Miracle-dz/UniFAR-FTUs huggingface dataset:
Person Re-Identification With Metric Learning Using Privileged Information

Despite the promising progress made in recent years, person re-identification remains a challenging task due to complex variations in human appearances from different camera views. This paper presents a logistic discriminant metric learning method for this challenging problem. Different with most existing metric learning algorithms, it exploits both original data and auxiliary data during training, which is motivated by the new machine learning paradigm—learning using privileged information. Such privileged information is a kind of auxiliary knowledge, which is only available during training. Our goal is to learn an optimal distance function by constructing a locally adaptive decision rule with the help of privileged information. We jointly learn two distance metrics by minimizing the empirical loss penalizing the difference between the distance in the original space and that in the privileged space. In our setting, the distance in the privileged space functions as a local decision threshold, which guides the decision making in the original space like a teacher. The metric learned from the original space is used to compute the distance between a probe image and a gallery image during testing. In addition, we extend the proposed approach to a multi-view setting which is able to explore the complementation of multiple feature representations. In the multi-view setting, multiple metrics corresponding to different original features are jointly learned, guided by the same privileged information. Besides, an effective iterative optimization scheme is introduced to simultaneously optimize the metrics and the assigned metric weights. Experiment results on several widely-used data sets demonstrate that the proposed approach is superior to global decision threshold-based methods and outperforms most state-of-the-art results.
Exploring the impacts of the interactions between lifecycles and other dynamics that influence the development of technology-based industries

To address future uncertainty within strategy and innovation, managers extrapolate past patterns and trends into the future. Several disciplines make use of lifecycles, often with a linear sequence of identified phases, to make predictions and address likely uncertainties. Often the aggregation of several cycles is then interpreted as a new cycle - such as product lifecycles into an industry lifecycle. However, frequently different lifecycle terms - technology, product, industry - are used interchangeably and without clear definition. Within the interdisciplinary context of technology management, this juxtaposition of dynamics can create confusion, rather than clarification. This paper explores some typical dynamics associated with technology-based industries, using illustrative examples from the automotive industry. A wide range of dimensions are seen to influence the path of a technology-based industry, and stakeholders need to consider the likely causality and synchronicity of these. Some curves can simply present the aggregation of components; other dynamics incur time lags, rather than being superimposed, but still have a significant impact. To optimise alignment of the important dimensions within any development, and for future strategy decisions, understanding these interactions will be critical.
Towards natural insect vision research

Visual world is naturally correlated both spatially and temporally. The correlations are used in vision to enhance performance of neurons. For gaining maximal neural performance of the visual neurons, the experiments, from stimulus to the analysis, should be designed to take advantage of the correlations. In this thesis methods for generating and analyzing natural stimuli were examined by using computations and algorithms. For analyzing responses to natural stimuli in visual neurons, a method with only a few assumptions was developed for estimating information rate in long responses. The novel method gave a good agreement with Shannon information rate with linear system and Gaussian input but was able to handle also nonlinear processing and non-Gaussian data. Secondly, a computer controlled 3D virtual environment with a spherical screen was developed, with a large visual field. The image of the world was projected to the screen with a DLP projector, giving good enough temporal performance for insect vision research. A track-ball was used in closed loop experiments. Thirdly, properties of single photon (“bump”) information transfer at various light levels were investigated in cockroach photoreceptor with a coarse computational model. At dim light (< 10 ph/s), where single bump responses were visible, shot noise was dominant. At higher light levels latency distribution of the bump decreased the information rate, but amplitude distribution of bump did not have an effect. Fourthly, the contribution of K channels to information rate and energy consumption was investigated by creating a database of computation models with varying channel compositions. The information rate has a maximum as a function of mean conductance, which was a sum of the average K conductance and the leak conductance. This maximum was fine-tuned by the K channel composition, which had high so-called novel contribution and relatively low amount of other conductances. Keyword: insect, vision, Hodgkin-Huxley model, natural stimulus, information rate, virtual environment
Competitive advantage in the ERP system's value-chain

Using the resource-based view, we present a set of propositions related to enterprise resource planning (ERP) development, reflections on competitive advantage and the different roles that stakeholders play in the value-chain. This has the goal of building a foundation for future research on ERPs and how stakeholders' desire to achieve competitive advantage influence ERP development, especially when it comes to development of a more standardised or precustomised ERP system. The propositions also act as a foundation for increasing our knowledge concerning the difficulty in developing improved ERP systems.
Identifying the Molecular Signatures of Agricultural Expansion in Amazonian Headwater Streams

