Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural and Mechanistic Implications of Rearrangement Frequencies within Human TCRBV Genes

The T cell repertoire is a function of thymic V(D)J rearrangement and of peripheral selection. The mature repertoire embodies TCR sequences that are important for survival and can identify important structural aspects of the TCR. Analysis of the circulating TCRBV19 CD8 T cell repertoire showed that a majority of NDN-encoded CDR3 amino acid motifs start at CDR3 position four, well within the V region. Rearrangement at this position indicates that the DNA hairpin loop is not opened at the position adjacent to the recombination signal sequence, but rather is trimmed back three or more bases. In this article, we show that the rearrangement frequency distribution within the V region reveals selection on CDR3 position four. The selection is already established in single-positive CD8 thymocytes. Crystal structures reveal a possible basis for this selection due to the location of this residue in a bend that positions the remaining portion of CDR3 to interact with the peptide and MHC. Examination of other TCRBV families also shows selection for rearrangement within the V region of a number of genes and for CD8 and CD4 cells. The exact profile of rearrangement within the V region appears to be V gene specific. The frequent observation of side chains associated with turn motifs at CDR3 positions three and four fits with the structural need for a bend. The data are discussed in terms of the generation of a structural turn motif, the rearrangement mechanism, and selection of the repertoire on the peptide and MHC.
Cognitive radio networks for smart grid communications

A critical component of smart grid is the integration of multiple communication technologies which can facilitate the development of smart grid. However, most of the traditional communication technologies can not satisfy the critical and complex requirements of smart grid, such as, efficiency, reliability, resilience, sustainability, and security. In this paper, the cognitive radio (CR) technology is leveraged to construct the communication infrastructure of smart grid. First, ISM bands and leased bands are introduced as backup bands to ensure the QoS of data communications in CR based networks, for which a rule that decides when to stop spectrum sensing and access the ISM bands is also provided. Furthermore, a proper communication scheme is proposed for distributed generation system based on the fact that different renewable energy source has different active period during a day. Some licensed bands whose idle time is in line with the active period of renewable energy sources are set aside exclusively for distributed generation system access. The two schemes improve both the efficiency of spectrum utilization and reliability of cognitive communications in smart grid.
The Role of Ethnicity in School-Based Obesity Intervention for School-Aged Children: A Pilot Evaluation.

BACKGROUND Rates of obesity have risen disproportionately for ethnic minority youth in the United States. School-based programs may be the most comprehensive and cost-effective way to implement primary prevention in children. In this study we evaluated the effect of a school-based obesity prevention on the outcome of body mass index percentile (BMI%), with baseline weight class and ethnicity examined as moderators. METHODS Participants (N = 125), ages 7-11 (56% female) from 4 urban, low-income, ethnic minority (58% black, 42% Latino) schools were recruited. Two schools received the Urban Initiatives Work to Play health intervention, and 2 demographically matched schools served as wait-list controls. RESULTS Hierarchical multiple regression was used to analyze the independent and interactive effects of key variables on BMI%. An interaction between intervention status and ethnicity revealed Latino youth in the intervention had lower BMI% than those in the control group. Participation did not cause BMI% outcomes to decrease for black participants. CONCLUSIONS The study demonstrates the intervention is effective, but that the effectiveness varies across ethnicity. Interventions can be made more efficient and cost-effective by targeting youth of a common ethnicity that has shown empirical responsiveness to certain program elements.
Search engine based resource discovery framework for Internet of Things

This paper proposes a search engine based resource discovery framework for Internet of Things (IoT) to discover resources, their capabilities, properties and URIs to access them regardless of communication technology. There is a central registry to store configurations of resources and they are indexed. Based on discovery request parameters, the search engine "looks up" the indices and returns the URI(s) to directly access the resource(s). The functionalities of the proposed framework are exposed to the consumers using RESTful web services. The framework is generic enough to be deployed in cloud platforms, M2M gateways and lightweight mobile application running on smartphones.
Dynamic zoning based on situational activitie for ICS security

In the previous paper, the authors proposed a design methodology of zones and conduits not only to isolate incidents caused by cyber-attacks but also to detect higher possibility of cyber-attacks and keep sufficient operability by evaluating process safety under the attacks. However, process plants generally have several operational modes, such as start-up, load-change and shutdown. In each mode, security and safety requirements should be defined based on the configuration of process and control structures. Therefore, zones and conduits have to be dynamically switched with the associated mode. In this paper, the authors propose a dynamic zoning methodology that is composed of zone design methodology and zone switching methodology.
An Empowerment-Based Diabetes Self-management Education Program for Hispanic/Latinos

