Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative MIMO Precoding with Distributed CSI: A Hierarchical Approach

The problem of network multiple-input multiple-output precoding under distributed channel state information is a notoriously challenging question, for which optimal solutions with reasonable complexity remain elusive. In this context, we assess the value of hierarchical information exchange, whereby an order is established among the transmitters (TXs) in such a way that a given TX has access not only to its local channel estimate but also to the estimates available at the less informed TXs. Assuming regularized zero forcing (RZF) precoding at the TXs, we propose naive, locally robust, and globally robust suboptimal strategies for the joint precoding design. Numerical results show that hierarchical information exchange brings significant performance gains, with the locally and globally robust algorithms performing remarkably close to the optimal RZF strategy. Lastly, the cost of hierarchical information exchange relative to the cooperation gain is examined and the optimal tradeoff is numerically evaluated.
Th17-Mediated Cross Protection against Pneumococcal Carriage by Vaccination with a Variable Antigen

ABSTRACT Serotype-specific protection against Streptococcus pneumoniae is an important limitation of the current polysaccharide-based vaccines. To prevent serotype replacement, reduce transmission, and limit the emergence of new variants, it is essential to induce broad protection and restrict pneumococcal colonization. In this study, we used a prototype vaccine formulation consisting of lipopolysaccharide (LPS)-detoxified outer membrane vesicles (OMVs) from Salmonella enterica serovar Typhimurium displaying the variable N terminus of PspA (α1α2) for intranasal vaccination, which induced strong Th17 immunity associated with a substantial reduction of pneumococcal colonization. Despite the variable nature of this protein, a common major histocompatibility complex class (MHC-II) epitope was identified, based on in silico prediction combined with ex vivo screening, and was essential for interleukin-17 A (IL-17A)-mediated cross-reactivity and associated with cross protection. Based on 1,352 PspA sequences derived from a pneumococcal carriage cohort, this OMV-based vaccine formulation containing a single α1α2 type was estimated to cover 19.1% of strains, illustrating the potential of Th17-mediated cross protection.
Functional role of the type 1 pilus rod structure in mediating host-pathogen interactions

Uropathogenic E. coli (UPEC), which cause urinary tract infections (UTI), utilize type 1 pili, a chaperone usher pathway (CUP) pilus, to cause UTI and colonize the gut. The pilus rod, comprised of repeating FimA subunits, provides a structural scaffold for displaying the tip adhesin, FimH. We solved the 4.2 Å resolution structure of the type 1 pilus rod using cryo-electron microscopy. Residues forming the interactive surfaces that determine the mechanical properties of the rod were maintained by selection based on a global alignment of fimA sequences. We identified mutations that did not alter pilus production in vitro but reduced the force required to unwind the rod. UPEC expressing these mutant pili were significantly attenuated in bladder infection and intestinal colonization in mice. This study elucidates an unappreciated functional role for the molecular spring-like property of type 1 pilus rods in host-pathogen interactions and carries important implications for other pilus-mediated diseases.
Human-robot collaboration for a shared mission

We are interested in collaboration domains between a robot and a human partner, the partners share a common mission without an explicit communication about their plans. The decision process of the robot agent should consider the presence of its human partner. Also, the robot planning should be flexible to human comfortability and all possible changes in the shared environment. To solve the problem of human-robot collaboration with no communication, we present a model that gives the robot the ability to build a belief over human intentions in order to predict his goals, this model counts mainly on observing the human actions. We integrate this prediction into a Partially Observable Markov Decision Process (POMDP) model to achieve the most appropriate and flexible decisions for the robot.
The Statistical Determinants of the Speed of Motor Learning

It has recently been suggested that movement variability directly increases the speed of motor learning. Here we use computational modeling of motor adaptation to show that variability can have a broad range of effects on learning, both negative and positive. Experimentally, we also find contributing and decelerating effects. Lastly, through a meta-analysis of published papers, we verify that across a wide range of experiments, movement variability has no statistical relation with learning rate. While motor learning is a complex process that can be modeled, further research is needed to understand the relative importance of the involved factors.
Designing Hybrid Nanoparticles

In the last few years, several 'bottom-up' and 'top-down' synthesis routes have been developed to produce tailored hybrid nanoparticles (HNPs). This book provides a new insight into one of the most promising 'bottom-up' techniques, based on a practical magnetron-sputtering inert-gas-condensation method. A modified magnetron-sputtering-based inert-gas-condensation (MS-IGC) system is presented, and its performances under different conditions are evaluated.
Museum Exhibit Identification Challenge for Domain Adaptation and Beyond

