Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized Z-homotopy fixed points of Cn spectra with applications to norms of MUR

We introduce a computationally tractable way to describe the Z-homotopy fixed points of a Cn-spectrum E, producing a genuine Cn spectrum E hnZ whose fixed and homotopy fixed points agree and are the Z-homotopy fixed points of E. These form the bottom piece of a contravariant functor from the divisor poset of n to genuine Cn-spectra, and when E is an N∞-ring spectrum, this functor lifts to a functor of N∞-ring spectra. For spectra like the Real Johnson–Wilson theories or the norms of Real bordism, the slice spectral sequence provides a way to easily compute the RO(G)-graded homotopy groups of the spectrum EhnZ, giving the homotopy groups of the Z-homotopy fixed points. For the more general spectra in the contravariant functor, the slice spectral sequences interpolate between the one for the norm of Real bordism and the especially simple Z-homotopy fixed point case, giving us a family of new tools to simplify slice computations.
Effect of Corrective Surgery on Lower Limb Mechanics in Patients with Crouch Gait

vi LIST OF FIGURES . x LIST OF ABBREVIATIONS . xii CHAPTER ONE: INTRODUCTION . 1 1.1 Motivation . 1 1.2 Research Goals . 4 CHAPTER TWO: MODEL DEVELOPMENT . 8 2.1 Clinical Data Collection . 8 2.2 Rigid-Body Musculoskeletal Model . 9 2.3 Kinematics . 11 2.4 Knee Finite Element Model . 14 2.5 Lower Extremity Finite Element Model. 15 2.6 Proportional-Integral Controlled Muscles . 16 2.7 Model Application . 19 CHAPTER THREE: MANUSCRIPT “EFFECT OF CORRECTIVE SURGERY ON LOWER LIMB MECHANICS IN PATIENTS WITH CROUCH GAIT” . 20 3.
MULTISTATIC AIRBORNE PASSIVE SYNTHETIC APERTURE RADAR IMAGING BASED ON TWO-LEVEL BLOCK SPARSITY

Available multiple illuminators in a multistatic airborne passive synthetic aperture radar (SAR) system can enhance SAR imaging quality. In this paper, a new imaging algorithm based on twolevel block sparsity for a multistatic airborne passive SAR system is proposed. The proposed imaging algorithm named by two-level block matching pursuit (BMP) algorithm utilizes both the spatially clustered property of observed targets and joint sparsity of the multistatic observation, i.e., two-level block sparsity to achieve the imaging reconstruction of an observed scene. The simulation results show that the proposed two-level BMP imaging algorithm for the multistatic airborne passive SAR system can reduce imaging reconstruction time and provide enhanced imaging reconstruction quality compared to the state-of-the-art structured sparse imaging algorithm.
MOX–Report No. 31/2009 Theoretical study and numerical simulation of textiles

We propose a new approach for developing continuum models t to describe the mechanical behavior of textiles. We develop a physically motivated model, based on the properties of the yarns, which can predict and simulate the textile behavior. The approach relies on the selection of a suitable topological model for the patch of the textile, coupled with constitutive models for the yarn behavior. The textile structural con guration is related to the deformation through an energy functional, which depends on both the macroscopic deformation and the distribution of internal nodes. We determine the equilibrium positions of these latter, constrained to an assigned macroscopic deformation. As a result, we derive a macroscopic strain energy function, which re ects the possibly nonlinear character of the yarns as well as the anisotropy induced by the microscopic topological pattern. By means of both analytical estimates and numerical experiments, we show that our model is well suited for both academic test cases and real industrial textiles, with particular emphasis on the tricot textile.
CITY AIR POLLUTION TRACKER

The world as it stride towards modernization also creates some serious effects to the environment. The pollution was becoming one of the major challenges for human lives. One such pollution is air pollution that leads human beings to “inhale polluted oxygen” that leads to serious effects like Asthma, Pneumonia, Influenza, Cancer etc. The government and social welfare organization are highly challenged in locating the hotspot location of air pollution. To provide solution for this, we propose a model to locate the polluted area exactly. This can be achieved by employing GIS mapping (maptitude) software that indicating the pollution level using color indicator.
Robot Vision Servo Control and Calibration of the Camera System

