Miracle-dz/UniFAR-FTUs huggingface dataset:
The application of genetics to marine management and conservation: Examples from the Indo-Pacific

Molecular tools and analyses have played pivotal roles in uncovering the processes and patterns of biodiversity in the Indian and Pacific oceans. However, integrating genetic results into management and conservation objectives has been challenging, with few examples that show practical applicability. This review aims to address some of the perceived barriers to an enhanced approach that integrates molecular data into management and conservation goals, by reviewing papers relevant to both conservation and fisheries management in the Indo-Pacific region, particularly with respect to phylogeography, connectivity, and species identification, as well as stock delineation, restoration of depleted wild stocks, mislabeled marine resources and "molecular forensics. " We also highlight case studies from each of these areas that illustrate how molecular analyses are relevant to conservation and management in the Indo- Pacific, spanning a variety of vertebrate and invertebrate species. We discuss the application of genetic data to the design and evaluation of the effectiveness of marine protected area networks, stock delineation, and restoration and the usage of exclusion tests and parentage analyses for fisheries management. We conclude that there is a distinct need for increasing public awareness and ownership of genetically unique lineages and, ultimately, the increased inclusion of genetic research into management policy and conservation. Finally, we make a case for the importance of clear and effective communication for promoting public awareness, public ownership, and for achieving conservation goals within the region.
Localization of the cannabinoid type‐1 receptor in subcellular astrocyte compartments of mutant mouse hippocampus

Astroglial type‐1 cannabinoid (CB1) receptors are involved in synaptic transmission, plasticity and behavior by interfering with the so‐called tripartite synapse formed by pre‐ and post‐synaptic neuronal elements and surrounding astrocyte processes. However, little is known concerning the subcellular distribution of astroglial CB1 receptors. In particular, brain CB1 receptors are mostly localized at cells' plasmalemma, but recent evidence indicates their functional presence in mitochondrial membranes. Whether CB1 receptors are present in astroglial mitochondria has remained unknown. To investigate this issue, we included conditional knock‐out mice lacking astroglial CB1 receptor expression specifically in glial fibrillary acidic protein (GFAP)‐containing astrocytes (GFAP‐CB1‐KO mice) and also generated genetic rescue mice to re‐express CB1 receptors exclusively in astrocytes (GFAP‐CB1‐RS). To better identify astroglial structures by immunoelectron microscopy, global CB1 knock‐out (CB1‐KO) mice and wild‐type (CB1‐WT) littermates were intra‐hippocampally injected with an adeno‐associated virus expressing humanized renilla green fluorescent protein (hrGFP) under the control of human GFAP promoter to generate GFAPhrGFP‐CB1‐KO and ‐WT mice, respectively. Furthermore, double immunogold (for CB1) and immunoperoxidase (for GFAP or hrGFP) revealed that CB1 receptors are present in astroglial mitochondria from different hippocampal regions of CB1‐WT, GFAP‐CB1‐RS and GFAPhrGFP‐CB1‐WT mice. Only non‐specific gold particles were detected in mouse hippocampi lacking CB1 receptors. Altogether, we demonstrated the existence of a precise molecular architecture of the CB1 receptor in astrocytes that will have to be taken into account in evaluating the functional activity of cannabinergic signaling at the tripartite synapse.
An unified neutral-point voltage controller for NPC converter fed induction machine drive

The control of the neutral-point (NP) voltage is one of the major challenges in the operation of the neutral-point-clamped (NPC) three-level converter. Some controllers are proposed in the literature which are based on the continuous system model. However, those models are function of either active or reactive power which limits their operation under certain operating point. As an example, the model with the active does not work properly for an induction machine drive under no load condition. In this paper, a hybrid modulation strategy is proposed which causes the NP current to be proportional to the sum of the active and reactive power. Using this, the dynamics of the NP voltage difference is modeled as a function of the sum of the active and reactive power. This approach is used to improve the performance of NPC converter feeding the induction machine under no load condition. In addition, a method to extend the limit of the control variable is also described. Simulation results are shown to verify the proposed modulation strategy and the controller based on that.
FORmal methods for the quantitative Evaluation of Collective Adaptive SysTems ( FORECAST )

