Miracle-dz/UniFAR-FTUs huggingface dataset:
Rebasing Instruction Prefetching: An Industry Perspective

Instruction prefetching can play a pivotal role in improving the performance of workloads with large instruction footprints and frequent, costly frontend stalls. In particular, Fetch Directed Prefetching (FDP) is an effective technique to mitigate frontend stalls since it leverages existing branch prediction resources in a processor and incurs very little hardware overhead. Modern processors have been trending towards provisioning more frontend resources, and this bodes well for FDP as it requires these resources to be effective. However, recent academic research has been using outdated and less than optimal frontend baselines that employ smaller structures, which may result in misleading outcomes. In this letter, we present a detailed FDP microarchitecture and evaluate two improvements, better branch history management and post-fetch correction. We believe that our FDP-based frontend design can serve as a new reference baseline for instruction prefetching research to bridge the gap between academia and industry.
Power system linear model selective identification by exploiting the Loewner interpolation method

This paper demonstrates the capabilities of the Loewner’s frequency interpolation method (LFIM) to extract the power system linear model in a selective-frequency range by employing the frequency response associated with inputs and outputs of the system. This is achieved taking advantage of the Loewner’s matrices that interpolate in frequency-domain the ratio between outputs and inputs. Thus, the state-space representation of the linear model is fitted providing parametric matrices, as the state matrix at one operating condition. Then, the small-signal analysis (SSA) can be addressed by computing the eigenvalues and mode-shape reproduction. Numerical results are attained after applying the proposed method to the well-known New England test system with 10 machines, 39 buses. For comparison purposes, the power system linear model is also obtained utilizing the Eigensystem realization algorithm (ERA), validating the proposition.
Chemicals from Greek Forestry Biomass: Constituents of the Leaf Oil of Myrtus communis L. Grown in Greece

Abstract The composition of leaf oil of Myrtus communis L. , grown in Greece was investigated by using GC/MS analysis. Twenty-one compounds were identified. The oil was found to be rich in α-pinene (18.0%), limonene (21.8%), linalyl acetate (31.4%) and geranyl acetate (6.5%). Minor compounds were: α-humulene (3.7%), β-caryophyllene (1,5%), neryl acetate (1.2%) and linalool (1.1%).
Cation disorder in ferroelectric Aurivillius phases of the typeBi2ANb2O9(A=Ba, Sr, Ca)

The structures of the ferroelectric two-layer Aurivillius phases Bi 2 ANb 2 O 9 (A=Ba, Sr, Ca) have been refined using a combination of X-ray and neutron powder diffraction data. Bi 2 BaNb 2 O 9 is not significantly distorted from idealised symmetry and has been refined in tetragonal space group I4/mmm, a=3.9362(1) and c=25.6582(7) A. The Sr and Ca compounds have been refined in orthorhombic space group A2 1 am, with a=5.5193(3), b=5.5148(3), c=25.0857(6) A and a=5.4833(1), b=5.4423(1), c=24.8984(6) A, respectively. The orthorhombic distortion increases with decreasing A 2+ cation size and originates from bonding requirements at the perovskite A site, in agreement with previous work. However, in contrast to earlier work, we find a partial mixing of Bi and A cations on their respective sites, which increases in the order Ca<Sr<Ba. This effect is also discussed in terms of bonding requirements at the metal sites and bond valence sum analysis. The combined use of X-ray and neutron powder diffraction data is found to be essential in determining this subtle effect, which may have important consequences in the interpretation of the ferroelectric behaviour of this family of materials.
Efficient Modeling of Plant Short and Long Term Behavioral Responses to a Stimuli

