Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparison of SLAM algorithms based on a graph of relations

In this paper, we address the problem of creating an objective benchmark for comparing SLAM approaches. We propose a framework for analyzing the results of SLAM approaches based on a metric for measuring the error of the corrected trajectory. The metric uses only relative relations between poses and does not rely on a global reference frame. The idea is related to graph-based SLAM approaches in the sense that it considers the energy needed to deform the trajectory estimated by a SLAM approach to the ground truth trajectory. Our method enables us to compare SLAM approaches that use different estimation techniques or different sensor modalities since all computations are made based on the corrected trajectory of the robot. We provide sets of relative relations needed to compute our metric for an extensive set of datasets frequently used in the SLAM community. The relations have been obtained by manually matching laser-range observations. We believe that our benchmarking framework allows the user an easy analysis and objective comparisons between different SLAM approaches.
The moderating effect of perceived quality of logistics services and gender in the relationship between trust, satisfaction and repurchase intention in E-commerce

In order to further research the effect of logistics service quality, this study explores the moderating effect of perceived quality of logistics services (PQLS) on the relationships between satisfaction, trust and repurchase intention. In addition, we also test whether there are gender differences in the relationships. Drawing on the theory of organizational trust, and based on a survey of 209 online consumers, we find that PQLS negatively moderates the relationship between trust in online retailer and consumer repurchase intention, because it relaxes customers' worry and anxiousness about the inefficiency and poor quality of products delivery. We also find that PQLS positively moderates the relationship between consumer satisfaction with online vendor and trust as it strengths consumers' reliance on past transaction experience to reestimate trust in the vendor. At last, we find that the moderating effect of gender on the relationship between satisfaction and trust isn't significant.
Optimal and Adaptive Algorithms for Online Boosting

We study online boosting, the task of converting any weak online learner into a strong online learner. Based on a novel and natural definition of weak online learnability, we develop two online boosting algorithms. The first algorithm is an online version of boost-by-majority. By proving a matching lower bound, we show that this algorithm is essentially optimal in terms of the number of weak learners and the sample complexity needed to achieve a specified accuracy. The second algorithm is adaptive and parameter-free, albeit not optimal.
Working Report on the Use of Mathematical Morphology for Blood Smears Processing

activity which involves subjectivity and is tedious for the operator. The increasing number of drugs in testing makes it necessary to automate or semi automate the process. We propose an automated method for malaria thin blood smear inspection based on mathematical morphology tools operated on the grayscale image. The system is presented without a validation scheme and possibilities for the validation are proposed. Future work is outlined.
CS 229, Autumn 2011 Modeling the Stock Market Using Twitter Sentiment Analysis

This project is based on Bollen, Mao and Zeng’s Twitter mood predicts the stock market, which shows that sentiment extracted from Twitter tweets can be used efficiently to enhance forecasts on the direction of stock market moves in the short term [1]. They claim an 87.6% accuracy in predicting stock market moves (up or down). Our objective will thus be to implement a trading mechanism based on Twitter data and past stock price time series, and to compare the performance of Twitter-enhanced strategies with more traditional algorithmic strategies.
Nephrin missense mutations: induction of endoplasmic reticulum stress and cell surface rescue by reduction in chaperone interactions

