Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Online Scheduling for Coflow-Aware Machine Learning Clusters

Distributed machine learning (DML) is an increasingly important workload. In a DML job, each communication phase can comprise a coflow, and there are dependencies among its coflows. Thus, efficient coflow scheduling becomes critical for DML jobs. However, the majority of existing solutions focus on scheduling single-stage coflows with no dependencies. While there are a few studies schedule dependent coflows of multi-stage jobs, they suffer from either practical or theoretical issues. Motivated by this situation, we study how to schedule dependent coflows of multiple DML jobs to minimize the total JCT in a shared cluster. We present a formal mathematical formulation for this problem and prove its NP-hardness. To solve this problem without job size information, we present an online coflow-aware optimization framework called Parrot. The core idea in Parrot is to infer the job with the shortest remaining processing time (SRPT) each time and dynamically control the inferred job's bandwidth based on how confident it is an SRPT job while being mindful of not starving any other job. Specifically, in the design of Parrot, we present a least per-coflow attained service (LPCAS) policy to infer the SRPT job. We further propose a dynamic job weight assignment mechanism and a linear program (LP) based weighted bandwidth scaling strategy for sharing bandwidth among DML jobs. We have proved that Parrot algorithm has a non-trivial competitive ratio. The results from large-scale trace-driven simulations further demonstrate that our Parrot can reduce the total JCT by up to 58.4 percent, compared to the state-of-the-art Aalo solution.
PARAMETRIC ANALYSIS AND COMPARISON OF MODELS USED IN THE ANALYSIS OF STEEL STRUCTURES

Performance-based seismic engineering has been gaining acceptance in the last decade. This philosophy seeks to ensure that a structure satisfies specific behavioral requirements for a given event. There are different guides and methodologies to evaluate structural performance, but conceptually they do not keep much difference. In order to perform an evaluation a mathematical model is required; however. However, the idealizations to represent the behavior of structural elements can vary significantly, giving rise to models with different degrees of complexity in their implementation or computational costs. Furthermore, the wide range of approaches, such as lumped or distributed plasticity and their calibration, can generate different results. To this, it must be added that not always a robust model is the best option for a performance analysis since it would not be practical to implement. This paper compares the pertinence of different modeling approaches to conduct a performance analysis on an 8-story building with Steel Special Moment Frames under different seismic intensity levels. Moreover, this article establishes the influence of various parameters (i.e., hysteretic detailing, Rayleigh damping, axial-moment interaction) within mathematical models on the overall response of the structure. For the purpose, FEMA P-695 methodology, as well as the ASCE 7-16 maximum-drifts requirements were used to run a sensitivity analysis between models aiming to warn of inappropriate practices. Within the findings, it can be emphasized that the secondary stiffness (in-cycle deterioration) of the element is the parameters that influence the most in the collapse response as opposed to cyclic degradation. Also, it must be noted that adding a smother yielding transition causes a higher seismic performance, which could be unconservative within an evaluation. Furthermore, the analyses illustrate how misusing an initial-stiffness proportional Rayleigh damping produces unrealistic performance values. Additional comments are made on the methodologies used to account for axial-moment interaction in lumped-plasticity models. 3655 EURODYN 2020 XI International Conference on Structural Dynamics M. Papadrakakis, M. Fragiadakis, C. Papadimitriou (eds.) Athens, Greece, 23–26 November 2020 Available online at www.easdprocedia. org EASD Procedia EURODYN (2020) 3655-3670 ISSN:2311-9020 © 2020 The Authors. Published by EASD Procedia. Peer-review under responsibility of the Organizing Committee of EURODYN 2020. doi: 10.47964/1120.9300. 19718 Bryam Astudillo, Sebastian Pozo and Francisco Flores
Experimental study of water adsorption on activated carbons

Two carbons of different origins (wood and coal) were oxidized with nitric acid. The materials were characterized using sorption of nitrogen, Boehm titration, and potentiometric titration. The water adsorption isotherms were measured at various temperatures close to ambient (relative pressure from 0.001 to 0.3). From these isotherms heats of adsorption were calculated using virial equation. The results showed that the isosteric heats of water adsorption are affected by surface chemical heterogeneity only at low surface coverage. The shapes of heats obtained indicate strong water−water interactions as a result of adsorption on secondary sites and cluster formation. In all cases the limiting heat of adsorption equal to the heat of water condensation (45 kJ/mol) was obtained.
Theranostics: A Boon in Cancer Diagnosis and Therapy

