Miracle-dz/UniFAR-FTUs huggingface dataset:
ns-3 Implementation of the 3GPP MIMO Channel Model for Frequency Spectrum above 6 GHz

Communications at mmWave frequencies will be a key enabler for the next generation of cellular networks, due to the multi-Gbps rate that can be achieved. However, before this technology can be widely adopted, there are still several problems that must be solved, primarily associated with the interplay between the variability of mmWave links and the complexity of mobile networks. An end-to-end network simulator represents a great tool to assess the performance of any proposed solution to meet the stringent 5G requirements. Given the criticality of channel propagation characteristics at higher frequencies, it is of fundamental importance to properly simulate detailed propagation behaviors. Towards this goal, in this paper we present our implementation of the 3GPP channel model for the 6-100 GHz band for the ns--3 end-to-end 5G mmWave module, and detail its associated MIMO beamforming architecture.
Geospatial Data Stream Processing in Python Using FOSS4G Components

Abstract. One viewpoint of current and future IT systems holds that there is an increase in the scale and velocity at which data are acquired and analysed from heterogeneous, dynamic sources. In the earth observation and geoinformatics domains, this process is driven by the increase in number and types of devices that report location and the proliferation of assorted sensors, from satellite constellations to oceanic buoy arrays. Much of these data will be encountered as self-contained messages on data streams - continuous, infinite flows of data. Spatial analytics over data streams concerns the search for spatial and spatio-temporal relationships within and amongst data “on the move”. In spatial databases, queries can assess a store of data to unpack spatial relationships; this is not the case on streams, where spatial relationships need to be established with the incomplete data available. Methods for spatially-based indexing, filtering, joining and transforming of streaming data need to be established and implemented in software components. This article describes the usage patterns and performance metrics of a number of well known FOSS4G Python software libraries within the data stream processing paradigm. In particular, we consider the RTree library for spatial indexing, the Shapely library for geometric processing and transformation and the PyProj library for projection and geodesic calculations over streams of geospatial data. We introduce a message oriented Python-based geospatial data streaming framework called Swordfish, which provides data stream processing primitives, functions, transports and a common data model for describing messages, based on the Open Geospatial Consortium Observations and Measurements (O&M) and Unidata Common Data Model (CDM) standards. We illustrate how the geospatial software components are integrated with the Swordfish framework. Furthermore, we describe the tight temporal constraints under which geospatial functionality can be invoked when processing high velocity, potentially infinite geospatial data streams. The article discusses the performance of these libraries under simulated streaming loads (size, complexity and volume of messages) and how they can be deployed and utilised with Swordfish under real load scenarios, illustrated by a set of Vessel Automatic Identification System (AIS) use cases. We conclude that the described software libraries are able to perform adequately under geospatial data stream processing scenarios - many real application use cases will be handled sufficiently by the software.
Performance of downlink control information signals using decision-feedback channel estimation for EPDCCH

In the Release (Rel.) 11 Long Term Evolution (LTE)-Advanced radio interface, the Enhanced Physical Downlink Control Channel (EPDCCH) is specified, which transmits downlink control information (DCI) signals. The EPDCCH is frequency-domain-multiplexed with data symbols and is used to transmit more DCI signals than the Physical Downlink Control Channel (PDCCH) for Rel. 8 LTE due to the application of multiuser multiple-input multiple-output (MIMO) and coordinated multi-point (CoMP) transmission and reception. This paper presents the effect of decision-feedback channel estimation (DFCE) using soft-symbol estimation of the DCI signals for the EPDCCH. We propose a DFCE method that improves the channel estimation accuracy by using soft-symbol estimation of the control signals based on the a posteriori log-likelihood ratio (LLR) at the soft output Viterbi algorithm (SOVA) for convolutional coding in addition to the demodulation reference signals (DM-RSs). Computer simulation results show that the DFCE is effective in decreasing the transmission power of the DM-RSs to approximately half compared to that for only conventional DM-RSs to achieve the same target block error rate from a low to high Doppler frequency region in a frequency-selective Rayleigh fading channel.
Comparative Analysis of Permanent Magnet Assisted Synchronous Reluctance Motor with External-Rotor

In this paper an effective procedure is employed to assess a set of parameters which have major effect on the rotor design of a permanent magnet assisted synchronous reluctance motor (PMaSynRM) with external-rotor and consequently to deal with the geometrically complicated nature of the rotor. Inserting permanent magnets bricks into the flux barriers has several merits which include saturating the iron ribs in the rotor structure, improvement the torque producing capability and higher power factor. Furthermore, magnetizing inductances along d- and q-axes are significantly important to develop high average torque with low torque pulsation concurrently. Hence, sensitivity analysis of the geometric key parameters of an external-rotor PMaSynRM is carried out. To validate the electromagnetic performance characteristics of the machine different finite element method (FEM) analyses are performed. The analyses results approve the validity of the torque and power factor relations for the studied PMaSynRM. According to the results the electromagnetic torque of the PMaSynRM is increased compared to the pure SynRM because of the added permanent magnet torque.
PRC2 recruitment and H3K27me3 deposition at FLC require FCA binding of COOLAIR

