Miracle-dz/UniFAR-FTUs huggingface dataset:
Granular collapse in two dimensions

An experimental investigation is conducted into the collapse of granular columns inside rectangular channels. The final shape is documented for slumps inside relatively wide channels, and for collapses inside much narrower slots. In both cases, the collapse is initiated by withdrawing a swinging gate or sliding door, and the flow remains fairly two-dimensional. Four different granular media are used; the properties of the materials vary significantly, notably in their angles of friction for basal sliding and internal deformation. If $H$ is the initial height of the column, $h_{\infty}$ the maximum final height of the column and $a$ the initial aspect ratio, then the data suggest that $H/h_{\infty} \,{\sim} a^{0.6}$ in wide channels and $H/h_{\infty} \,{\sim}\, a^{0.5}$ for narrow slots. For the runout, we find that $(l_{\infty}\,{-}\,L)/L \,{\sim}\, a^{0.9\pm 0.1}$ for wide channels, and $(l_{\infty}\,{-}\,L)/L \,{\sim}\, a^{0.65\pm0.05}$ or $l_\infty/L \,{\sim}\, a^{0.55\pm0.05}$ for narrow slots, where $l_{\infty}$ is the maximum runout of the material and $L$ the initial length of the column along the channel ($a\,{:=}\,H/L$). In all cases, the numerical constant of proportionality in these scaling relations shows clear material dependence. In wide slots, there is no obvious universal scaling behaviour of the final profile, but such a behaviour is evident in narrow slots. The experimental results are compared with theoretical results based on a shallow granular-flow model. The qualitative behaviour of the slump in the wide slot is reproduced by the theoretical model. However, there is qualitative disagreement between theory and the experiments in the narrow slot because of the occurrence of secondary surface avalanching.
Olarte-Sánchez, Cristian and Valencia-Torres, L. and Cassaday, Helen J. and Bradshaw, Chris and Szabadi, Elemer (2015) Quantitative analysis of performance on a progressive-ratio schedule: effects of reinforcer type, food deprivation and acute treatment

Rats’ performance on a progressive-ratio schedule maintained by sucrose (0.6 M, 50 l) and corn oil (100%, 25 l) reinforcers was assessed using a model derived from Killeen’s (1994) theory of schedulecontrolled behaviour, ‘Mathematical Principles of Reinforcement’. When the rats were maintained at 80% of their free-feeding body weights, the parameter expressing incentive value, a, was greater for the corn oil than for the sucrose reinforcer; the response-time parameter, ı, did not differ between the reinforcer types, but a parameter derived from the linear waiting principle (T0), indicated that the minimum postreinforcement pause was longer for corn oil than for sucrose. When the rats were maintained under freefeeding conditions, a was reduced, indicating a reduction of incentive value, but ı was unaltered. Under
Fisheries biology and movements of mangrove red snapper, Lutjanus argentimaculatus (Forsskål 1775), in New South Wales