Nephrin, an important component of the podocyte filtration slit diaphragm, plays a key role in the maintenance of glomerular permselectivity. Mutations in nephrin lead to proteinuria and congenital nephrotic syndrome. Nephrin undergoes posttranslational modifications in the endoplasmic reticulum (ER) prior to export to the plasma membrane. We examined the effects of human nephrin disease‐associated missense mutations on nephrin folding in the ER and on cellular trafficking in cultured cells. Compared with wild‐type (WT) nephrin, the mutants showed impaired glycosylation and enhanced association with the ER chaperone, calnexin, as well as accumulation in the ER. Nephrin mutants demonstrated enhanced ubiquitination, and they underwent ER‐associated degradation. Certain nephrin mutants did not traffic to the plasma membrane. Expression of nephrin mutants resulted in the stimulation of the activating transcription factor‐6 pathway of the unfolded protein response, and an increase in the ER chaperone, Grp94. We treated cells with castanospermine (an inhibitor of glucosidase I) in order to decrease the association of nephrin mutants with calnexin. Castanospermine increased plasma membrane expression of nephrin mutants; however, full glycosylation and signaling activity of the mutants were not restored. Modulation of ER quality control mechanisms represents a potential new approach to development of therapies for proteinuric kidney disease, including congenital nephrotic syndrome.
Effectiveness of solving traveling salesman problem using Ant Colony Optimization on distributed multi-agent middleware

Recently we have setup the goal of investigating new truly distributed forms of Ant Colony Optimization.We proposed a new distributed approach for Ant Colony Optimization (ACO) algorithms called Ant Colony Optimization on a Distributed Architecture (ACODA). ACODA was designed to allow efficient implementation of ACO algorithms on state-of-the art distributed multi-agent middleware. In this paper we present experimental results that support the feasibility of ACODA by considering a distributed version of the Ant Colony System (ACS). In particular we show the effectiveness of this approach for solving Traveling Salesperson Problem by comparing experimental results of ACODA versions of distributed ACS with distributed random searches on a high-speed cluster network.
On the robustness of bayesian compressive sensing for directions-of-arrival estimation

Compressive Sensing (CS) has demonstrated to be particularly adapt for dealing with the directions-of-arrival (DoAs) estimation of electromagnetic signals impinging on an array of sensors. Unlike deterministic CS methods, the Bayesian CS (BCS) allows to overcome some theoretical limitations of the CS, such to enable a reliable and versatile DoAs estimation tool able to work with different array, noise and signals configurations. Keywords-Bayesian Compressive Sensing; directions-of-arrival estimation; planar antenna array
Modeling of als intensity behavior as a function of incidence angle for coastal zone surface study

Backscatter intensity of the LiDAR, recorded simultaneously with the discrete topography measurements, was recently investigated, providing complementary information to study coastal environments. The aim of this study was (i) to analyze the intensity-incidence angle behavior for coastal environments (sea and moist sand surfaces) and other surfaces (fields and urban area) with different reflectance models and (ii) to choose the best modeling for all these surfaces. We compared three reflection models. Firstly, diffuse reflection is introduced by Lambert's cosine law. The illuminated surfaces are composed of numerous small mirror-like facets inducing a dominant specular diffusion. This scattering of micro-facets is defined by the Beckmann distribution. The last model is a combination of diffuse and specular reflection. In this paper, we found that Beckmann distribution well simulates the intensity-incidence behavior for specular and diffuse mechanisms with the advantage to have only one parameter to characterize the studied surfaces.
Achieving Magnet accreditation in the UK: a case study at Rochdale NHS Trust.

AIMS This study explored the Magnet accreditation process in the first health care organization outside the USA to attempt to gain the award, Rochdale NHS Trust United Kingdom. The development was supported by the American Nurses Credentialing Center as a pilot project and the research conducted as a case study in organizational response to the requirements of a new accreditation system. METHOD Information was collected via 23 face-to-face and three telephone interviews carried out with 11 senior figures at Rochdale during the 2-year period of the Magnet project, from field notes of meetings attended by the researchers and from analysis of documents associated with the project. RESULTS The work of applying for Magnet accreditation built upon a previous 2-3 year programme of shared governance and clinical leadership throughout the Trust which senior staff felt had been an essential foundation for the Magnet project. The process enabled staff to assemble evidence which held up a mirror to their practice and contributed to other quality-related initiatives. The experience at Rochdale suggests that Magnet enables care areas to identify and celebrate examples of good practice and for lessons to be learned and shared within the organization. Although the Magnet concept is primarily nursing oriented, medical and allied health professionals were able to contribute and benefit. The application was successful and Rochdale was awarded Magnet status in April 2002. CONCLUSIONS The Magnet project at Rochdale was essentially a process of collecting evidence to formally recognize previous leadership initiatives and their effects within the organization. The emergent approach to implementing the Magnet project was one which attempted to integrate and utilize existing systems and resources. The project provides evidence that Magnet can be transferred to non-US health care systems. The principal issues associated with this transfer were the costs incurred, the interpretation of terminology and the engagement of medical and allied health professionals.
Transcriptome and Difference Analysis of Fenpropathrin Resistant Predatory Mite, Neoseiulus barkeri (Hughes)

