Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and characterization of 23 polymorphic microsatellite loci for Amentotaxus argotaenia (Taxaceae), a relict vulnerable species

Premise of the Study New microsatellite markers were developed for the vulnerable conifer species Amentotaxus argotaenia (Taxaceae) to investigate population genetic variation and the effects of environmental heterogeneity on genetic structure. Methods and Results A total of 27 microsatellite loci were developed from A. argotaenia through a Fast Isolation by AFLP of Sequences COntaining repeats (FIASCO) protocol, of which 23 were polymorphic. These markers yielded 1–13 alleles and 1.0–7.9 effective alleles per locus; levels of observed and expected heterozygosity varied from 0.000–1.000 and 0.000–0.873, respectively. In total, 18 of the markers were transferable to the related species A. yunnanensis. Conclusions These polymorphic markers are a valuable genetic resource for investigating population genetic variation and the potential for local adaptation in A. argotaenia.
Feature Extraction in Sit-to-Stand Task Using M-IMU Sensors and Evaluatiton in Parkinson's Disease

This work proposes a broad analysis for the de-tection of the most relevant features for the sit-to-stand task analysis, in Parkinson's disease (PD) patients and healthysubjects (H). A group of sixteen PD patients and thirteen H subjects have been analyzed, using one magneto-inertial sensor, while the physician administers the UPDRS clinical scale. The PD group has been examined before and after thepharmacological therapy (respectively, OFF and ON phase), in order to monitor the different states of the PD, which implies changes in motor control. By calculating the features of this task, it has been possible to choose the most reliable indexes, already used in this task in order to identify differences in the score assigned through sensors. In addition to that, it has also been possible to find differences in the features' values which the clinical scale and the physician cannotidentify. Our study highlights how wearable motion sensors can detect statistically significant differences between OFF/ON phase and H subjects that the clinical evaluation can not. We conclude that our method provides a deep analysis of the sit-to-stand task with only one M-IMU, allowing to check PD patient status,providing a method for home care monitoring.
The post Nonaka concept of ba: Eclectic roots, evolutionary paths and future advancements

This paper investigates and analyses the concept of ba -- or enabling context - in the fields of information science, information systems and management/business literature in order to understand its conceptual evolution, discussions, applications and expansion since its introduction in 1998 by Nonaka et al. The qualitative methodology is bibliographic and comprises -- among others - the methods of citation analysis and content analysis. A resulting selection of 135 papers, 4 dissertations/theses and 4 books constituted the research's final database. Data analysis consisted of three flows of activities: data reduction, data displays (in the forms of both conceptual and mind maps) and conclusion drawing/verification. The results point out to the identification of four major groups of enabling conditions -- social/behavioral, cognitive/epistemic, informational and business/managerial - which can be singly or freely combined into different knowledge processes -- creation, sharing/transfer and use -- occurring in different levels of interactions -- individual, group, organizational and inter-organizational. Based on these results, a decision cube is proposed in the form of a framework for designing enabling contexts in knowledge organizations. The conclusions suggest that the concept of ba and its underlying concepts are indeed sine qua non conditions for organizational knowledge creation and innovation processes, though ba is still both theoretically and empirically under-explored. Organizations interested in pursuing knowledge management (KM), innovation and ba may wish to be guided by the enabling conditions presented in this paper.
F-Band, GaN Power Amplifiers

This paper reports the design and performance of two new GaN MMIC amplifiers operating at F-band frequencies. The first design produces 28–29 dBm from 102 to 118 GHz, while the second, a broadband design, produces a minimum of 25 dBm across the 98 to 122 GHz band. Both designs exhibit a small-signal gain of 20 dB. In addition, we report a multi-MMIC SSPA with an output power of 2–3 W from 102 to 116 GHz. These are the first reported GaN power results above 100 GHz and the highest power level for any solid-state technology at this frequen-cv.
Physical Layer security in Two-tier Heterogeneous Cellular Networks over Nakagami Channel during Uplink Phase

In this paper, we study the connection and secrecy performance under two-tier cellular network during uplink phase, where both large-scale factor (path propagation loss) and small-scale factor (Nakagami fading) are considered. , which are beyond the scope of the existing works. Analytical expressions of network connection and secrecy probabilities are derived. , which are validated through Monte Carlo simulations. Numerical results reveal that the theoretical expressions of connection and secrecy probabilities are in good agreement with simulation results. Moreover, simulation results demonstrate that larger $m$ value, which means stronger LOS component, leads to a worse connection performance, but a better secrecy secrecy performance.
Universal Radio Hacker: A Suite for Analyzing and Attacking Stateful Wireless Protocols