This project presents a camera calibration method and a novel visual servo control scheme. The camera calibration method takes into account the lens distortion and can reach the reconstruction errors of about 0.2 mm. We propose a criterion to measure the performance of the depth estimation. which turns out to be a control objective function. The proposed visual servo control scheme has good performance in both the depth estimation and the visual control.
Efficacy of a Community Health Worker–Based Intervention in Improving Dietary Habits Among Community-Dwelling Older People: A Controlled, Crossover Trial in Japan

Background. Community health workers (CHWs), often called “health promotion volunteers” in Japan, are individuals who act as a natural helping resource in the community. Aim. This study tested the efficacy of a CHW-based intervention to improve dietary habits among community-dwelling older people in Japan, using a controlled, crossover design. Method. Seventy-eight people aged 65 to 74 years with poor dietary variety living in four administrative districts in Hikone City (Shiga Prefecture, Japan) were nonrandomly allocated to an immediate-intervened group (IIG; n = 41) or a delayed-intervened group (DIG; n = 37). Participants joined a biweekly, four-session program (120 minutes/session), comprising “CHW drama-style lectures,” “group discussion among participants and CHWs,” “tasting of dishes,” and “take-home practical activities. ” For the initial 2-month period, the IIG received the intervention and the DIG did not. The groups were crossed over for the subsequent 2-month period. The primary outcome measure was participants’ dietary variety score (score range: 0-10). Results. The dietary variety score in the IIG significantly increased in the initial 2-month period compared with the DIG (effect size 1.60 points; 95% confidence interval: 0.75, 2.45). The intervention had a similar effect in the DIG in the subsequent 2-month period. Moreover, an analysis within the IIG showed that the intervention effects persisted for at least 2 months after the intervention. Conclusions. The CHW-based intervention improved dietary habits among older people. Our findings provide evidence that a CHW-based natural helping approach is a possible solution to promote healthy aging in the community.
Dysregulated lncRNA-miRNA-mRNA Network Reveals Patient Survival-Associated Modules and RNA Binding Proteins in Invasive Breast Carcinoma

Breast cancer is the most common cancer in women, but few biomarkers are effective in clinic. Previous studies have shown the important roles of non-coding RNAs in diagnosis, prognosis, and therapy selection for breast cancer and have suggested the significance of integrating molecules at different levels to interpret the mechanism of breast cancer. Here, we collected transcriptome data including long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA for ~1,200 samples, including 1079 invasive breast carcinoma samples and 104 normal samples, from The Cancer Genome Atlas (TCGA) project. We identified differentially expressed lncRNAs, miRNAs, and mRNAs that distinguished invasive carcinoma samples from normal samples. We further constructed an integrated dysregulated network consisting of differentially expressed lncRNAs, miRNAs, and mRNAs and found housekeeping and cancer-related functions. Moreover, 58 RNA binding proteins (RBPs) involved in biological processes that are essential to maintain cell survival were found in the dysregulated network, and 10 were correlated with overall survival. In addition, we identified two modules that stratify patients into high- and low-risk subgroups. The expression patterns of these two modules were significantly different in invasive carcinoma versus normal samples, and some molecules were high-confidence biomarkers of breast cancer. Together, these data demonstrated an important clinical application for improving outcome prediction for invasive breast cancers.
Differential Expression of the Metabotropic P2Y Receptor Family in the Cortex Following Status Epilepticus and Neuroprotection via P2Y1 Antagonism in Mice