Several fenpropathrin-resistant predatory mites have been reported. However, the molecular mechanism of the resistance remains unknown. In the present study, the Neoseiulus barkeri (N. barkeri) transcriptome was generated using the Illumina sequencing platform, 34,211 unigenes were obtained, and 15,987 were manually annotated. After manual annotation, attentions were attracted to resistance-related genes, such as voltage-gated sodium channel (VGSC), cytochrome P450s (P450s), and glutathione S-transferases (GSTs). A polymorphism analysis detected two point mutations (E1233G and S1282G) in the linker region between VGSC domain II and III. In addition, 43 putative P450 genes and 10 putative GST genes were identified from the transcriptome. Among them, two P450 genes, NbCYP4EV2 and NbCYP4EZ1, and four GST genes, NbGSTd01, NbGSTd02, NbGSTd03 and NbGSTm03, were remarkably overexpressed 3.64–46.69-fold in the fenpropathrin resistant strain compared to that in the susceptible strain. These results suggest that fenpropathrin resistance in N. barkeri is a complex biological process involving many genetic changes and provide new insight into the N. barkeri resistance mechanism.
Is There Extra Cost of Institutional Care for MS Patients?

Throughout life, patients with multiple sclerosis (MS) require increasing levels of support, rehabilitative services, and eventual skilled nursing facility (SNF) care. There are concerns that access to SNF care for MS patients is limited because of perceived higher costs of their care. This study compares costs of caring for an MS patient versus those of a typical SNF patient. We merged SNF cost report data with the 2001–2006 Nursing Home Minimum Data Set (MDS) to calculate percentage of MS residents-days and facility case-mix indices (CMIs). We estimated the average facility daily cost using hybrid cost functions, adjusted for facility ownership, average facility wages, CMI-adjusted number of SNF days, and percentage of MS residents-days. We describe specific characteristics of SNF with high and low MS volumes and examine any sources of variation in cost. MS patients were no longer more costly than typical SNF patients. A greater proportion of MS patients had no significant effect on facility daily costs (P = 0.26). MS patients were more likely to receive care in government-owned facilities (OR = 1.904) located in the Western (OR = 2.133) and Midwestern (OR = 1.3) parts of the USA (P < 0.05). Cost of SNF care is not a likely explanation for the perceived access barriers that MS patients face.
Potent Inhibition of Acid Ceramidase by Novel B-13 Analogues

The lipid-signalling molecule ceramide is known to induce apoptosis in a variety of cell types. Inhibition of the lysosomal acid ceramidase can increase cellular ceramide levels and thus induce apoptosis. Indeed, inhibitors of acid ceramidase have been reported to induce cell death and to display potentiating effects to classical radio- or chemo therapy in a number of in vitro and in vivo cancer models. The most potent in vitro inhibitor of acid ceramidase, B-13, recently revealed to be virtually inactive towards lysosomal acid ceramidase in living cells. In contrast, a number of weakly basic B-13 analogues have been shown to accumulate in the acidic compartments of living cells and to efficiently inhibit lysosomal acid ceramidase. However, introduction of weakly basic groups at the ω-position of the fatty acid moiety of B-13 led to a significant reduction of potency towards acid ceramidase from cellular extracts. Herein, we report a novel B-13-derived scaffold for more effective inhibitors of acid ceramidase. Furthermore, we provide hints for an introduction of basic functional groups at an alternative site of the B-13 scaffold that do not interfere with acid ceramidase inhibition in vitro.
A novel depression detection method based on pervasive EEG and EEG splitting criterion

