Miracle-dz/UniFAR-FTUs huggingface dataset:
Active Example Selection for In-Context Learning

With a handful of demonstration examples, large-scale language models demonstrate strong capability to perform various tasks by in-context learning from these examples, without any fine-tuning. We demonstrate that in-context learning performance can be highly unstable across samples of examples, indicating the idiosyncrasies of how language models acquire information. We formulate example selection for in-context learning as a sequential decision problem, and propose a reinforcement learning algorithm for identifying generalizable policies to select demonstration examples. For GPT-2, our learned policies demonstrate strong abilities of generalizing to unseen tasks in training, with a 5.8% improvement on average. Examples selected from our learned policies can even achieve a small improvement on GPT-3 Ada. However, the improvement diminishes on larger GPT-3 models, suggesting emerging capabilities of large language models.
J. S. Bach

Probably the one pianistic skill most desired by those who have studied piano or plan to study piano is the ability to sightread. This need and desire for sightreading skill is ably discussed in the opening chapter of Mr. Laurence's book. Despite the many books and articles written on the necessity of establishing good sightreading habits, many piano teachers continue to disregard their importance. The reasons may include lack of time at the private lesson or lack of knowledge of how to go about the actual teaching of the necessary habits to be established. The author of this book contends that the majority of piano teachers have concentrated upon the hands, the ears, and the mind, but have overlooked the eyes. With this in mind, he thoroughly explains and discusses adequate training in vertical reading combined with horizontal reading. The book has two main sections, the first being a detailed study of this particular aspect of reading. Results of actual surveys and experiments in remedial reading made by the author are included. This section closes with a discussion of the necessity for developing certain primary skills as a prerequisite to good sightreading. Since the author emphasizes the need for developing these fundamental skills "until they become second nature" before one can begin to work at the specific drills suggested, it might have been better to have preceded the the discussion of vertical reading with this excellent
Planes of Satellites around Simulated Disk Galaxies. II. Time-persistent Planes of Kinematically Coherent Satellites in ΛCDM

We use two zoom-in ΛCDM hydrodynamical simulations of massive disk galaxies to study the possible existence of fixed satellite groups showing a kinematically coherent behavior across evolution (angular momentum conservation and clustering). We identify three such groups in the two simulations, defining kinematically coherent persistent planes (KPPs) that last at least from virialization to z = 0 (more than 7 Gyr). This proves that orbital pole clustering is not necessarily set in at low redshift, representing a long-lived property of galaxy systems. KPPs are thin and oblate, represent ∼25%–40% of the total number of satellites in the system, and are roughly perpendicular to their corresponding central disk galaxies during certain periods, consistently with Milky Way z = 0 data. KPP satellite members are statistically distinguishable from satellites outside KPPs: they show higher specific orbital angular momenta, orbit more perpendicularly to the central disk galaxy, and have larger pericentric distances than the latter. We numerically prove, for the first time, that KPPs and the best-quality positional planes share the same space configuration across time, such that KPPs act as “skeletons” preventing the latter from being washed out in short timescales. In one of the satellite−host systems, we witness the late capture of a massive dwarf galaxy endowed with its own satellite system, also organized into a KPP configuration prior to its capture. We briefly explore the consequences this event has on the host’s KPP and on the possible enhancement of the asymmetry in the number of satellites rotating in one sense or the opposite within the KPP.
Analyzing the Evolution of Database Usage in Data-Intensive Software Systems

This chapter presents the research advancements in the field of data‐intensive software system evolution, 5 years after the publication of the IEEE Computer column presenting the challenges in this field (A. Cleve, T. Mens, and J.‐L. Hainaut (2010) Data‐intensive system evolution. Computer , 43 (8), 110–112). We present the state of the art in this research domain, and report on the evolution of open‐source Java projects relying on relational database technologies. We empirically analyze how the usage of Java database technologies evolve over time. We report on a coarse‐grained source‐code analysis carried out over several thousands of Java projects, and complement this with a fine‐grained longitudinal analysis of the coevolution between database schema changes and source code changes within three large Java projects. The presented results are the first steps toward a recommendation system supporting developers in writing database‐centered code.
Entry-Level Products with Consumer Learning

Abstract Dynamic motivations for the use of product line extensions in the form of entry-level products are considered. When consumers are uncertain of their valuations for products, and their purchasing power evolves over time, firms competing in a lucrative luxury market may try to influence the future buying decisions of young consumers. Offering entry-level products allows young consumers to experiment and thereby make better future decisions. Despite this efficiency, so providing information to consumers need not benefit a firm. The dynamic motivations for offensive product introductions differ discretely from defensive introductions.
OnBoard Vision Based Object Tracking Control Stabilization Using PID Controller

