Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast antenna subset selection in MIMO systems

Multiple antenna wireless communication systems have recently attracted significant attention due to their higher capacity and better immunity to fading as compared to systems that employ a single-sensor transceiver. Increasing the number of transmit and receive antennas enables to improve system performance at the price of higher hardware costs and computational burden. For systems with a large number of antennas, there is a strong motivation to develop techniques with reduced hardware and computational costs. An efficient approach to achieve this goal is the optimal antenna subset selection. In this paper, we propose a fast antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Our algorithm achieves almost the same outage capacity as the optimal selection technique while having lower computational complexity than the existing nearly optimal antenna selection methods. The optimality of the proposed technique is established in several important specific cases. A QR decomposition-based interpretation of our algorithm is provided that sheds a new light on the optimal antenna selection problem.
Wearable sensors for gait analysis Comparison between a MIMUs system and a gold standard electromechanical system

Systems based on inertial sensors are increasingly used in motion analysis due to their low cost, portability and wearability. However, since accuracy is crucial in clinical gait analysis, it is important to assess it in new systems. The aim of this study is to compare the performances of a magnetic and inertial sensors system (MIMUs) to a gold standard, the electromechanical system STEP32. Results shows that spatio-temporal parameters are accurately estimated by the MIMUs system. Joint kinematics does not reach the accuracy of the STEP32 system. In fact, although MIMUs measurements on the knee and hip joints are clinically acceptable, they are not yet reliable for the ankle joint. Keywords—gait analysis; gait parameters; IMUs; joint kinematics; spatio-temporal parameters.
Long-term MRI tracking of dual-labeled adipose-derived stem cells homing into mouse carotid artery injury

Background Stem cell therapy has shown great promise for regenerative repair of injured or diseased tissues. Adipose-derived stem cells (ADSCs) have become increasingly attractive candidates for cellular therapy. Magnetic resonance imaging has been proven to be effective in tracking magnetic-labeled cells and evaluating their clinical relevance after cell transplantation. This study investigated the feasibility of imaging green fluorescent protein-expressing ADSCs (GFP-ADSCs) labeled with superparamagnetic iron oxide particles, and tracked them in vivo with noninvasive magnetic resonance imaging after cell transplantation in a model of mouse carotid artery injury. Methods GFP-ADSCs were isolated from the adipose tissues of GFP mice and labeled with superparamagnetic iron oxide particles. Intracellular stability, proliferation, and viability of the labeled cells were evaluated in vitro. Next, the cells were transplanted into a mouse carotid artery injury model. Clinical 3 T magnetic resonance imaging was performed immediately before and 1, 3, 7, 14, 21, and 30 days after cell transplantation. Prussian blue staining and histological analysis were performed 7 and 30 days after transplantation. Results GFP-ADSCs were found to be efficiently labeled with superparamagnetic iron oxide particles, with no effect on viability and proliferation. Homing of the labeled cells into the injured carotid artery tissue could be monitored by magnetic resonance imaging. Conclusion Magnetically labeled ADSCs with expression of GFP can home into sites of vascular injury, and may provide new insights into understanding of cell-based therapy for cardiovascular lesions.
Changes in bone turnover in patients with anorexia nervosa during eleven weeks of inpatient dietary treatment.

BACKGROUND Many adolescents with anorexia nervosa suffer from severe osteopenia and osteoporosis. We hypothesized that individualized nutrition therapy may improve bone turnover in anorectic patients. METHODS We studied 19 female patients [mean age, 14.2 +/- 1.4 years; mean body weight, 39.3 +/- 5.4 kg; mean body mass index (BMI), 14.2 +/- 1.4 kg/m(2)] with anorexia nervosa (International Classification of Diseases-10: F50.0, F50.1) for a period of 3 months. Nutrition therapy began at the end of the first week and included individualized hypercaloric diets, high calcium intake (2000 mg/day), and administration of vitamin D (400 IU/day). Blood samples were taken at baseline and again in weeks 3, 7, and 11. We measured serum calcium, parathyroid hormone, bone formation and resorption markers, insulin-like growth factor 1 (IGF-1), and leptin. RESULTS Mean BMI increased significantly, from 14.2 +/- 1.4 to 17.1 +/- 0.7 kg/m(2) (P = 0.000001), during the course of treatment, whereas serum total calcium and phosphate concentrations remained unchanged. The bone formation markers procollagen-I carboxy-terminal propeptide and bone alkaline phosphatase almost doubled (P = 0.006). Both IGF-1 (P = 0.00001) and leptin (P = 0.000005) increased significantly by week 11. Parallel to this, the serum concentration of C-telopeptide, a bone resorption marker, decreased significantly (P = 0.009). CONCLUSIONS Nutritional rehabilitation, possibly as a result of increasing IGF-1 and leptin concentrations, may increase bone formation. It therefore provides additional objective evidence of the importance of nutrition for bone.
Structural cell-based VLSI circuit design using a genetic algorithm

