Miracle-dz/UniFAR-FTUs huggingface dataset:
Event based experiential computing in agro-advisory system for rural farmers

In our earlier proposed mKRISHI framework, which is a mobile phone based agriculture advisory system, a farmer can record a query with the help of audio-visual interface on the mobile phone application. The multi-modal sensory devices have been deployed to capture the context of the farm so that the query along with the context are presented to the agriculture expert at the web console for the investigation. In this paper, we propose an event based experiential computing approach for agro-advisory services. The classification and modeling of agricultural events, modeling of the agricultural experiences, and a method to browse through the history of agriculture experiences are the key contributions in the present work.
Protein Kinase C Activation Regulates Human Serotonin Transporters in HEK-293 Cells via Altered Cell Surface Expression

Antidepressant- and cocaine-sensitive serotonin (5-hydroxytryptamine, 5-HT) transporters (SERTs) dictate clearance of extracellular 5-HT after release. To explore protein kinase C-mediated SERT regulation, we generated a stable human SERT (hSERT)-expressing cell line (293-hSERT) and evaluated modulation of 5-HT activity via studies of 5-HT flux, hSERT-mediated currents under voltage clamp, and surface distribution of SERT protein. 293-hSERT cells exhibit saturable, high-affinity, and antidepressant-sensitive 5-HT uptake as well as hSERT-dependent whole-cell currents. In these cells, the protein kinase C activator β-PMA caused a time-dependent reduction in 5-HT uptake capacity (Vmax) after acute application and a reduction in SERT-mediated currents. Effects of β-PMA were mimicked by the phorbol ester β-PDBu, were not observed with the inactive α-isomers, and could be blocked by treatment of cells with the protein kinase C inhibitor staurosporine. Biotinylation/immunoblot analyses showed that activity reductions are paralleled by a staurosporine-sensitive loss of surface SERT protein. These data indicate that altered surface abundance, rather than reduced catalytic transport efficiency, mediates acute PKC-dependent modulation of 5-HT uptake.
Phosphate binders and management of hyperphosphataemia in end-stage renal disease.

Keywords: hyperphosphataemia; phosphate binders;renal failure; vascular calcificationsHyperphosphataemia is a known factor contributingto the increased risk of cardiac death both in patientswith end-stage renal disease (ESRD) and in thoseunder renal replacement treatment with dialysis [1,2]. In patients with renal disease, in fact, the well-knownrelationship between hyperphosphataemia, secondaryhyperparathyroidism, bone turnover and extra osseouscalcifications has recently been followed by therecognition of a major role played by elevated serumphosphate levels in the induction of vascular calcifi-cation [3–5], cardiac interstitial fibrosis and arterialthickening [6] which highly increase the risk of cardiacdeath [1,2]. In response to these findings, the NationalKidney Foundation Kidney Disease Outcome QualityInitiative (K/DOQI) Clinical Practice Guidelines forbone metabolism and disease in chronic kidney diseasehas recently recommended that more stringent levelsfor controlling serum phosphorus (serum phosphoruslevels be maintained between 3.5 and 5.5mg/dl) andCa/P product in order to improve patients’ qualityof life and longevity [7]. The involvement of the so-called ‘bone–coronaryaxis’ is the basis for the high clinical interest for serumconcentration of calcium and phosphate. In particular,the control or reduction of the phosphate levelin dialysis patients has become one of the maintherapeutic targets in the management of ESRD.This review focuses on the treatment of hyper-phosphataemia in patients with ESRD and in thoseunder renal replacement treatment with dialysis, anddiscusses in particular conventional phosphate bindersand emerging therapies aimed at reducing the incidenceof hyperparathyroidism, bone disease and calcificationin these patients.
Modeling viscoelasticity through spring–dashpot models in intermittent-contact atomic force microscopy

Summary We examine different approaches to model viscoelasticity within atomic force microscopy (AFM) simulation. Our study ranges from very simple linear spring–dashpot models to more sophisticated nonlinear systems that are able to reproduce fundamental properties of viscoelastic surfaces, including creep, stress relaxation and the presence of multiple relaxation times. Some of the models examined have been previously used in AFM simulation, but their applicability to different situations has not yet been examined in detail. The behavior of each model is analyzed here in terms of force–distance curves, dissipated energy and any inherent unphysical artifacts. We focus in this paper on single-eigenmode tip–sample impacts, but the models and results can also be useful in the context of multifrequency AFM, in which the tip trajectories are very complex and there is a wider range of sample deformation frequencies (descriptions of tip–sample model behaviors in the context of multifrequency AFM require detailed studies and are beyond the scope of this work).
Optimizing the Product Shape for Ergonomics Goodness Index. Part Ii: Elaboration for Material Properties