In this paper, we approach an open problem of artwork identification and propose a new dataset dubbed Open Museum Identification Challenge (Open MIC). It contains photos of exhibits captured in 10 distinct exhibition spaces of several museums which showcase paintings, timepieces, sculptures, glassware, relics, science exhibits, natural history pieces, ceramics, pottery, tools and indigenous crafts. The goal of Open MIC is to stimulate research in domain adaptation, egocentric recognition and few-shot learning by providing a testbed complementary to the famous Office dataset which reaches 90% accuracy. To form our dataset, we captured a number of images per art piece with a mobile phone and wearable cameras to form the source and target data splits, respectively. To achieve robust baselines, we build on a recent approach that aligns per-class scatter matrices of the source and target CNN streams [15]. Moreover, we exploit the positive definite nature of such representations by using end-to-end Bregman divergences and the Riemannian metric. We present baselines such as training/evaluation per exhibition and training/evaluation on the combined set covering 866 exhibit identities. As each exhibition poses distinct challenges e.g., quality of lighting, motion blur, occlusions, clutter, viewpoint and scale variations, rotations, glares, transparency, non-planarity, clipping, we break down results w.r. t. these factors.
Submucosal Exploration of EMG and Physiological Parameters in the Bladder Wall

An implantable sensor system has been developed to explore the physiological behaviour of the bladder wall. It consists of a 3-axis digital accelerometer and a pressure sensor on the upper side of a flexible polyimide printed circuit board. On the bottom side, two metallic hooks prevent migration of the device in the bladder wall while simultaneously acting as electrodes to record the electrical activity of the detrusor muscle. The full system is inserted at the interface between the detrusor and the mucosa, preventing exposure of the transducer to the urine. This ensures protection both for inflammation of the inner bladder, and from salts deposition on the device. Three packaging layers have been applied to ensure biocompatibility of the device: Parylene-C, medical epoxy and PDMS. The device was first tested in-vitro for water diffusion. Then, the feasibility of submucosal implant was demonstrated in a cadaver pig bladder, and in-vivo recordings were successfully acquired in a rat.
Efficient implementation of simeck family block cipher on 16-bit MSP430

In these days, there are a lot of the Internet of Things(IoT) devices according to the development of IoT technologies. However, it is difficult to implement the existing block ciphers such as AES, PRESENT, etc. on the IoT devices, because IoT devices have the resource-restricted environment. By this reason, there are light-weight block ciphers such as SIMON, SPECK, and Simeck support various block/key sizes. In this paper, authors propose efficient implementation methods and results of the Simeck family block cipher on 16-bit MSP430. The code size optimized On-The-Fly(OTF) version saves on average 11.62% and speed optimized OTF version speed up on average 2.18 times. The code size optimized Encryption is on average 19.32% smaller than and the speed optimized Encryption speed up on average 3.75 times faster.
Mechanical Constraints on the Hominin Pelvis and the “Obstetrical Dilemma”

The “obstetrical dilemma” posits that increases in birth canal dimensions during hominin evolution were constrained by mechanical factors associated with bipedal gait. This model has recently been challenged, in part on the basis of experimental data showing little association between pelvic and proximal femoral dimensions and locomotor costs among human experimental subjects. However, complete rejection of the model is premature, for two reasons: (1) it is difficult to extrapolate experimental results to naturalistic conditions and the much more varied body form and possibly locomotor style of early hominins. Relative pelvic breadth and femoral neck length in both australopiths and early Homo are at or beyond the limits observed among modern humans, and there is evidence that australopiths may have used an altered form of bipedal gait. (2) Other mechanical factors in addition to locomotor cost are important when assessing pelvic and proximal femoral morphology. Increasing biacetabular breadth increases the joint reaction force (JRF) on the femoral head. Increasing femoral neck length may reduce hip JRF, but also increases stress and fracture risk in the femoral neck. Increasing both biacetabular breadth and femoral neck length also increases mediolateral bending stress in the proximal femoral shaft, necessitating substantial buttressing of the diaphysis. Thus, there are mechanical consequences beyond simply locomotor costs that must be considered when evaluating variation in pelvic and femoral morphology among past and extant hominins. Anat Rec, 300:946–955, 2017. © 2017 Wiley Periodicals, Inc.
FC1000: normalized gene expression changes of systematically perturbed human cells

