Miracle-dz/UniFAR-FTUs huggingface dataset:
Antenna selection in MIMO radar with collocated antennas

: An antenna adjustment strategy is developed for the target tracking problem in the collocated multiple-input multiple-output (MIMO) radar. The basic technique of this strategy is to optimally allocate antennas by the prior information in the tracking recursive period, with the objective of enhancing the worst-case estimate precision of multiple targets. On account of the posterior Cramer-Rao lower bound (PCRLB) offering a quantitative measure for target tracking accuracy, the PCRLB of joint direction-of-arrival (DOA) and Doppler is derived and utilized as the optimization criterion. It is shown that the dynamic antenna selection problem is NP-hard, and an ef ﬁ cient technique which combines convex relaxation with local search is put forward as the solution. Simulation results demonstrate the outperformance of the proposed strategy to the ﬁ xed antenna con ﬁ guration and heuristic search algorithm. Moreover, it is able to offer close-to performance of the exhaustive search method.
Life Satisfaction Among Home-Dwelling Older People Who Have Experienced Falls and Have Declined Subjective Health

ABSTRACT This study investigated the reported life situations of home-dwelling older people who have experienced falls and have declined subjective health. Mixed method design was used and consisted of a quantitative study comprising questionnaires completed by 434 home-dwelling older people, and a qualitative study consisting of 30 interviews. The findings showed that declined physical function combined with limited health status was associated with falling. Despite limited physical condition, participants experienced well-being and life satisfaction in daily living. Insight obtained from these findings deepens our understanding of fallers and may provide a basis for future research leading to improvements within health care.
AIRBORNE LIDAR POINT CLOUD CLASSIFICATION BASED ON MULTILEVEL POINT CLUSTER FEATURES

Abstract. Airborne Light Detection And Ranging (LiDAR) has become an important means for efficient and high-precision acquisition of 3D spatial data of large scenes. It has important application value in digital cities and location-based services. The classification and identification of point cloud is the basis of its application, and it is also a hot and difficult problem in the field of geographic information science.The difficulty of LiDAR point cloud classification in large-scale urban scenes is: On the one hand, the urban scene LiDAR point cloud contains rich and complex features, many types of features, different shapes, complex structures, and mutual occlusion, resulting in large data loss; On the other hand, the LiDAR scanner is far away from the urban features, and is like a car, a pedestrian, etc., which is in motion during the scanning process, which causes a certain degree of data noise of the point cloud and uneven density of the point cloud.Aiming at the characteristics of LiDAR point cloud in urban scene.The main work of this paper implements a method based on the saliency dictionary and Latent Dirichlet Allocation (LDA) model for LiDAR point cloud classification. The method uses the tag information of the training data and the tag source of each dictionary item to construct a significant dictionary learning model in sparse coding to expresses the feature of the point set more accurately.And it also uses the multi-path AdaBoost classifier to perform the features of the multi-level point set. The classification of point clouds is realized based on the supervised method. The experimental results show that the feature set extracted by the method combined with the multi-path classifier can significantly improve the cloud classification accuracy of complex city market attractions.
Assessing the Effects of Rural Electrification on Household Welfare in Nigeria

A rural electrification (RE) strategy was adjudged as a means of extending electricity to unserved and underserved communities to bring about rural transformation and development. This study investigates the effect of Oyo State RE on household welfare indicators such as monthly income and per capita expenditure. Household survey data collected from the Nigerian Institute of Social And Economic Research (NISER) 2017 field survey were employed. Access to grid electricity increases household income by about 1.3 per cent. Although the coefficient was correctly signed, it was not significant. This outcome could be a result of constant electricity supply outages, which is strongly explained by the positive affirmation of 71 per cent of the respondents. Access to grid electricity increases household per capita monthly expenditure by about 6.4 per cent. Expenditure on electricity equally increases monthly per capita expenditure by about 4 per cent and is statistically significant at 1 per cent. Due to rapid decline in the cost of technology, mini-grid and off-grid systems have become viable options for extending electricity access that is more reliable, and hence has more economic benefits. JEL Classification: I31
The new FIGO staging system for ovarian, fallopian tube and primary peritoneal cancer — 2014 update

