Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Resolution of Reef-Coral Endosymbiont (Symbiodinium) Species Diversity, Ecology, and Evolution through psbA Non-Coding Region Genotyping

Ribosomal DNA sequence data abounds from numerous studies on the dinoflagellate endosymbionts of corals, and yet the multi-copy nature and intragenomic variability of rRNA genes and spacers confound interpretations of symbiont diversity and ecology. Making consistent sense of extensive sequence variation in a meaningful ecological and evolutionary context would benefit from the application of additional genetic markers. Sequences of the non-coding region of the plastid psbA minicircle (psbAncr) were used to independently examine symbiont genotypic and species diversity found within and between colonies of Hawaiian reef corals in the genus Montipora. A single psbAncr haplotype was recovered in most samples through direct sequencing (∼80–90%) and members of the same internal transcribed spacer region 2 (ITS2) type were phylogenetically differentiated from other ITS2 types by substantial psbAncr sequence divergence. The repeated sequencing of bacterially-cloned fragments of psbAncr from samples and clonal cultures often recovered a single numerically common haplotype accompanied by rare, highly-similar, sequence variants. When sequence artifacts of cloning and intragenomic variation are factored out, these data indicate that most colonies harbored one dominant Symbiodinium genotype. The cloning and sequencing of ITS2 DNA amplified from these same samples recovered numerically abundant variants (that are diagnostic of distinct Symbiodinium lineages), but also generated a large amount of sequences comprising PCR/cloning artifacts combined with ancestral and/or rare variants that, if incorporated into phylogenetic reconstructions, confound how small sequence differences are interpreted. Finally, psbAncr sequence data from a broad sampling of Symbiodinium diversity obtained from various corals throughout the Indo-Pacific were concordant with ITS lineage membership (defined by denaturing gradient gel electrophoresis screening), yet exhibited substantially greater sequence divergence and revealed strong phylogeographic structure corresponding to major biogeographic provinces. The detailed genetic resolution provided by psbAncr data brings further clarity to the ecology, evolution, and systematics of symbiotic dinoflagellates.
Peyronie's Disease: Evolving Surgical Management and the Role of Phosphodiesterase 5 Inhibitors

Peyronie's disease (PD) is a fibrotic disorder of the tunica albuginea of the penis. It is characterized by different degrees of penile curvature and sexual dysfunction. Several medical treatments have been employed to manage the disorder, with variable success rates. Surgical therapy is reserved for patients with severe penile deformity that fails to improve with medical treatment and impedes coital function. The advantages and disadvantages of various surgical approaches have long been debated. Herein, we describe the evolving surgical techniques for PD using knowledge obtained from the contemporary literature. In addition, we discuss the emerging data regarding the role of phosphodiesterase 5 inhibitors in the management of PD.
Comparison of integer frequency offset estimators for OFDM systems

In this paper, a new maximum likelihood (ML) estimator for the integer frequency offset estimation of OFDM systems is proposed and compared with the conventional SC estimator. Both estimators exploit the differential information between two consecutive blocks of OFDM data symbols in the frequency domain. The reason why the proposed ML estimator has better performance than the conventional SC method is analyzed. The mean and variance of the proposed and conventional estimators are discussed, and the estimation error probability is given. The computer simulation results are in good agreement with the analytical study.
Scalable Cluster-based Routing in Large Wireless Sensor Networks

Large control overhead is the leading factor limiting the scalability of wireless sensor networks (WSNs). Clustering network nodes is an efficient solution, and Passive Clustering (PC) is one of the most efficient clustering methods. In this letter, we propose an improved PC-based route building scheme, named Route Reply (RREP) Broadcast with Passive Clustering (in short RBPC). Through broadcasting RREP packets on an expanding ring to build route, sensor nodes cache their route to the sink node, which reduces the total route search times and thus the control overhead. Simulation results are also provided to show the efficiency of the proposed RBPC in terms of reduced overhead and energy consumption, and it is also shown that RBPC outperforms AODV/PC in the delivery ratio.
Talking to children about parental mental illness: The experiences of well parents