Abstract The systematic study of transcriptional responses to genetic and chemical perturbations in human cells is still in its early stages. The largest available dataset to date is the newly released L1000 compendium. With its 1.3 million gene expression profiles of treated human cells it offers many opportunities for biomedical data mining, but also data normalization challenges of new dimensions. We developed a novel and practical approach to obtain accurate estimates of fold change response profiles from L1000, based on the RUV (Remove Unwanted Variation) statistical framework. Extending RUV to a big data setting, we propose an estimation procedure, in which an underlying RUV model is tuned by feedback through dataset specific statistical measures, reflecting p-value distributions and internal gene knockdown controls. Applying these metrics – termed evaluation endpoints – to disjoint data splits and integrating the results to select an optimal normalization, the procedure reduces bias and noise in the L1000 data, which in turn broadens the potential of this resource for pharmacological and functional genomic analyses. Our pipeline and normalization results are distributed as an R package (nelanderlab.org/FC1000.html).
A novel random forests-based feature selection method for microarray expression data analysis

High-dimensional data and a large number of redundancy features in bioinformatics research have created an urgent need for feature selection. In this paper, a novel random forests-based feature selection method is proposed that adopts the idea of stratifying feature space and combines generalised sequence backward searching and generalised sequence forward searching strategies. A random forest variable importance score is used to rank features, and different classifiers are used as a feature subset evaluating function. The proposed method is examined on five microarray expression datasets, including leukaemia, prostate, breast, nervous and DLBCL, and the average accuracies of the SVM classifier in these datasets are 100%, 95.24%, 85%, 91.67%, and 91.67%, respectively. The results show that the proposed method could not only improve the classification accuracy but also greatly reduce the computation time of the feature selection process.
Computer-aided detection of pulmonary tuberculosis on digital chest radiographs: a systematic review.

OBJECTIVE To systematically review the diagnostic accuracy of computer-aided detection (CAD) of pulmonary tuberculosis (PTB) on digital chest radiographs (CXR). DESIGN We searched four databases for articles published between January 2010 and December 2015 comparing CAD of PTB on CXR to a microbiologic reference standard (smear, culture or polymerase chain reaction). We collected and summarised data on study design, CAD software and diagnostic accuracy (sensitivity, specificity, area under the curve [AUC]). RESULTS We included 5 of 455 articles identified by searching databases. PTB prevalence ranged from 18% to 60%, and human immunodeficiency virus (HIV) prevalence from 33% to 68%. All articles evaluated CAD4TB, the only commercially available software. AUC ranged from 0.71 to 0.84. Software settings that increased sensitivity resulted in important reductions in specificity, and vice versa. Risk of bias was low in prospective studies (n = 2), and high in retrospective studies (n = 3). CONCLUSION Evidence assessing CAD's diagnostic accuracy is limited by the small number of studies, most of which have important methodological limitations, the availability and evaluation of only one software programme, and limited generalisability to settings where PTB and HIV are less prevalent. Additional research is required.
Semantic parser for easy understandable speech broadcasting

In this paper, we propose a public-address system for broadcasting speech that are easy to understand. The system converts a broadcast speech into text using speech recognizer, and it converts the text into simple text using semantic parser. Then, having obtained text with a simple meaning, the system broadcasts it using speech synthesizer. Proposed semantic parser can use dependency analysis to appropriately obtain the place names of the evacuation origin and destination. A subjective evaluation of meaning comprehension using this system found an agreement rate of 79.0%.
Vancomycin Area Under the Curve Simplified

Background: Serum trough concentrations as the sole means of monitoring safety and efficacy of vancomycin are insufficient. The daily area under the curve (AUC24) of serum concentration versus time to minimum inhibitory concentration (MIC) ratio of greater than 400 mg × h/L has emerged as a more robust dosing target. A simple and practical method to extrapolate AUC24 from troughs is needed. Methods: This mathematical model computes the median and range AUC24 using the dose in mg/kg and the observed serum trough concentration. AUC24 is calculated using dose in mg/kg divided by the volume of distribution (Vd) and elimination constant (Ke). Vd is provided using the population median (range) of 0.7 (0.4–1) L/kg. Ke is calculated using the trough and population Vd. Results: For doses of 15–20 mg/kg, troughs of at least 11 mg/L will achieve AUC24 of greater than 400 mg × h/L, even with a Vd of 1 L/kg. Using the median Vd and lower, AUC24 greater than 400 mg × h/L can be achieved with troughs as little as 9 mg/L using doses of 15 mg/kg and greater. The AUC24:MIC goal of greater than 400 can still be attained with an MIC of 1.5 mg/L by using doses of at least 15 mg/kg and targeting troughs of at least 16 mg/L for a patient with a Vd of 0.7 L/kg or less. Conclusions: Troughs of 15–20 mg/L are rarely needed for organisms with an MIC of 1 mg/L or less. AUC24:MIC goals of greater than 400 can best be achieved with higher doses in mg/kg while targeting lower troughs.
The plasminogen receptor, Plg‐RKT, is essential for mammary lobuloalveolar development and lactation