A technique for the structural synthesis of VLSI circuits is presented. The technique uses a Genetic Algorithm which utilises a library of devices for the synthesis procedure which proved successful in searching a highly complex space of structures by producing designs which satisfy a multiple output circuit criteria which, in addition to satisfying the functionality constraint for each of the outputs, also satisfy hardware-specific criteria such as area and delay.
Work in progress: MiceNet: Monitoring behaviour of laboratory mice with sensor networks

Medical research uses laboratory mice for experimental studies. Currently, symptoms are manually observed and recorded, resulting in noisy data — requiring many animals to obtain statistically significant results. We propose the use of a camera sensor network attached to mice cages as a low-cost solution for continuously monitoring mouse behavior and providing remote access to the data for scientists. The benefits of this approach are discussed along with challenges encountered in the initial phases of deployment. The proposed hardware and software architecture is described and early experimentation results are presented.
Load-Balanced Trees for Data Collection in Wireless Sensor Networks

In static wireless sensor networks, it is an important research issue to achieve effectively periodic data collection and prolong the network lifetime. In this paper, a distributed k-load-balanced tree scheme is proposed to prolong the network lifetime for periodic data collection. A k-load-balanced tree is a tree that the difference of the number of children of each two non-leaf nodes in a network is less than k. Each node chooses the node with the least current number of children and number of neighbor as parent for avoiding that the difference of the number of children of each two non-leaf nodes in a network is more than k. The simulation results show that our scheme can prolong the network lifetime and the network delay time is close to the result of centralized method.
COMBINED EFFECTS OF GALAXY INTERACTIONS AND LARGE-SCALE ENVIRONMENT ON GALAXY PROPERTIES

We inspect the coupled dependence of physical parameters of the Sloan Digital Sky Survey galaxies on the small-scale (distance to and morphology of the nearest neighbor galaxy) and the large-scale (background density smoothed over 20 nearby galaxies) environments. The impacts of interaction on galaxy properties are detected at least out to the neighbor separation corresponding to the virial radius of galaxies, which is typically between 200 and 400 h−1 kpc for the galaxies in our sample. To detect these long-range interaction effects, it is crucial to divide galaxy interactions into four cases dividing the morphology of target and neighbor galaxies into early and late types. We show that there are two characteristic neighbor-separation scales where the galaxy interactions cause abrupt changes in the properties of galaxies. The first scale is the virial radius of the nearest neighbor galaxy rvir,nei. Many physical parameters start to deviate from those of extremely isolated galaxies at the projected neighbor separation rp of about rvir,nei. The second scale is at rp ≈ 0.05rvir,nei = 10–20 h−1 kpc, and is the scale at which the galaxies in pairs start to merge. We find that late-type neighbors enhance the star formation activity of galaxies while early-type neighbors reduce it, and that these effects occur within rvir,nei. The hot halo gas and cold disk gas must be participating in the interactions at separations less than the virial radius of the galaxy plus dark halo system. Our results also show that the role of the large-scale density in determining galaxy properties is minimal once luminosity and morphology are fixed. We propose that the weak residual dependence of galaxy properties on the large-scale density is due to the dependence of the halo gas property on the large-scale density.
A Data-Driven Approach to Quantifying Natural Human Walking

Our goal in this project was to implement and validate the results of recent work employing statistical techniques to automatically determine a “naturalness” measure of human motion data. Using a training set of motion capture data (that in effect embodies our definition of naturalness), we learn several models to represent this natural motion, and test them on a variety of hand-selected positive and negative examples. The models we consider are the Naive Bayes model, mixtures of Gaussians, and hidden Markov models. We restrict our study to walking motions, but nonetheless achieve convincing and meaningful results, which are illustrated using ROC curves. In addition, we mention shortcomings of the original paper, and provide a few suggestions for further work.
Position Control of an AC Servo Motor Using Sliding Mode Controller with Disturbance Estimator

In this work, a new control methodology to achieve accurate position control of an AC servo motor subjected to external disturbance is proposed. Unlike conventional sliding mode controller which requires a prior knowledge of the upper bound of external disturbance, the proposed technique, called sliding mode controller with disturbance estimator (SMCDE), can offer robust control performances without a prior knowledge of the disturbance bound. The SMCDE is featured by an integrated average value of the imposed disturbance over a certain sampling period. By doing this, undesirable chattering phenomenon in the estimation process can be effectively alleviated. The benefits of the proposed control methodology are empirically demonstrated on AC servo motor and control responses are evaluated through a comparative work between the proposed and conventional control schemes.
A new approach to estimate the missing value based on neighbor granular domain in the incomplete information system