Collective Adaptive Systems (CAS) consist of a large number of spatially distributed heterogeneous entities with decentralized control and varying degrees of complex autonomous behavior that may be competing for shared resources even when collaborating to reach common goals. It is important to carry out thorough quantitative modeling and analysis and verification of their design to investigate all aspects of their behavior before they are put into operation. This requires combinations of formal methods (e.g., stochastic process algebras and associated verification techniques, such as quantitative model checking) and applied mathematics (e.g., mean field/continuous approximation and control theory) which, moreover, scale to large-scale CAS. In this context, the FORECAST workshop on FORmal methods for the quantitative Evaluation of Collective Adaptive SysTems—held in Vienna (Austria) on July 8, 2016 as a satellite event of the 4th federated event on Software Technologies: Applications and Foundations (STAF 2016)—was organized to raise awareness in the software engineering and formal methods communities of the particularities of CAS, and the design and control problems that they bring. The guest editors of this special issue served as co-chairs of the workshop’s Program Committee and were responsible for its proceedings [4]. FORECAST was sponsored by the FP7-ICT-600708 European project QUANTICOL (A Quantitative Approach to Management and Design of Collective and Adaptive Behaviours), that ran from 2013 to 2017 [3, 5, 7]. We thank the project’s participants and in particular its coordinator, Jane Hillston, for entrusting us with the workshop’s organization.
Group A streptococci are protected from amoxicillin-mediated killing by vesicles containing β-lactamase derived from Haemophilus influenzae.

OBJECTIVES Group A streptococci (GAS) cause, among other infections, pharyngotonsillitis in children. The species is frequently localized with the Gram-negative respiratory pathogens non-typeable Haemophilus influenzae (NTHi) and Moraxella catarrhalis, which both produce outer membrane vesicles (OMVs). The aim of this study was to investigate whether OMVs isolated from NTHi contain functional β-lactamase and whether the OMVs hydrolyse amoxicillin and thus protect GAS from killing by the antibiotic. METHODS The antibiotic susceptibility of isolates was determined using the Etest. The resistance genes blaTEM-1 (encoding NTHi β-lactamase), bro-1 (encoding M. catarrhalis β-lactamase) and ftsI (encoding NTHi penicillin-binding protein 3) were searched for by PCR, followed by sequencing. OMVs were isolated by ultracentrifugation and the presence of β-lactamase was detected by western blots including specific rabbit polyclonal antibodies. The chromogenic substrate nitrocefin was used to quantify and compare the β-lactamase enzyme activity in the OMVs. The hydrolysis of amoxicillin by β-lactamase was estimated by an agar diffusion method. RESULTS We showed that OMVs released from β-lactam-resistant M. catarrhalis and NTHi contain functional β-lactamase that hydrolyses amoxicillin and protects GAS from killing by amoxicillin. CONCLUSIONS This is the first report of the presence of β-lactamase in NTHi OMVs. We suggest that OMV-derived β-lactamase from coinfecting pathogens such as NTHi and M. catarrhalis may contribute to the occasional treatment failures seen in GAS tonsillitis.
Spatial-temporal transcriptional dynamics of long non-coding RNAs in human brain

The functional architecture of the human brain is greatly determined by the temporal and spatial regulation of the transcription process. However, the spatial and temporal transcriptional landscape of long non-coding RNAs (lncRNAs) during human brain development remains poorly understood. Here, we report the genome-wide lncRNA transcriptional analysis in an extensive series of 1340 post-mortem human brain specimens collected from 16 regions spanning the period from early embryo development to late adulthood. We discovered that lncRNA transcriptome dramatically changed during fetal development, while transited to a surprisingly relatively stable state after birth till the late adulthood. We also discovered that the transcription map of lncRNAs was spatially different, and that this spatial difference was developmentally regulated. Of the 16 brain regions explored (cerebellar cortex, thalamus, striatum, amygdala, hippocampus and 11 neocortex areas), cerebellar cortex showed the most distinct lncRNA expression features from all remaining brain regions throughout the whole developmental period, reflecting its unique developmental and functional features. Furthermore, by characterizing the functional modules and cellular processes of the spatial-temporal dynamic lncRNAs, we found that they were significantly associated with the RNA processing, neuron differentiation and synaptic signal transportation processes. Furthermore, we found that many lncRNAs associated with the neurodegenerative Alzheimer and Parkinson diseases were co-expressed in the fetal development of the human brain, and affected the convergent biological processes. In summary, our study provides a comprehensive map for lncRNA transcription dynamics in human brain development, which might shed light on the understanding of the molecular underpinnings of human brain function and disease.
Handling out of domain topics by a conversational character

Unlike traditional task-oriented dialog systems, one of the goals of conversational applications is to keep the user engaged and interested for as long as possible. This paper describes a technique that we implemented for dealing with the problem of out-of-domain topics and successfully integrated in a fully functional conversational system. In our approach, we exploit a simple and freely available coarsegrained ontology, namely Google's directory' structure, in order to automatically categorize unknown words and combines it with the existing ontological properties and dialog acts to create an automated semantic representation. We also resort to available web-based question and answering (QA) systems to generate answers to user's questions that are outside the domains covered by the application. Further, we make a first attempt at categorizing the retrieved information to generate appropriate non-verbal behaviors synced up with spoken utterances. The evaluation of the complete system shows promising results for the future and suggests that we are on the right track in terms of our approach for a better handling of out-of-domain topics.
Data-driven approach for dip voltage fault detection and identification based on grid current vector trajectory analysis

