Miracle-dz/UniFAR-FTUs huggingface dataset:
Security Gaps due to Coupling of Energy Delivery Sub-systems

Description of research activity: In particular, this activity focuses on the following issues: 1. Natural gas is now the largest source of fuel for electricity generation (according to PJM). The gas network operation is also becoming more reliant on automation and therefore communication. Hence, cyber-attacks become a possibility, the repercussions of which could propagate to the electric grid, which relies heavily on natural gas. For example, SDG&E is rushing to complete a large battery storage project in record time, to avoid potential blackouts as a result of accidental or malicious disruption of service in the Alison Canyon gas storage facility. We will first mathematically model the dependency between these two sub-systems and then identify the security threats arising due to this coupling that may originate from cyber-attacks, and propose preventive/restorative actions. The tool/technology we envision is a protocol for communicating information to EMS and DMS that can trigger remedial actions. This tool would be equipped with an advanced intrusion detection system that comprises of three sub-components: 1) intra-domain intrusion detection for power grid, 2) intra-domain intrusion detection for natural gas grid, and 3) inter-domain intrusion detection that binds the intrusion detection in the gas and electric domain together. The structure of the proposed comprehensive intrusion detection system is illustrated in Fig. 1.
SUSTAINABLE MOBILITY TERMINOLOGY: TOWARDS UNIFICATION AND STANDARDIZATION

As the scientific and technical terminology plays one of the major roles in good-quality teaching and learning of languages for specific purposes (LSPs), this paper aims at providing a systematic insight into the problems encountered during the process of making a multilingual dictionary in the field of sustainable mobility, ICTs and sharing economy for Transport and Traffic Engineering (TTE) students. Terminological discrepancies and varieties, notional ambiguities, lack of unified and standardized specific terms in available relevant literature and other representative issues occurring in English, German, French and BCMS languages are presented and classified and solutions proposed in order to achieve a high-quality level of this and similar publications both from the standpoint of linguistics and technology.
Interactions between aphid species and beneficial organisms in sweet pepper protected crop

The interactions between different aphid species and beneficial organisms have been studied in the west region of Portugal, on sweet pepper protected crops. Assays were carried out during the years of 1998, 2002, 2003 and 2004. Aphid species and natural enemies were weekly collected, quantified and identified in laboratory. The aphid species that reached economic thresholds were Aphis craccivora Koch, Aphis gossypii Glover and Myzus persicae (Sulzer). Aulacorthum solani (Kaltenbach) and Macrosiphum euphorbiae (Thomas) were also observed. Indigenous predator activity by anthocorids, cecidomyiids, coccinelids, chrysopids, spiders, syrphids and some parasitoids, contributed to the control of aphid populations. However, in sweet pepper protected crops, aphid populations can reach high levels and the activity of natural enemies may be insufficient to control them. Introduction of beneficial enemies are mostly necessary. A biological control programme was implemented and adapted to the conditions observed during the assays. Therefore, to control A. craccivora and A. gossypii populations, whose reproductive rate is very high in protected pepper crops, the introductions of predators, namely coccinelids, should be considered due to its efficacy in controlling these aphid species. M. persicae populations can be controlled with parasitoid releases when the first colonies are observed. In this study the predator Coccinella septempunctata L. and the parasitoid Aphidius colemani Viereck were used.
Smart Sensing System to Prevent Accidents Using IOT

: Applications based on animal detection have a very important role in many real life situations. Some of these applications are detection and tracking of animals like elephant in forest for understanding their behavior with the environment, preventing animal vehicle collision on roads. In this paper first we will briefly summarize some of the methods used for detection of animals and then the application of our proposed method based on the sensors for identifying the animal. The proposed method has been applied for testing purpose to prevent collisions from human detection also. The results show that our proposed method is efficient and the system has very low false positive and false negative rates. An overall efficiency of 86.25% is achieved for animal detection.
SHEAR RESPONSE INVESTIGATION OF HSRC DEEP BEAMS WITHOUT WEB REINFORCEMENT PART I: COMPARISON OF DESIGN EQUATIONS

