Miracle-dz/UniFAR-FTUs huggingface dataset:
100 Gbps 0.8-m Wireless Link based on Fully Integrated 240 GHz IQ Transmitter and Receiver

In this work fully integrated wideband IQ transmitter and receiver circuits with on-chip antenna at 240 GHz are presented. The circuits are developed in 130 nm SiGe BiC-MOS technology with fT/ fmax = 300/500 GHz. Transmitter and receiver are mounted as die-on-board and used for a wireless communication experiment. A 6-dB RF bandwidth of 35 GHz is measured for the system in loop-back test, which is equivalent to 17.5 GHz channel bandwidth. Data rates up to 100 Gbps with 16-QAM modulation scheme are presented across a wireless link of 0.8m with EVM of 18.6%. The performance is compared to the literature, demonstrating a state-of-the-art data rate with high level of integration and without special packaging requirements.
Morphological Redescription of the Rare Caprellid Protogeton incertus (Crustacea: Amphipoda: Caprellidae) from Korea

Protogeton incertus Mayer, 1903 belonging to the family Caprellidae was collected from the South Sea, Korea. This species is very similar to Protogeton inflatus Mayer, but it is only distinguishable by the presence of biarticulate mandibular palp. Previous studies provided a very brief description of the species and lacked detailed illustration. In this study, the Korean Protogeton incertus is fully illustrated based on the mature and immature specimens.
Game Theory Approach in Multi-agent Resources Sharing

In multiple real life situations involving several agents, cooperation can be beneficial for all. For example, some telecommunication or electricity providers may cooperate in order to address occasional resources needs by giving to coopetitors some quantities of their own surplus while expecting in return a similar service. However, since agents are a priori egoist, the risk of being exploited is high.In this work, we propose to model this kind of situations as a social dilemma (a situation where Nash Equilibrium is non optimal) in which each agent knows only its own state. We design an algorithm modelling the agents whose goal is to make transactions in order to augment their own utility. The algorithm needs to be robust to defection and encourage cooperation.Our framework modelling each agent consists in iterations divided in four major steps: the communication of demands/needs, the detection of opponent cooperation, the cooperation response policy and finally the allocation of resources.In this paper, we focus on the cooperation response policy. We propose a new version of tit-for-tat and we evaluate it with metrics such as safety and incentive-compatibility. Several experiments are performed and confirm the relevance of our improvement.
Arterial Spin Labeling Image Synthesis From Structural MRI Using Improved Capsule-Based Networks

Medical image synthesis receives much popularity in recent years, and ample medical images can be synthesized by diverse deep learning models to alleviate the problem of lack of data in many medical imaging utilizations. However, most medical image synthesis methods still incorporate the well-known pooling operation in their convolutional neural networks-based / generative adversarial networks-based models, from which image details will be inevitably lost due to the pooling operation. In order to tackle the above problem, improved capsule-based networks, in which no pooling operation is executed and spatial details of images can be effectively preserved thanks to the equivariance characteristics of capsule models, are proposed in this paper to synthesize arterial spin labeling images, for the first time. Technically, three important issues in constructing improved capsule-based networks, including the depth of basic convolutions, the layer of capsules, and the capacity of capsules, are thoroughly investigated. Comprehensive experiments made up of region-based / voxel-based partial volume corrections and dementia diseases diagnosis based on two different datasets are conducted. The superiority of improved capsule-based networks introduced in this paper is substantiated from the statistical point of view.
AlloHaptic: Robot-Mediated Haptic Collaboration for Learning Linear Functions*