Agricultural impacts on aquatic ecosystems are well studied; however, most research has focused on temperate regions, whereas the forefront of agricultural expansion is currently in the tropics. At the vanguard of this growth is the boundary between the Amazon and Cerrado biomes in Brazil, driven primarily by expansion of soybean and corn croplands. Here we examine the impacts of cropland expansion on receiving lowland Amazon Basin headwater streams in terms of dissolved organic carbon (DOC) concentration and dissolved organic matter (DOM) composition via ultrahigh‐resolution mass spectrometry. Streams draining croplands had lower DOC concentrations and DOM molecular signatures enriched in N‐ and S‐containing formula in comparison to forested streams. Cropland streams were also enriched in aliphatic, peptide‐like, and highly unsaturated and phenolic (low O/C) compound categories in comparison to forest streams (enriched in polyphenolics, condensed aromatics, and highly unsaturated and phenolic [high O/C] compound categories) indicative of the shifting of sources from organic‐rich surface soils and litter layers to autochthonous and more microbial biomass. Distinct molecular assemblages were strongly correlated with cropland and forest catchments, highlighting headwater streams as sentinels for detecting change. On investigation of unique molecular formulae present in only cropland sites, four cropland markers provided the ability to track agricultural impacts in the region. Overall, these patterns indicate reduced organic matter inputs in croplands and greater microbial degradation at these sites leading to declining DOC concentrations, and DOM of more microbial character in receiving streams that is more biolabile, with clear ramifications for downstream ecology and biogeochemical cycles.
ICE matching, a novel approach for localization problem

This paper presents a novel technique for scan matching. The method is based on the family of feature to feature matching approaches. Our innovative method named ICE matching leads to a fast and accurate solution to solve the challenges of localization problem. Novelty in defining new features, matching mechanism and new state estimation approach, congregated in this method, creates a robust practical technique in terms of accuracy and convergence rate. Furthermore, The Comparison with some high quality scan matching methods from different viewpoints illustrates the performance of ICE matching.
PHYTOCHEMICAL, TOXICOLOGICAL EVALUATION AND ANTICATALEPTIC ACTIVITY OF NARDOSTACHYS JATAMANSI

Hydro alcoholic root extract from Nardostachys jatamansi was investigated for its antioxidant and anti cataleptic effects in the haloperidol-induced catalepsy rat model of the disease by measuring behavioral, biochemical parameters and neurotransmitter levels. Catalepsy was induced by administration of haloperidol (1 mg/kg, i.p) in male wistar rats. A significant (P < 0.01) reduction in the cataleptic scores were observed in all the drug-treated groups as compared to the haloperidol-treated group; with maximum reduction observed in the Nardostachys jatamansi (500 mg/kg body weight) administered group. Haloperidol administration increased generation of TBARS and significantly reduced GSH, which were restored to near normal level with the Nardostachys jatamansi treatment. Catalase and SOD levels were also increased to normal levels, having been reduced significantly by haloperidol administration. Haloperidol administration decreased the dopamine levels significantly, which were restored to near normal levels with the Nardostachys jatamansi treatment. Our findings of behavioral studies and biochemical estimations show that Nardostachys jatamansi reversed the haloperidol-induced catalepsy in rats.
An agent-based framework to support adaptive hypermedia

The field of adaptive hypermedia is a little over a decade old. It has a rich history in a range of fields such as artificial intelligence, user modelling, intelligent tutoring systems and hypertext. Early adaptive hypermedia work concentrated on application-led research; developing a range of systems for specific purposes. In 1996, Peter Brusilovsky reviewed the state-of-the-art and proposed a taxonomy of adaptive hypermedia techniques, thereby providing the means to categorise adaptive hypermedia systems. Since then, several practical frameworks for adaptive hypermedia applications have been produced, in addition to formal models for formalising adaptive hypermedia applications. This thesis presents a new framework for adaptive hypermedia systems based on agent technology, a field of research largely ignored within the adaptive community. Conceptually, this framework occupies a middle ground between the formal reference models for adaptive hypermedia and application-specific frameworks. This framework provides the means to implement formal models using variety of architectural approaches. Three novel adaptive hypermedia applications have been developed around this agent-based framework. Each system employs different architectural structures, they model the user with a variety of profiling techniques, and each provides a different set of adaptive features. The diversity of these three systems emphasises the flexibility and functionality of this proposed agent-based framework.
Amino Acid Transport Regulates Blastocyst Implantation1