In this paper, we propose a simple and effective vision-based tracking controller design for autonomous object tracking using multicopter. The multicopter based automatic tracking system usually unstable when the object moved so the tracking process can’t define the object position location exactly that means when the object moves, the system can’t track object suddenly along to the direction of objects movement. The system will always looking for the object from the first point or its home position. In this paper, PID control used to improve the stability of tracking system, so that the result object tracking became more stable than before, it can be seen from error of tracking. A computer vision and control strategy is applied to detect a diverse set of moving objects on Raspberry Pi based platform and Software defined PID controller design to control Yaw, Throttle, Pitch of the multicopter in real time. Finally based series of experiment results and concluded that the PID control make the tracking system become more stable in real time.
Using Partial Coverage Strategy to Prolong Service Time of a Cluster-Based Wireless Sensor Network

For the design of a wireless sensor network, researchers always focus on how to take advantage of all sensor nodes to work for covering the whole sense area. This strategy can be classified as complete coverage strategy. A criticism been ignored that the goal of complete coverage is detrimental to the lifespan of network because the overlapping of sensor area among nodes result in unnecessary waste of energy. This study proposes another proposition from the idea of partial coverage strategy. A near perfect coverage rate can be achieved by least nodes to save the energy of the whole system. The proposed method in this paper can adjust required coverage rate to achieve graceful degradation according to the amount of live sensor nodes, and forms a multi-hop cluster network with a required connectivity. The method is suitable for practical applications of largescale or high-density wireless sensor networks due to its distributed processing and scalable cluster topology.
A Probabilistic Approach for the System-Level Design of Multi-ASIP Platforms

(11/12/2018) A Probabilistic Approach for the System-Level Design of Multi-ASIP Platforms Application Specific Instruction-set Processors (ASIPs) offer a good trade off between performance and flexibility when compared to general purpose processors or ASICs. Additionally, multiple ASIPs can be included in a single platform and they allow the generation of customized heterogeneous MPSoC with a relatively short time-to-market. While there are several commercial tools for the design of a single ASIP, there is still a lack of automation in the design of multi-ASIP platforms.
Bee Inspired Online Vehicle Routing in Large Traffic Systems

Traffic congestions have been a major problem in metropolitan areas worldwide, causing enormous economical as well as ecological damage. We argue that, due to the highly dynamic character of congestion forming and dissolving, any adequate solution for individual online vehicle routing in large traffic systems will require distributed, adaptive coordination of local navigators in order to transmit directions in due time before any road intersection which would still be valid when carried out. In this paper a completely distributed and adaptive swarm intelligence based multi-layered approach termed BeeJamA is presented. It features dynamic deadlines. There is no need of global or centralized information. We report on extensive simulation experiments with the MATSim simulator verifying BeeJamA’s superior performance compared to existing models.
A PROPOSAL FOR PREDICTING MISSING VALUES IN A DATASET USING SUPERVISED LEARNING

Missing values occur frequently in various field experiments and trials of data. These missing values in a dataset pose challenges for the data miners and analysts working on that dataset. Hence knowing how to predict those missing values is important. The process of replacing missing value with the predicted value is called Imputation. In this paper we propose an Imputation method to predict the missing values based on supervised learning classification scheme. The proposed method first maps the missing value problem into a classification problem by discretization of the known available values. Further we make use of C 4.5 decision tree algorithm for prediction of the discrete nominal values corresponding to the missing values. Finally we predict the numeric values for the missing places using Local Closet Fit algorithm where the term local is defined by the discretization of the known values of the attribute with missing values. The performance of the proposed method is compared with the existing schemes for data imputation where the results show that the proposed method has higher prediction accuracy.
Super-Resolution Microscopy Opens New Doors to Life at the Nanoscale

Super-resolution fluorescence microscopy holds tremendous potential for discovery in neuroscience. Much of the molecular machinery and anatomic specializations that give rise to the unique and bewildering electrochemical activity of neurons are nanoscale by design, ranging somewhere between 1 nm and 1 μm. It is at this scale where most of the unknown and exciting action is and where cell biologists flock to in their dreams, but it was off limits for light microscopy until recently. While the optical principles of super-resolution microscopy are firmly established by now, the technology continues to advance rapidly in many crucial areas, enhancing its performance and reliability, and making it more accessible and user-friendly, which is sorely needed. Indeed, super-resolution microscopy techniques are nowadays widely used for visualizing immunolabeled protein distributions in fixed or living cells. However, a great potential of super-resolution microscopy for neuroscience lies in shining light on the nanoscale structures and biochemical activities in live-tissue settings, which should be developed and harnessed much more fully. In this review, we will present several vivid examples based on STED and RESOLFT super-resolution microscopy, illustrating the possibilities and challenges of nano-imaging in vivo to pique the interest of tech-developers and neurobiologists alike. We will cover recent technical progress that is facilitating in vivo applications, and share new biological insights into the nanoscale mechanisms of cellular communication between neurons and glia.
Starch/Poly (Glycerol-Adipate) Nanocomposite Film as Novel Biocompatible Materials