H3K27me3 deposition at FLC requires FCA-COOLAIR binding; SSU72 antagonizes this binding, thus reducing H3K27me3 deposition at FLC. The cold-induced antisense transcript COOLAIR represses FLOWERING LOCUS C (FLC) transcription with increased H3K27me3 and decreased H3K36me3 levels in response to cold temperatures. However, the molecular connection between COOLAIR and histone modification factors in the absence of cold treatment remains unclear. We report that the RNA binding protein FCA interacts with the PRC2 subunit CURLY LEAF (CLF) and binds nascent COOLAIR transcripts to allow deposition of H3K27me3 at FLC. Loss of COOLAIR function results in a reduction in FCA and CLF enrichment, which, in turn, decreases H3K27me3 levels at FLC. The Arabidopsis protein phosphatase SSU72 physically interacts with the RRM1 motif of FCA to antagonize FCA binding with COOLAIR. Mutations in SSU72 caused early flowering, reduced FLC transcription, increased CLF enrichment and H3K27me3, and enhanced affinity between FCA and COOLAIR. Our results suggest that FCA binding of COOLAIR and SSU72 is critical for PRC2 enrichment and H3K27me3 deposition in Arabidopsis.
Resource allocation for secure full-duplex OFDMA radio systems : (Invited paper)

In this paper, we study the resource allocation for an orthogonal frequency division multiple access (OFDMA) radio system employing a full-duplex base station for serving multiple half-duplex downlink and uplink users simultaneously. The resource allocation design objective is the maximization of the weighted system throughput while limiting the information leakage to guarantee secure simultaneous downlink and uplink transmission in the presence of potential eavesdroppers. The algorithm design leads to a mixed combinatorial non-convex optimization problem and obtaining the globally optimal solution entails a prohibitively high computational complexity. Therefore, an efficient successive convex approximation based suboptimal iterative algorithm is proposed. Our simulation results confirm that the proposed suboptimal algorithm achieves a significant performance gain compared to two baseline schemes.
Stemness and chemotherapeutic drug resistance induced by EIF5A2 overexpression in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most lethal malignancies of the digestive tract in East Asian countries. Multimodal therapies, including adjuvant chemotherapy and neo-adjuvant chemotherapy, have become more often used for patients with advanced ESCC. However, the chemotherapy effect is often limited by patients' drug resistance. This study demonstrated that EIF5A2 (eukaryotic translation initiation factor 5A2) overexpression induced stemness and chemoresistance in ESCC cells. We showed that EIF5A2 overexpression in ESCC cells resulted in increased chemoresistance to 5-fluorouracil (5-FU), docetaxel and taxol. In contrast, shRNAs suppressing eIF5A2 increased tumor sensitivity to these chemotherapeutic drugs. In addition, EIF5A2 overexpression was correlated with a poorer overall survival in patients with ESCC who underwent taxane-based chemotherapy after esophagectomy (P < 0.05). Based on these results, we suggest that EIF5A2 could be a predictive biomarker for selecting appropriate chemo-treatment for ESCC patients and EIF5A2 inhibitors might be considered as combination therapy to enhance chemosensitivity in patients with ESCC.
CD34 immunostaining enhances a distinct pattern of intratumor angiogenesis with prognostic implications in clear cell renal cell carcinoma

Clear cell renal cell carcinoma is an aggressive neoplasm related to VHL gene inactivation. The molecular events derived from this initial alteration lead to a permanent intracellular pseudo‐hypoxic status that stimulates vascular proliferation. The resulting increased intratumor angiogenesis is the target of most modern therapies. Although intratumor angiogenesis has received full attention in the last years, few studies have focused on its potential importance from a strict morphological approach. Intratumor angiogenesis has been analyzed in a retrospective series of clear cell renal cell carcinomas (n = 208) with long‐term follow‐up (n = 177). Two different patterns of angiogenesis have been highlighted with CD34 at the front of tumor invasion, termed continuous and discontinuous, respectively. The continuous pattern of angiogenesis showed a complete microvascular network surrounding totally tumor nests. Conversely, the discontinuous pattern displayed an incomplete network around tumor nests. The continuous pattern was associated to shorter 5‐year (p = 0.00064, hazard ratio = 2.8) and 15‐year (p = 0.014, hazard ratio = 1.7) survivals. Cox regression multivariate analysis also showed that the continuous pattern (p = 0.016373) remains a significant variable when considered together with grade (p = 0.001755) and stage (p = 0.000952). These findings support the notion that a continuous CD34+ pattern of intratumor angiogenesis may be useful for pathologists in predicting tumor behavior in clear cell renal cell carcinomas.
Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring

