Miracle-dz/UniFAR-FTUs huggingface dataset:
Ordered access memory and its application in parallel processors

In this paper, after analyzing the known memory access methods, conventional memory organization and its challenging problems, we propose new ordered memory access method and a new type of memory – the ordered access memory. This method is aimed at working with data arrays and provides memory access in the prescribed manner. Proposed method unlike widely used method of sequential memory access allows extending the functionality of the memory as it provides not only sequential, but also any other ordered memory access. Unlike another widely used method of address memory access, the implementation of the proposed method provides parallel conflict-free memory access. It also allows eliminating data binding to a specific memory location that makes it possible to disintegrate the apparatus for data ordering and eliminates the need to store addresses of locations the data are placed in, and the need to submit the address to the address inputs during data writing and reading. The new method distinctive features compared to the known memory access methods are considered. Input data, their indices and output data of the ordered access memory are described as well as the approaches to this type of memory design and use. The interface of the ordered access memory is considered as well as its advances compared to the random, associative, and sequential access memories. An example of the ordered access memory usage in application-specific processors with parallel and pipeline structures is demonstrated and the results of the ordered access memory implementation in FPGA are considered.
Ultra Low Power Tunable Filter for a Low Phase Shift on Electrocardiogram QRS-Complex Acquisition

Filtering with low and controlled delay and very low power consumption is required for wearable biomedical signal acquisition applied in the time estimation between two events. Such is the case of cuffless, non-invasive blood pressure monitoring based on the transit time approach. This work presents an ultra low power integrated filter design with low phase shift. Simulation results show less than 2ms delay for the QRS complex of the Electrocardiogram (ECG) with a total current consumption of $I_{DD}= 2.1\mathbf{nA}$ at $V_{DD}=1.2\mathbf{V}$ of power supply. This performance is based on the filter transfer function selection, novel gm-C architecture and tuning procedure.
How SVM Can Compensate Logit Based Response Label with Various Characteristics in Predictor? A Simulation Study

In general, supervised machine learning methods for classification can be categorized into two approaches, namely parametric and nonparametric. Parametric method has limitations in term of the assumptions must be satisfied. One way to handle this problem is using non parametric approaches. The state of the art classification method is support vector machine (SVM). However, the computational burden of kernel SVM limits its application to large scale datasets that demand high computational time. So, one way to cope the limitation is using ensemble approach that splits the data and applies learning procedure at each subset of data. In this work, the Clustered Support Vector Machine (CSVM) is chosen. So far, the studies of CSVM are limited to theoretical and direct application for real dataset. The application to real dataset directly has a weakness that we never know in detail how various characteristic in predictor affect the learning process. So, it is necessary to do a simulation study to further explore how complex the data, particularly in predictor, that can be handled by SVM and CSVM. There are ten scenarios conducted in this simulation study. The response label is generated using Iogistic regression model with various characteristic setting in predictor in each scenario. Given the true response label is generated using Iogit model, the results of this simulation study show that SVM and CSVM can compensate the performance of Iogistic regression in some scenarios. These results showed that SVM is powerful in classification method regardless how the response label is generated.
Post-quantum Security using Channel Noise

Post-quantum secure communication has attracted much interest in recent years. Known computationally secure post-quantum key agreement protocols are resource intensive for small devices. These devices may need to securely send frequent short messages, for example to report the measurement of a sensor. Secure communication using physical assumptions provides information-theoretic security (and so quantum-safe) with small computational over-head. Security and efficiency analysis of these systems however is asymptotic. In this poster we consider two secure message communication systems, and derive and compare their security and efficiency for finite length messages. Our results show that these systems indeed provide an attractive alternative for post-quantum security.
NF-κB/MAPK activation underlies ACVR1-mediated inflammation in human heterotopic ossification.

