Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching programming to beginners - choosing the language is just the first step

Over the years there has been an ongoing debate about which computer language to adopt for a first programming subject. Although some may not agree, the current consensus is that the object-oriented languages are winning the argument, and Java has increasingly become the language of choice for teaching beginners. But choosing the language is only the first step in designing a first programming subject. The adoption of an object-oriented language such as Java offers an opportunity to completely rethink our approach to teaching first-year programming, an opportunity that should not be missed. In this paper we identify what we see as the non language-specific core issues, and discuss how we approached these issues when designing and teaching a programming subject for beginners.
Polyhedral aspects of Submodularity, Convexity and Concavity

Seminal work by Edmonds and Lovasz shows the strong connection between submodularity and convexity. Submodular functions have tight modular lower bounds, and subdifferentials in a manner akin to convex functions. They also admit poly-time algorithms for minimization and satisfy the Fenchel duality theorem and the Discrete Seperation Theorem, both of which are fundamental characteristics of convex functions. Submodular functions also show signs similar to concavity. Submodular maximization, though NP hard, admits constant factor approximation guarantees. Concave functions composed with modular functions are submodular, and they also satisfy diminishing returns property. This manuscript provides a more complete picture on the relationship between submodularity with convexity and concavity, by extending many of the results connecting submodularity with convexity to the concave aspects of submodularity. We first show the existence of superdifferentials, and efficiently computable tight modular upper bounds of a submodular function. While we show that it is hard to characterize this polyhedron, we obtain inner and outer bounds on the superdifferential along with certain specific and useful supergradients. We then investigate forms of concave extensions of submodular functions and show interesting relationships to submodular maximization. We next show connections between optimality conditions over the superdifferentials and submodular maximization, and show how forms of approximate optimality conditions translate into approximation factors for maximization. We end this paper by studying versions of the discrete seperation theorem and the Fenchel duality theorem when seen from the concave point of view. In every case, we relate our results to the existing results from the convex point of view, thereby improving the analysis of the relationship between submodularity, convexity, and concavity.
Cluster Stability Analysis of a Brazilian Collection of Bacteria Bradyrhizobium spp

The taxonomy of N2-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined. This paper presents an application of a method aiming the identification of possible new clusters within a Brazilian collection of 119 Bradyrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability has been studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions. The method suggested here uses hierarchical clustering algorithms and Pearson correlation. Two clusters were clearly defined besides species B. japonicum and B. elkanii, indicating possible new species.
Mössbauer mineralogy of rock, soil, and dust at Gusev crater, Mars: Spirit's journey through weakly altered olivine basalt on the plains and pervasively altered basalt in the Columbia Hills

The Moessbauer spectrometer on Spirit measured the oxidation state of Fe, identified Fe-bearing phases, and measured relative abundances of Fe among those phases for surface materials on the plains and in the Columbia Hills of Gusev crater. Eight Fe-bearing phases were identified: olivine, pyroxene, ilmenite, magnetite, nanophase ferric oxide (npOx), hematite, goethite, and a Fe(3+)-sulfate. Adirondack basaltic rocks on the plains are nearly unaltered (Fe(3+)/Fe(sub T) Px), and minor npOx and magnetite. Columbia Hills basaltic rocks are nearly unaltered (Peace and Backstay), moderately altered (WoolyPatch, Wishstone, and Keystone), and pervasively altered (e.g., Clovis, Uchben, Watchtower, Keel, and Paros with Fe(3+)/Fe(sub T) approx.0. 6-0.9). Fe from pyroxene is greater than Fe from olivine (Ol sometimes absent), and Fe(2+) from Ol+Px is 40-49% and 9-24% for moderately and pervasively altered materials, respectively. Ilmenite (Fe from Ilm approx.3-6%) is present in Backstay, Wishstone, Keystone, and related rocks along with magnetite (Fe from Mt approx. 10-15%). Remaining Fe is present as npOx, hematite, and goethite in variable proportions. Clovis has the highest goethite content (Fe from Gt=40%). Goethite (alpha-FeOOH) is mineralogical evidence for aqueous processes because it has structural hydroxide and is formed under aqueous conditions. Relatively unaltered basaltic soils (Fe(3+)/Fe(sub T) approx. 0.3) occur throughout Gusev crater (approx. 60-80% Fe from Ol+Px, approx. 10-30% from npOx, and approx. 10% from Mt). PasoRobles soil in the Columbia Hills has a unique occurrence of high concentrations of Fe(3+)-sulfate (approx. 65% of Fe). Magnetite is identified as a strongly magnetic phase in Martian soil and dust.
2.5. Smart Pacemakers The evolution of pacemakers: an electronics perspective, from the hand crank to advanced wavelet analysis