The mangrove red snapper Lutjanus argentimaculatus is a medium to large tropical snapper (family Lutjanidae) found throughout the tropical and subtropical Indo-West Pacific. Lutjanus argentimaculatus biology has been thoroughly studied in tropical waters, where an ontogenetic migration from inshore juvenile habitats to offshore environments coincides approximately with sexual maturity. Tropical studies have also identified age-based demographic traits that render the species vulnerable to overexploitation, including longevity >50 years, low instantaneous natural mortality rates (M) and attainment of sexual maturity relatively late in life. However, the extent to which life-history traits described for tropical waters persist at the species’ cooler range limits, in the state of New South Wales (NSW) on the east coast of Australia, was unclear. Lutjanus argentimaculatus in NSW is not directly targeted by any commercial fisheries, but is prized by recreational line and spear fishers. Few species-specific regulatory measures have been set in the fishery and the NSW Saltwater Recreational Fishing Trust had identified the fishery biology of L. argentimaculatus as a researchable knowledge gap, providing an impetus for this project. The primary aim of the thesis was to provide biological and ecological information to inform management of this fishery. A secondary aim was to critically assess lutjanid age validation research. These aims are addressed in four major chapters contextualised by an Introduction and Synthesis. Chapter 2 critiques lutjanid age validation research through a literature review, and Chapter 3 presents an age and growth study using sectioned otoliths. The age structure described in Chapter 3 is consistent with ontogenetic migration from estuaries to offshore. Chapter 4 therefore seeks further evidence of ontogenetic migration by comparing gonadal development of estuarine and offshore L. argentimaculatus. Chapter 5 is an acoustic telemetry study that provides an additional line of evidence for ontogenetic migration, and also investigates L. argentimaculatus movements in three northern NSW estuaries. Chapter 2 demonstrates that age validation studies have uniformly supported annual increment formation in lutjanid otoliths, including those of L. argentimaculatus. The four main techniques used to validate lutjanid ages are marginal increment analysis (MIA), chemical marking, bomb radiocarbon dating and radiometric dating using the uranium pair 210Pb:226Ra (lead-radium dating). Bomb radiocarbon and lead-radium dating provide absolute age estimates, which can validate increment counts in calcified structures. However, bomb radiocarbon dating cannot accurately age fish older than ~55 years, an age some lutjanids meet or exceed. In contrast, lead-radium dating is applicable to fish aged up to approximately 100 years. Technical advances and empirical verification of key assumptions over the past two decades have established the lead-radium chronometer’s accuracy and validity, but precision varies with several…
Fen Bilgisi Öğretmenlerinin Ders Sürecinde Ve Yazılı Sınavlarda Sordukları Soruların Bilişsel Seviyelerinin Karşılaştırılması

Gunluk planlarda ve yazili sinavlarda sorulan sorularin niteligi ogrencilerin zihinsel ve sosyal gelisimlerini etkilemektedir. Egitim ogretim surecinde olcme ve degerlendirmede onemli bir yere sahip olan sorular, Bloom Taksonomisi dikkate alinarak hazirlanmaktadir. Bu arastirma, fen bilgisi ogretmenlerinin gunluk planlarinda yer verdikleri sorularla yazili sinavlarda sorduklari sorularin bilissel seviyelerini ve iliski duzeylerini ortaya koymak amaciyla yapilmistir. 20 fen bilgisi ogretmeninin gunluk planlarindaki 1166 degerlendirme sorusu ile 574 yazili sinav sorusu Bloom Taksonomisi’nin bilissel seviyeleri dikkate alinarak incelenmistir. Elde edilen verilerden ders islenis surecinde sorulan sorularin ogrencileri daha cok ezbere yonelten bilgi duzeyinde oldugu, yazili sinavlarda sorulan sorularin ise ust duzeyde oldugu tespit edilmistir. Ders islenis surecinde sorulan sorularin ve yazili sinavlarda sorulan sorularinin bilissel seviyelerinin birbiriyle paralellik gostermedigi sonucuna ulasilmistir
A Study on Prediction of Body Weights Using Biometrical Measurements in Nellore Brown Sheep under Field Conditions

This study was carried out for prediction of body weights in Nellore brown sheep by using statistical methods. The sheep were divided into four age groups based on the number of permanent teeth emerged out. Data on body weights and body measurements were collected from 897 Nellore brown sheep from five divisions of Kadapa district in Andhra Pradesh. Body weights and body measurements were significantly affected by the divisions. The male lambs were significantly heavier than females at all stages of growth. Body weight was found to be phenotypically highly positively correlated with height at withers (WH), chest girth (CG), paunch girth (PG), hip width (HW) and body length (BL). Simple regression and multiple regression analysis to predict body weight was carried out at all age groups. It is concluded that body weight could be predicted by statistical methods using several body measurements in Nellore brown sheep.
Linear profile decompositions for a family of fourth order Schrödinger equations