Modern approaches in improvement of new nanomaterials have gained enormous attention due to various biomedical application, along with cancer theranostics. The characteristic physico-chemical feature of these materials, including their small size and wide-range surface-to-volume ratio provide potentiality for cancer theranostics that combine diagnosis , biosensing , imaging detection and immune therapy.Recent procurement for cancer immunotherapy have gained considerable attention in controlling the body’s immune system to fight against cancer.In this abstract , nanomedicine with inherent immunomodulatory properties presents interesting window(of opportunity) which can stimulate the function of immune cell. The goal is to cover broad range of information about the immunomodulation properties of nanomedicine in cancer theranostics i.e factors like pH, hypoxia, tumor angiogenesis, tumor extracellular matrix which have a huge role in the immunomodulation of nanomedicine and also strategies to enhance cancer theranostics applications. According to recent studies, cancer therapy can be potentially improved through nanoparticle based immunotherapy.
Parallel Peak Cancellation Signal-Based PAPR Reduction Method Using Null Space in MIMO Channel for MIMO-OFDM Transmission

SUMMARY This paper proposes a parallel peak cancellation (PC) process for the computational complexity-e ﬃ cient algorithm called PC with a channel-null constraint (PCCNC) in the adaptive peak-to-average power ratio (PAPR) reduction method using the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. By simultaneously adding multiple PC signals to the time-domain transmission signal vector, the required number of iterations of the iterative algorithm is e ﬀ ectively reduced along with the PAPR. We implement a constraint in which the PC signal is transmitted only to the null space in the MIMO channel by beamforming (BF). By doing so the data streams do not experience interference from the PC signal on the receiver side. Since the fast Fourier transform (FFT) and inverse FFT (IFFT) operations at each iteration are not required unlike the previous al-gorithm and thanks to the newly introduced parallel processing approach, the enhanced PCCNC algorithm reduces the required total computational complexity and number of iterations compared to the previous algorithms while achieving the same throughput-vs.-PAPR performance.
On Smart-Buildings and their Integration into the Smart-Grid

Today’s electrical grid is undergoing deep changes, resulting from the large integration of distributed Renewable Energy Sources (RES) in an effort to decarbonize the generation of electrical energy. In addition to the emergence of this volatile electricity production, the worldwide demand for electricity increases due to a growing population and the intensified electrification of buildings. Smart-buildings represent promising assets for supporting the electrical grid in balancing demand with a supply based on non-dispatchable RES. A smart-building denotes a building equipped with sensor/actuator hardware connected to a federating Building Data Management System (BDMS) which enables high-level applications and services. Tapping into the flexibility inherent to its various entities (load, storage, and generation), a smart-building can provide Demand Response (DR) functionality through the optimization of its energy profile in response to varying electricity prices or commands from the grid. This PhD thesis provides a set of tools, algorithms, and frameworks, revolving around the notion of smart-buildings that foster an enhanced Building-to-Grid (BtG) integration. The tools developed here aim to fill the gap encountered in the literature created by the recent rollout of BDMSs and the ubiquitous Internet of Things (IoT). Furthermore, the mismatch between current DR and the future RES-based smart-grid opens the way to the development of innovative algorithms and frameworks to manage the flexibility offered by smart-buildings for grid-side agents. Built upon BDMSs, two open-source tools have been developed. Firstly, an integrated highspeed emulation and simulation software, dubbed Virtualization Engine (vEngine), allows the simulation of non-existing components of a building directly on-site. The multi-threaded, light architecture of vEngine permits efficient simulations, in a modular environment conceived for developers. Secondly, we describe Open Energy Management System (OpenEMS), a platform that seamlessly connects to any existing BDMS and provides its users with an environment to create their own energy management algorithms, with a focus on Model Predictive Control (MPC). Simulations using a realistic Swiss residential building model demonstrate the effectiveness and modularity of both tools. Additionally, we propose a multi-state load profile identification algorithm tailored to Non-Intrusive Load Monitoring (NILM). Applied to energy disaggregation, it shows promising results for enhanced energy feedbacks to the occupants. To attain daily energy balance within the smart-grid, we propose several algorithms and
Influence and Mitigation of Pedestrian Blockage at mmWave Cellular Networks

The large spectral bandwidth at millimeter-wave (mmWave) frequencies provides a mean to achieve very high data rates in wireless communication systems. A unique characteristic of mmWave is that mmWave links are very sensitive to blockage and have large propagation path loss, which exhibits low line-of-sight (LoS) probability, unstable connectivity and unreliable communication. This paper studies the influence of the blockage in pedestrian scenario, explains in detail how blockage affects the mmWave propagation characteristics. In particular, we study the behavior of the blockage due to human mobility and how it affects the timescale for outage due to blockage using knife-edge diffraction model (KED). One of the existing solutions to overcome the influence of blockage, is to associate the user equipment (UE) with other available base stations (BSs) by handover (HO) if the serving BS is blocked. In this paper, for a pedestrian scenario, we propose two reinforcement learning (RL) based user association algorithms, which accounts for the past experience of the blockage on the position of the UE. One focuses on the reward to increase the sum LoS probability and is named as blockage-aware user association (BAUA). The other focuses on the reward to balance the trade-off between the throughput and the LoS probability and is named as modified BAUA. We compare the proposed algorithm with the conventional user algorithms such as the maximum throughput based algorithm and the maximum SINR based algorithm. Simulation results show that to increase the sum LoS probability BAUA would be suitable, and to increase the average throughput maximum throughput based method would be suitable.
A Generic Multivector Model Predictive Control With Symmetric Pulse Pattern for Hybrid Multilevel Converters