Around 40% of all human deaths are attributed to cardiovascular diseases. Cardiac pacing has become a therapeutic tool used worldwide with over 250.000 pacemaker implants every year. The purpose of this article is to detail the significant advances in cardiac pacing systems. Our focus is on the evolution of circuit designs applied in pacemakers. Future pacemaker features and further improvements are also pointed out.
Testing Price Volume Relationship for Indian Commodity Futures with Linear Causality Test

Subhasis Biswas has been associated with biggest steel company of the country, SAIL, in Marketing for 18 years. Presently working with Jindal steel & Power Ltd, Kolkata as DGM (Mktg). He holds a Bachelor of Engineering(Met), Jadavpore University, PGDB from Indian Institute of Management Calcutta (Major in Finance & MIS) and currently pursuing his Ph. D. at VGSoM. Prabina Rajib is currently working as Associate Professor in Finance area at VGSoM. She has 25 research publications in refereed journals as well as around 15 conference proceedings. She is the coauthor of the book titled “Stock Exchanges, Investments and Derivatives: Straight Answers to 250 Nagging Questions”. She is a Fulbright Fellow and her teaching and research interest are in the area of Corporate Finance, Capital Market related issues, Financial and Commodity Derivatives. She did her MBA and Ph. D. from VGSoM, IIT Kharagpur. The nature of price volume relationship in asset market have been an interesting subject for financial research. There are two competing concept in price volume relationship. According to first model, mixture of distribution (MDH) hypothesis, positive contemporaneous causality exist between volume and price change due to contemporaneous dissemination of information. Other model, sequential information arrival hypothesis (SIH), suggests a positive intertemporal causal relationship between volume and price change. Several earlier studies found support of SIH. In this study the relation between price change and volume traded in Indian commodity futures market have been studied using Granger causality test with VAR methodology. The results suggest that bidirectional causality exist between return and volume which support SIH.
A tensor-based big data model for QoS improvement in software defined networks

The growing volume of network traffic and gradual deployment of SDN devices initiate a new era in which one distinguished feature is the application of big data technology to SDNs for construction of flexible, scalable, and self-managing networks. The primary purpose of this article is to develop a novel tensor-based model for efficient provisioning of QoS in software defined networks. First, a forwarding tensor model is proposed to formalize the networking functions in the data plane; then a controlling tensor model is presented for routing path recommendation in the control plane. Finally, the article introduces a transition tensor model for network traffic prediction and QoS provisioning. The three models can automatically monitor the network state, recommend routing paths and predict network traffic, respectively. A case study to recommend routing paths is investigated in the article.
Individual Preferences, Monetary Gambles, and Stock Market Participation: A Case for Narrow Framing

We argue that ? narrow framing,? whereby an agent who is offered a new gamble evaluates that gamble in isolation, may be a more important feature of decisionmaking than previously realized. Our starting point is the evidence that people are often averse to a small, independent gamble, even when the gamble is actuarially favorable. We find that a surprisingly wide range of utility functions, including many nonexpected utility specifications, have trouble explaining this evidence, but that this difficulty can be overcome by allowing for narrow framing. Our analysis makes predictions as to what kinds of preferences can most easily address the stock market participation puzzle. (JEL D81, G11)
Board Structures and Successful CDCs : Modeling the Ways

In just over thirty years, a new economic force has emerged in cities as thousands of Community Development Corporations (CDCs) have begun the task of revitalizing neighborhoods long abandoned by other engines of growth. As the organizations mature and founders begin to relinquish reigns on their organizations, the roles of the boards of directors are theoretically injected with new relevancy. It is the intention of this paper to place the role of the CDC board into the context of an evolving field, suggesting what CDC boards can learn from the generic governance literature and what the generic literature can learn from the case of CDC boards. Specifically we explore the impact of CDC contingency factors such as structure (e.g., size/age), environment (region, community), faith, and funding on the legitimacy of governance structures, compositions and processes/practices.
Design of a Fingertip-Mounted Tactile Display with Tangential Skin Displacement Feedback

Application of tangential skin displacement at the fingertip has been shown to be effective in communicating direction and has potential for several applications. We have developed a portable, fingertip-mounted tactile display capable of displacing and stretching the skin of the fingerpad, using a 7 mm hemispherical tactor. In vivo tests of fingerpad skin stiffness were performed to determine the forces required to effectively render stimuli. Other design parameters such as stimulus speed and displacement were derived from our earlier work. The tactile display is capable of rendering \pm 1 mm of displacement at arbitrary orientations within a plane and with rates of approximately 5 mm/s. Compliance and backlash in the device's drive train were characterized using external measurements, and were compensated for in software to reduce the impact on device hysteresis.
Discount Rate for Health Benefits and the Value of Life in India