Background: Children of parents with mental illness are not routinely included in psychoeducational and supportive family interventions provided by adult mental health systems. The family, therefore, is an important and, sometimes, the only source of information and support for them. Aim: To understand the experiences of well parents in talking to their children about parental mental illness. Method: This article presents the findings of a qualitative study of the experiences of well parents in talking to their children about parental mental illness. Ten well parents whose spouses were diagnosed with a severe mental illness participated in the study. Socio-demographic information, family details and history of the spouse’s mental illness along with their experiences of talking to children about parental mental illness, the perceived risks and benefits, challenges they faced and the role of others in the process were recorded. Qualitative data were analysed using interpretative phenomenological analysis. Findings: The themes of ‘distancing children from parental mental illness’, ‘avoiding conversations about the illness’, ‘giving and receiving emotional support’, ‘providing explanations of the illness’ and ‘regulating other sources of information’ show the complex ways in which well parents influence their children’s understanding of parental mental illness. The findings are examined in the background of what is known about this topic from the perspective of children or of the parent with illness. Possible ways to support well parents in families affected by parental mental illness are discussed. Conclusion: This study is a step forward in the understanding of how families talk to children about parental mental illness and provides the perspective of the well parent.
A novel semi-supervised approach for network traffic clustering

Network traffic classification is an essential component for network management and security systems. To address the limitations of traditional port-based and payload-based methods, recent studies have been focusing on alternative approaches. One promising direction is applying machine learning techniques to classify traffic flows based on packet and flow level statistics. In particular, previous papers have illustrated that clustering can achieve high accuracy and discover unknown application classes. In this work, we present a novel semi-supervised learning method using constrained clustering algorithms. The motivation is that in network domain a lot of background information is available in addition to the data instances themselves. For example, we might know that flow ƒ1 and ƒ2 are using the same application protocol because they are visiting the same host address at the same port simultaneously. In this case, ƒ1 and ƒ2 shall be grouped into the same cluster ideally. Therefore, we describe these correlations in the form of pair-wise must-link constraints and incorporate them in the process of clustering. We have applied three constrained variants of the K-Means algorithm, which perform hard or soft constraint satisfaction and metric learning from constraints. A number of real-world traffic traces have been used to show the availability of constraints and to test the proposed approach. The experimental results indicate that by incorporating constraints in the course of clustering, the overall accuracy and cluster purity can be significantly improved.
Acute Viral Escape Selectively Impairs Nef-Mediated Major Histocompatibility Complex Class I Downmodulation and Increases Susceptibility to Antiviral T Cells

ABSTRACT Nef-specific CD8+ T lymphocytes (CD8TL) are associated with control of simian immunodeficiency virus (SIV) despite extensive nef variation between and within animals. Deep viral sequencing of the immunodominant Mamu-B*017:01-restricted Nef165–173IW9 epitope revealed highly restricted evolution. A common acute escape variant, T170I, unexpectedly and uniquely degraded Nef's major histocompatibility complex class I (MHC-I) downregulatory capacity, rendering the virus more vulnerable to CD8TL targeting other epitopes. These data aid in a mechanistic understanding of Nef functions and suggest means of immunity-mediated control of lentivirus replication.
Systems biology of personalized nutrition