This article presents a generic multivector model predictive control (MV-MPC) method that has the potential to be applied to all hybrid multilevel converters (HMCs). It first locates the reference voltage vector in the 120° oblique coordinate to select the three adjacent voltage vectors to be applied over one control cycle. Then, the current tracking is guaranteed through duty cycle optimization and dc capacitor voltages are balanced by evaluating possible switching sequences that belong to the voltage vectors with optimal duty cycles. At last, the optimal switching sequence with a symmetric five- or seven-segment pulse pattern is generated using an external modulator. The proposed generic MV-MPC can significantly improve the quality of the output current, while achieving a constant equivalent switching frequency at the same time. Experimental studies on an all silicon carbide HMC prototype, i.e., an active neutral point clamped converter with cascaded H-bridge, are presented to validate the effectiveness of the proposed MV-MPC strategy.
Influencing Factors on Customer Satisfaction and Retention in Online Transportation in Indonesia

This study aims to investigate the effects of sales promotion, online customer service, offline customer service, online dependencies, and corporate reputation on satisfaction and the effect of satisfaction on customer retention on online transportation in Indonesia. The population of this study was individuals who had used online transportation. The sampling technique used was purposive sampling. The data analysis method in this study is using PLS-SEM. The results of this study show that sales promotion, online customer service, offline customer service, and online dependencies have a positive effect on satisfaction and satisfaction have a positive effect on customer retention. This research has succeeded in contributing to the online transportation industry regarding the importance of sales promotion in creating customer sat isfaction, the importance for the manager to manage their online and offline customer service in order to satisfy their customers, how online dependencies can effect customer satisfaction and also how to create the customer retention.
Two‐dimensional electrophoresis. The current state of two‐dimensional electrophoresis with immobilized pH gradients

2.2 Current method of horizontal IPG-Dalt . 2.2.1 Sample preparation . 2.2.2 Gel casting . 2.2.2.1 IPG gels . 2.2.2.2 SDS pore-gradient gels . 2.2. 3 2.2. 4 I E F i n I P G . 2.2. 5 Equilibration .
Optimal Design of Planar Spiral Coil for Uniform Magnetic Field to Wirelessly Power Position-Free Targets

A large circular transmitter (power pad) is often utilized for inductively wireless charging so that the power receiver can position itself freely within the power pad. However, the uneven magnetic field distribution leads to the impedance mismatch and the variable transferred power due to the misalignment between a receiving coil and a relatively large transmitter coil. In this paper, the effects of the turn numbers, trace spacing, and coil size on the uniformity of magnetic field distribution over a planar spiral coil (PSC) are investigated based on an analytical model. Then, the genetic algorithm is used to optimize the trace width and spacing of a ten-turn PSC with the fixed outer and inner diameters, whereas the magnetic field is numerically calculated by HFSS software. The geometrically optimal PSC is obtained with the trace width approximately equal to trace spacing for each turn by minimizing the coefficient of variation (COV) of magnetic field within an effective charging area over the coil. The results showed that the simulated and measured COVs of magnetic field were 0.130 and 0.121, respectively, which are obviously less than that of the uniformly spaced regular coil and show a little less than that of the optimally spaced coil with fixed trace width. Therefore, the trace spacing is a major consideration to achieve the uniform magnetic field, whereas the trace width variation is applied to refine the evenness of field. It is also expected that the proposed GA-based optimization is well applied to design other Txs with conformable shape in inductively WPT systems for stable power delivery regardless of the receiver positions.
EFFECT OF FLAXSEED FLOUR AND PACKAGING ON SHELF LIFE OF REFRIGERATED PASTA