Plant behavior and response to environmental stimuli has tremendous importance in science and agriculture. In particular, a plant’s root continuously senses changes in the environment, and responds in ways that optimize dynamically different essential parameters like its stability, and adequate food and water supplies. Some of the plant behavioral changes in response to environmental changes, like water shortage, can be reversible, and after certain “stress” time, the plant can get back to its normal behavioral patterns. In other cases, the plant behavior after the stress stimulus ends, is changed, due to effects on internal mechanisms, facilitating long-term behavioral changes. The main aim of this work is to derive a preliminary physical model and analysis tools to quantify the behavioral changes of a plant in response to a stimuli. To demonstrate the model, we examined, without loss of generality, the change in plant growth rate in response to electrical simuli. We showed how the suggested plant behavioral model can assist in computational analysis of short and long term plant response to changing stimuli, construct a common baseline for comparison with other stimuli, and derive new quantitative measurements that can be correlated with internal plant mechanism and assist in assessing behavioral plant patterns and in the design of more efficient agricultural technologies
Raman Spectroscopy of the Pentad of Isotopically-Enriched Methane 13CH4

We report on the Raman spectrum of chemically pure and isotopically enriched (>99.9% <sup>13</sup>C) methane <sup>13</sup>CH4 gas measured using a specially developed Raman gas spectrometer intended for the qualitative analysis of atmosphere impurities. The spectrum is measured in the range of 2700–3400 cm<sup>-1</sup> (the pentad) revealing the most intense peak at ~2915 cm<sup>−1</sup>.
Competencies detection approach from professional interactions

The competence is one of the resources which have capital importance for organizations and even out of organizations such as social networks or crisis situations. However, competence is a widely shared concept but differently appreciated as it refers to several elements that enable effective action in a workplace or provide solutions in a problem solving environment. Several methods are used in competence seeking such those based on curriculum vitae analysis or interviews but the results are strongly oriented by the declarations of CV’s redactors and the interviewed. Added to that, actors’ competencies evolution is rarely detected in an organization. This paper presents an approach based on the analysis of interactions to find competencies. Indeed, elements of competence are sometimes exchanged during the interactions between persons dealing with problem solving or facing specific situations. Our works are focused on detecting competence from professional mediated communications. For this purpose we used the "Ubuntu" corpus which consists on interactions within a community of interest dealing with Ubuntu operating system issues.
On the enhancement of TCP/IP protocol for use in High Frequency Communication Systems

High Frequency (HF) communications is widely utilised in military, safety and amateur radio systems. Utilising HF communication channels for TCP/IP is highly constrained due to the characteristics of the channel which are presented as low link reliability, limited bandwidth and high transmission delays. Low link reliability is the effect of error prone behavior of HF channels which are governed by physics and environmental conditions. Various implementations of Wideband HF (WBHF) provide additional bandwidth but the low reliability still pose a challenge for TCP/IP communications. In this paper, we present a novel TCP named HF-TCP which is an enhanced version of the standard TCP to provide better performance on HF communication channels. HF-TCP modifies key parameters of TCP to allow TCP sessions to remain open over an extended period of time while the low-data is transmitted with induced delays. Results from experiments show improvements in transmission success rate of 24 percent over standard TCP which failed to initiate or maintain communication. The proposed HF-TCP is backward compatible with generic Local Area Networks (LAN) and wide Area Networks (WAN).
Design and synthesis of superabsorbent polymers

A series of novel copolymer superabsorbents based on the monomers acrylamide (AM), acrylic acid (AA), acrylonitrile, methacrylic acid, sodium acrylate (SA), and 2-hydroxyethyl methacrylate (HEMA) were prepared by copolymerization using ammonium persulfate as an initiator and N,N-methylenebisacrylamide as a crosslinking agent. The experimental results of superabsorbent polymers (SAPs) show that the absorbency in water and NaCl solutions is maximum for AM, SA, HEMA and AM, AA, SA combinations. The copolymers were characterized by IR spectroscopy. The water retention of soil was also enhanced using the above superabsorbents. Use of SAPs for the growth of the croton plant was also investigated. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 80: 2635–2639, 2001
HFD-SRGAN: Super-Resolution Generative Adversarial Network with High-frequency discriminator