Purinergic signaling via P2 receptors is now widely accepted to play a critical role during increased states of hyperexcitability and seizure-induced pathology. In the setting of seizures and epilepsy, most attention has been paid to investigating the fast-acting ATP-gated P2X receptor family. More recent evidence has now also provided compelling evidence of an involvement of the slower-acting P2Y receptor family during seizures. This includes data demonstrating expression changes of P2Y receptors in the hippocampus following acute seizures and during epilepsy and anticonvulsive properties of P2Y-targeting drugs; in particular drugs targeting the P2Y1 subtype. Seizures, however, also involve damage to extra-hippocampal brain regions such as the cortex, which is thought to contribute to the epileptic phenotype. To analyze expressional changes of the P2Y receptor family in the cortex following status epilepticus and to determine the impact of drugs interfering with P2Y1 signaling on cortical damage, we used a unilateral mouse model of intraamygdala kainic acid-induced status epilepticus. Analysis of cortical tissue showed that status epilepticus leads to a global up-regulation of the P2Y receptor family in the cortex including P2Y1, P2Y2, P2Y4, and P2Y6, with the P2Y1 and P2Y4 receptor subtypes showing the strongest increase. Supporting a detrimental role of P2Y1 activation during status epilepticus, treatment with the P2Y1 agonist MRS2365 exacerbated high frequency high amplitude spiking, synonymous with injury-causing electrographic activity, and treatment with the P2Y1 antagonists MRS2500 protected against seizure-induced cortical damage. Suggesting P2Y1-mediated effects are predominantly due to increased microglia activation, treatment with the broad-spectrum anti-inflammatory drug minocycline abolished the observed neuroprotective effects of P2Y1 antagonism. In conclusion, our results further support a role for P2Y1-mediated signaling during seizure generation and seizure-induced neurodegeneration, suggesting P2Y1-targeting therapies as novel treatment for drug-refractory status epilepticus.
A Deep Learning Approach to Predict Abdominal Aortic Aneurysm Expansion Using Longitudinal Data

An abdominal aortic aneurysm (AAA) is a gradual enlargement of the aorta that can cause a life-threatening event when a rupture occurs. Aneurysmal geometry has been proved to be a critical factor in determining when to surgically treat AAAs, but, it is challenging to predict the patient-specific evolution of an AAA with biomechanical or statistical models. The recent success of deep learning in biomedical engineering shows promise for predictive medicine. However, a deep learning model requires a large dataset, which limits its application to the prediction of the patient-specific AAA expansion. In order to cope with the limited medical follow-up dataset of AAAs, a novel technique combining a physical computational model with a deep learning model is introduced to predict the evolution of AAAs. First, a vascular Growth and Remodeling (G&R) computational model, which is able to capture the variations of actual patient AAA geometries, is employed to generate a limited in silico dataset. Second, the Probabilistic Collocation Method (PCM) is employed to reproduce a large in silico dataset by approximating the G&R simulation outputs. A Deep Belief Network (DBN) is then trained to provide fast predictions of patient-specific AAA expansion, using both in silico data and patients' follow-up data. Follow-up Computer Tomography (CT) scan images from 20 patients are employed to demonstrate the effectiveness and the feasibility of the proposed model. The test results show that the DBN is able to predict the enlargements of AAAs with an average relative error of 3.1%, which outperforms the classical mixed-effect model by 65%.
DETERMINANT FACTORS AFFECTING WOMEN SOCIAL ENTERPRISE PERFORMANCES IN SOKOTO STATE, NIGERIA: A PILOT STUDY

There has been enormous research on factors influencing women social enterprise around the globe. Up to date there is scarcity of such study that aim to address issues related to performance of women social enterprise in Sokoto state, Nigeria. Hence this study aim to present the outcome of the pilot study conducted in Sokoto on research focusing on the performance of women social enterprise development in the state. Research Variables were adopted based on relevant literature in the related area of research and subjected to pilot study. The pilot study was necessary to ensure clarity, readability, face validity as well as reliability of the adopted variables and items under the variables. It is concluded that the variables adopted for the research have good internal consistencies
Evaluating the Impact of Performance-Based Financing in Healthcare Provision: A Case Study in Uganda