This paper proposes a data driven approach for dip voltage fault detection and identification using the grid current vector trajectory in the stationary reference frame. Three features are extracted for the different operating conditions to build the database and analysed using Linear Discriminant Analysis to identify the fault type and subtype. In the subspaces spanned by the factorial components the four faults and eight out of nine faults subtype are successfully identified and isolated with an error rate less than 5%. Simulation results prove the efficiency of the proposed algorithm.
Channel Diagonalization for Cloud Radio Access

The diagonalization of a conventional multiple-input multiple-output (MIMO) channel into parallel and independent subchannels via singular value decomposition (SVD) is a fundamental strategy that allows the MIMO channel capacity to be achieved using scalar channel codes. This letter establishes a similar channel diagonalization result for the uplink and the downlink of a cloud radio access network (C-RAN), in which a central processor is connected to a remote radio head (RRH) serving a single user via rate-limit digital fronthaul carrying the compressed baseband signal. Specifically, we show that the diagonalization of the MIMO channel between the RRH and the user via SVD and the subsequent independent and parallel quantization of scalar signals and channel coding in each of the subchannels is optimal. This letter establishes this fact using the majorization theory. Further, an uplink-downlink duality for the multiple-antenna C-RAN is identified for this single-user case.
11,001 New Features for Statistical Machine Translation

We use the Margin Infused Relaxed Algorithm of Crammer et al. to add a large number of new features to two machine translation systems: the Hiero hierarchical phrase-based translation system and our syntax-based translation system. On a large-scale Chinese-English translation task, we obtain statistically significant improvements of +1.5 Bleu and + 1.1 Bleu, respectively. We analyze the impact of the new features and the performance of the learning algorithm.
Modeling, Measuring and Exploiting Concept Drift in the Labour Market Domain

The Labour Market domain is a relatively narrow domain in terms of concept types that appear in it (as it typically consists of professions, skills and qualifications) but a very broad one in terms of actual concepts (as these professions and skills can be in all kinds of domains such as Technology, Education, Finance, etc). More importantly, it is a quite volatile domain in the sense that the meaning of many concepts changes (at different rates) over time. This phenomenon, known as semantic or concept drift, poses a challenge for the maintenance and evolution of knowledge graphs that represent such domains, and requires dedicated approaches for tackling it so as to prevent such graphs from becoming irrelevant. With that in mind, in this paper we describe our experiences from dealing with concept drift in an in-house developed labour market knowledge graph, and provide insights on: i) how concept drift can be effectively defined and modeled for labour market concepts, and ii) how it can be detected, measured and effectively incorporated in the knowledge graph lifecycle.
Matrix metalloproteinase‐8 levels in periodontal disease patients: A systematic review

Periodontal disease is characterized as a disorder of the oral microbiota resulting in an immune response which, in turn, leads to the destruction of periodontal tissue. Matrix metalloproteinase-8 (MMP-8) has been reported as the major metalloproteinase involved in periodontal disease, being present at high levels in gingival crevicular fluid and salivary fluid (SF). The aim of this systematic review was to evaluate the scientific literature regarding the expression of MMP-8 in gingival crevicular fluid and SF in patients with periodontal disease, analyzing its validity as a possible biomarker in the diagnosis of periodontal disease. A systematic review of the literature was performed using the PubMed/Medline, CENTRAL and Science Direct databases. Studies concerning the use of MMP-8 in the diagnosis of periodontal disease that evaluated its effectiveness as a biomarker for periodontal disease were selected. The search strategy provided a total of 6483 studies. After selection, six articles met all the inclusion criteria and were included in the present systematic review. The studies demonstrated significantly higher concentrations of MMP-8 in patients with periodontal disease compared with controls, as well as in patients presenting more advanced stages of periodontal disease. The findings on higher MMP-8 concentrations in patients with periodontal disease compared with controls imply the potential adjunctive use of MMP-8 in the diagnosis of periodontal disease.
X‐ray‐induced acoustic computed tomography for 3D breast imaging: A simulation study