BACKGROUND Inflammation helps regulate normal growth and tissue repair. Although bone morphogenetic proteins (BMPs) and inflammation are known contributors to abnormal bone formation, how these pathways interact in ossification remains unclear. METHODS We examined this potential link in patients with fibrodysplasia ossificans progressiva (FOP), a genetic condition of progressive heterotopic ossification caused by activating mutations in the Activin A type I receptor (ACVR1/ALK2). FOP patients show exquisite sensitivity to trauma, suggesting that BMP pathway activation may alter immune responses. We studied primary blood, monocyte, and macrophage samples from control and FOP subjects using multiplex cytokine, gene expression, and protein analyses; examined CD14+ primary monocyte and macrophage responses to TLR ligands; and assayed BMP, TGF-β activated kinase 1 (TAK1), and NF-κB pathways. RESULTS FOP subjects at baseline without clinically evident heterotopic ossification showed increased serum IL-3, IL-7, IL-8, and IL-10. CD14+ primary monocytes treated with the TLR4 activator LPS showed increased CCL5, CCR7, and CXCL10; abnormal cytokine/chemokine secretion; and prolonged activation of the NF-κB pathway. FOP macrophages derived from primary monocytes also showed abnormal cytokine/chemokine secretion, increased TGF-β production, and p38MAPK activation. Surprisingly, SMAD phosphorylation was not significantly changed in the FOP monocytes/macrophages. CONCLUSIONS Abnormal ACVR1 activity causes a proinflammatory state via increased NF-κB and p38MAPK activity. Similar changes may contribute to other types of heterotopic ossification, such as in scleroderma and dermatomyositis; after trauma; or with recombinant BMP-induced bone fusion. Our findings suggest that chronic antiinflammatory treatment may be useful for heterotopic ossification.
Optimization of Low-Complexity Pilot-Based DSP for High Spectral Efficiency $51\times 24$ Gbaud PM-64QAM Transmission

We implement a low-complexity pilot-based DSP and propose an overhead-throughput optimization method using achievable information rate. The optimization enables state-of-the-art spectral efficiency of 9.3 (8.3) bits/s/Hz with combined throughput of 11.9 (10.6) Tb/s after 480 (960) km of SSMF transmission with EDFA-only amplification.
Statistical analysis of Australian and New Zealand Power Transformer Catastrophic Fires

Modelling fires or explosions of power transformers is necessary to assist a utility determine the level of risk incurred from operating their network. However, a challenge is to collect enough data to establish a robust model when these events occur so rarely. Consequently, to collect such a large volume of usage data the Australian and New Zealand utilities were surveyed for information on their power transformers, and on those which had failed catastrophically (either fire or explosion). Approximately 88,000 service-years of operation were collected from 6,637 power transformers operated by 28 utilities between 2000 and 2016. Twenty-one fire or explosion events were identified over this period. Certain power transformer voltage groups appeared to be more likely to fail catastrophically as their age increased. The Poisson distribution was used to provide a method to determine in how many years a fire might be expected, as this can help plan asset replacement.
Behavioral Modeling of Steady-State Oscillators with Buffers Using Neural Networks

This paper describes a method to model the nonlinear time-domain steady-state behavior of oscillators with output buffers using neural networks. In the proposed model, an augmented neural network (AugNN) with a periodic unit is used to capture the periodicity of the oscillatory output waveform, where the nonlinear dynamic behavior of the output buffer is taken into account using recurrent neural networks (RNN). The model is trained using the data obtained from the simulation of transistor-level circuit models. The proposed model is compatible with Verilog-A. An example applied to a buffer-included ring oscillator demonstrates that the proposed modeling method offers good accuracy and significant simulation speed-up to facilitate time-domain analysis without compromising intellectual property (IP).
Superposition of DRA Modes with a Monopole

A $\mathbf{HE}_{\mathbf{11}\Delta}$ mode DRA with an axial hole was colocated with a monopole for 2.33GHz Satellite Digital Audio Service. The DRA had a $\mathbf{S}_{\mathbf{11}}\leq-\mathbf{10dB}$ bandwidth of 2%, while the monopole had 56% due to current stabilization like a sleeve monopole effect. As the monopole had a wide bandwidth, it was trialed with the $\mathbf{TM}_{\mathbf{011}+\Delta}$ mode to produce a circularly polarized monopole radiation pattern at 2.77GHz.
Secretary Ranking with Minimal Inversions