Goals of each cancer staging system are similar: it should give evidence about the prognosis of the patient, assist the clinician to plan appropriate treatment, allow for evaluation and comparison of treatment results in different centers and finally contribute to a deeper recognition of malignancy nature. The classification system should also meet three criteria: it should be credible, evidence-based and applicable in clinical practice. During recent years paramount changes have occurred in the pathogenesis of ovarian cancer and recent clinical studies have identified new prognostic factors. Therefore the last change in the classification of ovarian tumors in women was made at the beginning of 2014 and for the first time there were also included fallopian tube and primary peritoneal cancers. The main changes in the updated classification of cancer of the ovary, fallopian tube and the peritoneum are based on dividing the stage IC into three groups including surgical damage to the capsule of the tumor, tumor capsule rupture before the operation and the presence of malignant cells in the peritoneal fluid. Stage IIC has been omit ted. It was also considered that the presence of metastases limited to lymph nodes is a factor of better prognosis than peritoneal metastases and therefore this situation was distinguished as the stage IIIA1. Two subgroups were created on the basis of the morphology of lymph node metastases. Microscopic peritoneal metastasis outside the pelvis were staged as IIIA2. The new classification of stage IV was divided into two subgroups; IVA is defined as the presence of histologically or cytologically proven pleural involvment and IVB includs metastases to spleen or liver parenchyma as well as metastases outside the abdominal cavity.
Molecular Identification and Morphological Characteristics of the Longjaw Bonefish, Albula argentea Collected in Korea

One specimen of Albula argentea (296.3 mm in standard length), belonging to the family Albulidae, was collected in a set net in the coastal waters of Jejudo Island, Korea. As the adult A. argentea has not been caught from Korean waters, we described its morphological characters based on the collected specimen and compared them with those of the previous reports on A. argentea and A. koreaus. As a result, the present specimen was characterized by having 68~73 pored lateral line scales (vs. 77~78 for A. koreana), 72~73 vertebrae pored lateral line scales (vs. 77~80) and none streak on the check (vs. yellowish streak). Molecular analysis using the mitochondrial cytochrome b DNA sequences was also conducted to confirm the correctness of species identification and taxonomic status of the sample.
Fast online model learning for controlling complex real-world robots

FAST ONLINE MODEL LEARNING FOR CONTROLLING COMPLEX REAL-WORLD ROBOTS Pontus Loviken How can real robots with many degrees of freedom without previous knowledge of themselves or their environment act and use the resulting observations to efficiently develop the ability to generate a wide set of useful behaviours? This thesis presents a novel framework that enables physical robots with many degrees of freedom to rapidly learn models for control from scratch. This can be done in previously inaccessible problem domains characterised by a lack of direct mappings from motor actions to outcomes, as well as state and action spaces too large for the full forward dynamics to be learned and used explicitly. The proposed framework is able to cope with these issues by the use of a set of local Goal Babbling models, that maps every outcome in a low dimensional task space to a specific action, together with a sparse higher level Reinforcement Learning model, that learns to navigate between the contexts from which each Goal Babbling model can be used. The two types of models can then be learned online an in parallel, using only the data a robot can collect by interacting with its environment. To show the potential of the approach we present two possible implementations of the framework, over two separate robot platforms: a simulated planar arm with up to 1,000 degrees of freedom, and a real humanoid robot with 25 degrees of freedom. The results show that learning is rapid and essentially unaffected by the number of degrees of freedom of the robot, allowing for the generation of complex behaviours and skills after a relatively short training time. The planar arm is able to strategically plan series of motions in order to move its end-effector between any two parts of a crowded environment, within 10,000 iterations. The humanoid robot is able to freely transition between states such as lying on the back, belly, and sides, and occasionally also sitting up, within only 1,000 iterations. This corresponds to 30−60 minutes of real-world interactions. The main contribution of this thesis is to provide a framework for solving a control learning problem, previously largely unexplored with no obvious solutions, but with strong analogies to, for example, early learning of body orientation control in infants. This thesis examined two quite different implementations of the proposed framework, and showed success in both cases for two different control learning problem.
The Researches Detection Method of Illegal Parking Based on Convolutional Neural Network

Violation of parking is a legal term. Our country's law stipulates that there should be no-stop signs and markings, road sections with isolation facilities between motor vehicles and non-motor vehicle lanes and sidewalks, and crosswalks and construction sites. No parking; Railway crossings, sharp bends, narrow roads with widths less than 4 meters, bridges, steep slopes, tunnels, and sections within 50 meters of the above locations are not allowed to stop. In recent years, urban management is gradually developing towards information There are corresponding treatment mechanisms for illegal parking in urban management, but the method of detecting illegal parking based on machine vision is still under study. This paper takes a street in Hebei Province as the research object, and studies the illegal parking under the surveillance image. It also proposes to use the machine vision-based method to automatically detect the illegal parking. In the monitoring image, according to the street view image information detected by the computer, A status assessment of the vehicle placement can be achieved. The detection algorithm in this paper uses the multi-angle suggestion area to accurately locate the offending vehicles in the image and mark them on the detected vehicles. The experimental data shows that the algorithm has good adaptability to the detection of illegal parking in surveillance images, and effectively improves the inspection efficiency.
AZD2281 (KU-0059436), a PARP (poly ADP-ribose polymerase) inhibitor with single agent anticancer activity in patients with BRCA deficient ovarian cancer: Results from a phase I study