Essentials Plg‐RKT‐/− female mice give birth, but no offspring of Plg‐RKT−/− female mice survive to weaning. Causal mechanisms of potential lactational failure in Plg‐RKT−/− mice are unknown. Plg‐RKT regulates extracellular matrix remodeling, cell proliferation, apoptosis, fibrin surveillance. Plg‐RKT is essential for lactogenesis and mammary lobuloalveolar development.
EvaPlanner: an evacuation planner with social-based flocking kinetics

This paper demonstrates a system that exploits graph mining, social network analysis, and agent-based crowd simulation techniques to investigate the evacuation dynamics during fire emergency. We create a novel evacuation planning system, EvaPlanner, to deal with three tasks. First, the system identifies the preferable locations to establish the exits to facilitate efficient evacuation from the dangerous areas. Second, it determines the most effective positions to place the emergency signs such that panic crowd can quickly find the exits. Third, it faithfully simulates the evacuation dynamics of crowd considering not only the individual movement kinetics but also the social connections between people. EvaPlanner provides a flexible experimental platform for investigating the evacuation dynamics under a variety of settings, and can further be utilized for animation and movie production. In addition, it can serve as a tool to assist architects address the safety concern during the planning phase. The demo system can be found in the link: http://mslab.csie. ntu.edu. tw/evaplanner/
A Recurrent Neural Network for Hierarchical Control of Interconnected Dynamic Systems

A recurrent neural network for the optimal control of a group of interconnected dynamic systems is presented in this paper. On the basis of decomposition and coordination strategy for interconnected dynamic systems, the proposed neural network has a two-level hierarchical structure: several local optimization subnetworks at the lower level and one coordination subnetwork at the upper level. A goal-coordination method is used to coordinate the interactions between the subsystems. By nesting the dynamic equations of the subsystems into their corresponding local optimization subnetworks, the number of dimensions of the neural network can be reduced significantly. Furthermore, the subnetworks at both the lower and upper levels can work concurrently. Therefore, the computation efficiency, in comparison with the consecutive executions of numerical algorithms on digital computers, is increased dramatically. The proposed method is extended to the case where the control inputs of the subsystems are bounded. The stability analysis shows that the proposed neural network is asymptotically stable. Finally, an example is presented which demonstrates the satisfactory performance of the neural network
Automatic Generation of Language-Independent Features for Cross-Lingual Classification

Many applications require categorization of text documents using predefined categories. The main approach to performing text categorization is learning from labeled examples. For many tasks, it may be difficult to find examples in one language but easy in others. The problem of learning from examples in one or more languages and classifying (categorizing) in another is called cross-lingual learning. In this work, we present a novel approach that solves the general cross-lingual text categorization problem. Our method generates, for each training document, a set of language-independent features. Using these features for training yields a language-independent classifier. At the classification stage, we generate language-independent features for the unlabeled document, and apply the classifier on the new representation. To build the feature generator, we utilize a hierarchical language-independent ontology, where each concept has a set of support documents for each language involved. In the preprocessing stage, we use the support documents to build a set of language-independent feature generators, one for each language. The collection of these generators is used to map any document into the language-independent feature space. Our methodology works on the most general cross-lingual text categorization problems, being able to learn from any mix of languages and classify documents in any other language. We also present a method for exploiting the hierarchical structure of the ontology to create virtual supporting documents for languages that do not have them. We tested our method, using Wikipedia as our ontology, on the most commonly used test collections in cross-lingual text categorization, and found that it outperforms existing methods.
Application of Small Punch Techniques for the Determination of Gold Mechanical Properties

Abstract: Gold has been one of the most valuable materials since ancient times. These days it is mainly used as a business commodity or as an engineering material in jewellery, medical prostheses (mainly dental) or electronics. For these engineering purposes, knowledge of its mechanical properties is a key factor in order to improve design and performance. The properties of pure gold have already been reported, although the information on them is scarce and indeed no information on properties such as fracture resistance has been found by the authors of this work. Gold alloys, especially those used for dental implants, are better characterised, but the development of new alloys requires a new characterisation of their properties. At the same time, there have been important advances in recent years in the development of non‐destructive or quasi‐non‐destructive techniques for the mechanical characterisation of materials. Among these, the small punch technique has proven to be one of the most reliable and efficient (in terms of material consumption). This technique is here applied for the determination of 24 (pure gold) and 18 (75% gold) carat gold properties, as an example of how this experimental tool is capable and suitable for the characterisation of gold, gold alloys and any other scarce, valuable material. The estimated tensile properties of 24 carat gold correlate well with the values observed in the literature, obtained through traditional test techniques.