We study a twist on the classic secretary problem, which we term the secretary ranking problem: elements from an ordered set arrive in random order and instead of picking the maximum element, the algorithm is asked to assign a rank, or position, to each of the elements. The rank assigned is irrevocable and is given knowing only the pairwise comparisons with elements previously arrived. The goal is to minimize the distance of the rank produced to the true rank of the elements measured by the Kendall-Tau distance, which corresponds to the number of pairs that are inverted with respect to the true order. Our main result is a matching upper and lower bound for the secretary ranking problem. We present an algorithm that ranks $n$ elements with only $O(n^{3/2})$ inversions in expectation, and show that any algorithm necessarily suffers $\Omega(n^{3/2})$ inversions when there are $n$ available positions. In terms of techniques, the analysis of our algorithm draws connections to linear probing in the hashing literature, while our lower bound result relies on a general anti-concentration bound for a generic balls and bins sampling process. We also consider the case where the number of positions $m$ can be larger than the number of secretaries $n$ and provide an improved bound by showing a connection of this problem with random binary trees.
NE-UserCF: Collaborative Filtering Recommender System Model based on NMF and E2LSH

With the rapid development of big data and cloud computing, recommender systems (RSs) have gained significant attention in recent decades. However, there are still many challenges and drawbacks existed in RSs, such as complex and high-dimensional data, low recommendation accuracy, time-consuming and low-efficiency, which to a large extent restrict its applications. Non-negative Matrix Factorization algorithm (NMF) is a matrix factorization algorithm which finds the positive factorization of a given positive matrix. It can eliminate invalid and redundant features in user-rating matrix (URM), reduce URM’s dimension. Exact Euclidean Locality Sensitive Hashing (ELSH) is an advanced algorithm for solving the approximate or exact Near Neighbor Search in high dimensional spaces. It can cluster similar-interest users (SIUs) of URM efficiently. Therefore, the authors propose an improved recommender system model named NE-UserCF (NMF-ELSH-UserCF) based on NMF and ELSH to improve the quality and performance of recommendation. The authors first utilize the NMF to process original URM, get a new-URM without invalid and redundant features. Then use ELSH to cluster users in new-URM based on their interests and produce the similar-interest-user matrix (SIUM). The authors further process the Top-10 recommendations by adopting the user-based collaborative filtering algorithm (UserCF). Finally evaluate experimental results by analyzing metrics Precision, Recall, Coverage and Popularity. Experiments indicate that NE-UserCF proposed in this paper improves the quality of recommendation and has a good performance.
Alteration of the Reproductive Patterns in Drosophila melanogaster by Effects of High Concentrations of Boron on In Vitro Cultured Medium

El objetivo de este estudio fue evaluar el efecto del boro (B), usando como modelo biologico a Drosophila melanogaster. Especificamente analizar las respuestas sobre la descendencia a dosis de 6,0 y 12 mg/L y comparar con el grupo control cuya concentracion de boro en el agua del medio de cultivo no supera los 0,6 mg/L, segun los estandares de la Organizacion Mundial de la Salud. Los resultados muestran una alteracion significativa en el numero de la descendencia desde F1 a F3 y luego una tendencia a la normalizacion a partir de la F4 y F5. Tambien hay un cambio significativo en las proporciones entre machos y hembras, con un efecto agudo en F1 y luego un posible efecto cronico desde F2 a F5, aumentando la proporcion de hembras con respecto a los machos. Sin embargo estas diferencias entre sexos ya no son significativas solamente hasta F4. En F5 estas proporciones no son significativas. En F3 en dosis de 12 mg/L de boro, se observan los mayores cambios, alterando la expresion fenotipica, donde el numero de machos que incrementan su tamano, son significativamente mas altos con respecto a las hembras que aumentan de tamano. La tendencia a la normalidad en todos los patrones de estudio a partir de la descendencia F4 a F5, sobre todo en el porcentaje de sobreviva, posiblemente se deba a la accion de hormonas esteroidales de resistencia al estres, tal como la hormona "Ecdysona".
Nerve root sparing in posterior approach corpectomy and thoracolumbar spine reconstruction using an expandable cage: A novel technique

