Miracle-dz/UniFAR-FTUs huggingface dataset:
The resource coupling role of animal foraging pits in semi‐arid woodlands

Water is a strong driver of ecosystem function and diversity in resource‐limited drylands. Structures that alter the redistribution of water have the potential to affect vegetation pattern and productivity and the maintenance of spatial heterogeneity. We examined the role of surface foraging pits and mounds constructed by the short‐beaked echidna (Tachyglossus aculeatus) on runoff generation, sediment detention and seed capture. We speculated that pits dug into biologically crusted interspace soils would reduce overland flow and act as sinks for seed, while mounds of ejected soil would increase sediment availability. Runoff and sediment yield were examined under simulated rainfall with five levels of disturbance representing the pits and mounds of echidnas. Increasing the level of disturbance up to 47% cover of mounds and pits had no effect on time to ponding, steady‐state runoff or the coefficient of runoff. However, time to initiation of runoff, sediment removal rates and sediment concentration in runoff water increased with increasing disturbance. Pit‐to‐pit and surface‐to‐pit movements of Dodonaea viscosa seed tended to increase, while pit‐to‐surface movements tended to remain unchanged with increasing disturbance. Surface‐resident seed generally moved shorter distances with increasing disturbance. The results highlight the importance of mounds and pits of soil foraging animals for generating and trapping eroded sediment. Runoff and erosion processes may therefore provide a mechanism for coupling critical resources such as seed, water and sediment in resource‐rich patches that will contribute to the development of small‐scale heterogeneity in woodlands. Copyright © 2010 New South Wales, Australia.
Inventory competition and incentives to back-order

In this paper we consider the issue of inventory control in a multi-period environment with competition on product availability. Specifically, when a product is out of stock, the customer often must choose between placing a back-order or turning to a competitor selling a similar product. We consider a competition in which customers may switch between two retailers (substitute) in the case of a stock-out at the retailer of their first choice. In a multi-period setting, the following four situations may arise if the product is out of stock: (i) sales may be lost; (ii) customers may back-order the product with their first-choice retailer; (iii) customers may back-order the product with their second-choice retailer; or (iv) customers may attempt to acquire the product according to some other more complex rule. The question we address is: how do the equilibrium stocking quantities and profits of the retailers depend on the customers' back-ordering behaviors? In this work we consider the four alternative back-ordering scenarios and formulate each problem as a stochastic multi-period game. Under appropriate conditions, we show that a stationary base-stock inventory policy is a Nash equilibrium of the game that can be found by considering an appropriate static game. We derive conditions for the existence and uniqueness of such a policy and conduct a comparative statics analysis. Analytical expressions for the optimality conditions facilitate managerial insights into the effects of various back-ordering mechanisms. Furthermore, we recognize that often a retailer is willing to offer a monetary incentive to induce a customer to back-order instead of going to the competitor. Therefore, it is necessary to coordinate incentive decisions with operational decisions about inventory control. We analyze the impact of incentives to back-order the product on the optimal stocking policies under competition and determine the conditions that guarantee monotonicity of the equilibrium inventory in the amount of the incentive offered. Our analysis also suggests that, counterintuitively, companies might benefit from making their inventories “visible” to competitors' customers, since doing so reduces the level of competition, decreases optimal inventories and simultaneously increases profits for both players.
Human Papillomavirus (HPV) 16 and 18 Variants in Northern Spain

Human papillomaviruses (HPVs) comprise a large and diverse group of small DNA viruses, some of which play a main role in the development of different types of cancer such as oropharyngeal, vulva, penis, anal or cervical cancer (zur Hausen, 2000). For cervical cancer, these viruses are recognized as the cause of nearly all cancer cases, with an estimated 500,000 new cases and 274,000 deaths every year (www.who.int, accessed on 2015–02–23). Most HPV infections do not cause any lesion or symptoms but if the viral infection persists, cancer may develop. In our region, HPV prevalence is approximately 10.4% among women with normal cytology and up to 69.8% among those with abnor-
Predicting methionine and lysine contents in soybean meal and fish meal using a group method of data handling-type neural network

Artificial neural network models offer an alternative to linear regression analysis for predicting the amino acid content of feeds from their chemical composition. A group method of data handling-type neural network (GMDH-type NN), with an evolutionary method of genetic algorithm, was used to predict methionine (Met) and lysine (Lys) contents of soybean meal (SBM) and fish meal (FM) from their proximate analyses ( i.e. crude protein, crude fat, crude fibre, ash and moisture). A data set with 119 data lines for Met and 116 lines for Lys was used to develop GMDH-type NN models with two hidden layers. The data lines were divided into two groups to produce training and validation sets. The data sets were imported into the GEvoM software for training the networks. The predictive capability of the constructed models was evaluated by their abilities to estimate the validation data sets accurately. A quantitative examination of goodness of fit for the predictive models was made using a number of precision, concordance and bias statistics. The statistical performance of the models developed revealed close agreement between observed and predicted Met and Lys contents for SBM and FM. The results of this study clearly illustrate the validity of GMDH-type NN models to estimate accurately the amino acid content of poultry feed ingredients from their chemical composition.
A Study about Performance and Robustness of Model Predictive Controllers in WECs Systems

