Miracle-dz/UniFAR-FTUs huggingface dataset:
A broadband X-ray study of the asynchronous polar: CD Ind

Asimultaneous broadband analysis ofX-ray data obtainedwithXMM-Newton andNuSTARobservatories for the asynchronous polar source CD Ind is presented. The spin folded lightcurve in soft 0.3-3.0 keV band shows single broad hump-like structure superimposed with occasional narrow dips, indicating a single-pole accretion model with a complex intrinsic absorber. Lack of strong modulation in folded lightcurve above 3 keV reveals that emission from corresponding zone of post-shock region (PSR) remains in view throughout the spin phase. The broadband spectrum is modelled with a three-component absorbed plasma emission model and absorbed isobaric cooling flow model, both of which fit the data well with similar statistical significance. Presence of partial covering absorber is evident in the spectra with equivalent column density ∼ 7 × 1022 cm−2 and a covering fraction of ∼ 25%. Strong ionised oxygen Kα line emission is detected in the spectra. We notice spectral variability during spin phase 0.75-1.05, when there is a considerable increase in column density of overall absorber (from ∼ 1 × 1020 cm−2 to ∼ 9 × 1020 cm−2). We required at least three plasma temperatures to describe the multi-temperature nature of the PSR. The shock temperature ∼ 43.3+3.8 −3.4 keV, represented by the upper temperature of the cooling flow model, implies a white dwarf mass of ∼ 0.87+0.04 −0.03 M . The iron Kα line complex shows a strong He-like and a weak neutral fluorescence line. We could not unambiguously detect the presence of Compton reflection in the spectra, which is probably very small and signifying a tall shock height.
Comprehensive Review of Exoskeleton Technology: State of the art and development of physical and cognitive human robot interface

Exoskeletons and orthoses are wearable mobile systems providing mechanical benefits to the users. Despite significant improvements in the last decades, the technology is not fully mature to be adopted for strenuous and non-programmed tasks. To accommodate this insufficiency, different aspects of this technology need to be analysed and improved. Numerous studies have been trying to address some aspects of exoskeletons, e.g. mechanism design, intent prediction, and control scheme. However, most works have focused on a specific element of design or application without providing a comprehensive review framework. This study aims to analyse and survey the contributing aspects to the improvement and broad adoption of this technology. To address this, after introducing assistive devices and exoskeletons, the main design criteria will be investigated from a physical Human-Robot Interface (HRI) perspective. The study will be further developed by outlining several examples of known assistive devices in different categories. In order to establish an intelligent HRI strategy and enabling intuitive control for users, cognitive HRI will be investigated. Various approaches to this strategy will be reviewed, and a model for intent prediction will be proposed. This model is utilised to predict the gate phase from a single Electromyography (EMG) channel input. The outcomes of modelling show the potential use of single-channel input in low-power assistive devices. Furthermore, the proposed model can provide redundancy in devices with a complex control strategy.
Evaluating Local Explanations using White-box Models

Evaluating explanation techniques using human subjects is costly, time-consuming and can lead to subjectivity in the assessments. To evaluate the accuracy of local explanations, we require access to the true feature importance scores for a given instance. However, the prediction function of a model usually does not decompose into linear additive terms that indicate how much a feature contributes to the output. In this work, we suggest to instead focus on the log odds ratio (LOR) of the prediction function, which naturally decomposes into additive terms for logistic regression and naive Bayes. We demonstrate how we can benchmark different explanation techniques in terms of their similarity to the LOR scores based on our proposed approach. In the experiments, we compare prominent local explanation techniques and find that the performance of the techniques can depend on the underlying model, the dataset, which data point is explained, the normalization of the data and the similarity metric.
Towards automated optimisation of residual convolutional neural networks for electrocardiogram classification