In part I the developed methodology of the ergonomics shape optimization was introduced briefly. Part II presents the construction of the surface and the solid Finite Elements Models and the first results of the analysis. The presented results consider the estimation of the material properties of the part of the human that is involved in sitting. The analysis was done for a flat sitting support impressing a FE model of the human buttock area. Comparison with measured data should enable a reliable estimation of the stiffness of the FE model.
Duplicate-aware opportunistic routing for multi-hop wireless networks

Recently, opportunistic routing has been proposed to take good advantage of broadcast nature and spatial diversity to achieve high throughput, despite highly unpredictable and lossy wireless links in multi-hop wireless networks. Most previous works provide heuristic solutions to select as many candidates, and don't take inter-candidate delivery probability into account, which might suffer acknowledgement loss and lead to duplicate forwarding, ultimately degrades network throughput. In this paper, a discrete-time Markov model is firstly presented to analyze duplicate forwarding probability at the candidates, and then simple candidates optimization algorithm and acknowledgement enhancement mechanism are proposed to eliminate the effect of duplicate forwarding. Simulations are conducted to verify our algorithm, and results show that there is a 20% gain in throughput when compared with traditional opportunistic routing protocol.
Modelling Cell Assemblies

Neural Networks are very popular computational models that are generally said to be inspired by human neural functioning. However, neurons in most neural nets function quite diierently from natural systems. This paper describes a novel architecture, the CANT (Connections, Associations and Network Technology) model which is designed to function like natural neural systems. It rst elucidates the important aspects of the model and how they relate to natural systems. The basic idea is derived from D. O. Hebb's idea of the Cell Assembly which is the neural equivalent of a concept. The paper goes on to describe three instances of the model. In each case, stimulus is presented to the network by directly activating neurons in the system. In any given run of the network, this should lead to activation of the appropriate CA. When learning is involved, early runs on the system will not lead to activation of a CA. Instead, the early activation will lead to the system learning the CA. CAs are initially determined by appropriate levels of activation in the network. Later they are determined by statistical analysis of the activation patterns. The rst experiment shows that the CANT model generates CAs given a wide variety of parameter settings. Learning is essential in neural models; the second experiment shows how learning can develop a CA where mere parameter setting can not. In natural neural systems, multiple CAs must exist as natural systems must have multiple concepts. The third experiment shows how a simple net can contain two CAs. The paper concludes with a discussion of future developments of the model. These include duplicating psychological and neurobiological data. This will require further analysis of CAs, learning algorithms and development of higher order formalisms.
Prefetching as a Potentially Effective Technique for Hybrid Memory Optimization

The promise of 3D-stacked memory solving the memory wall has led to many emerging architectures that integrate 3D-stacked memory into processor memory in a variety of ways including systems that utilize different memory technologies, with different performance and power characteristics, to comprise the system memory. It then becomes necessary to manage these memories such that we get the performance of the fastest memory while having the capacity of the slower but larger memories. Some research in industry and academia proposed using 3D-stacked DRAM as a hardware managed cache. More recently, particularly pushed by the demands for ever larger capacities, researchers are exploring the use of multiple memory technologies as a single main memory. The main challenge for such flat-address-space memories is the placement and migration of memory pages to increase the number of requests serviced from faster memory, as well as managing overhead due to page migrations. In this paper we ask a different question: can traditional prefetching be a viable solution for effective management of hybrid memories? We conjecture that by tuning well-known prefetch mechanism for hybrid memories we can achieve substantial performance improvement. To test our conjecture, we compared the state of the art CAMEO migration policy with a Markov-like prefetcher for a hybrid memory consisting of HBM (3D-stacked DRAM) and Phase Change Memory (PCM) using a set of SPEC CPU2006 and several HPC benchmarks. We find that CAMEO provides better performance improvement than prefetching for 2/3rd of the workloads (by 59%) and prefetching is better than CAMEO for the remaining 1/3rd (by 19%). The EDP analysis shows that the prefetching solution improves EDP over the no-prefetching baseline whereas CAMEO does worse in terms of average EDP. These results indicate that prefetching should be reconsidered as a supplementary technique to data migration.
Impact of Off-Farm Employment on Farmers’ Willingness to Grow Switchgrass and Miscanthus

Current study analyzed the socio-economic factors that impact farmers’ willingness to grow switchgrass and Miscanthus in Missouri and Iowa. The results of study show that current level of farmers’ willingness to grow either crop is low. Hence, there are barriers to accomplishing to goal of producing 21 billion gallons of cellulosic ethanol by 2022, as set by the Energy Independence and Security Act of 2007. The results of the ordered probit regressions show that farmers with higher education levels and smaller farm sales are more willing to grow energy crops. The results of this study show that currently growing energy crops is more attractive to small farms as a source of crop diversification, rather than an alternative crop production in the big scale by large farms.
Molecular Cloning and Characterization of Full-Length cDNA of Calmodulin Gene from Pacific Oyster Crassostrea gigas