Proprietary wireless protocols used by IoT devices are designed under size and energy constraints, often neglecting the security. Therefore, attacks like opening wireless door locks or stealing cars are realistic threats. Software Defined Radios (SDR) propose a generic way to investigate such protocols as they can send and receive on nearly arbitrary frequencies. Most tools for SDR, however, focus on the HF side and offer little support for analyzing the actual protocol logic so custom tools or excel spreadsheets must be used. In this paper, we present the Universal Radio Hacker (URH), an open source tool which is designed for protocol analysis from the ground up and implements a full workflow including interfaces for SDRs, intuitive demodulation, customizable decodings, fuzzing support and a simulation component. URH splits the process down into the phases Interpretation, Analysis, Generation and Simulation, whereby results from one phase can be transferred to the other. The software offers all features needed for protocol investigation without overwhelming users with complexity. URH is developed with theoretic oriented researchers in mind who want to focus on protocol logic and try to avoid diving into the depths of HF and Digital Signal Processing.
The acyl-CoA Synthetase, pudgy, Promotes Sleep and Is Required for the Homeostatic Response to Sleep Deprivation

The regulation of sleep and the response to sleep deprivation rely on multiple biochemical pathways. A critical connection is the link between sleep and metabolism. Metabolic changes can disrupt sleep, and conversely decreased sleep can alter the metabolic environment. There is building evidence that lipid metabolism, in particular, is a critical part of mounting the homeostatic response to sleep deprivation. We have evaluated an acyl-CoA synthetase, pudgy (pdgy), for its role in sleep and response to sleep deprivation. When pdgy transcript levels are decreased through transposable element disruption of the gene, mutant flies showed lower total sleep times and increased sleep fragmentation at night compared to genetic controls. Consistent with disrupted sleep, mutant flies had a decreased lifespan compared to controls. pdgy disrupted fatty acid handling as pdgy mutants showed increased sensitivity to starvation and exhibited lower fat stores. Moreover, the response to sleep deprivation is reduced when compared to a control flies. When we decreased the transcript levels for pdgy using RNAi, the response to sleep deprivation was decreased compared to background controls. In addition, when the pdgy transcription is rescued throughout the fly, the response to sleep deprivation is restored. These data demonstrate that the regulation and function of acyl-CoA synthetase plays a critical role in regulating sleep and the response to sleep deprivation. Endocrine and metabolic signals that alter transcript levels of pdgy impact sleep regulation or interfere with the homeostatic response to sleep deprivation.
Flower classification using deep convolutional neural networks

Flower classification is a challenging task due to the wide range of flower species, which have a similar shape, appearance or surrounding objects such as leaves and grass. In this study, the authors propose a novel two-step deep learning classifier to distinguish flowers of a wide range of species. First, the flower region is automatically segmented to allow localisation of the minimum bounding box around it. The proposed flower segmentation approach is modelled as a binary classifier in a fully convolutional network framework. Second, they build a robust convolutional neural network classifier to distinguish the different flower types. They propose novel steps during the training stage to ensure robust, accurate and real-time classification. They evaluate their method on three well known flower datasets. Their classification results exceed 97% on all datasets, which are better than the state-of-the-art in this domain.
Analysis and Modeling of the Charge Collection Mechanism in 28-nm FD-SOI

TCAD simulations on 28-nm fully depleted silicon on insulator structures are used to analyze the charge collection mechanism leading to parasitic current when an ionizing particle passes through the devices. A description of the components constituting the parasitic current is carried out for several strike locations. The bipolar effect does not arise as the main cause of the parasitic current as usually reported. The impact of the drain–source polarization in the collection mechanism is highlighted. A compact model was made, and a quantitative effect was simulated for the pass-gates in an SRAM cell using a variation of the bitline supply.
Adaptive MIMO FSO communication systems with spatial mode switching

In this paper, we propose an adaptive multiple-input multiple-output (MIMO) free-space optical (FSO) system with dynamic adaptation between spatial modes of operation. The proposed adaptive system supports three MIMO modes. In the spatial multiplexing mode, the system transmits independent parallel data streams over multiple apertures to increase data rate. In diversity mode, the system transmits coded streams through multiple apertures to extract diversity gains. In hybrid mode, a trade-off between diversity and multiplexing gains is targeted. For each operation mode, we first derive the outage probability for the MIMO FSO system over log-normal turbulence channels. Then, we formulate the design of an adaptive FSO system to select the MIMO mode that yields the highest throughput while satisfying a predefined target outage probability. Extensive numerical results are provided to demonstrate the performance of the proposed adaptive scheme.
Moving Person Detection Using Blob Descriptors and Support Vector Machine