Depression is a mental disorder characterized by persistent occurrences of lower mood states in the affected person. According to the study of World Health Organization (WHO), depression will become the second largest cause of illness threatening the life of human beings in 2020, so early detection, early diagnosis and early treatment of depression is very important to save the health and life of human beings. In order to alleviate the damage caused by depression and make early detection, early diagnosis and early treatment of depression, a portable and accurate depression detection and diagnosis method is most necessary. Due to the highly complexity, nonlinearity and non-stationarity of electroencephalogram (EEG) data in nature, we present a novel method for pervasive EEG-based detection and diagnosis of depression with the resting state eye-closed EEG data of Fp1, Fpz and Fp2 locations of scalp electrodes, which are closely related to emotion, collected through three-electrode pervasive EEG collection device in this paper. Experiment has been conducted and totally 170 (81 depressive patients and 89 normal subjects) subjects' pervasive EEG data have been collected in resting state and eye-closed. Then, Support Vector Machine (SVM) is utilized to analyze the pervasive EEG data and the average accuracy reaches 83.07%. After Friedman Test and post-hoc two-tailed Nemenyi Test, we propose a splitting criterion for pervasive EEG. The data analysis experimental results show that the proposed method for detecting and diagnosing depression is effective and convenient, and it also demonstrate that the three-electrode pervasive EEG collection device has broad prospects in depression detection and diagnosis.
Crowdsourcing for ICD10 Code to Concept Relationships

In this work we leverage crowdsourcing in connection with machine learning techniques to validate candidate ICD10 Code to UMLS concept relationships that we generate. Our immediate use is in natural language understanding and machine learning approaches to automatically code electronic health record documents with ICD codes. Beyond auto-coding, the relationships will aid a wide variety of future medical applications, such as terminology-driven search in support of smart medical assistants.
Practical fast searching in strings

The problem of searching through text to find a specified substring is considered in a practical setting. It is discovered that a method developed by Boyer and Moore can outperform even special‐purpose search instructions that may be built into the computer hardware. For very short substrings however, these special purpose instructions are fastest—provided that they are used in an optimal way.
Redefining the Expression and Function of the Inhibitor of Differentiation 1 in Mammary Gland Development

The accumulation of poorly differentiated cells is a hallmark of breast neoplasia and progression. Thus an understanding of the factors controlling mammary differentiation is critical to a proper understanding of breast tumourigenesis. The Inhibitor of Differentiation 1 (Id1) protein has well documented roles in the control of mammary epithelial differentiation and proliferation in vitro and breast cancer progression in vivo. However, it has not been determined whether Id1 expression is sufficient for the inhibition of mammary epithelial differentiation or the promotion of neoplastic transformation in vivo. We now show that Id1 is not commonly expressed by the luminal mammary epithelia, as previously reported. Generation and analysis of a transgenic mouse model of Id1 overexpression in the mammary gland reveals that Id1 is insufficient for neoplastic progression in virgin animals or to prevent terminal differentiation of the luminal epithelia during pregnancy and lactation. Together, these data demonstrate that there is no luminal cell-autonomous role for Id1 in mammary epithelial cell fate determination, ductal morphogenesis and terminal differentiation.
Smooth hybrid inflation.