We establish linear profile decompositions for the fourth order Schr\"odinger equation and for certain fourth order perturbations of the Schr\"odinger equation, in dimensions greater than or equal to two. We apply these results to prove dichotomy results on the existence of extremizers for the associated Stein--Tomas/Strichartz inequalities; along the way, we also obtain lower bounds for the norms of these operators.
Special Issue on Data Mining in Finance C World Scientific Publishing Company Switching Portfolios

A constant rebalanced portfolio is an asset allocation algorithm which keeps the same distribution of wealth among a set of assets along a period of time. Recently, there has been work on on-line portfolio selection algorithms which are competitive with the best constant rebalanced portfolio determined in hindsight (Cover, 1991; Helmbold et al., 1996; Cover and Ordentlich, 1996). By their nature, these algorithms employ the assumption that high returns can be achieved using a fixed asset allocation strategy. However, stock markets are far from being stationary and in many cases the wealth achieved by a constant rebalanced portfolio is much smaller than the wealth achieved by an ad hoc investment strategy that adapts to changes in the market. In this paper we present an efficient portfolio selection algorithm that is able to track a changing market. We also describe a simple extension of the algorithm for the case of a general transaction cost, including the transactions cost models recently investigated in (Blum and Kalai, 1997). We provide a simple analysis of the competitiveness of the algorithm and check its performance on real stock data from the New York Stock Exchange accumulated during a 22-year period. On this data, our algorithm outperforms all the algorithms referenced above, with and without transaction costs.
Graphs with 1-factors

In this paper it is shown that if G is a connected graph of order 2n (n > 1) not containing a 1-factor, then for each k, 1 2. Let a, y E G be points of G which are a distance d apart and let D=a a . xy be a path of length djoining a andy. Suppose Received by the editors September 5, 1972. AMS (MOS) subject classiications (1970). Primary 05C99. @ American Mathematical Society 1974
Threshold and hitting time for high-order connectivity in random hypergraphs

We consider the following definition of connectivity in $k$-uniform hypergraphs: Two $j$-sets are $j$-connected if there is a walk of edges between them such that two consecutive edges intersect in at least $j$ vertices. We determine the threshold at which the random $k$-uniform hypergraph with edge probability $p$ becomes $j$-connected with high probability. We also deduce a hitting time result for the random hypergraph process -- the hypergraph becomes $j$-connected at exactly the moment when the last isolated $j$-set disappears. This generalises well-known results for graphs.
Voluntary Participation and Provision of Public Goods in Large Finite Economies

We consider a public good provision game with voluntary participation. Agents participating in the game provide a public good and pay the fees according to a mechanism (allocation rule), while non-participants can free-ride on the participants. We examine how the equilibrium public good provision level is a¤ected by enlarging the population of an economy. We introduce a condition for an allocation rule, the asymptotic uniform continuity in replication (AUCR), which requires that small changes in the population must yield only small changes in the public good provision and which is satis…ed by many mechanisms. We show that under AUCR, the equilibrium level of the public good converges to zero as the economy is replicated in the sense of Milleron (1972). Takamiya, and the two anonymous referees and the associate editor of the journal for their helpful comments. We also thank participants at Hitotsubashi COE Lectures and
Primer : The deconstruction of neuronal spike trains

As information flows through the brain, neuronal firing progresses from encoding the world as sensed by the animal to driving the motor output of subsequent behavior. One of the more tractable goals of quantitative neuroscience is to develop predictive models that relate the sensory or motor streams with neuronal firing. Here we review and contrast analytical tools used to accomplish this task. We focus on classes of models in which the external variable is compared with one or more feature vectors to extract a low-dimensional representation, the history of spiking is potentially incorporated, and these factors are nonlinearly transformed to predict the occurrences of spikes. We illustrate these techniques in application to datasets of different degrees of complexity. In particular, we address the fitting of models in the presence of strong correlations in the sensory stream, as occurs in natural external stimuli and with sensation generated by self-motion.
VR-Participation: The feasibility of the Virtual Reality-driven multi-modal communication technology facilitating e-Participation