Abstract Mouse blastocyst outgrowth in vitro and probably implantation in vivo require amino acid signaling via the target of rapamycin (TOR) pathway. This signaling does not simply support protein synthesis and trophoblast differentiation. Rather, it regulates development of trophoblast protrusive activity and may act as a developmental checkpoint for implantation. Moreover, intracellular amino acids per se are insufficient to elicit TOR signaling. Instead, de novo transport of amino acids, and particularly of leucine, stimulate mTOR activity at the blastocyst stage. The activity of the broad-scope and yet leucine-selective amino acid transport system B0,+ could produce such increases in intracellular amino acid concentrations. For example, system B0,+ uses a Na+ gradient to drive amino acid uptake, and the Na+ concentration in uterine secretions increases by nearly two-fold about 18 h before implantation. The resultant mTOR signaling could trigger polyamine, insulin-like growth factor II, and nitric oxide production in blastocysts and the increased cell motility sometimes associated with synthesis of these bioactive molecules.
Improved Decoding Algorithm of Serial Belief Propagation With a Stop Updating Criterion for LDPC Codes and Applications in Patterned Media Storage

In high density patterned media storage system, the “multiple islands per read head” model is taken into account for inter-track interference (ITI) in bit-patterned media (BPM). It has been proposed that low-density parity-check (LDPC) codes could improve the symbol error rate (SER) performance significantly when only considering AWGN noise alone over the storage channel. LDPC decoding algorithm could be applied in LDPC joint decoder of patterned media storage system. In this paper, we proposed a decoding algorithm of serial belief propagation (SBP) with a stop updating criterion for LDPC decoder. Simulation results show that the proposed decoding algorithm could reduce the times of generating and propagating the message in decoding with negligible error rate performance loss over AWGN channels when appropriately choosing the parameter that determines which variable node has been converged. By taking advantage of extrinsic information transfer (EXIT) charts, it is demonstrated that the proposed decoding algorithm could maintain superior SER performance and convergence rate compared with the traditional SBP decoding algorithm. To further explore the performance of the proposed decoding algorithm in “multiple islands per read head” model, we performed a large number of simulations over this channel model with different distribution percentages between the AWGN and the island position jitter noise. Simulation results show that the LDPC codes could improve the SER performance when considering jitter noise while the proposed decoding algorithm behaves excellently over the patterned media storage channel and over the AWGN channel.
Group endmember extraction algorithm based on Gram–Schmidt orthogonalization

Abstract. Endmember extraction is the key step in the mixed pixel decomposition for hyperspectral images. In view of the larger Markov property of endmember error in the sequence endmember extraction algorithm, which affects the endmember extraction accuracy, we propose an endmember extraction algorithm with three endmembers as a group based on Gram–Schmidt orthogonalization. According to the convex geometry theory, the spectral characteristic and the geometrical property of simplex in feature space have been analyzed, and the idea of group endmember extraction was introduced to reduce the Markov property of the endmember error, improving the endmember extraction accuracy accordingly. The orthogonal vector was searched by Gram–Schmidt orthogonalization and the image was projected to the orthogonal vector, so as to eliminate the effect of the extracted endmembers. The energy function was used as a measure index of the similarity for spectral vectors of different ground objects, and the measure index was used to determine the endmember. The algorithm was verified by using simulation data and real data. The experimental results indicated that the proposed algorithm may extract endmember automatically, and the corresponding endmember extraction accuracy was better than other algorithms.
Isolation and identification of compounds with antinociceptive action from Ipomoea pes-caprae (L.) R. Br.

This study describes the isolation and identification of several constituents from Ipomoea pes-caprae (L.) R. Br. , a medicinal plant frequently employed in folk medicine of many countries as a remedy against several diseases, including inflammation and pain. Our results demonstrate that some of these compounds, such as glochidone, betulinic acid, alpha- and beta-amyrin acetate, isoquercitrin, etc. showed pronounced antinociceptive properties in the writhing test and formalin test in mice. These data confirm our previous work concerning the antinociceptive action of the hydroalcoholic extract of I. pes-caprae and justify, at least in part, the popular use of this plant for the treatment of dolorous processes.
Susceptibility weighted imaging at ultra high magnetic field strengths: Theoretical considerations and experimental results

We present numerical simulations and experimental results for susceptibility weighted imaging (SWI) at 7 T. Magnitude, phase, and SWI contrast were simulated for different voxel geometries and imaging parameters, resulting in an echo time of 14 msec for optimum contrast between veins and surrounding tissue. Slice thickness of twice the in‐plane voxel size or more resulted in optimum vessel visibility. Phantom and in vivo data are in very good agreement with the simulations and the delineation of vessels at 7 T was superior compared to lower field strengths. The phase of the complex data reveals anatomical details that are complementary to the corresponding magnitude images. Susceptibility weighted imaging at very high field strengths is a promising technique because of its high sensitivity to tissue susceptibility, its low specific absorption rate, and the phase's negligible sensitivity to B1 inhomogeneities. Magn Reson Med 60:1155–1168, 2008. © Wiley‐Liss, Inc.
PARTIAL POWER DC-DC CONVERTERS FOR TWO STAGE PHOTOVOLTAIC ENERGY CONVERSION SYSTEMS

