V2X) communications have drawn a significant amount of attention. Emerging V2X applications demand the efficient utilization of heterogeneous access technologies, such as long-term evolution (LTE), Wi-Fi, and dedicated short-range communications. This work first develops a software-defined networking-based application-layer scheme to exploit the available bandwidth from the LTE and Wi-Fi networks in vehicle-to-infrastructure (V2I) communication. The newly proposed scheme utilizes the vehicles’ states information to obtain an optimal association of the vehicles with different access points for maximizing the system’s quality of experience (QoE) of all cars. We then incorporate the vehicle-to-vehicle (V2V) communications to further improve performance when some users’ V2I QoEs are not satisfactory. A heuristic solution that jointly determines the resource allocation as well as V2I and V2V connections are derived. The proposed schemes are evaluated in NS-3 to illustrate their good performance and low computational complexity.
Design and Analysis of a Novel Modular-Stator Tubular Permanent-Magnet Vernier Motor

This paper proposes a new modular-stator tubular permanent-magnet (PM) Vernier motor. The proposed motor offers a good fault-tolerant capability and an improved force performance, suitable for the electromagnetic active vehicle suspension. The proposed motor artfully integrates PM Vernier motors and tubular motors together, offering a zero-net radial force between the armature and mover, and the robust mover structure and high thrust force. Meanwhile, the modular complementary stator structure is designed to decouple the adjacent phase windings, hence offering the desired fault-tolerant capability. Moreover, the PMs with two magnetized directions are adopted, namely radially and axially. One is used to produce the main flux, while another can reduce fringing leakage flux, hence increasing the thrust force. The electromagnetic performances are analyzed by using the finite-element method, verifying the effectiveness of the theoretical analysis.
Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications

We present a tactile telepresence system for real-time transmission of information about object stiffness to the human fingertips. Experimental tests were performed across two laboratories (Italy and Ireland). In the Italian laboratory, a mechatronic sensing platform indented different rubber samples. Information about rubber stiffness was converted into on-off events using a neuronal spiking model and sent to a vibrotactile glove in the Irish laboratory. Participants discriminated the variation of the stiffness of stimuli according to a two-alternative forced choice protocol. Stiffness discrimination was based on the variation of the temporal pattern of spikes generated during the indentation of the rubber samples. The results suggest that vibrotactile stimulation can effectively simulate surface stiffness when using neuronal spiking models to trigger vibrations in the haptic interface. Specifically, fractional variations of stiffness down to 0.67 were significantly discriminated with the developed neuromorphic haptic interface. This is a performance comparable, though slightly worse, to the threshold obtained in a benchmark experiment evaluating the same set of stimuli naturally with the own hand. Our paper presents a bioinspired method for delivering sensory feedback about object properties to human skin based on contingency–mimetic neuronal models, and can be useful for the design of high performance haptic devices.
Experimental Validation of a Steady State Model Synthesis Method for a Three-Phase Unbalanced Active Distribution Network Feeder

This paper presents the field validation of a method that performs steady-state model synthesis (SSMS) of active distribution networks using syncrophasor measurements. The validation is performed by applying the SSMS method on a real active distribution feeder network by utilizing the measurements from real phasor measurement units (PMUs) installed at the EPFL campus. An extended version of total vector error and a power flow comparison at the PMU buses are used as performance assessment metrics. A real-time hardware-in-the-loop simulations set up at the Distributed Energy System Laboratory is used for further performance assessment of the SSMS application. The effectiveness of the SSMS application is demonstrated by testing it extensively for several different case studies.
FPAA/Memristor Hybrid Computing Infrastructure

This paper presents a circuit in which tungsten oxide -based analog memristors are post-processed on a CMOS-based Field-Programmable Analog Array Integrated Circuit (FPAA-IC). FPAAs are powerful tools for rapid analog experimentation, prototyping and power-efficient computing, and they allow custom analog circuits to be built and reconfigured. The primary motivation for this work is to introduce and demonstrate the operation of the FPAA/memristor hybrid circuit and the board-level infrastructure, and to form a basis for subsequent empirical work on analog memristive computing. The experiments shown in this paper demonstrate a successful fabrication of memristors on the FPAA substrate, and the usefulness of the hybrid computing infrastructure in terms of experimentation with memristors. The experiments suggest that a single state variable cannot capture the adaptation of a memristor. To this end, a SPICE compatible memristor model with two state variables is presented. Furthermore, a memristor-based adaptive coincidence detector is demonstrated on the FPAA/Memristor computing infrastructure.
Constructing an enriched domain taxonomy for hindi using word embeddings