Collaborative learning appears in a joint intellectual efforts of individuals to understand an object of knowledge collectively. In their search for understanding the problems, meanings, and solutions, learners employ different multi-modal strategies. In this work, we explore the role of force feedback in learners interaction with tangible hand-held robots. We designed a collaborative learning environment to provide embodied intuitions on linear mathematical functions combined with graphical representations and ran a first study involving 24 participants. Our analysis shows a positive learning gain for our learning activity. Moreover, to explore the link between different types of force feedback and learners’ collaboration, we designed a focus group study with 12 participants. Our results suggest that the haptic communication channel affects the collaboration dynamic differently according to the nature of the learning task. We finish by proposing design insights for future exploration of haptic in collaborative learning.
COVID-19 Outbreak through Tweeters’ Words: Monitoring Italian Social Media Communication about COVID-19 with Text Mining and Word Embeddings

In this paper we aim to analyze the Italian social media communication about COVID-19 through a Twitter dataset collected in two months. The text corpus had been studied in terms of sensitivity to the social changes that are affecting people's lives in this crisis. In addition, the results of a sentiment analysis performed by two lexicons were compared and word embedding vectors were created from the available plain texts. Following we tested the informative effectiveness of word embeddings and compared them to a bag-of-words approach in terms of text classification accuracy. First results showed a certain potential of these textual data in the description of the different phases of the outbreak. However, a different strategy is needed for a more reliable sentiment labeling, as the results proposed by the two lexicons were discordant. Finally, although presenting interesting results in terms of semantic similarity, word embeddings did not show a predictive ability higher than the frequency vectors of the terms.
The Chr X-linked Gct6 locus: A granulosa cell tumor suppressor in mice

Juvenile-type granulosa cell tumors (GCT) originate in the somatic tissues that surround the germ cells of the ovarian follicle in children and young women. Unlike Adult-type GCT that share a common, acquired mutation in the FOXL2 gene, the genetic determinants for juvenile-type GCT susceptibility are not so well defined. A spontaneous, early-onset GCT phenotype in SWR inbred female mice has revealed multiple Gct loci: Gct1 on Chromosome (Chr) 4 initiates the tumorigenic program; Gct4 on Chr X modifies trait penetrance and Gct6 on Chr X is a suppressor of GCT initiation. The Gct6 locus has been mapped to a 1.02 million base pair region with over 20 annotated genes. Two complementary approaches were taken to help prioritize Gct6 gene candidates. First, a congenic strain approach was taken to determine the tumor suppressor phenotype of the Gct6C57 allele in SWR.C57-X females. Second, a whole-locus capture and Next Generation Sequencing (NGS) protocol was applied to identify all nucleotide variations between SWR (tumor-susceptible SW) and Castaneus (CAST; tumor-resistant CA) alleles vs. the C57BL/6J (C57) genome. The congenic strain data supported the hypothesis that a common Gct6 tumor suppressor allele in C57 and CAST genomes was distinct from the permissive Gct6SW allele, which reduced the prioritized list of NGS variants (SNPs, INDELs) to 746. Priority was given to non-synonymous variants identified in the coding region of 5 candidate genes: BC065397, Esx1, Slc25a53, Tmsb15b1 and Tmsb15l. Sanger sequencing confirmed the 5 non-synonymous variants between C57 and SWR strains and identified a novel 28 bp deletion in the coding region of the Slc25a53 gene. Allele association analysis between 5 Gct6 permissive and 2 Gct6 suppressive strains demonstrated that the 5 non-synonymous variants were not conserved between permissive strains. However, all 5 permissive strains tested (SWR, SJL/J, PL/J, BUB/BnJ, ST/bJ) had deletion mutations with inferred deleterious frameshift effect in the Slc25a53 gene when compared to the GC tumor suppressive strains (CAST and C57), making Slc25a53 a promising candidate for shared identity with Gct6.
A Novel 32-Gb/s 5.6-Vpp Digital-to-Analog Converter in 100 nm GaN Technology for 5G Signal Generation