The interpretation of the electrocardiogram (ECG) gives clinical information and helps in assessing heart function. There are distinct ECG patterns associated with a specific class of arrythmia. The convolutional neural network is currently one of the most commonly employed deep learning algorithms for ECG processing. However, deep learning models require many hyperparameters to tune. Selecting an optimal or best hyperparameter for the convolutional neural network algorithm is a highly challenging task. Often, we end up tuning the model manually with different possible ranges of values until a best fit model is obtained. Automatic hyperparameters tuning using Bayesian optimisation (BO) and evolutionary algorithms can provide an effective solution to current labour-intensive manual configuration approaches. In this paper, we propose to optimise the Residual one Dimensional Convolutional Neural Network model (R-1D-CNN) at two levels. At the first level, a residual convolutional layer and one-dimensional convolutional neural layers are trained to learn patient-specific ECG features over which multilayer perceptron layers can learn to produce the final class vectors of each input. This level is manual and aims to lower the search space. The second level is automatic and based on our proposed BO-based algorithm. Our proposed optimised R-1D-CNN architecture is evaluated on two publicly available ECG Datasets. Comparative experimental results demonstrate that our BO-based algorithm achieves an optimal rate of 99.95%, while the baseline model achieves 99.70% for the MIT-BIH database. Moreover, experiments demonstrate that the proposed architecture fine-tuned with BO achieves a higher accuracy than the other proposed architectures. Our optimised architecture achieves excellent results compared to previous works on benchmark datasets.
CNN Encoding of Acoustic Parameters for Prominence Detection

Expressive reading, considered the defining attribute of oral reading fluency, comprises the prosodic realization of phrasing and prominence. In the context of evaluating oral reading, it helps to establish the speaker's comprehension of the text. We consider a labeled dataset of children's reading recordings for the speaker-independent detection of prominent words using acoustic-prosodic and lexico-syntactic features. A previous well-tuned random forest ensemble predictor is replaced by an RNN sequence classifier to exploit potential context dependency across the longer utterance. Further, deep learning is applied to obtain word-level features from low-level acoustic contours of fundamental frequency, intensity and spectral shape in an end-to-end fashion. Performance comparisons are presented across the different feature types and across different feature learning architectures for prominent word prediction to draw insights wherever possible.
Fair Integral Network Flows

A strongly polynomial algorithm is developed for finding an integer-valued feasible st-flow of a given flow amount, which is decreasingly minimal on a specified subset F of edges in the sense that the largest flow value on F is as small as possible; within this, the second largest flow value on F is as small as possible; within this, the third largest flow value on F is as small as possible, and so on. A characterization of the set of these st-flows gives rise to an algorithm to compute a cheapest F-decreasingly minimal integer-valued feasible st-flow of given flow amount. Decreasing minimality is a possible formal way to capture the intuitive notion of fairness.
Terahertz Meets Untrusted UAV-Relaying: Minimum Secrecy Energy Efficiency Maximization via Trajectory and Communication Co-Design

Unmanned aerial vehicles (UAVs) and Terahertz (THz) technology are envisioned to play paramount roles in next-generation wireless communications. In this paper, we present a novel secure UAV-assisted mobile relaying system operating at THz bands for data acquisition from multiple ground user equipments (UEs) towards a destination. We assume that the UAV-mounted relay may act, besides providing relaying services, as a potential eavesdropper called the untrusted UAV-relay (UUR). To safeguard end-to-end communications, we present a secure two-phase transmission strategy with cooperative jamming. Then, we devise an optimization framework in terms of a new measure $-$ secrecy energy efficiency (SEE), defined as the ratio of achievable average secrecy rate to average system power consumption, which enables us to obtain the best possible security level while taking UUR’s inherent flight power limitation into account. For the sake of quality of service fairness amongst all the UEs, we aim to maximize the minimum SEE (MSEE) performance via the joint design of key system parameters, including UUR’s trajectory and velocity, communication scheduling, and network power allocation. Since the formulated problem is a mixed-integer nonconvex optimization and computationally intractable, we decouple it into four subproblems and propose alternative algorithms to solve it efficiently via greedy/sequential block successive convex approximation and non-linear fractional programming techniques. Numerical results demonstrate significant MSEE performance improvement of our designs compared to other known benchmarks.
Look It Up: Bilingual Dictionaries Improve Neural Machine Translation