The high-frequencies of images is very important both in keeping the edges and suppressing artifacts. To improve the performance of single image super-resolution (SISR) based on the SRGAN framework, we propose Super-Resolution Generative Adversarial Networks with high-frequency discriminator (HFD- SRGAN) by designing an additional discriminator for image’s high-frequencies extracted by wavelets. Based on SRGAN, the image’s high frequencies extracted by discrete wavelet transformations (DWT) were then introduced into GAN. Moreover, an additional discriminator for these high frequencies was built. Since the proposed model provides a direct and efficient way to locates and estimates the high frequencies of the reconstruction image, the visual effects of reconstructed the images can be improved with fewer computation costs. Experiments show that HFD-SRGAN has improved the visual effects of SRGAN when using the same generator network as SRGAN. The evaluation results show the performance of our method is equal to the state-of-the-art methods.
Under-sampling and Classification of P300 Single-Trials using Self-Organized Maps and Deep Neural Networks for a Speller BCI

A Brain-Computer Interface (BCI) allows its user to control machines or other devices by translating its brain activity and using it as commands. This kind of technology has as potential users people with motor disabilities since it would allow them to interact with their environment without using their peripheral nerves, helping them to regain their lost autonomy. One of the most successful BCI applications is the P300-based Speller. Its operation depends entirely on its capacity to identify and discriminate the presence of the P300 potentials from electroencephalographic (EEG) signals. For the system to do this correctly, it is necessary to choose an adequate classifier and train it with a balanced data-set. However, due to the use of an oddball paradigm to elicit the P300 potential, only unbalanced data-sets can be obtained. This paper focuses on the training stage of two classifiers, a deep feedforward network (DFN) and a deep belief network (DBN), to be used in a P300-based BCI. The data-sets obtained from healthy subjects and post-stroke victims were pre-processed and then balanced using a Self-Organizing Maps-based under-sampling approach prior training looking to increase the accuracy of the classifiers. We compared the results with our previous works and observed an increase of 7% in classification accuracy for the most critical subject. The DFN achieved a maximum classification accuracy of 93.29% for a post-stroke subject and 93.60% for a healthy one.
Tissue oxygenation monitor using NIR spatially resolved spectroscopy

A new clinical tissue oxygenation monitor, the NIRO-300, has been developed. In addition to monitoring changes in hemoglobin concentration and redox state of cytochrome oxidase, the instrument can measure a Tissue Oxygenation Index (TOI), which is the ratio of oxygenated to total tissue hemoglobin, by utilizing NIR spatially resolved spectroscopy (SRS). In SRS, the slope of light attenuation versus distance is measured at a distant point from the light input, from which the TOI is calculated using photon diffusion theory. Four laser diodes are used as the light source and Class 1 laser light (IEC 825) is irradiated onto the skin. A high gain and low noise amplifier is used in the detector, which enables a large emitter-detector separations of around 5cm. To evaluate the TOI measured by the NIRO-300, it was compared to the data from a blood gas analyzer (S02 value) in measurements made on phantoms containing intralipid and blood. We also made simultaneous measurements by the NIRO-300 and an NIRS machine based on time resolved spectroscopy (TRS) on human arms. In the both measurements, TOI showed an excellent correlation with the data from blood gas analyzer and the TRS machine, which suggests the efficacy of the TOI data also in clinical use.
On the Design of Near-Optimal Variable-Length Error-Correcting Codes for Large Source Alphabets

In this paper, we focus on near-optimal designs for variable-length error-correcting (VLEC) codes, while considering the performance in terms of both the average codeword length (ACL) and the symbol-error rate (SER). The criteria for narrowing the search space and enhancing the SER performance are investigated. An efficient code construction algorithm is then devised based on a random search process. Taking advantage of the significantly reduced search complexity, we are able to construct near-optimal VLEC codes for large source alphabets. Numerical results obtained for various free distance values and alphabet sizes show that constructed VLEC codes have both reduced ACL values and enhanced SER performances. Performance improvement is more notable for large source alphabets.
Study on Aging Characteristics of XLPE Cable Insulation Based on Quantum Chemical Calculation