This study contributes to the literature by estimating discount rate for environmental health benefits and value of statistical life of workers in India. The discount rate is imputed from wage-risk trade-offs in which workers decide whether to accept a risky job with higher wages. The estimated real discount rate ranges between 2.7 and 3 percent, which is closer to the financial market rate for the study period and consistent with earlier studies from developed nations. The estimated value of life is Rs. 20 (US $ 1.107) million. The results of the study can aid policymakers, international agencies and other researchers in evaluating health projects in India and other developing countries.
A new model of agent spawning and mobility

Mobile agent technology is becoming more popular and has been implemented in many distributed computing domains. Several research have been conducted to address its challenges including two most important ones which are agent spawning and agent mobility. This paper discusses the issues of mobile agent technology, the background of mobile agent cloning and spawning, agent mobility as well as the problems faced by many researchers in their research on mobile agents. The paper finally proposes new agent spawning and mobility models to resolve some of the researchers' problems.
Introduction to the Special Issue on Spatial modeling to explore land use dynamics

Land Use and Land Cover Change (LUCC) is a central theme of global environmental change research (Turner II 1994, Vitousek et al. 1997). The LUCC project of the International Geosphere-Biosphere Programme (IBGP) and the International Human Dimensions Programme on Global Environmental Change (IHDP) aims at stimulating and coordinating research on land use change (Lambin et al. 2000, Turner II et al. 1995). Scientists associated with the LUCC community have a background in different disciplines, ranging from anthropology to mathematical programming. However, this diverse group of scientists shares a common, geographic, interest: the future of the land. Much of the integration of knowledge on land use change takes place through (spatial) models that aim at explaining the causes, locations, consequences and trajectories of land use change. The variety in disciplinary origin of the researchers contributing to LUCC has lead to a wide range of different modeling approaches and techniques. The papers in this special issue provide an overview of a number of representative approaches for land use modeling that have evolved since the start of the LUCC project in 1995. The papers are selected contributions out of a series of nine conference sessions dedicated to land use modeling at the ‘‘Framing Land Use Dynamics’’ conference at Utrecht University, Utrecht, the Netherlands, 16–18 April 2003. The contributions provide an overview of the state-of-the art in land use modeling by presenting a range of different modeling techniques as well as methods for integrating the contribution of different disciplines into land use research. At the same time, the papers address some of the big issues identified as priorities in land use modeling (Lambin et al. 2003, Veldkamp and Lambin 2001): integration of knowledge over different scales and disciplines; the focus on land use changes at the rural-urban interface and the validation of land use models. The integration between the social, economic and spatial sciences at different scales is still one of the main challenges for LUCC research. For many of the disciplines participating in LUCC research the integration with the spatial sciences is troublesome and some of the researchers in the social sciences are not able to make optimal use of the wealth of information available through remote sensing and spatial analysis methods. At the same time, spatial modelers face difficulties in using the insights obtained from case studies of land use change conducted by sociologists and anthropologists. The LUCC implementation strategy (Lambin et al. 2000) made the integration of disciplinary approaches one of the main objectives of the programme: ‘‘The depth of understanding brought to bear from bottom-up, fieldbased approaches must be made spatially explicit, including efforts to integrate results with remote sensing information (‘pixeling the social’); remote sensing International Journal of Geographical Information Science Vol. 19, No. 2, February 2005, 99–102
Learning A* underestimates: Using inference to guide inference

We present a technique for speeding up inference of structured variables using a prioritydriven search algorithm rather than the more conventional dynamic programing. A priority-driven search algorithm is guaranteed to return the optimal answer if the priority function is an underestimate of the true cost function. We introduce the notion of a probable approximate underestimate, and show that it can be used to compute a probable approximate solution to the inference problem when used as a priority function. We show that we can learn probable approximate underestimate functions which have the functional form of simpler, easy to decode models. These models can be learned from unlabeled data by solving a linear/quadratic optimization problem. As a result, we get a priority function that can be computed quickly, and results in solutions that are (provably) almost optimal most of the time. Using these ideas, discriminative classifiers such as semi-Markov CRFs and discriminative parsers can be sped up using a generalization of the A* algorithm. Further, this technique resolves one of the biggest obstacles to the use of A* as a general decoding procedure, namely that of coming up with a admissible priority function. Applying this technique results in a algorithm that is more than 3 times as fast as the Viterbi algorithm for decoding semi-Markov Conditional Markov Models.
A New Bit Synchronization Method for an Ultra-Tightly Integrated GPS Receiver

We developed a novel INS assisted bit synchronization algorithm for an Ultra-Tightly integrated GPS receiver. This algorithm computes an estimate of the bit energy for all possible bit boundary candidates and chooses that candidate which maximizes the energy. It uses INS assisted extended Kalman filters to track and remove the error in the carrier parameters. Computer simulations show a superior performance of this bit synchronization at very weak signal powers. The bit synchronization achieves a high bit edge detection rate and optimal bit error rate even at very low power signals.
Exploiting user movement patterns to enhance energy efficiency in wireless networks