Despite advances in neural machine translation 001 (NMT) quality, rare words continue to be prob- 002 lematic. For humans, the solution to the rare- 003 word problem has long been dictionaries, but 004 dictionaries cannot be straightforwardly incor- 005 porated into NMT. In this paper, we describe a 006 new method for “attaching” dictionary defini- 007 tions to rare words so that the network can learn 008 the best way to use them. We demonstrate im- 009 provements of up to 1.8 BLEU using bilingual 010 dictionaries. 011
Research on Application of Coal-Water Slurry Techniques to Disposal of Wheat Straw Pulping Black Liquor

A pilot test on disposal of wheat straw pulping black liquor applying Coal-Water Slurry (CWS) combustion technology as an alternative of traditional alkali recovery technique has been performed: Experimental study on combustion feature for several kinds of Coal-Blackliquor Slurry (CBS) was carried out in a 6.5 ton/hr chain-grate boiler. In the test flue gas, slag and dust were analyzed and boiler's heat liberation rate was measured. The results demonstrated that the combustion of CBS is efficient with low poisonous emission: The successful combustion of CBS demonstrated itself promising as a key technique in a novel measure of comprehensive disposal of wheat straw black liquor.
A Technique for Designing Variation Resilient Subthreshold Sram Cell

This paper presents a technique for designing a variability aware subthreshold SRAM cell. The architecture of the proposed cell is similar to the standard read-decoupled 8-transistor (RD8T) SRAM cell with the exception that the access FETS are replaced with transmission gates (TGs). In this work, various design metrics are assessed and compared with RD8T SRAM cell. The proposed design offers 2.14× and 1.75× improvement in T RA (read access time) and T WA (write access time) respectively compared with RD8T. It proves its robustness against process variations by featuring narrower spread in T RA distribution ( 2.35×) and T WA distribution (3.79 ×) compared with RD8T. The proposed bitcell offers 1.16 × higher read current (I READ ) and 1.64 × lower bitline leakage current (I LEAK ) respectively compared with RD8T. It also shows its robustness by offering 1.34 × ( 1.58 ×) tighter spread in I READ (I LEAK ) compared with RD8T. It exhibits 1.42 × larger I READ to I LEAK ratio. It shows 2.2 × higher frequency @ 250 mV with read bitline capacitance of 10 fF. Besides, the proposed bitcell achieves same read stability and write-ability as that of RD8T at the cost of 3 extra transistors. The leakage power of the proposed design is close to that of RD8T . ABSTRAK: Kertas kerja ini membentangkan teknik merekabentuk sel bawah ambang SRAM yang bolehubah. Senibina sel yang dicadangkan adalah sama dengan sel SRAM 8-transistor (RD8T) “pisahan-bacaan” piawai kecuali FET akses digantikan dengan sel pintu transmisi (TGs). Di dalam kajian ini, beberapa metrik rekabentuk dinilai dan dibandingkan dengan sel RD8T SRAM. Rekabentuk yang dicadangkan menawarkan peningkatan 2.14× dan 1.75× dalam T RA (masa akses baca) dan T WA (masa akses tulis) berbanding dengan RD8T. Ia membuktikan kekukuhan variasi proses dengan menampilkan tebaran yang lebih sempit dalam pengagihan T RA (2.35 ×) dan pengagihan T WA (3.79 ×) berbanding dengan RD8T. Sel- Bit yang dicadangkan mempunyai arus baca 1.16 × lebih tinggi ( I READ ) dan arus bocor bitline 1.64 × lebih rendah ( I LEAK ) berbanding dengan RD8T. Ia juga membuktikan kekukuhan dengan menawarkan 1.34 × (1.58 ×) penyebaran sempit di I READ (I LEAK ) berbanding dengan RD8T dan nisbah I READ / I LEAK 1.42 × lebih besar. Ia menunjukkan kekerapan 2.2 × lebih tinggi pada 250 mV dengan kemuatan membaca bitline sebanyak 10 fF. Selain itu, sel bit yang dicadangkan mencapai kestabilan membaca dan keupayaan menulis yang sama seperti RD8T dengan kos tambahan 3 transistor. Kebocoran kuasa rekabentuk yang dicadangkan hampir sama dengan RD8T. KEYWORDS : variability; robust, subthreshold; random dopant fluctuation (RDF); read static noise margin (RSNM); write static noise margin (WSNM).
Direct regulation of shikimate, early phenylpropanoid and stilbenoid pathways by Subgroup 2 R2R3-MYBs in grapevine.