Aims: Thoracolumbar fractures, especially when disintegration of the bony fragments occur, require surgery. However, no specific operative approach has so far been given precedence. We herewith propose a variant surgical procedure which may be indicated for the above purpose. Methods: The suggested technique should be carried out in a single stage, by posterior approach only. Following the generation of an appropriate access and evacuation of the bone debris, a titanium mesh cage should be inserted, using an original manipulation, shown in the enclosed video and which will cause minimal or no damage to the neural elements. Results: Fourteen patients were submitted to our variant operation, seven with Type A (according to the Aospine classification) fracture (three with two simultaneous fractures). Three suffered from C type fractures; Most patients presented with a preserved neurological status; Three were paraplegic on admission (Frankel grade A). The most marking benefits of this technique included optimal height restoration, immediate stability, and direct canal decompression. All patients except one improved in the postoperative period, by at least one grade on Frankel scale. Conclusion: The proposed procedure variant fulfilled most of our expectations, to the benefit of the patients. In addition, the duration of the surgery was shorter than that of the A-P procedure. Our technique could be further extended to fractures above and below the T11-L2 segment, and also include patients with Frankel grade A lesions.
The effect of XRCC3 rs861539 polymorphism on the risk of head and neck squamous cell carcinoma: a systematic review and meta-analysis

Background: Some studies suggested that XRCC3 rs861539 polymorphism might change the risk of Head and Neck Squamous Cell Carcinoma (HNSCC). However, other studies have reported negative results. Therefore, we did this meta-analysis to investigate the role of XRCC3 rs861539 polymorphism on HNSCC risk. Methods and Materials: Online electronic databases (PubMed, EMBASE and Wang fang database) were searched. The strength of association was assessed by calculating Odds Ratio (OR) with 95% Confidence Interval (CI). Results: A total of 5 studies with 868 cases and 1477 controls on the association between XRCC3 rs861539 polymorphism and HNSCC risk were included in this meta-analysis. Individuals with XRCC3 rs861539 polymorphism had an increased HNSCC risk (OR=1.65; 95% CI, 1.03-2.64; P=0.04). Subgroup analysis was performed according to smoking status. Light smokers with XRCC3 rs861539 polymorphism did not had an increased HNSCC risk (OR=3.73; 95% CI, 0.87-16.07; P=0.08). However, moderate smokers (OR=3.20; 95% CI, 1.79-5.70; P<0.0001) and heavy smokers (OR=3.69; 95% CI, 1.56-8.77; P=0.003) showed increased risk of HNSCC, respectively. Conclusions: In conclusion, this study suggested that XRCC3 rs861539 polymorphism was associated with HNSCC risk.
DNA-based Diagnosis of Uncharacterized Inherited Macrothrombocytopenias Using Next-generation Sequencing Technology with a Candidate Gene Array