The RF-power digital-to-analog converter (DAC) presented here provides RF-signals in the gigabit regime with voltage swings up to 8.32 V, suitable to drive subsequent single-stage microwave gallium nitride (GaN) power amplifer for sub-six frequencies. A current-steering architecture is driven by a custom algorithm to provide a programmable high output current, up to 250 mA, to a capacitive load such as the capacitive input impedance of an single-stage GaN power amplifier. This architecture provides data rates up to 32 Gb/s with an custom encoding, while the output voltage swing at the load capacitance is higher than 5 Vpp. Therefore, slew rates of up to 76 V/ns can be established.
The Impact of Social Robots in Education: Moral Considerations of Dutch Educational Policymakers

Social robots are increasingly studied and applied in the educational domain. Although they hold great potential for education, they also bring new moral challenges. In this study, we explored the moral considerations related to social robots from the perspective of Dutch educational policymakers by first identifying opportunities and concerns and then mapping them onto (moral) values from the literature. To explore their moral considerations, we conducted focus group sessions with Dutch Educational Policymakers (N = 20). Considerations varied from the potential to lower the workload of teachers, to concerns related to the increased influence of commercial enterprises on the educational system. In total, the considerations of the policymakers related to 15 theoretical values. We identified the moral considerations of educational policymakers to gain a better understanding of a governmental attitude towards the use of social robots. This helps to create the necessary moral guidelines towards a responsible implementation of social robots in education.
Interference Modelling for an Underlay D2D Network for Efficient Resource Allocation

Incorporation of Device-to-Device communication increases the capacity of a wireless network while simultaneously reducing its reliance on the core network, which makes D2D one of the most important enabling technology for 5G and beyond wireless systems. However, these gains in network performance are achieved alongside a considerable increase in interference. Hence, interference modelling is of prime importance.In this work, statistical analysis and modelling of the aggregate interference generated by an underlay D2D network has been done by Gaussian Mixture Models along with statistical validation through two-sample Kolmogorov-Smirnov test. The generated models are utilized for channel allocation and provide significant capacity improvement for a D2D link.The results and analysis presented in this paper provide novel insights upon an interference-resistant D2D network design.
Regret analysis of investment decisions under uncertainty in an integrated energy system

As energy markets underlie significant uncertainties, predictions regarding future developments are difficult and ex-post often proven wrong. In this paper, we develop a two-stage stochastic cost-minimization model of integrated European electricity and gas markets. The model identifies optimal investment decisions in power generation capacity and the scenario-specific optimal dispatch for assets in electricity and gas sectors. The paper presents a regret matrix that examines the performance of first-stage investment decisions under the later realization of considered scenarios. We find that the chance of high regrets strongly depends on the scenario the investment decision is based on. Furthermore, we analyze the impact of each uncertain parameter on the expected regret. We find that neglecting uncertainties with regard to electricity demand levels and CO2 prices in particular, result in a high regret. Furthermore, we quantify the value of perfect information.
Impact of Wide-Scale Data Centre Growth on Power System Operation with Large Share of Renewables

Driven by the large-scale adoption of cloud-based technologies, the past decade has experienced tremendous data centre growth around the globe. In addition to ongoing increases in energy consumption from the sector, the proliferation of data centres also induces a number of electrical network challenges. In this study, their potential to contribute to demand flexibility is analysed, exploring the trade-off between available flexibility and system energy costs, in a day-ahead electricity market. Data centre operation is modelled within a least cost energy mixed integer formulation for the 2030 Irish electricity sector, sourcing 70% of electrical demand from variable renewables. Subsequent impacts on generation and demand schedules, energy costs, renewable energy curtailment, emission levels, plant operational hours, etc. are evaluated, in order to demonstrate how large-scale data centre growth can affect a system’s ability to meet its renewable obligations.
Integrated Photonic Platform for Robust Differential Refractive Index Sensor