The stilbenoid pathway is responsible for the production of resveratrol in grapevine (Vitis vinifera L.). A few transcription factors (TFs) have been identified as regulators of this pathway but the extent of this control has not been deeply studied. Here we demonstrate how DNA affinity purification sequencing (DAP-Seq) allows for genome-wide TF binding site interrogation in grape. We obtained 5,190 and 4,443 binding events assigned to 4,041 and 3,626 genes for MYB14 and MYB15, respectively (around 40% of peaks located within -10kb of transcription start sites). DAP-Seq of MYB14/MYB15 was combined with aggregate gene co-expression networks (GCNs) built from more than 1,400 transcriptomic datasets from leaves, fruits and flowers to narrow down bound genes to a set of high confidence targets. The analysis of MYB14, MYB15 and MYB13, a third uncharacterised member of Subgroup 2 (S2), showed that in addition to the few previously known stilbene synthase (STS) targets, these regulators bind to 30 out of 47 STS family genes. Moreover, all three MYBs bind to several PAL, C4H and 4CL genes, in addition to shikimate pathway genes, the WRKY03 stilbenoid co-regulator and resveratrol-modifying gene candidates amongst which ROMT2-3 were validated enzymatically. A high proportion of DAP-Seq bound genes was induced in the activated transcriptomes of transient MYB15-overexpressing grapevine leaves, validating our methodological approach for delimiting TF targets. Overall, Subgroup 2 R2R3-MYBs appear to play a key role in binding and directly regulating several primary and secondary metabolic steps leading to an increased flux towards stilbenoid production. The integration of DAP-Seq and reciprocal GCNs offers a rapid framework for gene function characterisation using genome-wide approaches in the context of non-model plant species and stands up as a valid first approach for identifying gene regulatory networks of specialised metabolism.
Genomic landscape, polymorphism and possible LINE-associated delivery of G-Quadruplex motifs in the bovine genes

G-Quadruplex structures are non-B DNA structures that occur in regions carrying short runs of guanines. They are implicated in several biological processes including transcription, translation, replication and telomere maintenance as well as in several pathological conditions like cancer and thus they have gained the attention of the scientific community. The rise of the –omics era significantly affected the G-quadruplex research and the genome-wide characterization of G-Quadruplexes has been rendered a necessary first step towards applying genomics approaches for their study. While in human and several model organisms there is a considerable number of works studying genome-wide the DNA motifs with potential to form G-quadruplexes (G4-motifs), there is a total absence of any similar studies regarding livestock animals. The objectives of the present study were to provide a detailed characterization of the bovine genic G4-motifs’ distribution and properties and to suggest a possible mechanism for the delivery of G4 motifs in the genes. Our data indicate that the distribution of G4s within bovine genes and the annotation of said genes to Gene Ontology terms are similar to what is already shown for other organisms. By investigating their structural characteristics and polymorphism, it is obvious that the overall stability of the putative quadruplex structures is in line with the current notion in the G4 field. Similarly to human, the bovine G4s are overrepresented in specific LINE repeat elements, the L1_BTs in the case of cattle. We suggest these elements as vehicles for delivery of G4 motifs in the introns of the bovine genes. Lastly, it seems that a basis exists for connecting traits of agricultural importance to the genetic variation of G4 motifs, thus, cattle could become an interesting new model organism for G4-related genetic studies.
Energy Requirements Undermine Substrate Independence and Mind-Body Functionalism