Inherited macrothrombocytopenias comprise a heterogeneous group of inherited platelet disorders that are characterized by large platelets, thrombocytopenia and bleeding ten‐ dencies in affected individuals. Diagnostic platforms have traditionally involved a bat‐ tery of complex phenotypic tests that often fail to reach a diagnosis. Next-generation sequencing lacks the pre-analytical and analytical shortcoming of these tests and pro‐ vides an attractive alternate diagnostic approach. Our group has developed a candidate gene array targeting genes known to affect platelet function and tested it in a large cohort of Australasian patients with presumed platelet function disorders, particularly macro‐ thrombocytopenia. This array identified causative variants in a significant portion of pa‐ tients with uncharacterized platelet disorders, including transcription factor mutations that cannot easily be diagnosed with standard platelet phenotyping procedures. We pro‐ pose that targeted genotypic screening can identify the genetic basis of platelet function defects and has the potential to be developed into a powerful clinical platform to help clinicians diagnose these rare disorders. in in three from three families; pathogenic, whilst the third shown to represent a false positive result ( RUNX1 , heterozygous, stop/gain, c. 966T>G (p.Tyr322X), exon 6). False positivity was confirmed by Sanger sequencing that showed a wild-type sequence across that region.
A ROBUST CONTROLLER STRUCTURE FOR PICO-SATELLITE APPLICATIONS

Abstract This paper describes the development of a robust controller structure for use in pico-satellite missions. The structure relies on unknown disturbance estimation and use of robust control theory to implement a system that is robust to both unmodeled disturbances and parameter uncertainties. As one possible application, a satellite mission with the purpose of monitoring shipping routes for oil spills has been considered. However, it is the aim of the control structure to be widely applicable and adaptable for a wide variety of pico-satellite missions. The robust control structure has been evaluated using Monte Carlo simulations.
MOLECULAR GENETICS AND SSR MARKERS AS A NEW PRACTICE IN FARM ANIMAL GENOMIC ANALYSIS FOR BREEDING AND CONTROL OF DISEASE DISORDERS

Molecular genetics investigates the genetic makeup of individuals at the DNA level. That includes the identification and mapping of molecular genetic markers and genetic polymorphisms. Molecular genetic markers (DNA markers) are one of the most powerful means for the genomic analysis and allow the connection of hereditary traits with genomic variation. Molecular marker technology has developed rapidly over the last decade and two shapes of specific DNA based marker, Simple Sequence Repeats (SSRs), also known as microsatellites, and Single Nucleotide Polymorphisms (SNPs) prevail applications in modern genetic analysis.Genomic simple sequence repeats (SSRs, microsatellites) have been used for a variety of purposes, including gene tagging, physical mapping, genome mapping, estimation of genetic diversity, phylogenetic and conservation genetic purposes in farm animal breeding. SSR analyses are applied successfully in parentage verification and pedigree analysis, as disease markers and to locate the mutation in genetic disorders in livestock animals. The ultimate use of SSRs markers is for mapping quantitative trait loci (QTL), marker assisted selection (MAS) in order to practice genomic selection and improve the farm animal health. Developments in 'omics' technologies, such as genomic selection, may help overcome several of the limitations of traditional breeding programmes and will be especially beneficial in breeding for lowly heritable disease traits that only manifest themselves following exposure to pathogens or environmental stressors in adulthood. The current paper provides a brief overview of the present - day application of microsatellites markers in animal breeding and make significant contribution to the overall farm animal health and resistance to disease.
Can Convolution Neural Network (CNN) Triumph in Ear Recognition of Uniform Illumination Invariant?

Current deep convolution neural network (CNN) has shown to achieve superior performance on a number of computer vision tasks such as image recognition, classification and object detection. The deep network was also tested for view-invariance, robustness and illumination invariance. However, the CNN architecture has thus far only been tested on non-uniform illumination invariant. Can CNN perform equally well for very underexposed or overexposed images or known as uniform illumination invariant? This is the gap that we are addressing in this paper. In our work, we collected ear images under different uniform illumination conditions with lumens or lux values ranging from 2 lux to 10,700 lux. A total of 1,100 left and right ear images from 55 subjects are captured under natural illumination conditions. As CNN requires considerably large amount of data, the ear images are further rotated at every 5o angles to generate 25,300 images. For each subject, 50 images are used as validation/testing dataset, while the remaining images are used as training datasets. Our proposed CNN model is then trained from scratch and validation and testing results showed recognition accuracy of 97%. The results showed that 100% accuracy is achieved for images with lumens ranging above 30 but having problem with lumens less than 10 lux