Miracle-dz/UniFAR-FTUs huggingface dataset:
Technology supported collaborative learning for higher education: Comparative case studies in Tanzania

To learn, a person has to be able to communicate effectively with others about the knowledge to be learned. Communication processes in classrooms can be supported by Group Support Systems (GSS), that enable students to communicate anonymously and in parallel. Group Support Systems experiences suggest that the technology increases observed learning, self-reported learning, on-task participation, and satisfaction with the learning experience. The authors discuss case studies from higher education in Tanzania. The particular benefit of GSS in this environment was threefold: First, it encouraged meaningful interaction among students and between students and teachers. Local culture normally hinders this. Second, it allowed all participants to discuss sensitive topics freely. Finally, it exposed students to collaborative technologies that are expected to play a pivotal role in (global) collaborative development activities. Clearly, the use of collaborative technologies enables the participation of a broader range of students. © 2006 Wiley Periodicals, Inc.
Smart Home System Based on GSM Network

Due to increasing robbery and intrusion, establishing home-security system has become a correlated part of the modern houses, buildings, and offices. As the family members are not at home all the time, the traditional home security system, which makes alarm sound only, may not be efficient enough. Alternatively, Global System for Mobile communications (GSM) based security system can provide higher level of security and convenience compared to the traditionally used systems. The main objective of the current paper is to design and implement cost-efficient and reliable security, safety and home automation system for protection and occupants’ convenience. If any undesired events, such as intrusion, gas leakage and fire occurs in the house, our system warns the homeowner in real-time using Short Message Service (SMS). With the proposed system home appliances can also be controlled in three ways, namely sending SMS from the authorized numbers to the system through GSM network, smartphone app using Bluetooth module and infrared (IR) control using IR module
Including post-discharge mortality in calculation of hospital standardised mortality ratios: retrospective analysis of hospital episode statistics

Objectives To assess the consequences of applying different mortality timeframes on standardised mortality ratios of individual hospitals and, secondarily, to evaluate the association between in-hospital standardised mortality ratios and early post-discharge mortality rate, length of hospital stay, and transfer rate. Design Retrospective analysis of routinely collected hospital data to compare observed deaths in 50 diagnostic categories with deaths predicted by a case mix adjustment method. Setting 60 Dutch hospitals. Participants 1 228 815 patients discharged in the period 2008 to 2010. Main outcome measures In-hospital standardised mortality ratio, 30 days post-admission standardised mortality ratio, and 30 days post-discharge standardised mortality ratio. Results Compared with the in-hospital standardised mortality ratio, 33% of the hospitals were categorised differently with the 30 days post-admission standardised mortality ratio and 22% were categorised differently with the 30 days post-discharge standardised mortality ratio. A positive association was found between in-hospital standardised mortality ratio and length of hospital stay (Pearson correlation coefficient 0.33; P=0.01), and an inverse association was found between in-hospital standardised mortality ratio and early post-discharge mortality (Pearson correlation coefficient −0.37; P=0.004). Conclusions Applying different mortality timeframes resulted in differences in standardised mortality ratios and differences in judgment regarding the performance of individual hospitals. Furthermore, associations between in-hospital standardised mortality rates, length of stay, and early post-discharge mortality rates were found. Combining these findings suggests that standardised mortality ratios based on in-hospital mortality are subject to so-called “discharge bias. ” Hence, early post-discharge mortality should be included in the calculation of standardised mortality ratios.
Maximizing Growth Yield and Dispersal via Quorum Sensing Promotes Cooperation in Vibrio Bacteria