5510 Background: AZD2281 is a novel, potent orally active PARP inhibitor. It induces cancer specific synthetic lethality in homologous recombination repair defective cells, including BRCA-deficient tumors. We previously reported a first-in-human Phase I trial, with dose escalation guided by toxicity, pharmacokinetic and pharmacodynamic (PD) data (Yap et al, ASCO 2007 Abstr 3529). Method: Initial dose escalation phase included patients (p) with a wide range of drug-resistant cancers. Once a PD active dose was identified, enrichment of the population with p with BRCA-deficient tumors was encouraged. Doses started from 10mg daily for 2 of 3 weeks, escalating to 600mg bd continuously. After the maximum tolerated dose (400mg bd) was identified, an expansion phase in BRCA-deficient ovarian cancer (BDOC) at 200mg bd was opened. Results: Of the total 92 p treated, 44 p had BDOC (includes 1 p with compelling family history). Doses received were 40mg daily (1 p), 100mg bd (3 p), 200mg bd (34 p), 400mg bd (5 p) and .
Reassembling Electronic Patient Records after the National Programme for IT : contested visions and multiple enactments

This thesis is concerned with understanding how Electronic Patient Record systems (EPRs) are being problematised and enacted in NHS acute hospital Trusts following the dismantling of the National Programme for IT (NPfIT). The term EPR is widely used but has no uniform definition and has been applied to a wide range of systems. In policy, EPRs have often been envisaged as integrated, large-scale systems capable of transforming how healthcare is delivered. However, in practice such systems have proved difficult to achieve and many of the EPRs to be found in hospitals are much smaller standalone specialist departmental systems. Working with Actor-Network Theory (ANT), this thesis takes a sociotechnical approach in which differences in EPRs are understood as matters of ontology (variations in their enactment by multiple heterogeneous actors producing multiple, sometimes conflicting, realities) rather than matters of epistemology (differences in the interpretation of a single underlying reality).
Phytochemical Screening and Cytotoxicity Evaluation of Ethanolic Extract of Hypericum cordifolium (choisy) Leaves

Hypericum cordifolium is a medicinal plant traditionally used for the treatment of the menstrual disorder, backache, dislocation of bone, fever, diarrhea and dysentery due to the presence of potential bioactive secondary metabolites. Ethanolic extract of dried leaf powder was prepared using the Soxhlet apparatus, followed by qualitative phytochemical screening with different reagents. In-vitro cytotoxicity assay was screened by using brine shrimp bioassay and LC50 was calculated by probit analysis. Alkaloids, glycosides, amino acids, and fixed oils were present at very minute level whereas saponin, phenol and flavonoids were present at significant level. Cytotoxicity assay of the leaf extract showed significant results (p<0.05). LC50 of 273 ppm, which was less than 1000 ppm, showing that the plant is toxic. The study revealed that the plant possessed medicinal values, which could justify the ethno-medicinal importance scientifically. This research has pointed out further possibilities of works to be done on this virgin plant creating the opportunity for scientific researches to give birth of potent lead molecules.
A struggle for definition: online narratives of Italian trans women

ABSTRACT In recent years, literature in the field of trans studies suggested that there has been a widespread trend in academic debates about gender transitivity to produce monolithic conceptualizations of transness unable to account for the different gender experiences of trans individuals. This paper aims to provide a further contribution to debates in this area through an empirical investigation of trans narratives of identity and embodiment. Drawing on queer and transfeminist scholarship which framed social media as offering trans people a site for the re-negotiation of the meanings attached to gender transitivity, we conducted an abductive thematic qualitative analysis of 37 blog posts written by 10 Italian trans women concerning their experience of transness. Our findings suggest that in these posts, the bloggers realized a complex bricolage of scientific language, autobiographical storytelling and political statements which produced distinct narratives of gender transitivity. In particular, these accounts of transness diverge across different trajectories related to the negotiation of the medical discourse of gender diversity, to the articulation of the body as a site of empowerment and to how the bloggers defined which experiences of gender diversity should be included in the trans umbrella.
An Efficient NVoD Scheme Using Implicit Error Correction and Subchannels for Wireless Networks