It is an important research subject to estimate the missing value in the incomplete information system. In this paper, we formally define the incomplete information system, incomplete equivalence class, reflexive neighborhood, granularity, granularity domain, rough granularity domain, neighborhood granularity domain, and the property of neighborhood granularity domain. Then we put forward a new method based on neighborhood granularity domain to estimate missing value of the incomplete information system. First calculate the object incomplete equivalence class of the condition attributes and decision attributes, and then obtain granularity domain elements from the incomplete equivalence class, and calculate the rough granularity domain and the neighborhood granularity domain, and then divide all calculated objects of neighborhood granularity domain into according equivalence class, finally delete other equivalence class of the object. We presents the algorithm and examples, and the experimental results show that the algorithm is fast and the missing value estimation accuracy is high.
In Silico Simulation Represents Adenoviral Gene Knockdown of Myocardial Ventricular Cell

The Kyoto model, which is one of the most precise cell models, includes ion fluxes through all known myocardial ion channels, membrane potential, mitochondrial Ca handling, and contraction, and represent the dynamics of ventricular cell and sinoatrial node cell of the guinea pig [1, 3]. We have ported the Kyoto model to the E-Cell simulation environment for in silico investigations [4]. Last year, Miake and his colleagues showed that adenoviral gene transfer of mutant Kir2.1 transformed guinea pig’s ventricular cells into pacemakers [2]. Their experiments were modeled and are implemented to the Kyoto model, then in silico experiments were executed using the E-Cell system. in silico results resembled Miake’s results closely.
Comparison of RBF and MLP neural networks in short-term traffic flow forecasting

Expanding mathematical models and forecasting the traffic flow is a crucial case in studying the dynamic behaviors of the traffic systems these days. Artificial Neural Networks (ANNs) are of the technologies presented recently that can be used in the intelligent transportation system field. In this paper, two different algorithms, the Multi-Layer Perceptron (MLP) and the Radial Basis Function (RBF) have been discussed. In the training of the ANNs, we use historic data. Then we use ANNs for forecasting a daily real time short-term traffic flow. The ANNs are trained by the Back-Propagation (BP) algorithm. The variable coefficients produced by temporal signals improve the performance of the BP algorithm. The temporal signals provide a new method of learning called Temporal Difference Back-Propagation (TDBP) learning. We demonstrate the capability and the performance of the TDBP learning method with the simulation results. The data of the two lane street I-494 in Minnesota city are used for this analysis.
Nuclear Localization of Ataxin-3 Is Required for the Manifestation of Symptoms in SCA3: In Vivo Evidence

Spinocerebellar ataxia type 3 (SCA3) is an autosomal dominantly inherited neurodegenerative disorder caused by the expansion of a CAG repeat in the MJD1 gene resulting in an expanded polyglutamine repeat in the ataxin-3 protein. To study the course of the disease, we generated transgenic mice for SCA3 using full-length ataxin-3 constructs containing 15, 70, or 148 CAG repeats, respectively. Control mice (15 CAGs) were phenotypically normal and had no neuropathological findings. However, mice transgenic for ataxin-3 with expanded polyglutamine repeats were severely affected by a strong neurological phenotype with tremor, behavioral deficits, strongly reduced motor and exploratory activity, a hunchback, and premature death at 3 to 6 months of age. Neuropathological examination by immunohistochemical staining revealed ubiquitin- and ataxin-3-positive intranuclear inclusion bodies in a multitude of neurons. Directing ataxin-3 with 148 CAGs to the nucleus revealed an even more pronounced phenotype with more inclusions and earlier death, whereas mice transgenic with the same construct but attached to a nuclear export signal developed a milder phenotype with less inclusions. These studies indicate that nuclear localization of ataxin-3 is required for the manifestation of symptoms in SCA3 in vivo.
Robust Multi-unit Auction Protocol against False-name Bids

This paper presents a new multi-unit auction protocol (IR protocol) that is robust against false-name bids. Internet auctions have become an integral part of Electronic Commerce and a promising field for applying agent and Artificial Intelligence technologies. Although the Internet provides an excellent infrastructure for executing auctions, the possibility of a new type of cheating called false-name bids has been pointed out. A false-name bid is a bid submitted under a fictitious name. A protocol called LDS has been developed for combinatorial auctions of multiple different items and has proven to be robust against false-name bids. Although we can modify the LDS protocol to handle multi-unit auctions, in which multiple units of an identical item are auctioned, the protocol is complicated and requires the auctioneer to carefully predetermine the combination of bundles to obtain a high social surplus or revenue. For the auctioneer, our newly developed IR protocol is easier to use than the LDS, since the combination of bundles is automatically determined in a flexible manner according to the declared evaluation values of agents. The evaluation results show that the IR protocol can obtain a better social surplus than that obtained by the LDS protocol.
Functional and Phylogenetic Relatedness in Temporary Wetland Invertebrates: Current Macroecological Patterns and Implications for Future Climatic Change Scenarios