Currently, there is no general agreement on a theory describing the response of reinforced concrete members without web reinforcement. Many structural systems are usually performed using empirical or semi-empirical expressions provided by codes of practice that do not consider the influence of many governing parameters. In this paper, a comparison between values of current experimental shear strength and those of various international design approaches like ACI, Canadian, FIB and the method proposed by Sudheer, Zararis ,Zsutty ,Shah ,Bazant and Russo. Eighteen simple span high strength reinforced concrete “HSRC” deep beams without web reinforcement were tested and analyzed under two static point loads at mid-span of the beam to examine the contribution of various parameters on the shear capacity of HSRC beams. The main studied parameters are f‟cu=50 MPa, three values of tension reinforcement-ρ%-(0.73%,1.21% &1.83%) and shear span to effective depth ratio-a/d-( 2,1.5 &1). As a conclusion of this paper, ACI and FIB code provisions for shear in HSC are safe for use with the exception that CSA should be used with care. Despite numerous studies, there is still a need to develop a clear understanding of the shear behavior of HSC beams without web reinforcement. Therefore, this experimental program was arranged to evaluate the shear behavior and to increase the shear database on HSRC deep beams.
MATHEMATICAL MODELLING AND EXPERIMENTAL INVESTIGATION OF TWO-TANK VALVE-LESS IMPEDANCE PUMPING SYSTEM

When two tanks open at one end are connected by an elastic tube, a net flow can be generated by periodical excitation at asymmetrical ends of a flexible tube. A simple yet reliable mathematical modelling technique is proposed to represent the essential features of pumping systems based on impedance mismatch in general. Modelling algorithm based on energy balance over small lumps of fluid regions defined for the system is outlined for deriving a set of ordinary differential equations for fluid velocity flux. The developed algorithm is applied for the case of Two-tank model studied in earlier mathematical models and physical experiment studies. Parameters investigated include pinch frequency, pinch location, and physical parameters of a flexible tube. Using the model derived, phase synchronization between external pumping pressure and fluid flux at the junction between the elastic tube and tanks is identified as a key factor in determining the direction of net power. In addition, it has been clear that the magnitude of net power is proportional to the marginal fluid flux amplitudes. With larger elastic tube radius and smaller tube thickness, a substantial increase in net flow generated has been achieved at lower external pumping frequency. The numerical model further validated using experimental simulation is shown to well describe the fundamental flow characteristics of open tank Impedance pumping. Due to its simplicity, modelling technique could be promising to be extended for the system with more than two tanks and even more complicated structures such as in coronary blood flow where branching and varying geometries are present.
Study on Heterosis and Genetic Distance of S6 Inbred Lines of Maize

Objectives of this research were to find out the heterosis value and genetic distance on several inbred lines and to find out the relationship between the genetic distance and heterosis in maize. The research performed in February to November 2011, which comprised of 2 researches: molecular analysis and in the laboratory and the field trial. The molecular analysis on inbred lines, which would be used as parents, was performed in Biotechnology Laboratory of Agro ecology Department, Faculty of Agriculture, University of Brawijaya, and Malang of Indonesia. The field trial was conducted in Kajang, Junrejo, Batu. Materials of the laboratory research included 35 genotypes of maize, which comprised of 33 inbred lines of the sixth-generation of selection (S6), and as comparison, 2 open pollinated varieties were applied: Bisma and Lamuru. Steps for molecular analysis at the laboratory were as followed: (1) DNA isolation, (2) DNA-quality test, (3) PCR SSR, (4) Visualization of the amplification result. Materials for the field experiment included: 140 F1 hybrids, 28 lines, 5 testers was planted using Randomized Complete Block Design (RCBD) with 2 replications. Observation was taken on 9 agronomic characters of maize: the plant height (cm), leaf length (cm), days pollen to shed (day), ear weight plant -1 (kg), kernel weight plant -1 (kg), diameter of ear (cm), number of rows ear -1 , and kernel water content (%), as well as the grain (kg ha -1 ). Results of the research showed that there were any interaction of Line x Tester in all characters except for leaf length and kernel water content. The estimate values of specific combining ability (SCA) and the heterosis value were varied among F1 hybrid and among of the observed characters. The value of genotypic correlation among the characters were ranged 0.20 – 1. The genetic distance between parents of the F1 hybrid was ranged from 0.25 to 0.65. Correlation coefficient of Spearman’s Rank between the genetic distance and SCA ranged -0.009 – 0.143, correlation coefficient of Spearman’s Rank between the genetic distance and heterosis ranged -0.120 – 0.181.
Lunar Terrain Relative Navigation Using a Convolutional Neural Network for Visual Crater Detection