Abstract Personalized nutrition is fast becoming a reality due to a number of technological, scientific, and societal developments that complement and extend current public health nutrition recommendations. Personalized nutrition tailors dietary recommendations to specific biological requirements on the basis of a person’s health status and goals. The biology underpinning these recommendations is complex, and thus any recommendations must account for multiple biological processes and subprocesses occurring in various tissues and must be formed with an appreciation for how these processes interact with dietary nutrients and environmental factors. Therefore, a systems biology–based approach that considers the most relevant interacting biological mechanisms is necessary to formulate the best recommendations to help people meet their wellness goals. Here, the concept of “systems flexibility” is introduced to personalized nutrition biology. Systems flexibility allows the real-time evaluation of metabolism and other processes that maintain homeostasis following an environmental challenge, thereby enabling the formulation of personalized recommendations. Examples in the area of macro- and micronutrients are reviewed. Genetic variations and performance goals are integrated into this systems approach to provide a strategy for a balanced evaluation and an introduction to personalized nutrition. Finally, modeling approaches that combine personalized diagnosis and nutritional intervention into practice are reviewed.
Single object tracking using offline trained deep regression networks

In this paper we introduce a novel single object tracker based on two convolutional neural networks (CNNs) trained offline using data from large videos repositories. The key principle consists of alternating between tracking using motion information and adjusting the predicted location based on visual similarity. First, we construct a deep regression network architecture able to learn generic relations between the object appearance models and its associated motion patterns. Then, based on visual similarity constraints, the objects bounding box position, size and shape are continuously updated in order to maximize a patch similarity function designed using CNN. Finally, a multi-resolution fusion between the outputs of the two CNNs is performed for accurate object localization. The experimental evaluation performed on challenging datasets, proposed in the visual object tracking (VOT) international contest, validates the proposed method when compared with state-of-the-art systems. In terms of computational speed our tracker runs at 20fps.
Chaperone Requirements for Biosynthesis of the Trypanosome Variant Surface Glycoprotein

Background Trypanosoma brucei does not respond transcriptionally to several endoplasmic reticulum (ER) stress conditions, including tunicamycin or dithiothreitol, indicating the absence of a conventional unfolded protein response. This suggests divergent mechanisms for quality control (QC) of ER protein folding and export may be present in trypanosomes. As the variant surface glycoprotein (VSG) represents ∼90% of trypanosome plasma membrane protein, it is possible that VSG has evolved to fold efficiently to minimize ER folding burden. Methodology/Principal Findings We demonstrate the presence of a QC system by pharmacological inhibition of the trypanosome 26S proteasome. This indicates active proteasome-mediated VSG turnover as ∼2.5 fold more VSG is recovered from cell lysates following MG132 inhibition. An in silico scan of the trypanosome genome identified 28 open reading frames likely to encode polypeptides participating in ER nascent chain maturation. By RNA interference we monitored the importance of these gene products to proliferation, VSG abundance and cell morphology. 68% of the cohort were required for normal proliferation, and depletion of most of these factors resulted in increased VSG abundance, suggesting involvement in ERQC and degradation. Conclusions/Significance The retention of genes for, and the involvement of many gene products in, VSG folding indicates a substantial complexity within the pathways required to perform this role. Counterintuitively, for a super-abundant antigen VSG is apparently made in excess. The biosynthetic excess VSG appears to be turned over efficiently by the proteasome, implying that considerable VSG is rejected by the trypanosome ERQC mechanism. Accordingly, the VSG polypeptide is not well optimized for folding, as only ∼30% attains the native state. Finally as much of the core ERQC system is functionally conserved in trypanosomes, the pathway has an ancient evolutionary origin, and was present in the last common eukaryotic ancestor.
High order modulation backscatter systems characterization

The main objective of this paper is to present a calibrated measurement system with an application case focusing in characterize the backscatter modulation systems. The backscatter modulation have an important role in Internet of Things (IoT) because they do not use a radio transmitter to transfer information. Moreover, these devices are being used in wireless power transfer (WPT) scenarios because they do not need any battery to transmit information. For this purpose, it is important to design a calibrated measurement system capable of characterize and calculate the optimum points for M-QAM modulations in backscatter radio systems.
On the connectivity threshold for colorings of random graphs and hypergraphs