In this paper, quantum chemical calculation and isothermal relaxation current (IRC) measurement are performed on thermally aged XLPE cables to investigate the effect of defects on dielectric properties and trap energy distribution of XLPE insulation. Samples of XLPE cables are thermally aged at 135 °C up to 45 days. Microscopic experiments including gel permeation chromatography, differential scanning calorimetry, and Fourier transform infrared spectrometer show that the molecular weight and crystallinity of XLPE decreases with aging time. The IRC results show that both the trap density and the trap depth increase with aging. To quantitatively calculate the trap depth variation due to physical and chemical defects by thermal aging, a quantum chemical calculation is carried out based on Gaussian 09. It is found that the broken cross-linking bonds between molecular chains weaken the stability of the molecular network structure, introducing the shallow physical trap (0.3 eV) in the aged XLPE. The molecular chain is thermally oxidized, the carbonyl group is introduced as a deep chemical trap (1.44 eV) in the XLPE. The chemical defect not only changes the localised energy state, but also significantly decreases the intrinsic breakdown strength of XLPE molecule from 0.62 to 0.51 V/Angstrom in quantum chemistry calculation.
ResNet-LSTM for Real-Time PM2.5 and PM₁₀ Estimation Using Sequential Smartphone Images

Attempts have been made to estimate PM2.5 and PM10 values from smartphone images, given that deploying highly accurate air pollution monitors throughout a city is a highly expensive undertaking. Departing from previous machine learning studies which primarily focus on pollutant estimation based on single day-time images, our proposed deep learning model integrates Residual Network (ResNet) with Long Short-Term Memory (LSTM), extracting spatial-temporal features of sequential images taken from smartphones instead for estimating PM2.5 and PM10 values of a particular location at a particular time. Our methodology is as follows: First, we calibrated two small portable air quality sensors using the reference instruments placed in the official air quality monitoring station, located at Central, Hong Kong (HK). Second, we verified experimentally that any PM2.5 and PM10 values obtained via our calibrated sensors remain constant within a radius of 500 meters. Third, 3024 outdoor day-time and night-time images of the same building were taken and labelled with corresponding PM2.5 and PM10 ground truth values obtained via the calibrated sensors. Fourth, the proposed ResNet-LSTM was constructed and extended by incorporating meteorological information and one short path. Results have shown that, as compared to the best baselines, ResNet-LSTM has achieved 6.56% and 6.74% reduction in MAE and SMAPE for PM2.5 estimation, and 13.25% and 11.03% reduction in MAE and SMAPE for PM10 estimation, respectively. Further, after incorporating domain-specific meteorological features and one short path, Met-ResNet-LSTM-SP has achieved the best performance, with 24.25% and 20.17% reduction in MAE and SMAPE for PM2.5 estimation, and 28.06% and 24.57% reduction in MAE and SMAPE for PM10 estimation, respectively. In future, our deep-learning image-based air pollution estimation study will incorporate sequential images obtained from 24-hr operating traffic surveillance cameras distributed across all parts of the city in HK, to provide full-day and more fine-grained image-based air pollution estimation for the city.
Numerical Study on the Influence of Copper Former on AC Loss Characteristics of Conductor on Round Core cable

A conductor on round core (CORC) cable wound with REBCO tapes is promising for high current density applications. AC loss analysis can help us to understand its electromagnetic performance. This paper built a two-dimensional (2-D) CORC model by finite element method, and the AC losses induced by changing external magnetic field was examined. Individually, the AC loss dependence on the magnitude and frequency of the external magnetic field is examined. The results prove that the copper former will lead to an increase of the CORC cable magnetization losses in a high frequency.
Model Validation Lessons Learned through Implementing NERC MOD-033-1

