Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-Complexity Subspace MMSE Channel Estimation in Massive MU-MIMO System

Massive multi-user multiple-input multiple-output (massive MU-MIMO) technology is considered as a promising enabler to fulfill the rapid growth of traffic requirement for wireless mobile communications. The massive MU-MIMO system can achieve unlimited capacity when the base station (BS) has accurate channel state information (CSI). In time-division-duplex (TDD) mode, the BS estimates CSI by receiving pilot signals sent from user terminals (UEs). However, because of using non-orthogonal pilots, pilot contamination happens to degrade the quality of the CSI estimation. To deal with pilot contamination problem, a low-complexity subspace minimum mean square error (MMSE) estimation method is proposed in this paper. Specifically, our approach operates the MMSE estimation in a low-dimensional subspace to avoid large matrix manipulation. Meanwhile, subspace projection helps to discriminate the desired signal and interfering signals in the power domain. Interference analysis shows the MMSE estimation can achieve interference-free estimation even in a low-dimensional subspace with a large number of BS antennas, and non-overlapping angles of arrival (AoAs) between desired and interfering UEs. Furthermore, thanks to the low-rank property of the channel covariance matrix in massive MU-MIMO systems, a two-step covariance matrix subspace projection method is proposed for further computational complexity reduction. The complexity analysis and simulation results indicate that our proposed approach has better channel estimation accuracy with lower complexity than the conventional MMSE estimation when the number of BS antennas is large.
The Impact of Scope Creep on Project Success: An Empirical Investigation

Advocates of software engineering and software project management stated in the literature that creeping of scope is one of the most common causes for the failure of software projects. Also, advocates believed that it could occur in almost every software project, which leads to compromise in quality, delayed schedules, increase cost and decreased customer satisfaction. However, the lack of empirical evidence demands a comprehensive investigation to identify the factors of scope creep and to propose a conceptual framework to empirically evaluate the impact of scope creep on software project success. To determine the scope creep factors in this study, two exploratory methods, i.e. a Systematic Literature Review (SLR) and interview from experts are performed. Following the analysis of these methods, a conceptual framework is proposed. To empirically evaluate the proposed conceptual framework, data is collected through a survey method. Next, the collected data is analyzed through Partial Least Squares’ Structural Equation Modelling (PLS-SEM). From the results, it is evident that the identified factors of scope creep are negatively associated with software project success. The results of empirical evaluation also second the findings of SLR. The outcome of the study may help the practitioners to understand the dynamics of factors, which undermine scope creep in software SMEs and to assist them in the development of effective control and mitigation strategies, therefore, to increase the project success rate.
RegII Is a β-Cell Protein and Autoantigen in Diabetes of NOD Mice

The Reg family of proteins has been studied in the context of growth and regeneration in several organs including pancreatic islets. We previously suggested that Reg proteins act as autoantigens in type 1 diabetes, based on evidence that a member of the Reg family (hepatocellular carcinoma intestine pancreas [HIP]/pancreatitis-associated protein [PAP]) was overexpressed in the islets of a patient who died after sudden onset of type 1 diabetes, and that, in NOD mice, Reg-specific T-cells adoptively transferred diabetes. In the current study, we developed antisera to detect individual Reg members in mouse islets and found that RegIIIα was present in the non–β-cell portion of the islets, while RegII was predominantly expressed in β-cells. Vaccination of NOD mice with the separately expressed N-terminal (NtfrII) or C-terminal (CtfrII) portion of RegII revealed a dichotomy: NtfrII vaccination accelerated and CtfrII vaccination delayed type 1 diabetes. Vaccination with CtfrII was more effective when given at later stages in the pathogenesis of type 1 diabetes, a time dependency different from that seen with other antigen-dependent vaccine strategies in NOD mice, which might have therapeutic implications. In conclusion, RegII is a novel β-cell–derived autoantigen in NOD mice. The autoimmune response against this protein may convert a regenerative into an islet-destructive process accelerating development of type 1 diabetes.
GATE: Graph-Attention Augmented Temporal Neural Network for Medication Recommendation

Medication recommendation based on Electronic Health Records (EHRs) is an important research direction, which aims to make prescription recommendations according to EHRs of patients. Most existing methods either only make recommendation through EHRs of the current admission while ignoring the patient’s historical records, or fail to fully consider the correlations among the clinical events from every single admission. These methods have shown their limitations in dealing with the complex structural correlations and temporal dependencies of clinical events in EHRs, which results in the defect of recommendation quality as well as the lack of temporal prediction ability. For that, a novel graph-attention augmented temporal neural network is proposed to model both the structural and temporal information simultaneously. For each admission record, a co-occurrence graph is constructed to establish the correlations among clinical events, and then a graph-attention augmented mechanism is used to learn the structural correlations on the graphs to obtain better representation of this admission. Then a temporal updating module based on the gated recurrent units is further proposed to learn the temporal dependencies between multiple admissions of each patient. Furthermore, our proposed model is also constrained by the co-occurrence graph, which can capture the internal correlations of clinical events and provide better modeling capability when the training data is sparse. Experiments illustrate that our model is superior to the state-of-the-art methods on a real-world dataset MIMIC-III in all effectiveness measures.
Variations in harbour seal Phoca vitulina diet and dive‐depths in relation to foraging habitat