Abstract Substrate independence and mind-body functionalism claim that thinking does not depend on any particular kind of physical implementation. But real-world information processing depends on energy, and energy depends on material substrates. Biological evidence for these claims comes from ecology and neuroscience, while computational evidence comes from neuromorphic computing and deep learning. Attention to energy requirements undermines the use of substrate independence to support claims about the feasibility of artificial intelligence, the moral standing of robots, the possibility that we may be living in a computer simulation, the plausibility of transferring minds into computers, and the autonomy of psychology from neuroscience.
Understanding innovation of health technology assessment methods: the IHTAM framework

Abstract Adequate methods are urgently needed to guarantee the good practice of health technology assessment (HTA) for technologies with novel properties. The aim of the study was to construct a conceptual framework to help understand the innovation of HTA methods (IHTAM). The construction of the IHTAM framework was based on two scoping reviews, one on the current practice of innovating methods, that is existing HTA frameworks, and one on theoretical foundations for innovating methods outside the HTA discipline. Both aimed to identify and synthesize concepts of innovation (i.e., innovation processes and roles of stakeholders in innovation). Using these concepts, the framework was developed in iterative brainstorming sessions and subsequent discussions with representatives from various stakeholder groups. The framework was constructed based on twenty documents on innovating HTA frameworks and fourteen guidelines from three scientific disciplines. It includes a generic innovation process consisting of three phases (“Identification,” “Development,” and “Implementation”) and nine subphases. In the framework, three roles that HTA stakeholders can play in innovation (“Developers,” “Practitioners,” and “Beneficiaries”) are defined, and a process on how the stakeholders innovate HTA methods is included. The IHTAM framework visualizes systematically which elements and stakeholders are important to the development and implementation of novel HTA methods. The framework could be used by all stakeholders involved in HTA innovation to learn how to engage dynamically and collaborate effectively throughout the innovation process. HTA stakeholders in practice have welcomed the framework, though additional testing of its applicability and acceptance is essential.
Omega-3 Fatty Acid Supplementation and Its Impact on Systemic Inflammation and Body Weight in Patients With Cancer Cachexia—A Systematic Review and Meta-Analysis

Body weight loss and inflammation are major alterations related to cancer cachexia, an important wasting syndrome highly prevalent in many types of cancer. Nutritional components modulate inflammation in several chronic diseases. Omega-3 fatty acids (n-3) are well known for their anti-inflammatory properties. However, the effects of n-3 on cancer cachexia are still controversial. This systematic review and meta-analysis aims to evaluate the reported effects of n-3 supplementation on body weight and inflammatory markers in patients with cancer cachexia. Articles indexed in the major scientific platforms were retrieved in agreement with the Preferring Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and 167 references were initially found. After removing duplicates and applying the inclusion and exclusion criteria, this systematic review included six studies. Using a random-effects model with 95% CI, three effect sizes were expressed as standard mean difference (SMD). No differences were found regarding the effect of n-3 on interleukin-6, C-reactive protein, and albumin levels. Body weight analysis included only two studies, devoid of robust conclusions. The low number of studies, low sample size, and great intra-variability precluded a stronger analysis. More studies evaluating n-3 supplementation in cancer cachexia are still needed.
Evasion of Host Antiviral Innate Immunity by Paramyxovirus Accessory Proteins

For efficient replication, viruses have developed multiple strategies to evade host antiviral innate immunity. Paramyxoviruses are a large family of enveloped RNA viruses that comprises diverse human and animal pathogens which jeopardize global public health and the economy. The accessory proteins expressed from the P gene by RNA editing or overlapping open reading frames (ORFs) are major viral immune evasion factors antagonizing type I interferon (IFN-I) production and other antiviral innate immune responses. However, the antagonistic mechanisms against antiviral innate immunity by accessory proteins differ among viruses. Here, we summarize the current understandings of immune evasion mechanisms by paramyxovirus accessory proteins, specifically how accessory proteins directly or indirectly target the adaptors in the antiviral innate immune signaling pathway to facilitate virus replication. Additionally, some cellular responses, which are also involved in viral replication, will be briefly summarized.