This article describes the results of applying four unsupervised anomaly detection algorithms to data from two rocket propulsion testbeds.The first testbed uses historical data from the Space Shuttle Main Engine. The second testbed uses data from an experimental rocket engine test stand located at NASA Stennis Space Center. The article describes nine anomalies detected by the four algorithms.The four algorithms use four different definitions of anomalousness. Orca uses a nearest-neighbor approach, defining a point to be an anomaly if its nearest neighbors in the data space are far away from it. The Inductive Monitoring System clusters the training data, and then uses the distance to the nearest cluster as its measure of anomalousness. GritBot learns rules from the training data, and then classifies points as anomalous if they violate these rules. One-class support vector machines map the data into a high-dimensional space in which most of the normal points are on one side of a hyperplane, and then classify points on the other side of the hyperplane as anomalous. Because of these different definitions of anomalousness, different algorithms detect different anomalies. We therefore conclude that it is useful to use multiple algorithms.
Programming the Deliberation Cycle of Cognitive Robots

This paper presents an overview of ongoing research that aims to develop a programming language for high level control of cognitive robots and software agents. The language is called 3APL and its formal specification is already presented in (Hindriks et al. 1999). We explain 3APL programming constructs and its existing interpreter. We argue that a part of the deliberation cycle, which is fixed in the interpreter, should be programmable. We discuss a set of programming constructs that can be used to program some aspects of the deliberation cycle.
Interference management in software-defined mobile networks

Software-Defined Networking promises to deliver more flexible and manageable networks by providing a clear decoupling between control plane and data plane and by implementing the latter in a logically centralized controller. However, if such principles are to be applied also to wireless networks, new primitives and abstractions capable of providing programmers with a global view of the network capturing channel quality and interference must be devised. Moreover, the dynamic radio environment necessitates fast adaptation of physical parameters such as power, modulation and coding schemes. So the wireless SDN abstractions should allow for such adaptations to happen closer to the air interface. In this paper, we present high level abstractions for channel quality, interference and network reconfiguration; the latter permits operations differing in timescales to be carried out at different controller entities. The proposed concepts have been implemented and evaluated over a WiFi-based WLAN. Empirical measurements show that the proposed platform can be used to implement typical WiFi network management tasks such as channel assignment and interference monitoring.
Transterm: a database of messenger RNA components and signals

Transterm facilitates studies of messenger RNAs and translational control signals. Each messenger RNA (mRNA) from GenBank is extracted and broken into its functional components, its coding sequence, initiation context, termination context, flanking sequence representing its 5' UTR (untranslated region), 3' UTR and translational signals. In addition, numerical parameters characterising each coding region in Transterm, including codon and GC bias, are available. For each species in Transterm, the initiation and termination regions are aligned by their start or stop codons and presented as base frequency matrices and tables of the information content of the bases in the alignments. Users can obtain summaries of characteristics of the mRNAs for species of their choice and search for translational signals both in the Transterm database and in their own sequence. The current release contains data from over 10 000 species, including the complete genomes of 20 prokaryotes and three eukaryotes. Both flat-file and relational database forms of Transterm are accessible via the WWW at http://biochem.otago. ac.nz/Transterm/
Class I Integrons and SXT Elements in El Tor Strains Isolated before and after 1992 Vibrio cholerae O139 Outbreak, Calcutta, India

We examined the distribution of class I integrons and SXT elements in Vibrio cholerae O1 El Tor strains, isolated in Calcutta, India, before and after the V. cholerae O139 outbreak in 1992. Class I integrons, with aadA1 gene cassette, were detected primarily in the pre-O139 strains; the SXT element was found mainly in the post-O139 strains.
A METHOD FOR COMPARATIVE ANALYSIS OF FOLK MUSIC BASED ON MUSICAL FEATURE EXTRACTION AND NEURAL NETWORKS

A common problem in comparative musicology and ethnomusicology is that large collections of music are difficult to classify and visualize. Therefore, a tool which could be applied to either acoustic signals or symbolic representations would be useful. The choice of the features that are extracted from a collection of music and subsequently used by the tool should be psychologically relevant for the task. This study presents a simple data-mining tool for databases that use a symbolic representation of melodic information. The statistical distributions of melodic events are considered as a suitable features for several reasons. Firstly, the distributions are relatively straightforward to analyze computationally. Secondly, it has been shown that listeners are sensitive to pitch distributional information (Kessler et al. 1984; Oram & Cuddy, 1995; Krumhansl et al, 1999) and they can be used to predict similarity relationships between melodies (Eerola et al, 2001). It is also noteworthy that ethnomusicology has a long tradition in using statistical information to classify music (Freeman and Merriam, 1956; Lomax, 1968) and that there has been more recent attempts to classify musical styles according to their statistical features (Jarvinen, Toiviainen, & Louhivuori, 1999).
Comparing Outcomes of Two Vascular Inflow Occlusion Techniques and Treatment without Vascular Occlusion during Major Hepatectomy in Patients with Hepatitis B-Related Hepatocellular Carcinoma