Let $\Omega_q=\Omega_q(H)$ denote the set of proper $[q]$-colorings of the hypergraph $H$. Let $\Gamma_q$ be the graph with vertex set $\Omega_q$ and an edge ${\sigma,\tau\}$ where $\sigma,\tau$ are colorings iff $h(\sigma,\tau)=1$. Here $h(\sigma,\tau)$ is the Hamming distance $|\{v\in V(H):\sigma(v)\neq\tau(v)\}|$. We show that if $H=H_{n,m;k},\,k\geq 2$, the random $k$-uniform hypergraph with $V=[n]$ and $m=dn/k$ then w.h. p. $\Gamma_q$ is connected if $d$ is sufficiently large and $q\gtrsim (d/\log d)^{1/(k-1)}$.
State-dependent judgement bias in Drosophila: evidence for evolutionarily primitive affective processes

Affective states influence decision-making under ambiguity in humans and other animals. Individuals in a negative state tend to interpret ambiguous cues more negatively than individuals in a positive state. We demonstrate that the fruit fly, Drosophila melanogaster, also exhibits state-dependent changes in cue interpretation. Drosophila were trained on a Go/Go task to approach a positive (P) odour associated with a sugar reward and actively avoid a negative (N) odour associated with shock. Trained flies were then either shaken to induce a purported negative state or left undisturbed (control), and given a choice between: air or P; air or N; air or ambiguous odour (1 : 1 blend of P : N). Shaken flies were significantly less likely to approach the ambiguous odour than control flies. This ‘judgement bias’ may be mediated by changes in neural activity that reflect evolutionarily primitive affective states. We cannot say whether such states are consciously experienced, but use of this model organism's versatile experimental tool kit may facilitate elucidation of their neural and genetic basis.
A 110dB-CMRR 100dB-PSRR multi-channel neural-recording amplifier system using differentially regulated rejection ratio enhancement in 0.18μm CMOS

Multi-channel neural-recording amplifier systems have evolved into the method of choice for analyzing neurophysiological behavior, and are leading to a deeper understanding of the human brain [1-4]. Such systems operate from a noisy supply and ground, especially when they are powered wirelessly. As shown in Fig. 29.7. 1, the amplifiers ought to be low-noise, low-power, and resilient against environmental noise and interferences that are capacitively coupled from the power lines (220V/60Hz). Specifications-wise, these requirements translate into high CMRR, TCMRR, and PSRR. TCMRR (total CMRR) is a more realistic specification than CMRR as it includes the effect of the impedances of both electrodes (Ze) and the amplifier input (ZCin) as well. In fact, the TCMRR should be >70dB for reliable detection of a 5μVrms neural signal [1].
Optimization of Enzyme Treatment for Banana Fiber

Owing to environmental concern, it is imperative to utilize natural resources. Banana fibers, one of the minor cellulosic fibers are obtained from the pseudostem of banana plant. The pseudostems are normally discarded as biomass after harvesting the fruit. Banana fibers are potential textile fibers due to their excellent strength and lustre, however lacks spin ability due to stiffness. Lignin present in the bast fibers is one of the reasons that add to stiffness. Hence the present study is about softening banana fibers using enzymes. Four different enzymes were applied individually to optimize the concentration and conditions and a final treatment was standardized in combinations. The order of application of enzyme treatment as combination was also studied. Accordingly this paper also discusses the development towards the sequential and simultaneous mixed enzyme systems to accomplish softness.
Analytical Performance of a Gene Expression Classifier for Medullary Thyroid Carcinoma.