Model validation is crucial for maintaining power-grid efficiency and reliability because models are the foundation of many operation and planning applications. The model validation process implemented by Southwest Power Pool (SPP) is presented in this paper. To set up proper steady-state operational conditions of a planning model, generations, loads and external networks in the model are adjusted to match the snapshot of an operational model extracted from the energy management system (EMS). The power flows of all the transmission lines of100 kV and above are compared between the two model cases. A measure of significant differences is established. The differences are reconciled in an iterative manner that includes transmission system impedance and topology alignment using root-cause analysis. To evaluate the accuracy of the SPP system dynamic models, two simulation approaches (i.e., system-wide simulation and event playback) are utilized. The simulated response of the planning dynamic model is compared with the processed phasor measurement unit (PMU) data. The sampling rate of the PMU data is increased through linear interpolation. Results and observations are presented in the paper.
Evaluation of Interventional Planning Software Features for MR-guided Transrectal Prostate Biopsies

This work presents an interventional planning software to be used in conjunction with a robotic manipulator to perform transrectal MR guided prostate biopsies. The interventional software was designed taking in consideration a generic manipulator used under the two modes of operation: side-firing and end-firing of the biopsy needle. Studies were conducted with urologists using the software to plan virtual biopsies. The results show features of software relevant for operating efficiently under the two modes of operation.
Enabling Interaction with Virtual Fluids and Mixed Media using a High Dexterity Hand Exoskeleton

Advances in exoskeleton technology now enable interacting with rigid objects in a virtual or remote environment using one’s hand and fingertips. However, interaction with non-solid materials – such as liquids, sediments and regolith – alongside solids, can greatly extend the versatility of this technology. Rendering rigid objects adequately requires a control loop with high update rates, whereas fluid dynamics equations are computationally expensive. To accommodate this, the fluid dynamics can be simplified - particularly for fluids with high viscosity - resulting in a fast-to-calculate model to enabling haptic rendering of viscous fluids and rigid bodies simultaneously using DLR’s Exodex Adam hand exoskeleton. Viscosity as a proprioceptive cue of fluids can be presented to the human through force feedback at multiple points on the human hand - fingers and palm - letting the user interact with a virtual environment in a more natural way and making the experience more immersive. We carry out two user studies to investigate the human perception abilities of virtual fluids rendered with simplified dynamics, and the discernability of different viscosity in virtual fluids compared real fluids. Results show that virtual media can give the user the perception of interacting with a fluid, even with simplified models, at a high update frequency. Furthermore, the material discernibility corresponds well to actual interaction with real viscous fluids. This shows great promise forward for haptic in-hand interaction in fluid and mixed media environments.
Improvement of the 1.57-micron laser absorption sensor with chirp modulation to evaluate spatial averaging carbon dioxide density

A 1.57-μm laser remote sensor using differential absorption spectrometory is being developed as a candidate for the next space-based mission to observe atmospheric CO2 and/or other trace gases. In a previous study, the performance of a proto-type system with sinusoidal modulation was evaluated based on ground and airborne measurements. The airborne measurements showed that the LAS with sinusoidal modulation could detect strong CO2 plume, and suppress the impact of an aerosol layer over high surface reflectivity. Based on those results, an outline of LAS system on the space platform such as the International Space Station Japan Experimental Module (ISS-JEM) was desined. However, an elevated layer in the observation path is still remain, which leads to reduce effective observed data as long as current sinusoidal modulation is employed. In order to prevent the impact of elevated layer, different modulation schemes such as random or frequency modulation are capable. We are currently improving the LAS system with a chirp modulation scheme for the purpose. Some of recent airborne measurements using sinusoidal modulation and ground-based measurements using chirp modulation in progress will be shown in this meeting.