Starch is one of the most abundant polysaccharides on the earth and it is the most important source of energy intake for humans. Thermoplastic starch (TPS) is also widely used for new bio-based materials. The blending of starch with other molecules may lead to new interesting biodegradable scaffolds to be exploited in food, medical, and pharmaceutical fields. In this work, we used native starch films as biopolymeric matrix carriers of chemo enzymatically-synthesized poly (glycerol-adipate) (PGA) nanoparticles (NPs) to produce a novel and biocompatible material. The prototype films had a crystallinity ranging from 4% to 7%. The intrinsic and thermo-mechanical properties of the composite showed that the incorporation of NPs in the starch films decreases the glass transition temperature. The utilization of these film prototypes as the basis for new biocompatible material showed promise, particularly because they have a very low or even zero cytotoxicity. Coumarin was used to monitor the distribution of the PGA NPs in the films and demonstrated a possible interaction between the two polymers. These novel hybrid nanocomposite films show great promise and could be used in the future as biodegradable and biocompatible platforms for the controlled release of amphiphilic and hydrophobic active ingredients.
Genome Survey Sequencing and Genetic Background Characterization of the Wolf Spider Pardosa pseudoannulata (Araneae: Lycosidae)

ABSTRACT: The wolf spider Pardosa pseudoannulata is a typical wandering spider and is frequently viewed as a biological indicator. However, published information on the P. pseudoannulata genome is limited. To explore the genomic structure of P. pseudoannulata, we performed a genome survey using high-throughput sequencing technologies at approximately 16.41X coverage depth. We obtained 67.48 Gb of sequence data, with an estimated genome size of 4.11 Gb and guanine plus cytosine (GC) content of 35.34%. The repeat ratio of the P. pseudoannulata genomic sequence was 79.16% and the heterozygote rate was 0.4%. By analysing the characteristics of the genome, 150,288 simple sequence repeats (SSRs) were identified. Among these SSRs, the mononucleotide repeat type was the most abundant (62.56% of total SSRs), followed by the dinucleotide (23.84%), trinucleotide (7.39%), tetranucleotide (3.94%), pentanucleotide (2.24%), and hexanucleotide (0.03%) repeat types. This is the first genome-wide characterization of P. pseudoannulata, which highlighted the genomic characteristics of low hybridization, high repetition, large size, and complex structure. The data obtained from our genome survey will not only aid the design of future P. pseudoannulata whole-genome sequencing projects but will also be valuable for further studies on genetic diversity and evolutionary analysis.
Nonlinear transient analysis of FG pipe subjected to internal pressure and unsteady temperature in a natural gas facility

This study investigates the response of functionally graded (FG) gas pipe under unsteady internal pressure and temperature. The pipe is proposed to be manufactured from FGMs rather than custom carbon steel, to reduce the erosion, corrosion, pressure surge and temperature variation effects caused by conveying of gases. The distribution of material graduations are obeying power and sigmoidal functions varying with the pipe thickness. The sigmoidal distribution is proposed for the 1st time in analysis of FG pipe structure. A Two-dimensional (2D) plane strain problem is proposed to model the pipe cross-section. The Fourier law is applied to describe the heat flux and temperature variation through the pipe thickness. The time variation of internal pressure is described by using exponential-harmonic function. The proposed problem is solved numerically by a two-dimensional (2D) plane strain finite element ABAQUS software. Nine-node isoparametric element is selected. The proposed model is verified with published results. The effects of material graduation, material function, temperature and internal pressures on the response of FG gas pipe are investigated. The coupled temperature and displacement FEM solution is used to find a solution for the stress displacement and temperature fields simultaneously because the thermal and mechanical solutions affected greatly by each other. The obtained results present the applicability of alternative FGM materials rather than classical A106Gr.B steel. According to proposed model and numerical results, the FGM pipe is more effective in natural gas application, especially in eliminating the corrosion, erosion and reduction of stresses.
Improvement properties of EPDM rubber using hybrid chitin/clay filler for industrial products