We use information on the at-sea distribution of radio-tagged seals to identify the summer foraging areas used by 31 harbour seals from two different haul-out sites in the Moray Firth, N.E. Scotland. We then determine whether seals tend to occur over particular sediment types or water depths as hypothesized by Harkonen (1987b), and assess whether local geographical variations in diet composition can be related to local differences in available foraging habitat. The majority of seals foraged within 30 km of their haul-out site, consequently there was broad overlap between the foraging areas used by animals from the same site, but little overlap in the areas used by seals from different sites. Most seals foraged in water depths of 10-50 m with mainly sandy sea-bed sediments. Data on the distribution of dive depths of five seals which were fitted with time-depth-recorders indicated that seals were generally diving on, or close to, the sea-bed. Occasional pelagic dives between the more common benthic dives were also observed. Between-site differences in the seals' use of different water depths and sea-bed sediments suggest that local geographical variations in diet were related to local differences in foraging habitats, but that habitat use also differed between individual seals.
IETCR: An Information Entropy Based Test Case Reduction Strategy for Mutation-Based Fault Localization

Mutation-based fault localization (MBFL) is a recently proposed technique with the advantage of high fault localization accuracy. However, such a mutation analysis based technique is difficult to be accepted by industry due to its huge computational cost on mutation analysis. There are three ways to improve MBFL’s efficiency, which are reducing the number of mutants, optimizing the mutants’ execution process, and reducing the number of test cases. The former two ways have been mainly studied and shown promising results, but for the latter way, the related studies are limited since this kind of method will reduce the precision of MBFL. In this paper, we mainly focus on the latter way and propose an information entropy based test case reduction (IETCR) strategy for MBFL. In particular, we first calculate the entropy change of test cases and select a proportion of them according to their value. Then we use a reduced test suite to execute mutants. To show the effectiveness of the IETCR strategy, we choose six real-world programs with 112 faulty versions. In terms of mutation reduction rate, we find MBFL with the IETCR strategy can reduce 56.3%~88.3% cost while keeping almost the same fault localization accuracy when compared to the original MBFL without test case reduction. Moreover, we use Wilcoxon signed-rank test for statistical analysis, which shows that there is no statistically significant difference between MBFL with IETCR strategy and the original MBFL.
Tumnanosat Nanosatellite and Kibocube Program

This paper presents a brief overview of the first Moldavian satellite – TUMnanoSAT designed at the Technical University of Moldova Space Technology Center, included in KiboCube Program. In the paper are described educational missions of this nanosatellite and overall system overview, including: structure, electrical power supply, processing and data management and telemetry communications.
SIGNIFICANCE OF QUINONES IN THE CLASSIFICATION OF BACTERIA

Recently, instrumental analysis of metabolic products and cellular components have been applied to bacterial taxonomy. YAMADA et al. (1) already reported that the kind of quinones and the length of its isoprenoid side-chain may be used as a simple and effective criterion to distinguish the genera Gluconobacter and Acetobacter without exception. On the relation between gram stain and the kind of quinones, CRANE (2) described that only ubiqui none was found in the gram-negative bacteria, only menaquinone in the gram-positive bacteria, and both types of quinones in Escherichia coli and Proteus vulgaris, although his data were incomplete. In the case of genus Bacillus, gram stain, one of the moat important criteria of bacterial classification, cannot be used to characterize the genus because the bacteria classified in the genus Bacillus have gram-positive, -negative, and variable stainability. Therefore, examinations were made on whether the kind of quinones and the length of its side chain were different or not in the case of such bacteria which show varieties in gram staining. The 20 strains of genus Bacillus were obtained from JAM Culture Collection, University of Tokyo. The cells cultured for 1, 3, and 6 days on nutrient agar slants at 30°, except for Bacillus stearothermophilus at 37°, were stained by the HUCKER modification (3). Among these 20 strains of the genus Bacillus, 9 were found to be gram-positive, 5 gram-variable, and 6 gram negative (Table 1). The types of quinone were decided by the following methods. The cells were cultured to stationary phase in nutrient broth with shaking at the temperature mentioned above. They were collected by centrifugation, washed twice with water, and lyophilized. Quin ones were extracted from the lyophilized cells with ethanol-ether (3: 1). The solvent was distilled off under vacuum, the residue was dissolved in acetone,, and the insoluble phospholipid was removed (4). The purified extract was further purified over alumina column and/or by thin-layer chromatography
The role of the farnesoid X receptor in metabolic control