Terrain relative navigation can improve the precision of a spacecraft’s position estimate by detecting global features that act as supplementary measurements to correct for drift in the inertial navigation system. This paper presents a system that uses a convolutional neural network (CNN) and image processing methods to track the location of a simulated spacecraft with an extended Kalman filter (EKF). The CNN, called LunaNet, visually detects craters in the simulated camera frame and those detections are matched to known lunar craters in the region of the current estimated spacecraft position. These matched craters are treated as features that are tracked using the EKF. LunaNet enables more reliable position tracking over a simulated trajectory due to its greater robustness to changes in image brightness and more repeatable crater detections from frame to frame throughout a trajectory. LunaNet combined with an EKF produces a decrease of 60% in the average final position estimation error and a decrease of 25% in average final velocity estimation error compared to an EKF using an image processing-based crater detection method when tested on trajectories using images of standard brightness.
Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning

As modern neural networks have grown to billions of parameters, meeting tight latency budgets has become increasingly challenging. Approaches like compression, sparsification and network pruning have proven effective to tackle this problem - but they rely on modifications of the underlying network. In this paper, we look at a complimentary approach of optimizing how tensors are mapped to on-chip memory in an inference accelerator while leaving the network parameters untouched. Since different memory components trade off capacity for bandwidth differently, a sub-optimal mapping can result in high latency. We introduce evolutionary graph reinforcement learning (EGRL) - a method combining graph neural networks, reinforcement learning (RL) and evolutionary search - that aims to find the optimal mapping to minimize latency. Furthermore, a set of fast, stateless policies guide the evolutionary search to improve sample-efficiency. We train and validate our approach directly on the Intel NNP-I chip for inference using a batch size of 1. EGRL outperforms policy-gradient, evolutionary search and dynamic programming baselines on BERT, ResNet-101 and ResNet-50. We achieve 28-78% speed-up compared to the native NNP-I compiler on all three workloads.
Contradictory results from different methods for measuring direction of insect flight

SUMMARY 1. Stream ecologists have been puzzled by the apparent paradox that invertebrate populations persist in headwater streams despite the high frequency with which individuals drift downstream. To resolve this ‘drift paradox’, directions and distances of both larval and adult movement must be identified. Using over 50 interception traps in combination with results from several mark–capture experiments using 15 N as a label, we tested the assumption that interception traps accurately represent the ultimate direction of adult insect flight. 2. In several streams in the Hubbard Brook Experimental Forest, 76% of 15 N-labelled stoneflies (Leuctra ferruginea) had flown upstream from where they emerged to where they were captured. In contrast, over 60% of stoneflies were flying downstream when captured, i.e. on the upstream side of an interception trap. 3. The instantaneous direction, as indicated by the side of the interception trap on which they were captured, indicated the ultimate flight direction for fewer than 1/3 of the individuals captured. Thus, such traps did not accurately reflect the ultimate flight patterns of individuals, as indicated by mark–capture data. 4. Conclusions drawn from interception trap counts regarding the direction of movement and the distribution and persistence of populations may need to be re-evaluated. We suggest that better tracking methods, including mass mark–capture studies using stable isotopes, be used to evaluate the potentially complex patterns of adult insect movement and the consequences of that movement for individuals and populations.
THE PHYSICAL MAPPING OF MICROSATELLITE MARKERS IN WHEAT