ABSTRACT Quorum sensing (QS) is a form of bacterial chemical communication that regulates cellular phenotypes, including certain cooperative behaviors, in response to environmental and demographic changes. Despite the existence of proposed mechanisms that stabilize QS against defector exploitation, it is unclear if or how QS cooperators can proliferate in some model systems in populations mostly consisting of defectors. We predicted that growth in fragmented subpopulations could allow QS cooperators to invade a QS defector population. This could occur despite cooperators having lower relative fitnesses than defectors due to favored weighting of genotypes that produce larger populations of bacteria. Mixed metapopulations of Vibrio QS-proficient or unconditional cooperators and QS defectors were diluted and fragmented into isolated subpopulations in an environment that requires QS-regulated public good production to achieve larger population yields. Under these conditions, we observed global invasions of both cooperator genotypes into populations composed of primarily defectors. This spatially dependent increase in cooperator frequency was replicated for QS cooperators when mixed populations were competed in soft agar motility plates under conditions that allowed cooperators to disperse and outcompete defectors at the population edge, despite being less motile in isolation than defectors. These competition results show that the coordinated growth and dispersal of QS cooperators to additional resources is heavily favored in comparison to unconditional cooperation, and that dispersal of cooperators by motility into new environments, examined here in laboratory populations, constitutes a key mechanism for maintaining QS-regulated cooperation in the face of defection. IMPORTANCE Behaviors that are cooperative in nature are at risk of exploitation by cheating and are thus difficult to maintain by natural selection alone. While bacterial cell-cell communication, known as quorum sensing (QS), can stabilize microbial cooperative behaviors and is widespread in Vibrio species, it is unclear how QS can increase the frequency of cooperative strains in the presence of defectors without additional mechanisms. In this study, we demonstrate under multiple conditions that QS-mediated cooperation can increase in populations of Vibrio strains when cells experience narrow population bottlenecks or disperse from defectors. This occurred for both conditional cooperation mediated by QS and for unconditional cooperation, although conditional cooperators were better able to stabilize cooperation over a much wider range of conditions. Thus, we observed that population structuring allowed for assortment of competing genotypes and promoted cooperation via kin selection in microbes in a QS-dependent manner.
An unbiased equation error identifier and reduced-order approximations

The equation error (EE) identification technique is modified to remove the parameter bias problem induced by uncorrelated measurement errors. The modification replaces a "monic" constraint with a "unit-norm" constraint; the asymptotic solution replaces a normal equation with an eigenequation. The resulting algorithm is simpler than previous schemes, while at the same time preserving the desirable properties of the conventional EE method: simplicity of an on-line algorithm, unimodality of the performance surface, and consistent identification in the sufficient-order case. In the more realistic undermodeled case, a robustness result shows that the mean optimal parameter values of both the monic and unit-norm EE schemes correspond to a stable transfer function for all degrees of undermodeling, and for all stationary output disturbances, provided the input sequence satisfies an autoregressive constraint; otherwise an unstable model may result. Model approximation properties for the undermodeled case are exposed in detail for the case of autoregressive inputs; although both the monic and unit-norm variants provide Pade approximation properties, the unit-norm version is capable of autocorrelation matching properties as as well, and yields the optimal solution to a first- and second-order interpolation problem. Finally, the mismodeling error for the undermodeled case is shown to be a well-behaved function of the Hankel singular values of the unknown system. This modification allows EE methods to be admitted to the class of unbiased identification and approximation techniques. >
Adversarial Discriminative Heterogeneous Face Recognition

The gap between sensing patterns of different face modalities remains a challenging problem in heterogeneous face recognition (HFR). This paper proposes an adversarial discriminative feature learning framework to close the sensing gap via adversarial learning on both raw-pixel space and compact feature space. This framework integrates cross-spectral face hallucination and discriminative feature learning into an end-to-end adversarial network. In the pixel space, we make use of generative adversarial networks to perform cross-spectral face hallucination. An elaborate two-path model is introduced to alleviate the lack of paired images, which gives consideration to both global structures and local textures. In the feature space, an adversarial loss and a high-order variance discrepancy loss are employed to measure the global and local discrepancy between two heterogeneous distributions respectively. These two losses enhance domain-invariant feature learning and modality independent noise removing. Experimental results on three NIR-VIS databases show that our proposed approach outperforms state-of-the-art HFR methods, without requiring of complex network or large-scale training dataset.
A practical analysis of shared‐appreciation mortgages

In addition, the appreciation potential provides the lender with some protection against inflation risk.3 The protection against inflation risk is greater if the lender holds a diversified portfolio of SAMs because the average appreciation on a portfolio of residences is generally more highly correlated with inflation than the appreciation on an individual residence that has a significant amount of unsystematic risk.4 This inflation protection is especially valuable to the lender in times of high and volatile inflation rates.
Vascular Active Contour for Vessel Tree Segmentation

In this paper, a novel active contour model is proposed for vessel tree segmentation. First, we introduce a region competition-based active contour model exploiting the Gaussian mixture model, which mainly segments thick vessels. Second, we define a vascular vector field to evolve the active contour along its center line into the thin and weak vessels. The vector field is derived from the eigenanalysis of the Hessian matrix of the image intensity in a multiscale framework. Finally, a dual curvature strategy, which uses a vesselness measure-dependent function selecting between a minimal principal curvature and a mean curvature criterion, is added to smoothen the surface of the vessel without changing its shape. The developed model is used to extract the liver and lung vessel tree as well as the coronary artery from high-resolution volumetric computed tomography images. Comparisons are made with several classical active contour models and manual extraction. The experiments show that our model is more accurate and robust than these classical models and is, therefore, more suited for automatic vessel tree extraction.
Analyzing Insurance‐Linked Securities