Farnesoid X receptor (FXR, NR1H4) has been implicated in control of fat and energy metabolism but the physiological role of this nuclear receptor in fat tissue is not understood. We show that, on a chow diet, transgenic mice that overexpress FXR under the control of the aP2 (Fabp4) promoter have enlarged adipocytes in white adipose tissue (WAT). On a high-fat diet (HFD), these mice show limited expansion of WAT due to impaired adipogenesis and inability of existing adipocytes to enlarge further. Adipose tissue transcriptome and secretome profi ling revealed extensive FXR-dependent extracellular matrix (ECM) remodeling, suggesting that alterations in ECM contribute to disturbed WAT expansion. As in WAT, brown adipose tissue (BAT) of chow-fed FXR transgenic mice shows evidence of reduced differentiation and ECM alterations. Consequently, BAT functioning was attenuated upon metabolic and environmental stressors like HFD-feeding and cold exposure. These studies establish that FXR is a determinant of fat tissue development and function. Induction of extracellular matrix deposition in fat depots may be key herein. This work suggests that FXR in adipose tissue is implicated in obesity and obesity-associated pathologies related to ectopic fat deposition.
Broadband Substrate Integrated Waveguide Cavity-Backed Irregular Shaped Slot Antenna using Particle Swarm Optimization

In this paper, a broadband substrate integrated waveguide (SIW) cavity-backed irregular shaped slot antenna is proposed. The irregularly shaped slot whose dimensions have been optimized using an evolutionary algorithm called particle swarm optimization (PSO) by fixing its position has been proposed to achieve the broadband response. This antenna maintains the characteristics of low profile, unidirectional radiation while enhancing the bandwidth. The cavity size of the antenna is designed such that it generates two modes (TE110 and TE120) in the desired frequency range. The shape of the slot aids to couple the two obtained modes in a vicinity region and thus increasing the effective bandwidth.
Social Internet of Things (SIoT): Techniques, Applications and Challenges

Internet of Things (IoT) is anticipated to be run over by huge amount of connected instances (both homogeneous and heterogeneous) enabling the interaction with each object for developing the various services in IoT domain. In addition with, involvement the social or human actions in IoT platform derives the new paradigm in IoT environment that is called as Social Internet of Things (SIoT). The working layer of SIoT divided into 3 layer structures with different set of functionalities, techniques, protocols for computation and communications. Through the SIoT prototype, the potential of social beings and objects to discover, select, and use with their services in the IoT is augmented. Now, the SIoT grows in rapid manner in the various real time IoT applications with different I(oT instances like IP based phones, cameras, healthcare devices, television, and cars with determined user interference. Finally, this paper surveyed on various techniques, applications, inferences and challenges associated with Social IoT (SIoT).
An Evaluation of the Physical Layer Characterization of 5G Networks

The Next-Generation Network (NGN), referred to as the Fifth Generation (5G) network, is required to provide users with very high data rates, extremely low latency, massive connectivity, network reliability, and energy efficiency for a wide range of applications. 5G will only achieve these goals through the help of vital enabling technologies such as millimeter Wave (mmWave) communication system, massive Multi Input Multi Output (mMIMO) technology, Heterogeneous Network systems (HetNets), each with varying propagation characteristics and underlying channel conditions. This research aims at conducting an evaluation of the physical layer characteristics of 5G network, by modeling the diverse channel conditions, and comparing them in terms of the average sum and cumulative density function (CDF) of the spectral efficiency (SE), signal to interference noise ratio (SNR), power consumption, and general energy efficiency respectively. The MATLAB tool is employed to perform channel modeling, resource allocation, channel estimation, and simulation for the different 5G Channels. The results indicate that mmWave technology operating a mMIMO system presents a higher SE when related to the number of Base Station (BS) antennas used in both Line of Sight (LOS) and Non-Line of Sight (NLoS) deployments. The HetNet system, however, yields greater spectral efficiency when related to the number of User Equipments (UEs) connected. Furthermore, the mMIMO also shows a faster response in overall SE when the number of connections are relatively small as compared to other technologies. This is due to the lower bandwidth and operations below 6 GHz frequencies. In terms of backup power for the UEs in a dense network, mMIMO deployment shows a faster response with more effective SE.
Environment Sound Event Classification With a Two-Stream Convolutional Neural Network