In freshwater ecosystems, species compositions are known to be determined hierarchically by large to small‑scale environmental factors, based on the biological traits of the organisms. However, in ephemeral habitats this heuristic framework remains largely untested. Although temporary wetland faunas are constrained by a local filter (i.e., desiccation), we propose its magnitude may still depend on large-scale climate characteristics. If this is true, climate should be related to the degree of functional and taxonomic relatedness of invertebrate communities inhabiting seasonal wetlands. We tested this hypothesis in two ways. First, based on 52 biological traits for invertebrates, we conducted a case study to explore functional trends among temperate seasonal wetlands differing in the harshness (i.e., dryness) of their dry season. After finding evidence of trait filtering, we addressed whether it could be generalized across a broader climatic scale. To this end, a meta-analysis (225 seasonal wetlands spread across broad climatic categories: Arid, Temperate, and Cold) allowed us to identify whether an equivalent climate-dependent pattern of trait richness was consistent between the Nearctic and the Western Palearctic. Functional overlap of invertebrates increased from mild (i.e., Temperate) to harsher climates (i.e., Arid and Cold), and phylogenetic clustering (using taxonomy as a surrogate) was highest in Arid and lowest in Temperate wetlands. We show that, (i) as has been described in streams, higher relatedness than would be expected by chance is generally observed in seasonal wetland invertebrate communities; and (ii) this relatedness is not constant but climate-dependent, with the climate under which a given seasonal wetland is located determining the functional overlap and the phylogenetic clustering of the community. Finally, using a space-for-time substitution approach we suggest our results may anticipate how the invertebrate biodiversity embedded in these vulnerable and often overlooked ecosystems will be affected by long-term climate change.
Timing Synchronization for MIMO-OFDM WLAN Systems

In the paper, a novel timing synchronization method is proposed for MIMO-OFDM based wireless local area networks (WLAN) systems. For coarse timing synchronization, a sliding window differentiator is used after a conventional autocorrelation device so that the timing ambiguity caused by the auto-correlation metric plateau can be removed. For fine timing synchronization, a metric called signal-to-interference ratio (SIR) is devised. Based on this metric, a fine timing synchronization method is developed to improve the timing precision. Compared with the conventional cross-correlation synchronization methods, this method is more robust to multipaths and pseudo multipaths caused by the cyclic delay diversity (CDD) scheme, which may be adopted in the next generation WLAN IEEE 802.11n system. At last, the timing is refined to precisely estimate the time of arrival for location applications by searching the cross-correlation peak in a small window around the fine timing estimation.
Malaria and Growth

The authors explore the two-sided link between malaria morbidity and Gross Domestic Product (GDP) per capita growth. Climate significantly affects cross-country differences in malaria morbidity. Tropical location is not destiny, however: greater access to rural health care and greater income equality are associated with lower malaria morbidity. But the interpretation of this link is ambiguous: does greater income inequality allow for improved anti-malaria efforts, or does malaria itself increase income inequality? Allowing for two-sided causation, the authors find a significant negative causal effect running from malaria morbidity to the growth rate of GDP per capita. In about a quarter of their sample countries, malaria is estimated to reduce GDP per capita growth by at least 0.25 percentage point a year.
Targeted Genome Editing via CRISPR in the Pathogen Cryptococcus neoformans

Low rates of homologous integration have hindered molecular genetic studies in Cryptococcus neoformans over the past 20 years, and new tools that facilitate genome manipulation in this important pathogen are greatly needed. To this end, we have investigated the use of a Class 2 CRISPR system in C. neoformans (formerly C. neoformans var. grubii). We first expressed a derivative of the Streptococcus pyogenes Cas9 nuclease in C. neoformans, and showed that it has no effect on growth, production of virulence factors in vitro, or virulence in a murine inhalation model. In proof of principle experiments, we tested the CAS9 construct in combination with multiple self-cleaving guide RNAs targeting the well-characterized phosphoribosylaminoamidazole carboxylase-encoding ADE2 gene. Utilizing combinations of transient and stable expression of our constructs, we revealed that functionality of our CRISPR constructs in C. neoformans is dependent upon the CAS9 construct being stably integrated into the genome, whilst transient expression of the guide RNA is sufficient to enhance rates of homologous recombination in the CAS9 genetic background. Given that the presence of the CRISPR nuclease does not influence virulence in a murine inhalation model, we have successfully demonstrated that this system is compatible with studies of C. neoformans pathogenesis and represents a powerful tool that can be exploited by researchers in the field.