Insurance‐linked securities can benefit both issuers and investors; they supply insurance and reinsurance companies with additional risk capital at reasonable prices (with little or no credit risk), and supply excess returns to investors that are uncorrelated with the returns of other financial assets. This article explains the terminology of insurance and reinsurance, the structure of insurance‐linked securities, and provides an overview of major transactions. First, there is a discussion of how stochastic catastrophe modeling has been applied to assess the risk of natural catastrophes, including the reliability and validation of the risk models. Second, the authors compare the risk‐adjusted returns of recent securitizations on the basis of relative value. Compared with high‐yield bonds, catastrophe (“CAT”) bonds have wide spreads and very attractive Sharpe ratios. In fact, the risk‐adjusted returns on CAT bonds dominate high‐yield bonds. Furthermore, since natural catastrophe risk is essentially uncorrelated with market risk, high expected excess returns make CAT bonds high‐alpha assets. The authors illustrate this point and show that a relatively small allocation of insurance‐linked securities within a fixed income portfolio can enhance the expected return and simultaneously decrease risk, without significantly changing the skewness and kurtosis of the return distribution.
Capital inflows to Latin America

Capital inflows are not an unmitigated blessing for the receiving region or country; in fact, they may pose serious dilemmas for economic policy. Large capital inflows are often associated with money and credit expansion, inflationary pressures, a real exchange rate appreciation, and a deterioration in the current account of the balance of payments. In addition, the history of Latin America provides ample evidence that massive capital inflows may also have strong impacts on the stock market, the real estate market, and the money market-impacts which may well threaten tbe stability of these markets and of the financial system as a whole.
Personal and social impacts of significant financial loss

This paper examines the impact on individuals who suffer significant financial loss. The collapse of Storm Financial is used as a qualitative case study to investigate such impacts, based on elements of grounded theory and narrative analysis. Significant financial loss is devastating, with an individual’s emotional wellbeing a primary casualty, and mental health also vulnerable. One’s social world is impacted, including relationships with family and friends, engagement in community activities and familial/cultural roles. Financial victims perceive a sense of judgement from society about their losses, further exacerbating emotive and social impacts. These impacts demonstrate that significant vulnerability exists when encouraging self-sufficiency in retirement.
Tree plantations, politics of possession and the absence of land grabs in Vietnam

Viewed from the lens of ‘land grabs’, Vietnam's fast-growing tree plantations look like an anomaly; many of them are tiny, owned and operated by rural households. In contrast, private companies and transnational corporations have not been able to get much of a foot into Vietnam's plantation sector. This paper identifies the practices and processes underlying the apparent anomaly. On the basis of fieldwork in four villages, it points to the concrete mechanisms by which households have gained access to land, finance, and wood markets. Government policy emerges as a critical factor enabling household access, not in the sense of a coherent policy package but understood as sedimented outcomes of everyday processes of state formation over the past three decades. A central element in contestations over the state is what I call ‘politics of possession’: possession, referring to entitlement and control, has been closely tied to ideas about the state. The paper uses these empirical observations to contribute towards theoretical understandings of land grabs and exclusion. Land grabs may have to say as much about dynamics of state formation as processes of commodification and market expansion.
An Approximate Flow Betweenness Centrality Measure for Complex Network

In complex network analysis, there are various measures to characterize the centrality of each node within a graph, which determines the relative importance of each node. The more centrality a node has in a network, the more significance it has in the spread of infection. As one of the important extensions to shortest-path based betweenness centrality, the flow betweenness centrality is defined as the degree to which each node contributes to the sum of maximum flows between all pairs of nodes. One of the drawbacks of the flow betweenness centrality is that its time complexity is somewhat high. This Letter proposes an approximate method to calculate the flow betweenness centrality and provides experimental results as evidence. key words: complex network, centrality, flow betweenness centrality, approximate flow betweenness centrality
Magnetoresistance in constrained domain walls