Purpose The purpose of this pilot study was to evaluate the effects of a culturally sensitive, empowerment-based diabetes self-management education program for Spanish-speaking Hispanic/Latinos. Methods A prospective quasi-experimental repeated measures design tested the effectiveness of the ¡Si, Yo Puedo Controlar Mi Diabetes! diabetes self-management education program. In sum, 144 persons residing in 2 Texas counties at the Texas-Mexico border (Starr and Hidalgo) served as participants. Two groups were formed, an intervention and a control (wait list). Clinical (A1C), cognitive, attitudinal, behavioral, and cultural assessments were collected at baseline and 3 months. Results Demographic characteristics for the intervention and control groups were similar. Both groups were predominately female, low income, older than 40 years, and minimally acculturated. Baseline and posttest findings showed that the intervention group had a significant reduction in A1C values; median difference was 0.3 (n = 45), especially for those with higher baseline values. Participants in the intervention group also improved in their self-efficacy and self-care scores. Conclusions Findings from the study suggest that additional dissemination of a diabetes self-management education program for Spanish-speaking Hispanic/Latinos is warranted to improve clinical outcomes and associated diabetes self-efficacy and self-care behaviors.
Outdoor experiments on 5G radio access using distributed MIMO and beamforming in 28-GHz frequency band

This paper presents outdoor field experimental results that clarify 4-by-8 multiple-input multiple-output (MIMO) in the downlink throughput performance when applying distributed MIMO in the 28 GHz frequency band of a 5G cellular radio access system. A variety of transmission point (TP) deployments with narrow antenna beam forming is evaluated in order to investigate the downlink and uplink throughput performance and appropriate TP deployment for distributed MIMO. The experimental results show that the throughput is limited to approximately 7 Gbps in the downlink and 1 Gbps in the uplink in a parking area with localized MIMO. A distributed MIMO throughput gain is achieved with various TP deployments for both the downlink and uplink using two radio units. The outdoor parking area is an open space and multipaths are not anticipated, so a distinct advantage from distributed MIMO is expected. The distributed MIMO gain of 60% in the downlink and from 50 to 200% in the uplink is achieved at the cumulative distribution function of 80%. As a result of implementing distributed MIMO, throughput exceeding 10 Gbps in the downlink and 1.9 Gpbs in the uplink is achieved in the 28-GHz frequency band.
Efficient Wireless Power Transfer System Integrating With Metasurface for Biological Applications

Wireless power transfer (WPT) is a key technique for many existing and emerging applications in biomedical devices. This paper presents a novel implantable magnetic coupling resonate WPT system by integrating with metasurface for biological applications. The receiver element is implanted under the skin surface 3 mm and has the dual-band property for transferring power and data telemetry simultaneously. A conformal strongly coupled magnetic resonator coil is used as the transmitting coil to construct the wireless power link. In addition, we integrate the proposed WPT system with negative permeability (MNG) metasurface over the human skin surface as a miniaturized wearable device to improve the WPT efficiency. The property of the MNG and its effect on the WPT efficiency are analyzed. Considering the special implantable environment, various misalignment tolerances between the metasurface and the receiver are discussed to evaluate the coupling response of the proposed WPT system. Finally, the efficient WPT system integrating with MNG has been verified by the experimental measurements, and the measured result shows that 15.7 dB coupling enhancement can be obtained by integrating with the MNG metasurface.
Impact of thoracic endovascular aortic repair on radial strain in an ex vivo porcine model

Objectives To quantify the impact of thoracic endovascular aortic repair (TEVAR) on radial aortic strain with the aim of elucidating stent-graft-induced stiffening and complications. Methods Twenty fresh thoracic porcine aortas were connected to a mock circulatory loop driven by a centrifugal flow pump. A high-definition camera captured diameters at five different pressure levels (100, 120, 140, 160, and 180 mmHg), before and after TEVAR. Three oversizing groups were created: 0-9% ( n = 7), 10-19% ( n = 6), and 20-29% ( n = 6). Radial strain (or deformation) derived from diameter amplitude divided by baseline diameter at 100 mmHg. Uniaxial tensile testing evaluated Young's moduli of the specimens. Results Radial strain was reduced after TEVAR within the stented segment by 49.4 ± 24.0% ( P < 0.001). As result, a strain mismatch was observed between the stented segment and the proximal non-stented segment (7.0 ± 2.5% vs 11.8 ± 3.9%, P < 0.001), whereas the distal non-stented segment was unaffected ( P = 0.99). Stent-graft oversizing did not significantly affect the amount of strain reduction ( P = 0.30). Tensile testing showed that the thoracic aortas tended to be more elastic proximally than distally ( P = 0.11). Conclusions TEVAR stiffened the thoracic aorta by 2-fold. Such segmental stiffening may diminish the Windkessel function considerably and might be associated with TEVAR-related complications, including stent-graft-induced dissection and aneurysmal dilatation. These data may have implications for future stent-graft design, in particular for TEVAR of the highly compliant proximal thoracic aorta.
An evaluation of multi-probe locality sensitive hashing for computing similarities over web-scale query logs