Microsatellite markers represent a new class of genetic markers in plants. Such markers reveal a high level of polymorphism even in species with a narrow genetic base, such as hexaploid wheat (Triticum aestivum L.). We used a large set of such markers and 25 deletion stocks of 'Chinese Spring' in a deletion-mapping experiment to study the physical distribution of dinucleotide microsatellite markers in homoeologous group 2 chromosomes of hexaploid wheat. Thirty-one microsatellite markers identified 14 loci in chromosome 2A, 9 loci in chromosome 2B, and 10 loci in chromosome 2D. The microsatellite loci were evenly distributed along the chromosome length, marking 18 of 27 defined physical intervals, including centromeric, interstitial, and telomeric regions. The apparent random distribution indicates that microsatellite markers provide excellent coverage of the wheat genome.Key words: deletion stocks, group 2 homoeologues, microsatellites, wheat.
A-MAL: Automatic Movement Assessment Learning from Properly Performed Movements in 3D Skeleton Videos

The task of assessing movement quality has recently gained high demand in a variety of domains. The ability to automatically assess subject movement in videos that were captured by affordable devices, such as Kinect cameras, is essential for monitoring clinical rehabilitation processes, for improving motor skills and for movement learning tasks. The need to pay attention to low-level details while accurately tracking the movement stages, makes this task very challenging. In this work, we introduce A-MAL, an automatic, strong movement assessment learning algorithm that only learns from properly-performed movement videos without further annotations, powered by a deviation time-segmentation algorithm, a parameter relevance detection algorithm, a novel time-warping algorithm that is based on automatic detection of common temporal points-of-interest and a textual-feedback generation mechanism. We demonstrate our method on movements from the Fugl-Meyer Assessment (FMA) test, which is typically held by occupational therapists in order to monitor patients' recovery processes after strokes.
Characteristics of adhesion pads formed during imbibition and germination of urediniospores of Uromyces viciae-fabae on host and synthetic surfaces

To imbibe and germinate urediniospores require free water or near saturated atmospheres in which both adsorption of water is maximal and capillary condensation pads form. The rate of spore germination is influenced by the amount of free water available. During imbibition, spores swell and capillary pads form beneath spores in contact with the substratum. These pads greatly increase the area of contact with the substratum. Pad area fluctuates and may depend on the balance between the rate of capillary condensation and the rate of uptake of fluid by spores. When spores, on leaves or cellulose acetate, are misted with water they imbibe rapidly and germinate. Adhesion pads which form under fully imbibed, germinating spores are morphologically similar to capillary pads but they differ in composition. On synthetic surfaces, during imbibition of spores and under microscopic glass beads, pads are composed principally of volatile capillary condensation and are removed when samples are freeze-dried. On host surfaces, when spores are fully imbibed and germinating, pads contain non-volatile soluble materials derived from both pathogen and host. These substances are not removed by extended freeze-drying.
A STUDY ON USING ASSOCIATION RULES FOR PREDICTING PROMOTER SEQUENCES

The problem of promoter identication in DNA sequences is of major importance within bioinformatics. As the conditions for a re- gion of DNA to function as a promoter are not known, machine learning based classication models are still developed to approach this problem. Relational association rules are a particular type of association rules and describe numerical orderings between attributes that commonly occur over a data set. This paper aims to investigate a classication model based on relational association rules mining for the problem of promoter sequences prediction. Some further extensions to this model are introduced and we provide a comparison of the original algorithm with its newly introduced versions.
The Big-O Problem for Labelled Markov Chains and Weighted Automata