The shell of the pearl oyster (Pinctada fucata) mainly comprises aragonite whereas that of the Pacific oyster (Crassostrea gigas) is mainly calcite, thereby suggesting the different mechanisms of shell formation between above two mollusks. Calmodulin (CaM) is an important gene for regulating the uptake, transport, and secretion of calcium during the process of shell formation in pearl oyster. It is interesting to characterize the CaM in oysters, which could facilitate the understanding of the different shell formation mechanisms among mollusks. We cloned the full-length cDNA of Pacific oyster CaM (cgCaM) and found that the cgCaM ORF encoded a peptide of 113 amino acids containing three EF-hand calcium-binding domains, its expression level was highest in the mantle, hinting that the cgCaM gene is probably involved in shell formation of Pacific oyster, and the common ancestor of Gastropoda and Bivalvia may possess at least three CaM genes. We also found that the numbers of some EF hand family members in highly calcified species were higher than those in lowly calcified species and the numbers of these motifs in oyster genome were the highest among the mollusk species with whole genome sequence, further hinting the correlation between CaM and biomineralization.
Computerized Recognition System for Historical Manuscripts

The article describes the process of creating a universal computerized recognition system of historical manuscripts, including historical shorthand records dating back to the 19th and early 20th centuries. We discuss the problem of getting the original graphical representation of symbols from historical manuscripts using a threshold binarization method. We search for a similar graphical representation of symbols in the database. Moreover we present a prototype of a computerized recognition system of historical manuscripts.
Enabling Efficient Peer to Peer Resource Discovery in Dynamic Grids Using Variable Size Routing Indexes

Existing Methods and techniques utilized by Peer-to-Peer (P2P) systems could address the scalability issue faced by Grid systems. Today's Grid systems have to deal with potentially a large number of resources which their status changes over time. Therefore, accurate, fast and scalable discovery of resources are key issues that Grid systems should deal with. Typical P2P systems enable sharing static resources, such as files, among users. However, resources in Grids are dynamic. In this paper, we propose a solution for efficient processing of range queries on available resources. We examine our proposed method using simulation data. The experimental results show that our proposed method improves the performance of existing methods in terms of precision of query processing, average hit rate and network bandwidth consumption.
Chapter 11 3 D NoC : A Promising Alternative for Tomorrow ’ s Nanosystem Design

Four primary aspects of chip design are processor, memory, I O, and communication. Communication amalgamated over a SoC (system-on-chip) is the basis of origin of an NoC (network-on-chip). Continuous increase in processing/communication needs with the rapid growth in VL SI industry providing higher and higher integration density within a single die has boosted the step towards this new paradigm shift by the researchers. Advent of three dimensional integrated circuits design technolog ies has given this direction another positive thrust. Researchers are indeed very hopeful with the amalgamation o f these two different technologies and thereby in developing new methodologies for designing 3D NoCs to cat er the need of high performance nanoscale computing and communication systems tomorow. This chapter describes different design challenges, available technologies, design and performance issues and parametri c asurement of such nanoscale systems, emerging cutting-edge technologies, and possible future direction s n designing 3D NoC based nanosystems.
A Concurrent Skeleton-based Approach for the Characterization of Wood Fibers with Sub-pixel Precision for Fiber Board Production

The automatic derivation of fiber properties by means of mass data (image) analysis is a current and interesting research area. Skeleton-based approaches have already proven to be adequate in paper pulp quality control [1–3]. However, the derivation for thermo mechanical pulp (TMP) used for the production of medium dense fiberboards (MDF) is, due to the wide range of fiber lengths and fiber morphology, far more challenging. Currently, trained experts are performing the quality assessment visually and haptically on small samples. Since this cannot replace an objective measurement, we propose a fast skeletonbased approach, which is able to derive a variety of fiber characteristics at sub-pixel precision from images of fibers. The algorithm is supposed to work automatically under a laboratory environment for fiber samples, and makes use of concurrency to reduce the processing time and the memory needed. In practice, one measurement cycle is based on approx. 1700 single images with usually more than 1,000,000 automatically measured fibers. Comparisons of the automatically measured fibers with manual microscopic measurements yield in a high reliability and quality of the results.
Estimating Clonality