Many modern applications of AI such as web search, mobile browsing, image processing, and natural language processing rely on finding similar items from a large database of complex objects. Due to the very large scale of data involved (e.g., users’ queries from commercial search engines), computing such near or nearest neighbors is a non-trivial task, as the computational cost grows significantly with the number of items. To address this challenge, we adopt Locality Sensitive Hashing (a.k.a, LSH) methods and evaluate four variants in a distributed computing environment (specifically, Hadoop). We identify several optimizations which improve performance, suitable for deployment in very large scale settings. The experimental results demonstrate our variants of LSH achieve the robust performance with better recall compared with “vanilla” LSH, even when using the same amount of space.
Combing Single Shot Multibox Detector with transfer learning for ship detection using Chinese Gaofen-3 images

SAR images have the advantages of all-whether and all-time, leading to be increasingly used for ship detection to ensure marine transportation and security. Single Shot MultiBox Detector (SSD) has the advantages of fast speed and high accuracy, achieving great success in optical images. In this paper, SSD is applied to ship detection in SAR images. Besides, transfer learning is adopted because it performs well even in small training dataset. More specific, two types of SSD models integrated with transfer learning, namely SSD-300 and SSD-512 with input size of 300 and 512 in both height and width respectively, are applied to ship detection. To evaluate our approaches three SAR images acquired by Chinese Gaofen-3 satellite are used. First, SAR images are cut into patches with size of 256, and then these small images are divided into training, validation, and test with the ratio 70%, 20% and 10% according to machine learning routines. Secondly, both training and validation dataset are resized to feed to SSD with fine tuning VGG16 to train the model. Finally, test images are used to evaluate our approach. Experimental results reveal that compared to SSD-300, SSD-512 achieves more than 0.02 in probability of ship detection, whereas 0.05 worse in false alarm.
Development of a wireless physiological computing platform using a national instruments' myRIO embedded device

We designed a physiological computing platform, which is easy to configure and setup using National Instruments' myRIO embedded device. Physiological signal acquisition, processing, and visualization are required for the most basic sort of physiological computing platform. Therefore, the proposed platform consisted of these three basic modules. (1) Signal acquisition module: the physiological signals captured via the biosensors were sent wirelessly using the myRIO's analog input channels to a PC or mobile handheld devices such as, tablet or smartphone. (2) Signal processing module: the signal processing procedures were conducted using a graphical design software i.e., LabVIEW. (3) Visualization module: the signals and computing results were on the screen for the user. In this paper, we demonstrated the effectiveness of proposed platform on non-contact measurement of the heart and respiration rates using microwave radar.
Adaptive unstructured road detection using close range stereo vision

Detection of road regions is not a trivial problem especially in unstructured and/or off-road domains since traversable regions of these environments do not have common properties unlike urban roads or highways. In this paper a novel unstructured road detection algorithm that can continuously learn the road region is proposed. The algorithm gathers close-range stereovision data and uses this information to estimate the long-range road region. The experiments show that the algorithm gives satisfactory results even under changing light conditions.
Angle constrained path to cluster multiple manifolds

In this paper, we propose a method to cluster multiple intersected manifolds. The algorithm chooses several landmark nodes randomly and then checks whether there is an angle constrained path between each landmark node and every other node in the neighborhood graph. When the points lie on different manifolds with intersection they should not be connected using a smooth path, thus the angle constraint is used to prevent connecting points from one cluster to another one. The resulting algorithm is implemented as a simple variation of Dijkstras algorithm used in Isomap. However, Isomap was specifically designed for dimensionality reduction in the single-manifold setting, and in particular, can-not handle intersections. Our method is simpler than the previous proposals in the literature and performs comparably to the best methods, both on simulated and some real datasets.
Early childhood presentation of Czech dysplasia

Czech dysplasia, metatarsal type is an autosomal dominant skeletal disorder that is characterized by early-onset, progressive arthritis, brachydactyly of the 3rd and 4th toes, and characteristic radiographic findings in patients of normal stature. Patients with Czech dysplasia typically present in late childhood or later. In the present report, whole exome sequencing identified a mutation in COL2A1 (c.823C>T, p.R275C) known to be associated with Czech dysplasia in a 3.5 year old female who had a family history of early-onset arthritis and who was asymptomatic except for prominent knees. The use of whole exome sequencing facilitated diagnosis of this rare disease (less than 15 families in the literature) in the presymptomatic period and thus enabled us to provide early anticipatory guidance and genetic counseling for the family.
Peripheral Serotonin 1B Receptor Transcription Predicts the Effect of Acute Tryptophan Depletion on Risky Decision-Making