Textual communication which currently has largely shifted from paper to digital space is predominant in the domain of e-Participation. Even though the ubiquitous text-based communication through forums, chats, emails and social media is easy to use and process it shows significant lack of expressivity. Despite the proliferation of voice-based and video-based teleconferencing solutions compensating the communication gap in textual channels the contemporary digital communication systems struggle to deliver close to face-to-face group communication experience. Therefore, major government and citizen meetings and hearings have to be held in person to ensure quality discussions. In this paper, we argue that multi-modal communication enabled by the emerging, affordable and accessible VR technologies creates an opportunity to integrate the majority of mainstream channels into one communication platform.
Changes in the Long-Term Geophysical Eruptive Precursors at Piton de la Fournaise: Implications for the Response Management

Anticipating eruptions early enough to give warning to authorities is one of the main goals in volcanology. However, identifying and providing unequivocal identification on volcano reawakening remain challenging issues, mostly when unrests are sudden or undetectable. At the Piton de la Fournaise volcano, a clear increase in both the seismicity and the ground displacements are systematically observed a few days/weeks before eruptions, and appear as clear eruptive precursors. Here a systematic study of these long-term precursors demonstrates the changes in their intensity, duration, and time of appearance during 1998-2017 (43 eruptions), directly linked to the influence of the pre-and post-summit caldera formation (April 2007) and to changes in the deep magma refilling process since 2016. These changes in the precursors were not without consequence on the early alert to the authorities, with some false alerts and late alerts. It is thus of prime importance for crisis management to bear in mind the possibility of these rapid changes and that of sudden volcanic unrest with little warnings, to be able to take the most appropriate decisions, in particular raising the level of alert or lifting it totally. The findings of this study have enabled the relevant authorities to improve the alert chain protocol, and scientists to communicate more efficiently with the decision-makers.
Large-Scale Order Dispatch in On-Demand Ride-Hailing Platforms: A Learning and Planning Approach

We present a novel order dispatch algorithm in large-scale on-demand ride-hailing platforms. While traditional order dispatch approaches usually focus on immediate customer satisfaction, the proposed algorithm is designed to provide a more efficient way to optimize resource utilization and user experience in a global and more farsighted view. In particular, we model order dispatch as a large-scale sequential decision-making problem, where the decision of assigning an order to a driver is determined by a centralized algorithm in a coordinated way. The problem is solved in a learning and planning manner: 1) based on historical data, we first summarize demand and supply patterns into a spatiotemporal quantization, each of which indicates the expected value of a driver being in a particular state; 2) a planning step is conducted in real-time, where each driver-order-pair is valued in consideration of both immediate rewards and future gains, and then dispatch is solved using a combinatorial optimizing algorithm. Through extensive offline experiments and online AB tests, the proposed approach delivers remarkable improvement on the platform's efficiency and has been successfully deployed in the production system of Didi Chuxing.
Fast Searching Strategy for Critical Cascading Paths Toward Blackouts

The analysis of severe cascading blackouts is an essential issue in power grid planning and operation. As there are a tremendous number of possible cascade paths in a large power system, it is very challenging to determine the critical cascading paths that may have catastrophic consequences. This paper proposes a complex network theory based methodology to determine such critical cascading paths with high efficiency. To this end, we construct an improved interaction graph to cope with the situation where the $(N-1)$ criterion is not satisfied during the follow-up cascade propagation after an initial fault. Subsequently, based on the graph, we derive a modified PageRank model to fast rank the influence of individual transmission lines on blackout risks. Further, leveraging the results of influence ranking, we devise an efficient strategy for searching critical cascading paths. Then, we derive an unbiased probability estimation method for individual cascading paths and the blackout. Simulations carried out on the IEEE 39-bus system, the IEEE 118-bus system, and a real-world 1122-bus system in China show that our method can enhance the searching efficiency by up to three orders of magnitude compared with standard Monte Carlo approaches, demonstrating its potential for cascading blackout analysis in large-scale power systems. Results also verify that the proposed probability estimation method is unbiased, and it can provide an efficient way for probability estimation of the blackouts with very low probability but high losses.
Fuzzy Logic Sensor Fusion for Obstacle Avoidance Mobile Robot