In this paper a method dedicated to people detection in videos is presented. We have constructed a system which extracts moving objects using background subtraction, then computes HOG descriptors for each object and classifies the objects into “person” or “non-person” using a Support Vector Machine. We have also analyzed possible improvements for background model updating during background subtraction and the opportunity of using a simplified, faster than HOG, descriptor for moving objects. We present and comment our experimental results, pointing out advantages and disadvantages.
SEE Error-Rate Evaluation of an Application Implemented in COTS Multicore/Many-Core Processors

This paper evaluates the error rate of a memory-bound application implemented in different commercial-off-the-shelf multicore and many-core processors. To achieve this goal, two quantitative experiments are performed: fault-injection campaigns and radiation ground testing. In addition, this paper proposes an approach for predicting the application error rate by combining the results issued from both types of experiments. The usefulness of the approach is illustrated by three case studies implemented in processors having different manufacturing technologies and architectures: 45-nm silicon-on-insulator (SOI) free-scale P2041 quad-core processor, 65-nm CMOS Adapteva Epiphany multicore processor, and 28-nm CMOS Kalray multipurpose processing array-256 many-core processor. The reliability of the processors for avionics is obtained from their experimental error rates extrapolated to avionic altitudes. Reliability curves are plotted for observing the prediction accuracy. A comparison of the failure in time of the selected processors shows that the greater single-event effect vulnerability of CMOS technology compared with the SOI one can be compensated with the implementation of effective error detection and correction. These protection mechanisms allow the use of CMOS devices having huge memory capacity in applications operating in severe radiation environments.
MultiFlow: Cross-Connection Decoy Routing using TLS 1.3 Session Resumption

Most approaches to circumventing Internet censorship and monitoring use conventional proxies which are accessed directly by their IP addresses and so are easily blocked. Decoy routing is an alternative approach that deploys a proxy in association with a router, called a decoy router, that is only accessible indirectly when traffic traverses the router. In this work, we design MultiFlow, a new decoy routing protocol that re-uses the TLS protocol’s session resumption mechanism to enable the decoy router itself to resume a client’s session. As a consequence, MultiFlow is able to (1) authenticate a client without blocking traffic inline on the decoy router, and (2) use information provided by the client to bootstrap the establishment of additional secure connections for covert communication. The client and decoy router then use a message board-like tunnel to communicate across multiple connections in a way that mitigates probing and traffic analysis attacks.
FANCI : Feature-based Automated NXDomain Classification and Intelligence

FANCI is a novel system for detecting infections with domain generation algorithm (DGA) based malware by monitoring non-existent domain (NXD) responses in DNS traffic. It relies on machine-learning based classification of NXDs (i.e., domain names included in negative DNS responses), into DGA-related and benign NXDs. The features for classification are extracted exclusively from the individual NXD that is to be classified. We evaluate the system on malicious data generated by 59 DGAs from the DGArchive, data recorded in a large university’s campus network, and data recorded on the internal network of a large company. We show that the system yields a very high classification accuracy at a low false positive rate, generalizes very well, and is able to identify previously unknown DGAs.
Multi-View Graph Embedding Using Randomized Shortest Paths

Real-world data sets often provide multiple types of information about the same set of entities. This data is well represented by multi-view graphs, which consist of several distinct sets of edges over the same nodes. These can be used to analyze how entities interact from different viewpoints. Combining multiple views improves the quality of inferences drawn from the underlying data, which has increased interest in developing efficient multi-view graph embedding methods. We propose an algorithm, C-RSP, that generates a common (C) embedding of a multi-view graph using Randomized Shortest Paths (RSP). This algorithm generates a dissimilarity measure between nodes by minimizing the expected cost of a random walk between any two nodes across all views of a multi-view graph, in doing so encoding both the local and global structure of the graph. We test C-RSP on both real and synthetic data and show that it outperforms benchmark algorithms at embedding and clustering tasks while remaining computationally efficient.
Translation Leak-aside Buffer: Defeating Cache Side-channel Protections with TLB Attacks