In recent years, with the construction of intelligent cities, the importance of environmental sound classification (ESC) research has become increasingly prominent. However, due to the non-stationary nature of environment sound and the strong interference of ambient noise, the recognition accuracy of ESC is not high enough. Even with deep learning methods, it is difficult to fully extract features from models with a single input. Aiming to improve the recognition accuracy of ESC, this paper proposes a two-stream convolutional neural network (CNN) based on raw audio CNN (RACNN) and logmel CNN (LMCNN). In this method, a pre-emphasis module is first constructed to deal with raw audio signal. The processed audio data and logmel data are imported into RACNN and LMCNN, respectively to obtain both of time and frequency features of audio. In addition, a random-padding method is proposed to patch shorter data sequences. In such a way, the available data for experiment are greatly increased. Finally, the effectiveness of the methods has been verified based on UrbanSound8K dataset in experimental part.
A Comparative Study on the Support in Engineering Courses: A Case Study in Brazil and Spain

The gender gap in engineering careers is a well-known problem. Despite several studies showing the under-representation of women in STEM fields, few explore the factors that influence before entering and during the engineering studies, including the practices in the labor market. The support from the social context, such as family, friends, or teachers, can influence the attraction rates and dropout rates of the engineering studies. This paper presents a survey to analyze the gender and culture perceptions of supports in engineering studies, involving 208 female and male undergraduate students of engineering courses from Spain and Brazil. Some findings of this study show that the sample average (32.69%) followed the standard ratio of around 30% of women in STEM careers. Almost 70% of the female students decided to enroll in an engineering career during high school or vocational training courses. In Spain, the support of families and friends is higher than Brazil, but the support received from their academic institutions and teachers were low in both countries, regardless of gender. In the labor market, the male workers in Spain seem to be less supported than their female colleagues.
A General Mathematical Model for LVRT Capability Assessment of DER-Penetrated Distribution Networks

Low voltage ride through (LVRT) is one of the indispensable issues of recent decade in the context of grid codes. LVRT stands for the ability of a generation facility to stay connected during the voltage dip. Despite the numerous discussions in recent works, but they mostly concentrate on the LVRT-based control of distributed energy resources (DERs) integrated into a microgrid and its improvement. However, what has been hidden and not addressed any more yet is an index to measure the LVRT capability of a DER-penetrated distribution network (DPDN) under different voltage sags. This takes precedence when we want to evaluate the LVRT capability of DPDNs with consideration of various LVRT categories of DERs mandated in IEEE 1547 standard. This paper introduces a general framework for LVRT assessment of a DPDN by solving a system of differential algebraic equations (DAEs). Then expected LVRT capability of a DPDN is evaluated by a proposed LVRT index through the implementation of Monte Carlo simulation technique.
Fairness-Aware Offloading and Trajectory Optimization for Multi-UAV Enabled Multi-Access Edge Computing

Multiple unmanned aerial vehicles (UAVs) can compensate for the performance deficiencies of a single UAV in multi-access edge computing (MEC) systems, thus providing improved offloading services to user equipments (UEs). In multi-UAV enabled MEC systems, the offloading strategy and UAVs’ trajectories affect the fairness of both UEs and UAVs, which affects the UE experience and UAVs’ existence durations. Therefore, we investigate fairness-aware offloading and trajectory optimization in the system. To ensure fairness of energy consumptions (ECs) for both UEs and UAVs, we minimize the weighted sum of the maximum EC among UEs and the maximum EC among UAVs subject to the task delay, the offloading strategy and UAVs’ trajectories constraints. Despite the non-convexity of the original formulated joint optimization problem, we transform the problem into two sub-problems and solve them one by one. Finally, an iterative optimization algorithm is proposed to alternately optimize the offloading strategies and the UAVs’ trajectories. Simulation results show that the proposed algorithm can effectively reduce both the maximum EC among UEs and the maximum EC among UAVs and ensure the fairness of both the UEs and UAVs.
Movements and Home Ranges of Crocodylus johnstoni in the Lynd River, Queensland

Movements of Australian freshwater crocodiles, Crocodylus johnstoni, were examined by a mark‐recapture study spanning 20 years in the Lynd River, Queensland. After adjustment for detection bias, there was a minor upstream direction to movements. Seasonal changes of location were not evident from field trips taken only twice yearly. Annual movements averaged less than 1 km except for those of pubescent males, which appeared to be nomadic. Creche dispersal was randomly directed but associated with a threshold in mass/length ratio. On average, males were found further from previous capture sites than were females. Adults of both sexes moved shorter distances than did immature crocodiles with a clear reduction in movements occurring as mass/length ratios approached 0·17 kg per cm snout‐vent length. Reduced movement at that general size ratio probably indicated the onset of territoriality associated with maturity. Females usually remained near breeding sites even in years when they did not breed. Nomadic tendencies of pubescent males are probably associated with unsuccessful attempts at entering local dominance hierarchies. Linear home ranges were estimated to be 1·5‐1·9 km for immature animals, 1·2 km for pubescent females, 30·3 km for pubescent males, 0·6 km for mature females and 1·6 km for adult males.