This work is located in a growing sector within the field of renewable energies, wave energy converters (WECs). Specifically, it focuses on one of the point absorbers wave (PAWs) of the hybrid platform W2POWER. With the aim of maximising the mechanical power extracted from the waves by these WECs and reduce their mechanical fatigue, the design of five different model predictive controllers (MPCs) with hard and soft constraints has been carried out. As contribution of this paper, two of the MPCs have been designed with the addition of an embedded integrator. In order to validate the MPCs, an exhaustive study on performance and robustness is realized through simulations carried out in which uncertainties in the WEC dynamics are considered. Furthermore, looking for realistic in these simulations, an identification methodology for PAWs is proposed and validated by means of real time series of a scale prototype.
Reconstructing Pulse-Code Modulation Telemetry Data with Dropouts

A data handling system was developed which transfers serial pulse-code modulation (PCM) telemetry data from an analog tape to a digital tape for analysis on a digital computer. The PCM data were collected from field experiments in snow skiing which measured the excitation between the ski boot and the ski. PCM data were FM transmitted and stored on an analog tape recorder. In the laboratory, data were decoded from the tape and parallel input to a Nova minicomputer which buffered the data and wrote tapes compatible with a CDC 6400 computer. A custom-built PCM decoder provided control and status commands to drive the minicomputer interrupt logic. The data transfer rate was 50 kbits/s. Special consideration was given to the problem of information losses. Lost data frames were not stored by the minicomputer and the data time series on the digital tape is discontinuous at each loss point. Spectral analysis of data with discontinuities produces erroneous results. Fourier coefficients and power spectra were computed for both continuous and discontinuous signals. Discontinuities caused significant reductions in amplitude and increase in bandwidth of spectrum estimates. Unique software eliminated data discontinuities by reconstructing the original time-base with linearly interpolated pseudo-data. Results are presented which show the enhanced accuracy obtained in spectrum estimates with the reconstructed data.
Collaborative Meeting as an Integrative Mechanism in a Multinational Investment Project

In multinational and complex projects that are often implemented by multiple organizations, the entire projects need to be divided into manageable subprojects. At the same time, all subprojects are needed to be kept aligned with the project goals and targets by integration and coordination. The purpose of this article is to study the role of a particular, work-shop type, collaborative meeting by utilizing the characteristics of an integrative information processing framework. A single case study method was used to observe the practices of collaborative meetings. This study contributes to the project management research by analysing how collaborative meeting practice can be used as a mechanism to reduce uncertainty and equivocality in a large investment project. The results of this study are two folds: Firstly, the case project’s collaborative meetings are described in detail; secondly, the perceived features and procedures of the collaborative meetings in the case project are illustrated showing the role of the collaborative meetings as an integrative tool. Moreover, the perceived integrative characteristics of the collaborative meetings reducing uncertainty and equivocality are presented. This study indicates that collaborative meeting is an integrative mechanism reducing uncertainty and equivocality in a large investment project context.
Evaluation on star tree simulation data Supplementary material for Alignment Tool Evaluation

Based on the star phylogenetic tree, we used PSPE to generate benchmark promoter sequences at 15 different divergence distances. The data were simulated under the HKY85 nucleotide substitution model with Gamma and invariant rate (Г+І) for modeling substitution rate heterogeneity. For each divergence distance, we generated 1,000 replicate homologous sets, each having four promoter sequences with the same divergence distance from their ancestral sequence. Each sequence contained exactly one functional binding site for each of the six transcription factors: Pax6, TP53, IRF2, PPARG, ROAZ, and YY1E2F. YY1E2F is a composite TFBS consisting of YY1 and E2F binding sites that reportedly interact with each other in cell cycle gene regulation [1]. Binding sites were subject to a set of functional constraints (Table 1) which were set to allow for turnover within a restricted distance, but keeping the overall order of the binding sites unchanged. Simulation allowed us to quantify the amount of turnover, how many non-aligned functional sites were due to turnover as compared to “simple” misalignments, and whether some tools would in fact be able to align functional sites despite turnover. We used this dataset to assess performances of five widely-used MSA tools: CLUSTALW [2], DIALIGN [3], AVID/MAVID [4, 5], LAGAN/MLAGAN [6], and MUSCLE [7]. The performance was measured as TFBS detection accuracy, defined as the proportion of nucleotides in functionally homologous TFBS which were correctly aligned. The detection accuracy reported here is the average value over 1,000 replicates at each divergence distance.
Centre stage diagrams: a new method to develop constructivist grounded theory – late-stage Parkinson’s disease as a case exemplar