We propose a variant of hybrid inflation which is applicable in a wide class of supersymmetric grand unified models. The observed temperature perturbations of cosmic background radiation can be reproduced with natural values of the parameters of the theory and a grand unification scale which is consistent with the unification of the minimal supersymmetric standard model gauge couplings as measured at CERN LEP. The termination of inflation is smooth and does not produce any topological defects. Finally, we present a specific supersymmetric model where our smooth hybrid inflationary scenario is realized.
Multistationary and Oscillatory Modes of Free Radicals Generation by the Mitochondrial Respiratory Chain Revealed by a Bifurcation Analysis

The mitochondrial electron transport chain transforms energy satisfying cellular demand and generates reactive oxygen species (ROS) that act as metabolic signals or destructive factors. Therefore, knowledge of the possible modes and bifurcations of electron transport that affect ROS signaling provides insight into the interrelationship of mitochondrial respiration with cellular metabolism. Here, a bifurcation analysis of a sequence of the electron transport chain models of increasing complexity was used to analyze the contribution of individual components to the modes of respiratory chain behavior. Our algorithm constructed models as large systems of ordinary differential equations describing the time evolution of the distribution of redox states of the respiratory complexes. The most complete model of the respiratory chain and linked metabolic reactions predicted that condensed mitochondria produce more ROS at low succinate concentration and less ROS at high succinate levels than swelled mitochondria. This prediction was validated by measuring ROS production under various swelling conditions. A numerical bifurcation analysis revealed qualitatively different types of multistationary behavior and sustained oscillations in the parameter space near a region that was previously found to describe the behavior of isolated mitochondria. The oscillations in transmembrane potential and ROS generation, observed in living cells were reproduced in the model that includes interaction of respiratory complexes with the reactions of TCA cycle. Whereas multistationarity is an internal characteristic of the respiratory chain, the functional link of respiration with central metabolism creates oscillations, which can be understood as a means of auto-regulation of cell metabolism.
Consistency of Causal Inference under the Additive Noise Model

We analyze a family of methods for statistical causal inference from sample under the socalled Additive Noise Model. While most work on the subject has concentrated on establishing the soundness of the Additive Noise Model, the statistical consistency of the resulting inference methods has received little attention. We derive general conditions under which the given family of inference methods consistently infers the causal direction in a nonparametric setting.
Evaluation of anti-complement immunofluorescence test in cytomegalovirus infection

The anti-complement immunofluorescence (ACIF) technique was evaluated for the diagnosis of human cytomegalovirus (CMV) infection in a group of sera derived from renal transplant recipients and donors by comparing it with the indirect immunofluorescence (FA) and complement fixation (CF) TESTS. The ACIF and FA tests yielded similar results. However, the ACIF test had a distinct advantage over the indirect FA test, since it eliminated the nonspecific cytoplasmic staining that may result in false positive readings in inexperienced hands. Both the indirect FA and ACIF tests were more sensitive than the CF test. In primary CMV infection, the FA and ACIF antibodies appeared earlier and had significantly higher titer than corresponding CF titers. This difference in titers was not seen in seropositive individuals who lacked overt infection. Our previously reported correlation between the seropositivity of the donor and CMV infection in seronegative recipients has been confirmed.
Optimal uncertainty quantification for legacy data observations of Lipschitz functions

We consider the problem of providing optimal uncertainty quantification (UQ) – and hence rigorous certification – for partially-observed functions. We present a UQ framework within which the observations may be small or large in number, and need not carry information about the probability distribution of the system in operation. The UQ objectives are posed as optimization problems, the solutions of which are optimal bounds on the quantities of interest; we consider two typical settings, namely parameter sensitivities (McDiarmid diameters) and output deviation (or failure) probabilities. The solutions of these optimization problems depend non-trivially (even non-monotonically and discontinuously) upon the specified legacy data. Furthermore, the extreme values are often determined by only a few members of the data set; in our principal physically-motivated example, the bounds are determined by just 2 out of 32 data points, and the remainder carry no information and could be neglected without changing the final answer. We propose an analogue of the simplex algorithm from linear programming that uses these observations to offer efficient and rigorous UQ for high-dimensional systems with high-cardinality legacy data. These findings suggest natural methods for selecting optimal (maximally informative) next experiments.