Implicit Error Correction (IEC) is a near Video-on-Demand (nVoD) scheme that trades bandwidth utilization for initial playback delay to potentially support an infinite number of users. Additionally, it provides error protection without any further bandwidth increase by exploiting the implicit redundancy of nVoD protocols, using linear combinations of the segments transmitted in a given time slot. However, IEC packet loss protection is weaker at the beginning of the playback due to the lack of implicit redundancy and lower decoding efficiency, resulting in worse subjective playback quality. In tackling this issue, this paper contributes with an extension of the original nVoD architecture, enhancing its performance by adding a new element namely, subchannels. These subdivisions of the original channels do not provide further packet loss protection but significantly improve the decoding efficiency, which in turn increases playback quality, especially at the beginning. Even for very high packet loss probabilities, subchannels are designed to obtain higher decoding efficiency which results in greater packet loss protection than that provided by IEC. The proposed scheme is especially useful in wireless cooperative networks using techniques such as network coding, as content transmissions can be split into different subchannels in order to maximize network efficiency.
Daily Life, Communication and Affections of Siblings and Parents of Military Service Members in Mission

Abstract The Portuguese military in mission state that parents and siblings are a fundamental support; however, research is very scarce in this area. This study aimed to investigate the impact of a mission on the daily life, communication and emotional responses of 227 relatives of 92 military personnel, 114 siblings (M age = 29.14, SD = 9.81) e 113 parents (M age = 55.06, SD = 9.12). A questionnaire related to the mission was applied, focusing on changes in the daily life, social support, communication and advice to other family members; and the Positive and Negative Affect Schedule since receiving notification. The results revealed that the parents suffered more with the notification and that there were changes in family functioning and in the functional support. Communication with the deployed military service member strengthens family relationships, morale, and well-being. Participants reported emotions of concern and pride, and gave advice based on a positive attitude toward the military and the mission.
Optimization model and algorithm of logistics distribution path based on urban road network time-varying

In the urban road network, the speed of different sections is different; In the same road section, the speed is different at different times. Therefore, on the basis of considering the temporal variability of the road network, this paper takes the shortest delivery time as the optimization objective to find the optimal logistics distribution path between the urban logistics distribution nodes in different time periods. Based on this, an urban logistics distribution path optimization model with the shortest delivery time as the optimization objective is established. In order to improve the solution quality and efficiency of the model, the time impedance matrix of urban logistics distribution network was constructed and an improved distance matrix algorithm was designed to solve the model. Finally, an example is given to verify the effectiveness of the model and algorithm.
The Effect of Konjac Glucomannan Fibre Gel on Satiety and Energy Intake

Konjac glucomannan (KGM) is a viscous dietary fibre that forms a firm, low-energy gel (KGMgel) with shapes resembling common food staples. Despite a history of use in Asia, no study to date as assessed the effect of replacing energy-dense foods with KGM-gel foods. Therefore, we conducted two acute, randomized, controlled, crossover trials in healthy individuals to assess KGM-gel food substitution at a moderate and high level in single and repeated meals on appetite and energy intake. In both studies, KGM-gel substitution proportionally reduced the energy content of test meals compared to control. While high substitution lowered satiety, moderate substitution did not reduce satiety and cumulative energy intake was inversely proportional KGM-gel substitution. KGM-gel foods may assist in reducing energy intake without increasing appetite when replacing a modest amount of energy-rich foods. These results may have relevance in weight loss regimes and should be evaluated in overweight or obese populations.
Penalized proportion estimation for non parametric mixture of regressions

Abstract In this article, we propose a penalized local log-likelihood method to locally select the number of components in non parametric finite mixture of regression models via proportion shrinkage method. Mean functions and variance functions are estimated simultaneously. We show that the number of components can be estimated consistently, and further establish asymptotic normality of functional estimates. We use a modified EM algorithm to estimate the unknown functions. Simulations are conducted to demonstrate the performance of the proposed method. We illustrate our method via an empirical analysis of the housing price index data of United States.
Dynamic Electromagnetic Positioning System for Accurate Close-Range Navigation of Multirotor UAVs

An accurate close-range positioning and navigation system is the key to autonomous cruise and the fine operations of multi-rotor UAVs. In this paper, a dynamic electromagnetic positioning system is designed and implemented to accurately navigate a UAV to a very small landing zone. The system is composed of three quasi-static electromagnetic field generators (EGs) installed around the landing zone, and one electromagnetic field sensor (ES) mounted on the UAV. The ES adaptively controls its gain and adjusts the power of the EGs, so it can detect electromagnetic signals under a high SNR (signal-to-noise ratio) condition and has an anti-saturation ability. Consequently, the coordinate and azimuthal angle of the UAV can be measured during the process of the UAV approaching the landing zone. Hardware experiments demonstrate that the prototype system can effectively navigate a UAV to a small landing zone that is slightly larger than the size of the UAV, and the terminal positioning error is less than 2 cm.