BACKGROUND The aim of this study was to demonstrate the analytical validity of an RNA classifier for medullary thyroid carcinoma (MTC). METHODS Fresh-frozen tissue specimens were obtained from commercial sources, and MTC diagnoses were confirmed by histopathology review. De-identified patient fine-needle aspiration biopsies (FNABs) and whole blood from normal donors were obtained. Total RNA was extracted, amplified, and hybridized to custom microarrays for gene expression analysis. Gene expression data were normalized and classified via a machine learning algorithm. Positive control materials were produced from MTC tissues and tested across multiple experiments and laboratories. Twenty-seven MTC tissue specimens were used to evaluate the sensitivity of the MTC classifier. Gene expression data from tissues and FNABs were used to model classifier response to mixtures of MTC samples with normal thyroid tissue, a benign thyroid nodule, a Hürthle cell adenoma, and whole blood. Select mixture conditions were confirmed in vitro. Assay tolerance to RNA input variation (5-25 ng) and genomic DNA contamination (30% by mass) was evaluated. The intra- and inter-run reproducibility and inter-laboratory accuracy of MTC classifier results were characterized. RESULTS The MTC classifier sensitivity of 96.3% [confidence interval 81.0-99.9%] was determined retrospectively using 27 MTC confirmed tissue specimens. One false-negative result in a necrotic tissue implicated sample necrosis in reduced classifier sensitivity. Dilution modeling of MTC samples with normal or benign tissues showed consistent detection of MTC down to 20% sample proportions, with in vitro confirmation of 20% analytical sensitivity. Classifier tolerance to RNA input variation (5-25 ng), genomic DNA contamination (30% by mass), and an interfering substance (blood) was demonstrated with 100% accurate classifier results under all tested conditions. The maximum observed run-to-run score difference for a single FNAB sample was ∼1 unit compared with the average score difference between 38 MTC and non-MTC FNABs of ∼32 units. MTC classifier results for 20 tissues processed from total RNA in two different laboratories showed 100% concordance. CONCLUSIONS The MTC classifier, offered as part of the routine molecular testing of cytology-indeterminate thyroid nodules, demonstrates robust analytical sensitivity, specificity, accuracy, and reproducibility.
Global Phylogeography with Mixed-Marker Analysis Reveals Male-Mediated Dispersal in the Endangered Scalloped Hammerhead Shark (Sphyrna lewini)

Background The scalloped hammerhead shark, Sphyrna lewini, is a large endangered predator with a circumglobal distribution, observed in the open ocean but linked ontogenetically to coastal embayments for parturition and juvenile development. A previous survey of maternal (mtDNA) markers demonstrated strong genetic partitioning overall (global ΦST = 0.749) and significant population separations across oceans and between discontinuous continental coastlines. Methodology/Principal Findings We surveyed the same global range with increased sample coverage (N = 403) and 13 microsatellite loci to assess the male contribution to dispersal and population structure. Biparentally inherited microsatellites reveal low or absent genetic structure across ocean basins and global genetic differentiation (F ST = 0.035) over an order of magnitude lower than the corresponding measures for maternal mtDNA lineages (ΦST = 0.749). Nuclear allelic richness and heterozygosity are high throughout the Indo-Pacific, while genetic structure is low. In contrast, allelic diversity is low while population structure is higher for populations at the ends of the range in the West Atlantic and East Pacific. Conclusions/Significance These data are consistent with the proposed Indo-Pacific center of origin for S. lewini, and indicate that females are philopatric or adhere to coastal habitats while males facilitate gene flow across oceanic expanses. This study includes the largest sampling effort and the most molecular loci ever used to survey the complete range of a large oceanic predator, and findings emphasize the importance of incorporating mixed-marker analysis into stock assessments of threatened and endangered shark species.
ClassBeacons: Designing Distributed Visualization of Teachers' Physical Proximity in the Classroom

As necessary for creating a learner-centered environment, nowadays teachers are expected to be more mindful about their proximity distribution: how to spend time in different locations of the classroom with individual learners. However feedback on this is only given to teachers by experts after classroom observation. In this paper we present the design and evaluation of ClassBeacons, a novel ambient information system that visualizes teachers' physical proximity through tangible devices distributed over the classroom. An expert review and a field evaluation with eight secondary school teachers were conducted to explore potential values of such a system and gather user experiences. Results revealed rich insights into how the system could influence teaching and learning, as well as how a distributed display can be seamlessly integrated into teachers' routines.