A recent advance to the ‘classic’ grounded theory approach of Glaser and Strauss’ seminal work has been the development of constructivist grounded theory. While constructivist grounded theory has significant utility, centre stage diagrams were developed by the authors to help integrate ‘storied meaning’ and diagramming into a method of data collection, analysis and theory development/presentation. Centre stage diagrams are co-constructed by the researcher and participant and use the participant’s own life course, language and conceptual visualization of their subjective experience and are created over prolonged engagement. Centre stage diagrams are reached by the researcher and participant mutually engaged and interacting with two inter-related questions: i) what is the centre stage storyline in the lived representation of the phenomenon under study? and ii) who is centre stage in that lived experience? Our work in late-stage Parkinson’s disease is used to illustrate this approach to theory building and generating constructivist grounded theory. Centre stage diagrams have potential for development as a practice tool and/or as an independent research method.
Optimal filtering for polynomial measurement nonlinearities with additive non-Gaussian noise

We consider the problem of estimating the n-dimensional state of a dynamic system based on m-dimensional discrete-time measurements. The measurements depend nonlinearly on the state and are corrupted by white non-Gaussian noise. The problem is solved by recursively calculating the complete posterior density of the state given the measurements. For that purpose, a new exponential type density is introduced, the so called pseudo Gaussian density, which is used to represent the complicated non-Gaussian posterior densities resulting from the recursion. For polynomial measurement nonlinearities and pseudo Gaussian noise densities, it is shown that the result of the optimal Bayesian measurement update is exactly obtained by a Kalman filter operating in a higher dimensional space. The resulting filtering algorithms are easy to implement and always guarantee valid posterior densities.
Caries Risk Management Protocols in Australia and New Zealand: a Scoping Review

The introduction of community water fluoridation programs, fluoridated dentifrices and other professional products alongside enhanced oral self-care practices have contributed to a general decline in dental caries experience globally. This is particularly noticeable over the past few decades amongst high-income countries.1,2. The WHO Global Oral Health Data Bank1 report showed that Australian and New Zealand children have experienced very low (mean DMFT <1.2) and low (mean DMFT between 1.2 and 2.6) levels of dental caries in children aged 12 years, respectively, whereas the adult cohorts of both these countries presented high caries levels (mean DMFT>13.9) at 35-44 years of age.
Diffuse reflectance spectra and optical properties of some sulphides and related minerals

Summary The results of measurements of diffuse reflectance over the wavelength range 200 < λ < 2500 nm are reported for sphalerite, cinnabar, alabandite, chalcopyrite, bornite, orpiment, stibnite, bismuthinite, enargite, and pyrargyrite, and for eight pyrite-type and four NiAs-type compounds. Some spectral assignments have been made. Optical properties are related to the absorption spectrum (and through this to composition and structure) in a rational way. Absolute reflectances tend to increase with mean atomic number (z) through the operation of the ‘z-sum rule’, and at constant z they decrease as the band gap increases. Bireflectance is structurally controlled, being weak in derivatives of the cubic sphalerite and pyrite structures, moderate in derivatives of wurtzite and NiAs, and strong in anisodesmic structures such as that of stibnite. Extreme bireflectance occurs in anisodesmic structures with strong dichroic absorption bands in the visible (molybdenite, covelline). The dispersion of reflectance (dR/dλ) depends on the position of the centre of the main absorption envelope in relation to the visible spectrum. For λ > , dispersion is normal (R blue > R red, dR/dλ negative), the streak is light or coloured, and polished surfaces tend to be bluish. For λ < , dispersion is reversed (R red > R blue), the streak is dark, and polished surfaces are yellowish. Polished surfaces are white or grey if absorption varies little through the visible or strongly coloured if it varies rapidly (covelline, chalcopyrite).
Nymble Counter Measures for Failure Tolerant Anonymzing Networks