PURPOSE The objective of this study is to demonstrate the feasibility of x-ray-induced acoustic computed tomography (XACT) for early breast un-palpable microcalcification (μCa) detection in three dimensions (3D). The proposed technique provides the true 3D imaging for breast volume which overcomes the disadvantage of the tissue superposition in mammography. METHODS A 3D breast digital phantom was rendered from two-dimensional (2D) breast CT slices. Three different tissue types, including the skin, adipose tissue, and glandular tissue, were labeled in the 3D breast phantom. μCas were manually embedded in different locations inside the breast phantom. For each tissue type, the initial pressure rise caused by the x-ray-induced acoustic (XA) effect was calculated according to its themoacoustic properties. The XA wave's propagation from the point of generation and its detection by ultrasound detector array were simulated by Matlab K-Wave toolbox. The 3D breast XACT volume with μCa was acquired without tissue superposition, and the system was characterized by μCas placed at different locations. RESULTS The simulation results illustrated that the proposed breast XACT system has the ability to show the μCa cluster in 3D without any tissue superposition. Meanwhile, μCa as small as 100 μm in size can be detected with high imaging contrast, high signal to noise ratio (SNR), and high contrast to noise ratio (CNR). The dose required by the proposed XACT configuration was calculated to be 0.4 mGy for a 4.5 cm-thick compressed breast. This is one-tenth of the dose level of a typical two-view mammography for a breast with the same compression thickness. CONCLUSIONS The initial exploration for the feasibility of 3D breast XACT has been conducted in this study. The system feasibility and characterization were illustrated through a 3D breast phantom and simulation works. The 3D breast XACT with the proposed system configuration has great potential to be applied as a low-dose screening and diagnostic technique for early un-palpable lesion in the breast.
Peer-reviewed version of the manuscript published in final form at Chemical Society Reviews (2018) Peptide and protein nanoparticle conjugates: versatile platforms for biomedical applications

Peptideand protein-nanoparticle conjugates have emerged as powerful tools for biomedical applications, enabling the treatment, diagnosis, and prevention of disease. In this review, we focus on the key roles played by peptides and proteins in improving, controlling, and defining the performance of nanotechnologies. Within this framework, we provide a comprehensive overview of the key sequences and structures utilised to provide biological and physical stability to nano-constructs, direct particles to their target and influence their cellular and tissue distribution, induce and control biological responses, and form polypeptide self-assembled nanoparticles. In doing so, we highlight the great advances made by the field, as well as the challenges still faced in achieving the clinical translation of peptideand proteinfunctionalised nano-drug delivery vehicles, imaging species, and active therapeutics.
An efficient grid-based clustering method by finding density peaks

Clustering or categorizing an unprocessed data set is essential and critical in many areas. Much success has been published, which first needs to calculate the mutual distances between data points. It suffers from considerable computational costs, preventing the state-of-the-art methods such as the clustering method by fast search and find of density peaks (FSFDP, published in Science, 2014) from applying into real life (e.g., with thousands of data points). In this paper, an efficient grid-based clustering (GBC) method by finding density peaks is described. It keeps the advantage of the friendly interactive interface in the FSFDP, at the mean time, decreases enormously the computation complexity. The time complexity of the FSFDP is o(np(np - 1)/2) while our method decreases it to o(np * size of (grid)), where np is the number of data points and the size of grid is always much smaller than np so that the time complexity of our approach is almost linearly proportional to np. The presented GBC method by finding density peaks was able to calculate the densities and categorize datasets within much less time, which makes the density-peak-based algorithm practical. By using the presented algorithm, it was possible to cluster high-dimensional data sets as well. The GBC method by finding density peaks was successfully verified in clustering several datasets, which are commonly used to test clustering algorithms in published articles. It turned out that the presented method is much faster and efficient in clustering datasets into different categories than the conventional density-based ones, which makes the proposed method more preferable.
Asymmetry during Functional Movement Screening and injury risk in junior football players: A replication study

An indicator of movement quality and potential injury risk during Functional Movement Screen (FMS) testing is the presence of asymmetry when comparing the left and right sides of the body. The aim of the study was to investigate the reproducibility of the injury risk model proposed in our previous research (Chalmers et al. 2017; derivation study) that showed an increased injury risk for elite junior Australian football players demonstrating ≥2 asymmetrical FMS subtests. We used a direct replication design. Players underwent pre‐season FMS testing, and an injury surveillance system monitored 277 male participants during the subsequent regular season competition. Designated club officials monitored the weekly competition participation of players. The definition of an injury was “a trauma or medical condition which caused a player to miss a competitive game”. Cox proportional hazards regression models were used to investigate the relationship between asymmetry and number of games played before first injury (ie, survival time). The level of reproducibility was determined according to statistical significance, effect size, and subjective assessment. Demonstrating asymmetry during FMS testing was not associated with a significant increase in prospective injury risk in the replication study (P > .05). Moreover, effect sizes (hazard ratios) from the derivation dataset were not within the 95% confidence intervals of the respective asymmetry predictor in the replication dataset. Subjectively, researchers were in agreement that the findings from the derivation data were not successfully reproduced. Clinicians and researchers should be cautious about using FMS asymmetry findings to derive injury risk for junior football players.