We demonstrate an integrated photonic platform comprising a refractive index (RI) sensor based on Photonic Molecule (PM) that effectively mitigates the influence of environmental perturbations using a differential measurement scheme while providing high quality-factor (Q) resonances. The RI sensor consists of a partially unclad microdisk resonator coupled to an external clad microring resonator fabricated on silicon-on-insulator (SOI) platform. We report a RI sensitivity of 24 nm/RIU, achieving a limit of detection (LOD) of 1.7 × 10−3 refractive index units (RIU) with improved stability for an operation range of 0.15 RIU in a compact footprint of 40 × 40 µm2, representing an important solution for real-life applications in which measurement conditions are not easily controllable.
AMMI analysis for stability of grain yield of pearl millet (Pennisetum typhoides L.) hybrids

Nine pearl millet (Pennlsetum typhaldes L.) genotypes (eight hybrids and one variety) were tested over fourteen environments (years/locations) in different zones of Maharashtra. Grain yield data were subjected to the Additive main-effects and multiplicative interaction (AMMI) analyses. Results indicated a significant genotype x environment interaction (GEl) that influenced the relative ranking of the hybrids across the environments. It was evident from AMMI analysis that genotype, environment and the first principal component of interaction effect accounted for 95.20% of treatment sum of squares and the first three principal components of interaction effect were found significant. As per the AMMI model, four genotypes (RHRBH-9802, RHRHH-8609, RHRBH-9807 and RHRBH-9808) were identified as having general adaptability. Further, two environments i.e. 1998/Rahuri-II and 2000/Rahuri-II were found ideal for stable performance of the hybrids.
A Fast and Low Capacity Virtual RAN Recovery based on PDCP Split and Optical Fronthaul Traffic Filtering

This paper proposes a Packet Data Convergence Protocol (PDCP) traffic filtering with virtual distributed unit (vDU) and central unit (vCU) hot-backup to reduce the fronthaul connection recovery time during the virtualized function failure. This architecture permits to maintain the communication between the Evolved Packet Core (EPC) and the User Equipment (UE). Experimental results show that a service recovery time is able to achieve in three seconds.
The effects of synthetic and natural scaffolds on viability and proliferation of adipose-derived stem cells

ABSTRACT This study presents a comparative assessment of adipose-derived stem cell (ADSCs) proliferation rates and their viability on five different scaffolds. Five different biomaterial scaffolds were prepared: alginate, poly lactic-co-glycolic acid, fibrin glue, inactive platelet-rich plasma, and active platelet-rich plasma (APRP). Stem cells were isolated from human adipose tissue. Flow cytometry analysis was performed. Specifically, adipogenesis/osteogenesis/chondrogenesis-associated genes expression was analyzed by real-time polymerase chain reaction. These cells were seeded in the prepared scaffolds. After 14 days, the proliferation and viability of MSCs were evaluated using an MTT assay. Also, stemness genes expression was analyzed with the reverse transcriptasepolymerase chain reaction (RT-PCR) method. In addition, the DNA content assay was also performed. The obtained results showed a significant difference between cell proliferation and viability of different scaffolds. APRP and alginate were shown to be the most and least suitable scaffolds in terms of enhancing cell proliferation and maintaining cell viability respectively (p < .05). RT-PCR reactions demonstrated the expression of the various stemness-related markers (Nanog, Octamer4A, and Sox2) when ADSC cells were grown separately on the five different scaffolds. Our study indicates that compared with the scaffolds, APRP could be the best scaffold for support of ADSC proliferation.
Investigation into the role of odontocete teeth in sound reception on the example of the common bottlenose dolphin, Tursiops truncatus.