This paper presents an initial study on how to model user mobility in a wireless cellular network scenario. The model provides realistic patterns of movement between a number of locations. The aforementioned mobility model is built upon to introduce a base station (BS) energy efficient power state control algorithm (EESC) that is able to provide significant energy savings for the simulated scenario. Erratic subsequent on and off BS behavior is avoided by referring to an average loading curve, generated for each BS during a learning period, when making decisions. Moreover, BSs are turned off only when the users can be handed off to nearby cells with a predefined maximum allowed predicted loss in data rate. The resulting system is able to deliver an energy consumption reduction between 36% and 11% over an always on benchmark for the simulated scenarios. There is negligible loss in terms of achieved data rate per user.
Mining Popular Crime Patterns in Incremental Databases

The Crime investigation department have very significant role in police system in all countries in the world. Computer systems are placed in almost all police stations to store and retrieve the crimes and criminal data and for subsequent reporting. For crime analysts, it is a challenging, time-consuming to determine who have been committed crimes from the large set of crimes that are happening every year. Our goal is to identify recent popular crime patterns from large set of crime databases that are updating every day. To do this, we are proposing a popular crime pattern detection algorithm from incremental crime databases. Such data mining technologies are helpful to design proactive services to reduce crime incidences in the police stations jurisdiction. Our experiment results show the efficiency in time consuming for mining popular crime patterns.
Statistical analysis of large DNA sequences using distribution of DNA words

Conventional sequence alignment techniques for comparing and analysing relatively smaller DNA sequences of nearly equal sizes are not applicable to data consisting of large sequences with widely varying sizes. In this article DNA sequences have been analysed based on distributions of DNA words. DNA word frequencies are simple yet effective statistical tools to capture information about structural patterns, and they can reveal biologically significant features in DNA sequence. Our analysis demonstrates how such simple statistical summaries of large DNA data can enable us to detect the structural signature of a genome as well as to identify phylogenetic relationships among different species reflected in the variation of word distributions in their DNA sequences.
I/O-efficient strong connectivity and depth-first search for directed planar graphs

We present the first I/O-efficient algorithms for the following fundamental problems on directed planar graphs: finding the strongly connected components, finding a simple-path 2/3-separator, and computing a depth-first spanning (DFS) tree. Our algorithms for the first two problems perform O(sort(N)) I/Os, where N = V + E and sort(N) = /spl Theta/((N/B)) is the number of I/Os required to sort N elements. The DFS-algorithm performs O(sort(N) log(N/M)) I/Os, where M is the number of elements that fit into main memory.
Applying CBR for Document Retrieval

In this paper, we report about the application of Case-Based Reasoning to the task of document retrieval. We briefly describe the main features of the FALLQ system which is the result of a cooperation with an industrial partner. The objective of the system is to provide a tool that, for a given query text, helps finding related documents, such as sections of Frequently Asked Questions databases. The system is currently under practical evaluation at our partner
The impact of cooperative physical layer network coding on multicast short range networks

In this paper, we exploit the characteristics of physical layer network coding (PNC) in multicast short range communication (SRC) networks. We present a scalable scenario of partially overlapping SRC networks, where collisions are resolved through indirect inter-group cooperation based on the features of PNC. Our scenario consists of a central network and several peripheral networks. In our previous work we proved that the central network presents significant gains in terms of throughput, delay and energy efficiency when applying the proposed scheme. Here we explore the impact of that scenario on the peripheral networks through a decomposition approach and we prove that they also present significant performance gains.
Bidirectional Plasticity of Intrinsic Excitability Controls Sensory Inputs Efficiency in Layer 5 Barrel Cortex Neurons in Vivo

Responsiveness of cortical neurons to sensory inputs can be altered by experience and learning. While synaptic plasticity is generally proposed as the underlying cellular mechanism, possible contributions of activity-dependent changes in intrinsic excitability remain poorly investigated. Here, we show that periods of rhythmic firing in rat barrel cortex layer 5 pyramidal neurons can trigger a long-lasting increase or decrease in their membrane excitability in vivo. Potentiation of cortical excitability consisted of an increased firing in response to intracellular stimulation and a reduction in threshold current for spike initiation. Conversely, depression of cortical excitability was evidenced by an augmented firing threshold leading to a reduced current-evoked spiking. The direction of plasticity depended on the baseline level of spontaneous firing rate and cell excitability. We also found that changes in intrinsic excitability were accompanied by corresponding modifications in the effectiveness of sensory inputs. Potentiation and depression of cortical neuron excitability resulted, respectively, in an increased or decreased firing probability on whisker-evoked synaptic responses, without modifications in the synaptic strength itself. These data suggest that bidirectional intrinsic plasticity could play an important role in experience-dependent refinement of sensory cortical networks.