Background Significant hemorrhage together with blood transfusion has negative impact on postoperative morbidity, mortality, and long-term survival of liver resection. Various techniques of vascular occlusion have been developed to reduce intraoperative blood loss. The objective of this study was to compare the outcomes of Pringle maneuver, hemi-hepatic vascular occlusion, and treatment without vascular occlusion used during liver resection. Method Data of 574 patients with Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), who underwent major hepatectomy between January 2009 to March 2013 by Pringle maneuver (N = 158), hemi-hepatic vascular inflow occlusion (N = 216), or without any vascular occlusion (N = 200), were included in this retrospective study. Perioperative blood transfusion, intraoperative blood loss, and postoperative liver function, and surgical complications were analyzed and compared between the three groups. Result There were no significant difference observed in postoperative bilirubin, liver enzyme, and albumin levels between three groups (P>0.05). 5 patients (2.5%) in no occlusion group, 2 (1.3%) in Pringle group, and 8 (3.7%) in hemi-hepatic group had liver failure; but, there were no differences (P>0.05). The overall postoperative complications rate between three groups did not reach significant differences (33.5% vs 34.2% vs 42.6%, respectively; P>0.05). However, significant differences in intraoperative blood loss between no occlusion group (638.2±426.8 ml) and Pringle group (518.0±451.0 ml) or hemi-hepatic group (513.0±366.7 ml) (P<0.01). Conclusion Although there were no differences found between three groups regarding postoperative complications rate, no vascular occlusion group had more blood loss than the other two groups during liver resection.
Effects of phylogenetic reconstruction method on the robustness of species delimitation using single-locus data

Coalescent‐based species delimitation methods combine population genetic and phylogenetic theory to provide an objective means for delineating evolutionarily significant units of diversity. The generalised mixed Yule coalescent (GMYC) and the Poisson tree process (PTP) are methods that use ultrametric (GMYC or PTP) or non‐ultrametric (PTP) gene trees as input, intended for use mostly with single‐locus data such as DNA barcodes. Here, we assess how robust the GMYC and PTP are to different phylogenetic reconstruction and branch smoothing methods. We reconstruct over 400 ultrametric trees using up to 30 different combinations of phylogenetic and smoothing methods and perform over 2000 separate species delimitation analyses across 16 empirical data sets. We then assess how variable diversity estimates are, in terms of richness and identity, with respect to species delimitation, phylogenetic and smoothing methods. The PTP method generally generates diversity estimates that are more robust to different phylogenetic methods. The GMYC is more sensitive, but provides consistent estimates for BEAST trees. The lower consistency of GMYC estimates is likely a result of differences among gene trees introduced by the smoothing step. Unresolved nodes (real anomalies or methodological artefacts) affect both GMYC and PTP estimates, but have a greater effect on GMYC estimates. Branch smoothing is a difficult step and perhaps an underappreciated source of bias that may be widespread among studies of diversity and diversification. Nevertheless, careful choice of phylogenetic method does produce equivalent PTP and GMYC diversity estimates. We recommend simultaneous use of the PTP model with any model‐based gene tree (e.g. RAxML) and GMYC approaches with BEAST trees for obtaining species hypotheses.
The use of recombinant human TSH in the follow‐up of differentiated thyroid cancer: experience from a large patient cohort in a single centre

background Periodic evaluation of serum thyroglobulin (Tg) and whole body 131I imaging (131I‐WBS) are essential in the follow‐up of differentiated thyroid carcinoma (DTC); both diagnostic modalities require stimulation by high levels of TSH. Administration of recombinant human TSH (rhTSH) is an alternative to the withdrawal of thyroid hormone therapy.
Effective Page Segmentation Combining Pattern Analysis and Visual Separators for Browsing on Small Screens

Page segmentation plays a key role in browsing on small screens. It breaks a large page into smaller segments according to their semantic relationships. Then, various approaches such as single column adaptation and thumbnail view with zooming links can be implemented based on these page segments. However, for current flexible Web pages, segmentation remains a challenging task. This paper proposes an effective automatic segmentation method which combining pattern analysis and visual separators. The basic idea is that a page's semantic structure is largely reflected by repeated continuous patterns and visual separators, which coincides with human's visual perception. The proposed method works in three steps: generating a refined tag tree from the DOM tree, recognizing and merging inexact patterns recursively, and segmenting the others by visual separators. Our experimental results show that the proposed method outperforms existing methods, especially for pages automatically generated from templates