ABSTRACT The effects of flaxseed (Linum usitatissimum) flour (FF) and packaging conditions on microbial counts, lipid stability and cooking quality were determined for fresh pasta stored 7 weeks at 4C. Fresh pastas made from semolina or semolina blended with 15% (w/w) FF (FF-pasta) were packaged in metallized bags under three conditions: ambient air, nitrogen and vacuum. Packaging conditions did not affect aerobic or anaerobic plate counts. Mold and yeast counts were lower for pasta packaged under vacuum than under ambient air or nitrogen. Compared with traditional fresh pasta, FF-pasta had lower microbial counts during storage. Free fatty acid content in FF-pasta increased from 1.9 to 2.4% during storage. Lipid oxidation was lowest with vacuum-packaged pasta. Packaging conditions had little or no effect on cooking quality. Compared with traditional pasta, FF-pasta had lower cooked firmness and cooking loss. Cooked firmness was found to decrease only during the first week of storage; no further decrease occurred during the subsequent weeks. PRACTICAL APPLICATIONS This research would have practical applications to the fresh, refrigerated pasta industry. Although limited in scope, the results indicate that flaxseed flour (FF) has some bacteriostatic and fungistatic activity that may be useful in extending shelf life of fresh, refrigerated pasta/noodle products, and that further research to improve and maintain the cooking quality of FF-pasta during storage is needed.
The effects of lithification on fossil assemblage biodiversity and composition: An experimental test

Lithification of unconsolidated sediment into solid rock can bias the tabulation of taxonomic diversity from fossil assemblages in several ways. Methodological biases result from the relative difficulty of extracting fossils from lithified sediments, whereas diagenetic biases result from poor preservation or destruction of fossils by dissolution or other processes. Here, we use an experimental approach to isolate the effects of methodological biases. Replicate samples of Pleistocene mollusks were collected from the same series of horizons at the same outcrop. One set of replicates was sieved and the other was cemented into artificial rocks before identifying and counting species. These procedures probably represent a best-case scenario for recovering biological signals: the artificial rocks were only poorly lithified, the sampling process was not highly destructive, and the smallest mollusks (< 4 mm) were excluded. However, minor biases were still introduced by the non-random nature of locating and identifying species in the lithified samples, despite efforts at random sampling. After standardizing sampling effort, the cemented samples actually appeared slightly more diverse than the uncemented replicates due to the oversampling of rare species. Assemblage composition was affected slightly by lithification, notably in the undersampling of oysters, whose irregular shells were probably more difficult to identify in matrix. The methodological effects of lithification doubtlessly vary – sample processing will be more destructive for some rocks and fossils – but methodological biases can be quite mild in some cases. Gwen M. Daley. Department of Chemistry, Physics and Geology, Winthrop University, Rock Hill, South Carolina 29733, USA. daleyg@winthrop.edu Andrew M. Bush. Department of Geosciences and Department of Ecology and Evolutionary Biology, University of Connecticut, 354 Mansfield Rd, Storrs, Connecticut 06269-1045, USA. andrew.bush@uconn.edu
Prioritisation of antibiotics, antiparasitics, carbamates and NSAIDs for monitoring in horse, goat, sheep and milk

of nature to improve the q uality of life” . U nder the banner Wageningen U niversity & Research, Wageningen U niversity and the specialised research institutes of the Wageningen Research Foundation have j oined forces in contributing to inding solutions to important q uestions in the domain of healthy food and living environment. With its roughly 30 branches, 5,000 employees and 12,000 students, Wageningen U niversity & Research is one of the leading organisations in its domain. The uniq ue Wageningen approach lies in its integrated approach to issues and the collaboration between different disciplines. Wageningen Food Safety Research P.O. Box 230 6700 AE Wageningen The Netherlands T +31 (0)317 48 02 56 www.wur. eu/food-safety-research
TRANSIENT ANALYSIS IN HALF-SPACE COMBINING IGA AND THE PERFECTLY MATCHED LAYER METHOD

This contribution is concerned with a numerical approach to represent the elastic half-space subjected to dynamic forces. The proposed numerical solution is achieved by combining the advantages of the isogeometric analysis concept and the absorbing boundary technique, Perfectly Matched Layer (PML). Due to the nature of the half-space modeling, the attenuation or propagation of the wave motion to inﬁnity as well as an optimal representation of the dynamic response of the media must be validated. Both conditions are needed to obtain acceptable results for dynamic analysis. In this contribution, the PML in combination with the B-Splines is adopted. On one hand, B-Splines is capable of describing more precisely the geometry, dynamic effects and the unknown ﬁeld of the problem. On the other hand, the spurious reﬂections are avoided employing the PML method. This is deﬁned using an artiﬁcial layer surrounding the computational domain. Using these two formulations, a better representation of the half-space domain can be achieved with less computational effort and higher accuracy. In order to evaluate the performance of this approach, a numerical example is presented for the 2D case considering a homogeneous linear elastic domain. The equation of motion is solved using the displacement-based formulation and approximated by an implicit time integration method. The variation of spatial and temporal reﬁnement of the selected domain, the order of interpolation functions and geometrical properties of the absorbing layer are the considered aspects to investigate the performance of this approach. The results are also compared with the standard FEM.