Given two weighted automata, we consider the problem of whether one is big-O of the other, i.e., if the weight of every finite word in the first is not greater than some constant multiple of the weight in the second. We show that the problem is undecidable, even for the instantiation of weighted automata as labelled Markov chains. Moreover, even when it is known that one weighted automaton is big-O of another, the problem of finding or approximating the associated constant is also undecidable. Our positive results show that the big-O problem is polynomial-time solvable for unambiguous automata, coNP-complete for unlabelled weighted automata (i.e., when the alphabet is a single character) and decidable, subject to Schanuel's conjecture, when the language is bounded (i.e., a subset of $w_1^*\dots w_m^*$ for some finite words $w_1,\dots,w_m$). On labelled Markov chains, the problem can be restated as a ratio total variation distance, which, instead of finding the maximum difference between the probabilities of any two events, finds the maximum ratio between the probabilities of any two events. The problem is related to $\epsilon$-differential privacy, for which the optimal constant of the big-O notation is exactly $\exp(\epsilon)$.
Structure of accretion flows in the nova-like cataclysmic variable RW Tri

We obtained photometric observations of the nova-like (NL) cataclysmic variable RW Tri and gathered all available AAVSO and other data from the literature. We determined the system parameters and found their uncertainties using the code developed by us to model the light curves of binary systems. New time-resolved optical spectroscopic observations of RW Tri were also obtained to study the properties of emission features produced by the system. The usual interpretation of the single-peaked emission lines in NL systems is related to the bi-conical wind from the accretion disc’s inner part. However, we found that the Hα emission profile is comprised of two components with different widths. We argue that the narrow component originates from the irradiated surface of the secondary, while the broader component’s source is an extended, low-velocity region in the outskirts of the accretion disc, located opposite to the collision point of the accretion stream and the disc. It appears to be a common feature for long-period NL systems – a point we discuss.
Emoji Prediction: Extensions and Benchmarking

Emojis are a succinct form of language which can express concrete meanings, emotions, and intentions. Emojis also carry signals that can be used to better understand communicative intent. They have become a ubiquitous part of our daily lives, making them an important part of understanding user-generated content. The emoji prediction task aims at predicting the proper set of emojis associated with a piece of text. Through emoji prediction, models can learn rich representations of the communicative intent of the written text. While existing research on the emoji prediction task focus on a small subset of emoji types closely related to certain emotions, this setting oversimplifies the task and wastes the expressive power of emojis. In this paper, we extend the existing setting of the emoji prediction task to include a richer set of emojis and to allow multi-label classification on the task. We propose novel models for multi-class and multi-label emoji prediction based on Transformer networks. We also construct multiple emoji prediction datasets from Twitter using heuristics. The BERT models achieve state-of-the-art performances on all our datasets under all the settings, with relative improvements of 27.21% to 236.36% in accuracy, 2.01% to 88.28% in top-5 accuracy and 65.19% to 346.79% in F-1 score, compared to the prior state-of-the-art. Our results demonstrate the efficacy of deep Transformer-based models on the emoji prediction task. We also release our datasets at this https URL for future researchers.
Josephson effect with superfluid fermions in the two-dimensional BCS-BEC crossover

We investigate the macroscopic quantum tunneling of fermionic superfluids in the two-dimensional BCS-BEC crossover by using an effective tunneling energy which explicitly depends on the condensate fraction and the chemical potential of the system. We compare the mean-field effective tunneling energy with the beyond-mean-field one, finding that the mean-field tunneling energy is not reliable in the BEC regime of the crossover. Then we solve the Josephson equations of the population imbalance and the relative phase, calculating the frequency of tunneling oscillation both in the linear regime and in the nonlinear one. Our results show that the Josephson frequency is higher in the intermediate regime of the BCS-BEC crossover due to the peculiar behavior of the effective tunneling energy in the crossover.