Echolocation is the primary tool dolphins depend on for their survival underwater. Without this ability, the localization of food and navigation would be much harder for the animals. This active sonar is characterised by narrow transmission and reception directivity patterns, over a variety of ranges. In Cetaceans, only toothed whales and dolphins (odontocetes) are able to echolocate. The main concept for echolocation is to emit sound and listen to the returning echoes. Where sound enters the head first and how the signals are transmitted to the mandibular fats and inner ears is not fully understood. There are several theories on how sound reaches the fatty tissues in the lower jaw: through a thin region in the lower jaw called the pan bone, through the throat region and an opening in the rear mandibles and through the teeth, acting as an end-fire array and enhancing the directional hearing. The hypothesis on sound reception via the teeth was investigated further in this thesis. The sound pressure was modelled at the teeth of a bottlenose dolphin (Tursiops truncatus) using acoustic characteristics of different components of the entire jaw. The angle of the jaw was changed from 0° to ±10° in 1 degree steps and from ±10° to ±90° in 5 degree steps. The pressure was measured at 3 front and back teeth and the difference between pressure values compared. The pressure was also measured at each of the 22 teeth on both sides of the jaw for two different angles, 0° and +5°. Multiple scattering and the influence from the relative positions and sizes of teeth as well as the effect of missing teeth was investigated. Results show that the propagation of sound varies with size and position of the teeth. The simulations display the relation between neighbouring teeth and the attenuation or amplification of the signals at other teeth. Teeth cannot be considered as individual point-like receivers. A pressure tendency can be seen at the back teeth for the first ±15°, which indicates that directional hearing occurs for the first degrees the dolphin moves its head. It also shows that hearing takes place primarily at the back of the jaw.
Interviewing Style for a Social Robot Engaging Museum Visitors for a Marketing Research Interview

We design and evaluate a robot interviewer for collecting visitor data in a museum for marketing purposes. We take inspiration from research on face-to-face human intercept interviews. We develop a personal interviewing style that is expected to motivate participants to answer more questions and compare this with a more formal style. We also evaluate whether a greeting ritual performed by the robot increases participation and whether taking a picture with the robot is an effective incentive for visitors to participate in an interview.Our study is conducted "in the wild" and we analyse sessions with the robot and passersby in a museum. The independent variables were interviewing style and whether an incentive was offered or not. The dependent variables were participation and continuation rate, and museum ratings. Contrary to expectations, we find that the participation rate is lower when the robot provides an incentive. Although we find that a personal style is perceived as more social, it does not influence the continuation rate. Museum ratings were also not affected by style. Our style manipulation may not have been strong enough to produce these effects.Our study shows that social robots have a high potential for conducting intercept interviews. Willingness to participate in a robot interview is high, while this is one of the main challenges with intercept interviews. To improve data collection, people detection and speech recognition skills could be improved.
Characterisation of the yeast RNA helicase Prp43

Characterisation of the yeast RNA helicase Prp43 R helicases have many important roles in cell metabolism and are involved in numerous pathways, e.g. translation, pre-mRNA splicing and biogenesis. Interestingly, an increasing number of RNA helicases have been shown to be required for more than one cellular pathway. Therefore, protein cofactors have been suggested to recruit multifunctional RNA helicases to their substrates and regulate their activity. The best characterised family of helicase cofactors are G-patch proteins, which all contain a glycine-riche domain. This work focuses on the characterisation of the yeast RNA helicase Prp43 and its G-patch protein cofactors. Additionally, a new G-patch protein cofactor of Prp43 was identifi ed and characterised. Together, the data suggest that protein cofactors can regulate the distribution and activity of RNA helicases in different pathways.
A DC-32GHz 7-Bit Passive Attenuator with Capacitive Compensation Bandwidth Extension Technique in 55 nm CMOS

This paper presents a 7-bit wideband passive attenuator with low insertion loss (IL) and high attenuation accuracy from DC to Ka band, designed and fabricated in a 55-nm CMOS technology. Staggered π-type and bridge-T type stages with capacitive compensation are proposed to minimize amplitude and phase errors, and to extend its operation bandwidth. The chip demonstrates a 32.385-dB attenuation range with a 0.255-dB attenuation step and a 3.5-8.4 dB IL across DC to 32 GHz. The measured RMS amplitude and phase errors are below 0.32 dB and 5.33° respectively. The die occupies 0.054 mm2(0.632 mm × 0.086 mm) core area and consumes negligible power. To the best of our knowledge, this work shows the smallest area and the widest bandwidth among the reported switch type attenuators.