Domain-specific taxonomies constitute a valuable resource as they offer extensive support in information retrieval related activities like browsing, searching, recommendations and personalization. Such taxonomies can bridge the gap between the lack of domain-specific querying knowledge in potential users and the actual content. In case of multilingual content, taxonomies can play a pivotal role in boosting search performance for content across language barriers. In this paper, a domain-agnostic framework for building an evolving, domain-specific taxonomy for the Hindi, given a set of well-organized data points is proposed. The approach is intended for designing a hierarchical taxonomy enriched with synonyms and other morphological variants using WordNet and Word2vec models respectively. The hierarchical structure acts as a base which binds the taxonomy to a given domain. Such enrichment can improve taxonomy coverage within the given domain. The focus is also on building a taxonomy that can self-evolve over time, with high precision and recall, with minimal manual effort.
Enriched Gabor Feature Based PCA for Face Recognition with One Training Image per Person

Gabor feature based classification approaches are widely used in face recognition, because they are insensitive to changes in illumination and facial expression. However, most of strategies only use the magnitude of the Gabor wavelet representation of images to generate feature vectors. When only single training image per person is available, the performance of these methods may be limited. In this paper, by making use of the slope angle as well as the magnitude of the Gabor wavelet response, we propose a novel Enriched Gabor feature based Principal Component Analysis (EGPCA) algorithm for face recognition with one training image per person. Experiment results show that the algorithm has better performance than other methods such as (PC)$^{2}$A, E(PC)$^{2}$A and SVD perturbation in a face recognition task when using the FERET database.
A Semi-parametric Recursive Trivariate Probit Modeling of the Contemporaneous Dynamics of Literacy, Labor Market Participation and Poverty in Burkina Faso: What role does Formal Education Play?

This research contributes to the overall debate on education for sustainable development (ESD) by shedding lights on the contributing role of formal education to the contemporaneous dynamics of literacy, labor market participation and poverty reduction in Africa, with a focus on Burkina Faso. The study uses a semi-parametric recursive trivariate probit modeling approach, and data from the 2014 National Survey on Household Living Conditions in Burkina Faso. The results show that the embraced systemic approach in this analysis is statistically significant as shown by the 95% confidence intervals on the three correlation coefficients in the model. Furthermore, education does improve literacy skills, however improved literacy skills in itself does not guaranty active labor market participation in Burkina Faso. Active labor market participation seem to be affected by labor market rates of return, and individual reservation wage (or income). When labor market rate of return is short of high literacy skilled individuals’ reservation wage, then the natural response is a choice of inactivity in the labor market, by the later group. Simultaneously however, it is found that active labor market participation leads to poverty reduction; therefore, in addition to new industrial policies for structural transformation of the economy, policy makers in Burkina Faso should consider education and minimum wage reforms to give highly literate household members the incentive to be active in the labor market.
Band Structures and Transport Properties of Half-Heusler Compounds NbMSb (M = Fe, Ru)

The band structures and transport properties of Half-Heusler compounds NbFeSb and NbRuSb were studied using ab initio calculations and the Boltzmann transport equation with constant scattering time approximation (CSTA). Both compounds were identified as good p-type thermoelectric materials because of the combination of heavy and light bands in the valence band maximum (VBM). The Seebeck coefficients for NbRuSb were lower than that for NbFeSb; while the electrical conductivities for NbRuSb were little higher than that for NbFeSb. Consequently, the power factors in the p-type regimes for both compounds were similar at a given temperature. NbFeSb and NbRuSb could be efficient materials for thermoelectric generators based on the results in the present investigation.
Spatial variation in high-frequency oscillation rates and amplitudes in intracranial EEG

Objective To assess the variation in baseline and seizure onset zone interictal high-frequency oscillation (HFO) rates and amplitudes across different anatomic brain regions in a large cohort of patients. Methods Seventy patients who had wide-bandwidth (5 kHz) intracranial EEG (iEEG) recordings during surgical evaluation for drug-resistant epilepsy between 2005 and 2014 who had high-resolution MRI and CT imaging were identified. Discrete HFOs were identified in 2-hour segments of high-quality interictal iEEG data with an automated detector. Electrode locations were determined by coregistering the patient's preoperative MRI with an X-ray CT scan acquired immediately after electrode implantation and correcting electrode locations for postimplant brain shift. The anatomic locations of electrodes were determined using the Desikan-Killiany brain atlas via FreeSurfer. HFO rates and mean amplitudes were measured in seizure onset zone (SOZ) and non-SOZ electrodes, as determined by the clinical iEEG seizure recordings. To promote reproducible research, imaging and iEEG data are made freely available (msel.mayo.edu). Results Baseline (non-SOZ) HFO rates and amplitudes vary significantly in different brain structures, and between homologous structures in left and right hemispheres. While HFO rates and amplitudes were significantly higher in SOZ than non-SOZ electrodes when analyzed regardless of contact location, SOZ and non-SOZ HFO rates and amplitudes were not separable in some lobes and structures (e.g., frontal and temporal neocortex). Conclusions The anatomic variation in SOZ and non-SOZ HFO rates and amplitudes suggests the need to assess interictal HFO activity relative to anatomically accurate normative standards when using HFOs for presurgical planning.