We estimate the effect of introducing performance-based financing on the allocative efficiency and quality of healthcare provision. We use a unique panel of output and expenditure data from small private not-for-profit healthcare facilities in Uganda in combination with a patient satisfaction survey focused on the perceived quality of healthcare. In the observed facilities, performance-based financing increases output and allocative efficiency by more than 25% with no apparent reduction in quality. The result is robust to more traditional estimation techniques.
Women’s response to the question of development in the Niger Delta, Nigeria

Women are the champions for peace in any society because women are always at the receiving end of any out-break of disasters, especially war. Women lose virtually everything from property to life. Women have also been known to challenge repressive governments. Women, throughout history have led various social movements that brought change to the society. This paper examines the roles played by women to address exploitation in Nigeria’s Niger Delta. It also examines the modus operandi of women to address the question of under-development in the area. Social Exchange Theory is employed in this paper to explain the reason why women engage in protests in order to redress injustice in the Niger Delta. Qualitative method of In-depth Interviews was employed to collect data from women’s organizations in the randomly selected oil-producing States in the Niger Delta. The paper main finding is that women have been drastically affected by the activities of oil companies in the area. Also, the restiveness among women was found to be caused by injustice, neglect, deprivation, and unequal distribution of resources. The paper, therefore, recommends the creation of a special account to finance women development projects. And also, women rights must not only be recognized by government and oil companies, but must be upheld and respected.
Temporal and Spatial Autocorrelations from Expendable Digital Dropsondes (XDDs) in Tropical Cyclones

The newly developed Expendable Digital Dropsondes (XDDs) allow for high spatial and temporal resolution observations of the kinematic and thermodynamic structures in tropical cyclones (TCs). It is important to evaluate both the temporal and spatial autocorrelations within the recorded data to address concerns about spatial interpolation, statistical significance of individual data points, and launch-rate spatial requirements for future dropsonde studies in TCs. Data from 437 XDDs launched into Hurricanes Marty (27–28 September), Joaquin (2–5 October), and Patricia (20–23 October) during the 2015 Tropical Cyclone Intensity (TCI) experiment are used to compute temporal and spatial autocorrelations for vertical velocity, temperature, horizontal wind speed, and equivalent potential temperature. All of the examined variables had temporal autocorrelation scales between approximately 10 and 40 s, with most between 20 and 30 s. Most of the spatial autocorrelation scales were estimated to be 3–10 km. The temporal autocorrelation scales for vertical velocity, horizontal wind speed, and equivalent potential temperature were correlated with updraft depth. Vertical velocity usually had the smallest mean, and median, temporal and estimated spatial autocorrelation scales of approximately 20 s and 3–6 km, respectively. The estimated horizontal scales are below the median sounding spacing and suggest that an increase in the launch rate of the XDDs by a factor of 3–4 from the TCI sampling rate is needed to adequately depict TC kinematics and structure in transects of soundings. The results also indicate that current temporal sampling rates are adequate to depict TC kinematics and structure in a single sounding.
By Example of a European Map of Cultural Heritage

As GISystems become more mature and spatial research questions more complex, time is regarded as a crucial component to GIS data models. Cartographic visualization can be one useful method of presenting dynamic spatial data and visualizing changes over time, hence assisting the study of spatio-temporal patterns and phenomena. The rise of interactive mapping applications, together with the growing demand to incorporate time in GIS, however, fuel the need for efficient navigation tools in space, time and topic. This paper summarizes the current results of an ongoing PhD work that contributes in the following areas: Study of the effects that changes in one of the dimensions should trigger on the navigation and visualization of the dependent dimensions, compilation of a taxonomy of spatiotemporal and thematic questions, in order to understand how navigation tools can assist in answering these questions and development of a sophisticated user interface for thematic navigation in space and time by creating a prototype of a european map of cultural heritage.
FIRE AND BIRDS IN THE SOUTHWESTERN UNITED STATES