Abstract Background The effects of acute tryptophan depletion on human decision-making suggest that serotonin modulates the processing of rewards and punishments. However, few studies have assessed which of the many types of serotonin receptors are responsible. Methods Using a within-subject, double-blind, sham-controlled design in 26 subjects, we examined whether individual differences in serotonin system gene transcription, measured in peripheral blood, predicted the effect of acute tryptophan depletion on decision-making. Participants performed a task in which they chose between successive pairs of fixed, lower-stakes (control) and variable, higher-stakes (experimental) gambles, each involving wins or losses. In 21 participants, mRNA from 9 serotonin system genes was measured in whole blood prior to acute tryptophan depletion: 5-HT1B, 5-HT1F, 5-HT2A, 5-HT2B, 5-HT3A, 5-HT3E, 5-HT7 (serotonin receptors), 5-HTT (the serotonin transporter), and tryptophan hydroxylase 1. Results Acute tryptophan depletion did not significantly influence participants’ sensitivity to probability, wins, or losses, although there was a trend for a lower tendency to choose experimental gambles overall following depletion. Significant positive correlations, which survived correction for multiple comparisons, were detected between baseline 5-HT1B mRNA levels and acute tryptophan depletion-induced increases in both the overall tendency to choose the experimental gamble and sensitivity to wins. No significant relationship was observed with any other peripheral serotonin system markers. Computational analyses of decision-making data provided results consistent with these findings. Conclusions These results suggest that the 5-HT1B receptor may modulate the effects of acute tryptophan depletion on risky decision-making. Peripheral levels of serotonin markers may predict response to treatments that act upon the serotonin system, such as selective serotonin reuptake inhibitors.
A Privacy-Preserving Framework for Trust-Oriented Point-of-Interest Recommendation

Point-of-interest (POI) recommendation has attracted many interests recently because of its significant potential for helping users to explore new places and helping location-based service (LBS) providers to carry out precision marketing. Compared with the user-item rating matrix in conventional recommender systems, the user-location check-in matrix in POI recommendation is usually much more sparse, which makes the notorious cold start problem more prominent in POI recommendation. Trust-oriented recommendation is an effective way to deal with this problem but it requires that the recommender has access to user check-in and trust data. In practice, however, these data are usually owned by different businesses who are not willing to share their data with the recommender mainly due to privacy and legal concerns. In this paper, we propose a privacy-preserving framework to boost data owners willingness to share their data with untrustworthy businesses. More specifically, we utilize partially homomorphic encryption to design two protocols for privacy-preserving trust-oriented POI recommendation. By offline encryption and parallel computing, these protocols can efficiently protect the private data of every party involved in the recommendation. We prove that the proposed protocols are secure against semi-honest adversaries. Experiments on both synthetic data and real data show that our protocols can achieve privacy-preserving with acceptable computation and communication cost.
Electromechanical Imaging and Spectroscopy of Ferroelectric and Piezoelectric Materials: State of the Art and Prospects for the Future

Piezoresponse force microscopy (PFM) has emerged as a powerful and versatile tool for probing nanoscale phenomena in ferroelectric materials on the nanometer and micrometer scales. In this review, we summarize the fundamentals and recent advances in PFM, and describe the nanoscale electromechanical properties of several important ferroelectric ceramic materials widely used in memory and microelectromechanical systems applications. Probing static and dynamic polarization behavior of individual grains in PZT films and ceramics is discussed. Switching spectroscopy PFM is introduced as a useful tool for studying defects and interfaces in ceramic materials. The results on local switching and domain pinning behavior, as well as nanoscale fatigue and imprint mapping are presented. Probing domain structures and polarization dynamics in polycrystalline relaxors (PMN-PT, PLZT, doped BaTiO 3 ) are briefly outlined. Finally, applications of PFM to dimensionally confined ferro-electrics are demonstrated. The potential of PFM for studying local electromechanical phenomena in polycrystalline ferroelectrics where defects and other inhomogeneities are essential for the interpretation of their macroscopic properties is illustrated.
Privacy Protection against Query Prediction in Location-Based Services

In mobile Internet, Location-Based Services (LBSs) as a popular kind of context-aware recommendation systems can recommend Point of Interest (POI) data according to current locations of users. However, the inherent feature leads to leak sensitive location information of users into untrusted LBS providers. This paper aims at the location privacy problem on query prediction which forecasts next locations and violates user privacy seriously. To tackle this, we propose a novel location privacy protection solution. The contribution is three-fold. First, we model query prediction on cloaking regions using the Bayesian inference. Next, the proposed location anonymization method can generalize locations into safer cloaking regions against such query prediction attacks. Finally, a series of experiments evaluate the performance of this solution and demonstrate its availability.