Autonomous mobile robots have in recent times gained interest from many researchers. A reliable collision avoidance methodology is needed for effective navigation. Normally robots are fitted with transducers such as ultrasonic sensors, infrared and camera for detecting environment. However, they are usually unreliable because of pertinent problems of dealing with vagueness in the surroundings. Many researcher present three input Fuzzy Controller for obstacle avoidance robots usually resulting in dead zone and difficulties in avoiding obstacles. A fusion model using Fuzzy logic is proposed. It uses eight input distance sensors, two output variables and twenty seven fuzzy rules for robot navigation. Simulations are performed to validate feasibility and efficacy of proposed model using V-REP and MATLAB software.
Inferring, Characterizing, and Investigating Internet-Scale Malicious IoT Device Activities: A Network Telescope Perspective

Recent attacks have highlighted the insecurity of the Internet of Things (IoT) paradigm by demonstrating the impacts of leveraging Internet-scale compromised IoT devices. In this paper, we address the lack of IoT-specific empirical data by drawing upon more than 5TB of passive measurements. We devise data-driven methodologies to infer compromised IoT devices and those targeted by denial of service attacks. We perform large-scale characterization analysis of their traffic, as well as explore a public threat repository and an in-house malware database, to underlie their malicious activities. The results expose a significant 26 thousand compromised IoT devices "in the wild," with 40% being active in critical infrastructure. More importantly, we uncover new, previously unreported malware variants that specifically target IoT devices. Our empirical results render a first attempt to highlight the large-scale insecurity of the IoT paradigm, while alarming about the rise of new generations of IoT-centric malware-orchestrated botnets.
Toward Refactoring Evaluation with Code Naturalness

Refactoring evaluation is a challenging research topic because right and wrong of refactoring depend on various aspects of development context such as developers' skills, development cost, deadline and so on. Many techniques have been proposed to evaluate refactoring objectively. However, those techniques do not consider individual contexts of software development. Currently, the authors are trying to evaluate refactoring automatically and objectively with considering development contexts. In this paper, we propose to evaluate refactoring with code naturalness. Our technique is based on a hypothesis: if a given refactoring raises the naturalness of existing code, the refactoring is beneficial. In this paper, we also report our pilot study on open source software.
Rationale for Combining Bispecific T Cell Activating Antibodies With Checkpoint Blockade for Cancer Therapy

T cells have been established as core effectors for cancer therapy; this has moved the focus of therapeutic endeavors to effectively enhance or restore T cell tumoricidal activity rather than directly target cancer cells. Both antibodies targeting the checkpoint inhibitory molecules programmed death receptor 1 (PD1), PD-ligand 1 (PD-L1) and cytotoxic lymphocyte activated antigen 4 (CTLA4), as well as bispecific antibodies targeting CD3 and CD19 are now part of the standard of care. In particular, antibodies to checkpoint molecules have gained broad approval in a number of solid tumor indications, such as melanoma or non-small cell lung cancer based on their unparalleled efficacy. In contrast, the efficacy of bispecific antibody-derivatives is much more limited and evidence is emerging that their activity is regulated through diverse checkpoint molecules. In either case, both types of compounds have their limitations and most patients will not benefit from them in the long run. A major aspect under investigation is the lack of baseline antigen-specific T cells in certain patient groups, which is thought to render responses to checkpoint inhibition less likely. On the other hand, bispecific antibodies are also restricted by induced T cell anergy. Based on these considerations, combination of bispecific antibody mediated on-target T cell activation and reversal of anergy bears high promise. Here, we will review current evidence for such combinatorial approaches, as well as ongoing clinical investigations in this area. We will also discuss potential evidence-driven future avenues for testing.