Fire is an important ecological force in many southwestern ecosystems, but frequencies, sizes, and intensities of fi re have been altered historically by grazing, logging, exotic vegetation, and suppression. Prescribed burning should be applied widely, but under experimental conditions that facilitate studying its impacts on birds and other components of biodiversity. Exceptions are Sonoran, Mojave, and Chihuahuan desert scrub, and riparian woodlands, where the increased fuel loads caused by invasions of exotic grasses and trees have increased the frequency and intensity of wildfi res that now are generally destructive to native vegetation. Fire once played a critical role in maintaining a balance between herbaceous and woody vegetation in desert grasslands, and in providing a short-term stimulus to forb and seed production. A 3–5 yr fi re-return interval likely will sustain most desert grassland birds, but large areas should remain unburned to serve species dependent upon woody vegetation. Understory fi re once maintained relatively open oak savanna, pinyonjuniper, pine-oak, ponderosa pine (Pinus ponderosa), and low elevation mixed-conifer forests and their bird assemblages, but current fuel conditions are more likely to result in stand-replacement fi res outside the range of natural variation. Prescribed burning, thinning, and grazing management will be needed to return fi re to its prehistoric role in these habitats. Fire also should be applied in high elevation mixed-conifer forests, especially to increase aspen stands that are important for many birds, but this will be an especially diffi cult challenge in an ecosystem where stand-replacement fi res are natural events. Overall, surprisingly little is known about avian responses to southwestern fi res, except as can be inferred from fi re effects on vegetation. We call for cooperation between managers and researchers to replicate burns in appropriate habitats that will permit rigorous study of community and population-demographic responses of breeding, migrating, and wintering birds. This research is critical and urgent, given the present threat to many southwestern ecosystems from destructive wildfi res, and the need to develop fi re management strategies that not only reduce risk but also sustain bird populations and other components of southwestern biological diversity.
Federal Information Processing Standards Publication: guideline for the use of advanced authentication technology alternatives

This Guideline describes the primary alternative methods for verifying the identities of computer system users, and provides recommendations to Federal agencies and departments for the acquisition and use of technology which supports these methods. Although the traditional approach to authentication relies primarily on passwords, it is clear that password-only authentication often fails to provide an adequate level of protec¬ tion. Stronger authentication techniques become increasingly more important as informa¬ tion processing evolves toward an open systems environment. Modern technology has produced authentication tokens and biometric devices which are reliable, practical, and cost-effective. Passwords, tokens, and biometrics can be used in various combinations to provide far greater assurance in the authentication process than can be attained with
Optimizing Acceleration-based Activity Models with User’s Physical Characteristics Information

In the activity recognition task using bodyworn accelerometers, we can construct an activity recognition model with placing small burdens on an end user by employing the crowdsourcing approach, i.e., obtaining training data from numerous numbers of other users. However, the training data are noisy and decrease recognition accuracy for the end user’s training data. In this study, we attempt to find training data from other users that decrease the recognition accuracy with user’s physical characteristics information to train an activity model adapted to the end user.
Organisational Learning with SaaS CRM - A case study of Higher Education

Customer Relationship Management (CRM) generally has a reputation as a technology that does not live up to its over-inflated expectations. Yet, implementations in higher education remain on the rise. Higher Education institutions (HEIs) are embracing cloud-based CRM systems to upsurge performance, encourage better management practices, and enhance their relationship with staff and students. CRM success however relies heavily on an adaptive organisational learning (OL) process upon which proactive decisions can be made. This paper emphasises that committed learning in post-implementation use is paramount to attaining further understanding of the capabilities, features and functionality of the CRM. Investigating how SaaS CRM usage reflect an organisation’s learning in a Higher Education context, the paper presents theoretical and practical contributions in a framework for effective SaaS CRM utilisation, and recommends a continuous cycle of exploration-exploitation-exploration. Yet the reality is that organisations explore, exploit, and then stop exploring.