Two-stage photovoltaic (PV) configurations (for microinverters, string or multistring inverters) have become increasingly popular due to the decoupling between the inverter dc-link voltage and the PV voltage, adding flexibility to extend the MPPT range. However, the additional dc-dc converter increases the component count, reduces the volume and power converter losses. The concept of partial power converters (PPC), which reduces the amount of power handled by the dc-stage can mitigate this effect. However, the type of topology, its power and voltage rating, efficiency, and operating range can vary significantly depending on the type of PV application and scale. Furthermore, the type of function of the dc-dc stage will also differ depending on the PV application. From boosting with a high step-up ratio for one module in a microinverter, to a buck mode for larger PV strings when using modern 1500V isolation modules. This thesis provides an analysis of the possible combinations of connections and corresponding applications based on the scale of the PV system. The three most suitable solutions for practical PV systems are further elaborated, including simulations and experimental validation. Experimental results show that the PPC greatly improves the overall PV system efficiency, even when the efficiency of the isolated dc-dc converter is low. An added benefit is that the dc-dc stage power rating achieved are only a fraction of the PV system, reducing size and increasing power density of the power converter without affecting system performance.
Costs of Intravenous Adverse Drug Events in Academic and Nonacademic Intensive Care Units

Background:Adverse drug events (ADEs), particularly those involving intravenous medications (IV-ADEs), are common among intensive care unit (ICU) patients and may increase hospitalization costs. Precise cost estimates have not been reported for academic ICUs, and no studies have included nonacademic ICUs. Objectives:To estimate increases in costs and length of stay after IV-ADEs at an academic and a nonacademic hospital. Research Design:This study reviewed medical records to identify IV-ADEs, and then, using a nested case-control design with propensity-score matching, assessed differences in costs and length of stay between cases and controls. Subjects:A total of 4604 adult ICU patients in 3 ICUs at an academic hospital and 2 ICUs at a nonacademic hospital in 2003 and 2004. Measures:Increased cost and length of stay associated with IV-ADEs. Results:Three hundred ninety-seven IV-ADEs were identified: 79% temporary physical injuries, 0% permanent physical injuries, 20% interventions to sustain life, and 2% in-hospital deaths. In the academic ICUs, patients with IV-ADEs had $6647 greater costs (P < 0.0001) and 4.8-day longer stays (P = 0.0003) compared with controls. In the nonacademic ICUs, IV-ADEs were not associated with greater costs ($188, P = 0.4236) or lengths of stay (−0.3 days, P = 0.8016). Cost and length-of-stay differences between the hospitals were statistically significant (P = 0.0012). However, there were no differences in IV-ADE severity or preventability, and the characteristics of patients experiencing IV-ADEs differed only modestly. Conclusions:IV-ADEs substantially increased hospitalization costs and length of stay in ICUs at an academic hospital but not at a nonacademic hospital, likely because of differences in practices after IV-ADEs occurred.
Atomic roughness enhanced friction on hydrogenated graphene

Atomic friction on hydrogenated graphene is investigated using molecular dynamics simulations. Hydrogenation is found to increase friction significantly, and the atomic-level information provided by the simulations reveals that atomic roughness induced by hydrogenation is the primary cause of the friction enhancement. Other proposed mechanisms, specifically adhesion and rigidity, are excluded based on the simulation results and analyses performed using the Prandtl–Tomlinson model. In addition, it is found that friction does not monotonically increase with hydrogen coverage on the graphene surface; instead, a maximum friction is observed at a hydrogen coverage between 5 and 10%.
Addressing medication adherence technology needs in an aging population

Using technology to inspire behavior change motivated by a health goal is a challenge. Technologies, often rooted in sound scientific principles, sometimes do not perform as expected in real world scenarios. Quite often the barriers to use are not inherent in the behavior change model of the product or service, but are issues associated with the failure to appropriately consider the needs of the end users when designing an intervention. We deployed a large, multi-stage research study with aging adults to assess the facilitators and barriers of technologies aimed to create or support behavior changes related to medication adherence. Using the Fogg Behavior model, we analyzed the triggers made on behavior change through data from surveys, in-home interviews, participatory design workshops and the deployed technologies. Our results indicate that the user experience associated with delivery of the content is at least as important as the content. Additionally, experienced users are far better prepared to help researchers identify potential design issues than novice users. Because our participants were knowledgeable about the technologies and the features that worked and did not work, the concluding participatory design sessions were highly efficient in providing feedback on the type of mechanisms that resonate with this population and could lead to higher levels of behavior change in future technologies.