In magnetic materials, domains of magnetic orientation in opposite direction are often alternated. The transition in orientation between these domains, the domain wall, is not abrupt but spatially extended. When a current is passed through the magnetic material, the resistance of the material is dependent on whether such domain wall exists, which in its turn depends on the external magnetic field. This magneto-resistance is larger for smaller domain walls. Although the domain wall width is in principle a materials parameter, by patterning the magnetic sample into certain nanostructures, it is possible to constrain the domain wall such that its width is smaller than its natural unconstrained width. We have measured domain wall magnetoresistance in a single lithographically constrained domain wall. An H-shaped Ni nanobridge was fabricated by either e-beam lithography or a combination of e-beam lithography and helium ion milling. The two sides of the device are both single magnetic domains showing independent magnetic switching. The connection between the sides constrains the domain wall when the sides line up antiparallel. The magnetoresistance curve clearly identifies the magnetic configurations that are expected from a spin-valve like structure. The room temperature domain wall measurements give a magneto-resistance ratio of 0.1 % for the 94 nm and 0.2 % for the 32 nm constriction. Although these values are in itself small, they are the first results on lithographically prepared single domain spin valves. The single-layered device might allow for easier fabrication and space savings for high dense storage applications as compared to giant magneto-resistance and tunneling magneto-resistance. Also, the research of spin-based logic devices will benefit from the physical understanding that follows from measurements of magneto-resistance devices without material interface.
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

Recent studies have highlighted the vulnerability of deep neural networks (DNNs) to adversarial examples — a visually indistinguishable adversarial image can easily be crafted to cause a well-trained model to misclassify. Existing methods for crafting adversarial examples are based on L2 and L∞ distortion metrics. However, despite the fact that L1 distortion accounts for the total variation and encourages sparsity in the perturbation, little has been developed for crafting L1-based adversarial examples. In this paper, we formulate the process of attacking DNNs via adversarial examples as an elastic-net regularized optimization problem. Our elastic-net attacks to DNNs (EAD) feature L1-oriented adversarial examples and include the state-of-the-art L2 attack as a special case. Experimental results on MNIST, CIFAR10 and ImageNet show that EAD can yield a distinct set of adversarial examples with small L1 distortion and attains similar attack performance to the state-of-the-art methods in different attack scenarios. More importantly, EAD leads to improved attack transferability and complements adversarial training for DNNs, suggesting novel insights on leveraging L1 distortion in adversarial machine learning and security implications of DNNs.
Combining Resource‐Based and Evolutionary Theory to Explain the Genesis of Bio‐networks

This paper examines new firms creating innovative networks to support their development in emerging industries. Resource‐based and evolutionary theories are combined to explain the genesis of a new business ecosystem. Two case studies of biopharm ventures developing drugs against cancer showed how participants altered their selection environment as they enhanced their network's capability. Resource building took place at the firm and network level through collaborative business models involving innovative contractors. This approach uncovered previously unnoticed features of networks for drug development: resource asynchronies were found to be a stimulus to innovation in development networks, as in the Penrosean firm.
Two-sided estimates for stock price distribution densities in jump-diffusion models

We consider uncorrelated Stein-Stein, Heston, and Hull-White models and their perturbations by compound Poisson processes with jump amplitudes distributed according to a double exponential law. Similar perturbations of the Black-Scholes model were studied by S. Kou. For perturbed stochastic volatility models, we obtain two-sided estimates for the stock price distribution density and compare the tail behavior of this density before and after perturbation. It is shown that if the value of the parameter, characterizing the right tail of the double exponential law, is small, then the stock price density in the perturbed model decays slower than the density in the original model. On the other hand, if the value of this parameter is large, then there are no significant changes in the behavior of the stock price distribution density.
Response to Comment on “Late Pleistocene human skeleton and mtDNA link Paleoamericans and modern Native Americans”

Prüfer and Meyer raise concerns over the mitochondrial DNA (mtDNA) results we reported for the Hoyo Negro individual, citing failure of a portion of these data to conform to their expectations of ancient DNA (aDNA). Because damage patterns in aDNA vary, outright rejection of our findings on this basis is unwarranted, especially in light of our other observations.
How do Firms Change in the Face of Constraints to Change? Toward an Agenda for Research on Strategic Organization

The field of Strategy, which emerged as an independent discipline during the 1980s, addresses a broad range of issues about how individuals, organizational units, firms, and industries develop over time. Today, issues of strategic organization are commanding the attention of scholars from the fields of Strategy and related disciplines. The interdisciplinary agenda of strategic organization deals with such questions as how the organizational structures of firms influence corporate performance, and how companies restructure in response to changes in their environments. While this agenda falls within the range of issues in Strategy, it also deals with questions of central concern in Strategy’s antecedent disciplines, especially sociology, organization theory, and economics.