To stop side channel attacks on CPU caches that have allowed attackers to leak secret information and break basic security mechanisms, the security community has developed a variety of powerful defenses that effectively isolate the security domains. Of course, other shared hardware resources exist, but the assumption is that unlike cache side channels, any channel offered by these resources is insufficiently reliable and too coarse-grained to leak general-purpose information. This is no longer true. In this paper, we revisit this assumption and show for the first time that hardware translation lookaside buffers (TLBs) can be abused to leak fine-grained information about a victim's activity even when CPU cache activity is guarded by state-of-the-art cache side-channel protections, such as CAT and TSX. However, exploiting the TLB channel is challenging, due to unknown addressing functions inside the TLB and the attacker's limited monitoring capabilities which, at best, cover only the victim's coarse-grained data accesses. To address the former, we reverse engineer the previously unknown addressing function in recent Intel processors. To address the latter, we devise a machine learning strategy that exploits high-resolution temporal features about a victim's memory activity. Our prototype implementation, TLBleed, can leak a 256-bit EdDSA secret key from a single capture after 17 seconds of computation time with a 98% success rate, even in presence of state-of-the-art cache isolation. Similarly, using a single capture, TLBleed reconstructs 92% of RSA keys from an implementation that is hardened against FLUSH+RELOAD attacks.
An exploratory analysis on unsuccessful image searches

As a way of understanding users' information needs for image, this study aims to explore unsuccessful image search questions in context of a social Q&A service. To achieve this purpose, 41 unsuccessful image seeking questions in Yahoo! Answers were explored. 41 questions for image were analyzed in terms of information needs types and image attributes. The findings of this preliminary study show that information needs types are primarily recognized in the Specific and General/Nameable categories with approximately 50%, respectively. More importantly, these information needs are interlaced with multiple image attributes including bibliographic information, quality of image in non-visual feature and image attributes in interpretive category.
"We make it a big deal in the company": Security Mindsets in Organizations that Develop Cryptographic Products

Cryptography is an essential component of modern computing. Unfortunately, implementing cryptography correctly is a non-trivial undertaking. Past studies have supported this observation by revealing a multitude of errors and developer pitfalls in the cryptographic implementations of software products. However, the emphasis of these studies was on individual developers; there is an obvious gap in more thoroughly understanding cryptographic development practices of organizations. To address this gap, we conducted 21 in-depth interviews of highly experienced individuals representing organizations that include cryptography in their products. Our findings suggest a security mindset not seen in other research results, demonstrated by strong organizational security culture and the deep expertise of those performing cryptographic development. This mindset, in turn, guides the careful selection of cryptographic resources and informs formal, rigorous development and testing practices. The enhanced understanding of organizational practices encourages additional research initiatives to explore variations in those implementing cryptography, which can aid in transferring lessons learned from more security-mature organizations to the broader development community through educational opportunities, tools, and other mechanisms. The findings also support past studies that suggest that the usability of cryptographic resources may be deficient, and provide additional suggestions for making these resources more accessible and usable to developers of varying skill levels.
A High-Efficiency E-band SiGe HBT Frequency Tripler with Broadband Performance

A compact E-band frequency tripler with broadband performance is implemented in a $0.13\ \mu \mathrm{m}$ SiGe BiCMOS technology. A high pass filter and transformers impedance matching were used in a fully differential cascode topology to improve the harmonic suppression and broadband performance. Besides, a RF virtual ground capacitor in parallel with base of the CB transistor was proposed in the buffer stage that can enhance the output power by more than 1.7 dB. Followed by a buffer amplifier, the proposed tripler exhibits a measured 3-dB bandwidth ranging from 69 to 86 GHz with a peak output power of 9.9 dBm at 78 GHz. The suppression of fundamental and second-harmonic frequency is more than 35 and 33 dBc, respectively. The tripler can work properly between industrial temperature range (-40°C to 125°C). The tripler with buffer amplifier occupies only 158 mW from a 3.3 V supply. To the best of our knowledge, the proposed tripler demonstrates the highest output power and DC-to-RF efficiency, largest harmonic suppression that covers industrial temperature range compared with other silicon based E-band triplers.
Questions are content: A taxonomy of questions in a microblogging environment

Microblogging services such as twitter.com have become popular venues for informal information interactions. An important aspect of these interaction is question asking. In this paper we report results from an analysis of a large sample of data from Twitter. Our analysis focused on the characteristics and strategies that people bring to asking questions in microblogs. In particular, based on our analysis, we propose a taxonomy of questions asked in microblogs. We find that microblog authors express questions to accomplish a wide variety of social and informational tasks. Some microblog questions seek immediate answers, while others accrue information over time. Our overarching finding is that question asking in microblogs is strongly tied to peoples' naturalistic interactions, and that the act of asking questions in Twitter is not analogous to information seeking in more traditional information retrieval environments.