Tor is a form of Anonymzing networks comprised of virtual tunnels that allows people and groups to improve their privacy and security on the Internet. Individuals use Tor to keep websites from tracking them. Anonymzing networks provide users with anonymous browsing capabilities over the web using a series of routers to hide the client’s IP address. Under the cover of anonymity, certain users have repeatedly launched deface/dos attacks over popular web sites such as Wikipedia. Since web site administrators cannot blacklist individual adversaries’ IP addresses, they end up blacklisting the entire Anonymzing network resulting in loss of service to genuine users thus effecting entire Anonymzing network services. Previously to counter these issues Nymble System was proposed and implemented which is essentially a combination of Anonymization Network along with Pseudo Manager for nymble token operations, ip hiding activities and Nymble Manager for encountering and acting on adversaries, interfacing the clients with anonymizing network. Although Nymble System was effective in syncing target servers with the system for an efficient reporting and countering mechanisms, it has a huge computation overhead. So we propose to tweak Nymble System to allow users to access Internet services privately by using a series of mix servers and proxy repositories to hide the client’s IP address from the target servers instead of the multiple routers based ip hiding approach of prior systems. These methods ensure that the number of algorithms to sync target servers with Nymble system is not beyond 10 thus reducing the computation overhead. An implementation validates the claim of the proposed system's ability to offer and preserve anonymization services yet effectively handling adversaries of the network.
EmoDetect – Smart Emotion Detection from Facial Expressions

Human emotion detection is important to improve the interaction between humans and computers, by allowing computers to tailor their behavior according to the mood of the human operating the computer. In this project, we present a study of various feature extraction methods — Gabor features, Histogram of Gradients, Haar-like features, Moments) coupled with different machine learning algorithms — Support Vector Machines (SVM), Random Trees (aka Random Forests TM ), and Artificial Neural Networks (ANN) to recognize and identify human emotion using facial expressions. We train the classifier on a database of around 10,000 images of 14 subjects emoting Anger, Disgust, Fear, Happiness, Neutral, Sadness, and Surprise. We train and cross validate over these extractorlearner combinations to find the best parameters; and then compare their relative performances. We also conduct experiments to test how accurately humans identify emotion. Our results show that the best performance is obtained using Gabor features coupled with a linear SVM with an accuracy of around 63%. However, we find that humans show an accuracy of around 74% and outperform every extractor-learner combination that we implemented.
A participatory evaluation of the health promotion programme “more healthy years of life” programme among senior citizens in Sweden

Abstract Background: Older adults have, in general, been sparsely involved in development and evaluation of programmes intended to promote their health. Aim: To describe older adults’ reflections on and involvement in the development and evaluation of a health promotion programme. Material and Method: Ten older persons participated in a health promotion programme (HPP) focusing on activity during four sessions. After each HPP session, focus group discussions were held, analysed through qualitative content analysis. Results: The main theme; “Being involved adds value and new experiences to life“, were built from sub-themes; “From sceptical individual to engaged group member”, “From beholder to active co-creator”, and “From individual knowledge recipient to collective knowledge sharer”. Conclusions: Having a leader with a gerontological competence was mentioned as important, as well as to integrate existential topics into the HPP. Social inclusion together with the possibility to influence the HPP had a positive effect on the participants and provided a sense of belonging. Significance: Several contributions to the development of the HPP were given, that would not have been captured without the reflections and involvement of the participants. However, more and larger studies are needed to develop strategies that enable older adult’s involvement in the development of HHP.
Customs Automation: The X-ray and Computerized Risk Management Systems Era

Though established by the promulgation of the Customs and Excise Management Act of 1958, The Nigeria Customs Service (NCS) traces its origin to 1891 when the British colonial administration appointed the first Director-General of Customs, Mr. T.A. Wall. Having operated as a major Government revenue collection agency for decades, the customs formation formally embraced<br>automation in 2006 when the Federal government through the Federal Ministry of Finance entered into a 7-year build-own-operate transfer contract with four private companies to provide computerized risk management system (CRMS) and X-ray cargo scanning services to modernize Customs operations, boost revenue generation, and protect the economy and lives of Nigerians. This paper reviews the state of the journey to automation and the current state of affairs in this very important revenue collection and enforcement agency. We also discussed the problems, challenges, prospects of computerized automation.
Pan Olympus : Sensor Privacy through Utility Aware

Personal data garnered from various sensors are often offloaded by applications to the cloud for analytics. This leads to a potential risk of disclosing private user information. We observe that the analytics run on the cloud are often limited to a machine learning model such as predicting a user’s activity using an activity classifier. We present Olympus, a privacy framework that limits the risk of disclosing private user information by obfuscating sensor data while minimally affecting the functionality the data are intended for. Olympus achieves privacy by designing a utility aware obfuscation mechanism, where privacy and utility requirements are modeled as adversarial networks. By rigorous and comprehensive evaluation on a real world app and on benchmark datasets, we show that Olympus successfully limits the disclosure of private information without significantly affecting functionality of the application.