Challenges of assessing complexity and clonality in populations of mixed species arise in diverse areas of modern biology, including estimating diversity and clonality in microbiome populations, measuring patterns of T and B cell clonality, and determining the underlying tumor cell population structure in cancer. Here we address the problem of quantifying populations, with our analysis directed toward systems for which previously defined algorithms allow the sequence-based identification of clonal subpopulations. Data come from replicate sequencing libraries generated from a sample, potentially with very different depths. While certain properties of the underlying clonal distribution (most notably the total number of clones) are difficult to estimate accurately from data representing a small fraction of the total population, the population-level "clonality" metric that is the sum of squared probabilities of the respective species can be calculated. (This is the sum of squared entries of a high-dimensional vector $p$ of relative frequencies.) The clonality score is the probability of a clonal relationship between two randomly chosen members of the population of interest. A principal takeaway message is that knowing a functional of $p$ well may not depend on knowing $p$ itself very well. Our work has led to software, which we call {\it lymphclon}; it has been deposited in the CRAN library.
Software continuance from the Switching Costs Perspective: a Case of Web Browser

It has been observed that people tend to resist changing their software even alternatives are better then the current one. This study examines the user resistance to change in the use of software from the switching costs perspective based on status quo bias theory. For this study, we select Web Browser as software. Based on the classification of switching costs into three groups (psychological, procedural, and loss), this study identifies six types of switching costs (uncertainty, commitment, learning, setup, lost performance, and sunk costs). This study tests the effects of six switching costs on user resistance to change based on the survey of 204 web browser users. The results indicate that lost performance costs and emotional costs have significant effects on user resistance to change. This research contributes towards understanding of switching costs and the effects on user resistance to change. This study also offers suggestions to software vendors for retaining their users and to organizations for managing user resistance in switching and adopting software.
An intelligent control architecture for unmanned aerial systems (UAS) in the National Airspace System (NAS)

In recent times, Unmanned Aerial Systems (UAS) have been employed in an increasingly diverse range of applications. Numerous UAS market forecasts portray a burgeoning future, with many applications in both the military and civilian domains. Within the civilian realm, UAS are expected to be useful in performing a wide range of missions such as disaster monitoring (e.g. wildfires, earth-quakes, tsunamis and cyclones), search and support, and atmospheric observation. However, to realise these civilian applications, seamless operation of UAS within the National Air Space (NAS) will be required. Increasing the levels of onboard autonomy will help to address this requirement. Additionally, increased autonomy also reduces the impact of onboard failures, potentially lower operational costs, and decrease operator workload. Numerous intelligent control architectures do exist in the literature for mobile robots, space based robots and for UAS. These include: the WITAS project, Open Control Platform, Remote Agent and TRAC/ReACT. However, none of these are specifically targeted at providing the required support for a wide range of civilian UAS missions. Operation of UAS in the NAS for civil applications require robust methods for dealing with emergency scenarios such as performing forced landings and collision avoidance to preserve the safety of people and property. This paper presents a new multi layered intelligent control architecture. The highest layer provides deliberative reasoning and includes situational awareness and mission planning subsystems. The middle layers deals with navigational aspects (such as path planning and manoeuvre generation). Finally, there is a functional control layer which comprises sensor and actuator subsystems and provides reactive functionality to enable forced landings and collision avoidance. Collision avoidance and forced landing technologies are currently under development at the Australian Research Centre for Aerospace Automation (ARCAA).
Intellectual capital: an exploratory study that develops measures and models

This paper details an empirical pilot study that explores the development of several conceptual measures and models regarding intellectual capital and its impact on business performance. The objective of this pilot study is to explore the development of items and constructs through principal components analysis and partial least squares (PLS). The final retained, subjective measures and optimal structural specification show a valid, reliable, significant and substantive causal link between dimensions of intellectual capital and business performance. These results should help both academics and practitioners more readily understand the components of intellectual capital and provide insight into developing and increasing it within an organization. Suggestions are then made to advance and improve this research programme.
Creating a Gold Standard for Sentence Clustering in Multi-Document Summarization

Sentence Clustering is often used as a first step in Multi-Document Summarization (MDS) to find redundant information. All the same there is no gold standard available. This paper describes the creation of a gold standard for sentence clustering from DUC document sets. The procedure of building the gold standard and the guidelines which were given to six human judges are described. The most widely used and promising evaluation measures are presented and discussed.
An adaptive vocabulary learning application through modeling learner's linguistic proficiency and interests

This paper introduces a vocabulary learning application called “Avocado” that aims to provide suitable learning materials to learners by modeling their language proficiency and topical interests. A learner's vocabulary level is estimated through aggregating words that he identifies as difficult in given text passages; and his topical interests are gathered by utilizing the social network (Facebook) profile. The application recommends a set of recent news articles that are 1) at an appropriate level to the learner, and 2) closely related to the topics that he finds interesting.