This work deals to synthesis chitin from Shrimp shells, that were collected from the local market scraped, washed, and ground. Deproteinization and decalcification process were applied on the ground shells to obtain pure chitin that identified and characterized by FTIR spectra, thermogravimetric analysis and scanning electron microscope SEM. The rubber compounds were prepared by incorporation of chitin as biomaterial and the other additive as curative system in ethylene propylene diene monomer (EPDM) rubber matrix using the laboratory two-roll mill. The rheological characteristics were tested using oscillating disc rheometer. The physico-mechanical properties of the prepared rubber vulcanizates before and after exposure to thermal oxidative ageing swelling properties, water uptake and chitin dispersion in rubber were investigated. It was found that at 5 phr of chitin the value of tensile strength of EPDM/chitin vulcanizates has higher value than the other concentrations of chitin. While the modulus at 50 % elongation and hardness increased with increasing chitin concentration. The samples containing 5 and 10 phr chitin show good thermal stability. Also, the effect of nanoclay concentration (3,5,7 and 10 Phr) as binary hybrid filler properties of EPDM rubber were evaluated. It was observed that, the rheological characteristics and the physico-mechanical properties were improved due to apply nanoclay as binary hybrid filler with chitin.
Influence of nucleating agent type on the morphology of extruded polyetherimide foam for printed circuit boards*

This work focuses on the development of foamed high temperature thermoplastic substrates for printed circuit boards. For this application it is necessary to achieve mean cell diameters smaller than 30 µm in order to be able to realize vias and high packaging densities (miniaturization). Different additives as nucleating agents, namely macro- and micro-crystalline talc, silica, calcium carbonate, and wollastonite, were melt-compounded with polyetherimide using a twin-screw extruder. Foamed samples are prepared by foam extrusion using a slit die and CO2 as physical blowing agent. The aim of this study is to analyze the influence of the mean particle size and the particle surface tension on the mean cell diameters. Therefore, the shape of the additives, the foam morphology, and the elongational viscosity were considered. The additives with a suitable particle size and surface tension exhibit a positive influence on the foam morphology, resulting in smaller cell diameters (<30 µm), a narrower cell size distribution and a foam density lower than 900 kg/m3. If the mean particle diameter of the nucleating agents is lower than 0.6 µm in this study, no nucleation effect could be observed. This is related to the fact that no heterogeneous nucleation occurs, if the particle diameter is too small. If the mean particle diameter of the used additives is larger than 1.5 µm, which could be demonstrated in this study in case of polyetherimide, then the additive acts as nucleating agent and heterogeneous nucleation occurs. Furthermore, it was observed that the mean cell diameter was affected by the different surface tensions of the studied nucleating agents.
Increase in Surface Friction Dominates the Observed Surface Wind Speed Decline during 1973–2014 in the Northern Hemisphere Lands

During 1973–2014, a reduction trend in the observed surface wind speed (10 m) in the Northern Hemisphere lands has been widely reported; this reduction is referred to as “global stilling. ” The primary determining factors of global stilling include atmospheric circulation, turbulent friction, and surface friction when ignoring the vertical influencing factors. Most of the existing studies on the attribution of global stilling do not take changing surface friction into account. In addition, there are other changes in the climate system, such as aerosol loading, which could have an impact on atmospheric circulation, but are not included in the majority of current models either. Here, we developed a novel approach based on modeled winds calculated from sea level pressure observations and applied the method to approximately 4000 weather stations in the Northern Hemisphere lands from 1973 to 2014 to attribute the stilling in the three factors. In our methods, we neglected the vertical influencing factors on surface wind speed but took the aerosols’ changes on atmospheric circulation and gradual urbanization effect on surface wind speed into account. We found that atmospheric circulation has dictated the monthly variation in surface wind speed during the past four decades. However, the increased surface friction dominates the long-term declining trend of wind stilling. Our studies had uncertainties while neglecting the influence of vertical factors on surface wind stilling, despite most of the existing studies showing their effect was minor compared to the three factors explored in our study.
Exploring User Engagement in Information Networks: Behavioural – based Navigation Modelling, Ideas and Directions

Revealing an endless array of user behaviors in an online environment is a very good indicator of the user’s interests either in the process of browsing or in purchasing. One such behavior is the navigation behavior, so detected user navigation patterns are able to be used for practical purposes such as: improving user engagement, turning most browsers into buyers, personalize content or interface, etc. In this regard, our research represents a connection between navigation modelling and user engagement. A usage of the Generalized Stochastic Petri Nets concept for stochastic behavioral-based modelling of the navigation process is proposed for measuring user engagement components. Different types of users are automatically identified and clustered according to their navigation behaviors, thus the developed model gives great insight into the navigation process. As part of this study, Peterson’s model for measuring the user engagement is explored and a direct calculation of its components is illustrated. At the same time, asssuming that several user sessions/visits are initialized in a certain time frame, following the Petri Nets dynamics is indicating that the proposed behavioral – based model could be used for user engagement metrics calculation, thus some basic ideas are discussed, and initial directions are given.