Miracle-dz/UniFAR-FTUs huggingface dataset:
Going Viral: Researching Safely on Social Media

Safety issues for researchers conducting and disseminating research on social media have been inadequately addressed in institutional policies and practice globally, despite posing significant challenges to research staff and student well-being. In the context of the COVID-19 pandemic and given the myriad of advantages that web-based platforms offer researchers over traditional recruitment, data collection, and research dissemination methods, developing a comprehensive understanding of and guidance on the safe and effective conduct of research in web-based spaces has never been more pertinent. In this paper, we share our experience of using social media to recruit participants for a study on abortion stigma in Australia, which brought into focus the personal, professional, and institutional risks associated with conducting web-based research that goes viral. The lead researcher (KV), a postgraduate student, experienced a barrage of harassment on and beyond social media. The supportive yet uncoordinated institutional response highlighted gaps in practice, guidance, and policy relating to social media research ethics, researcher safety and well-being, planning for and managing web-based and offline risk, and coordinated organizational responses to adverse events. We call for and provide suggestions to inform the development of training, guidelines, and policies that address practical and ethical aspects of using social media for research, mental and physical health and safety risks and management, and the development of coordinated and evidence-based institutional- and individual-level responses to cyberbullying and harassment. Furthermore, we argue the case for the urgent development of this comprehensive guidance around researcher safety on the web, which would help to ensure that universities have the capacity to maximize the potential of social media for research while better supporting the well-being of their staff and students.
Prediction of cancer mutation states using multiple data modalities reveals the utility and consistency of gene expression and DNA methylation

In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal may be unclear. In this study, we consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem. Since functional signatures of cancer mutation have been identified across many data types, this problem presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. The TCGA Pan-Cancer Atlas contains genetic alteration data including somatic mutations and copy number variants (CNVs), as well as several -omics data types. From TCGA, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts. Across a collection of cancer-associated genetic alterations, RNA sequencing and DNA methylation were the most effective predictors of alteration state. Surprisingly, we found that for most alterations, they were approximately equally effective predictors. The target gene was the primary driver of performance, rather than the data type, and there was little difference between the top data types for the majority of genes. We also found that combining data types into a single multi-omics model often provided little or no improvement in predictive ability over the best individual data type. Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, we recommend focusing on gene expression or DNA methylation as first-line readouts.
Using Card Sorting to Design Faceted Navigation Structures

This paper describes how a variation of card sorting‘repeated single-criterion sorting’, can be applied to the information architecture design of digital music services. 52 respondents were asked to sort, using their own choice of criteria, 12 popular songs using an online card sorting tool. Once respondents had chosen a construct for a particular sort, e.g. “Genre”, they placed each card into a named category, e.g. “Rock”, “Pop”, and were encouraged to repeat this process until they could think of no more constructs. High levels of agreement were found for a small number of constructs such as “genre”, “gender”, and “speed of song” but the remaining constructs were individual to each respondent, e.g. “songs that make me cry”. The results highlighted differences with current approaches to music categorisation, as well as the potential for repeated single-criterion sorting to be used to design faceted navigation structures.
Explainability and Continuous Learning with Capsule Networks

: Capsule networks are an emerging technique for image recognition and classiﬁcation tasks with innovative approaches inspired by the human visual cortex. State of the art is that capsule networks achieve good accuracy for future image recognition tasks and are a promising approach for hierarchical data sets. In this work, it is shown that capsule networks can generate image descriptions representing detected objects in images. This visualisation in combination with reconstructed images delivers strong and easily understandable explainability regarding the decision-making process of capsule networks and leading towards trustworthy AI. Furthermore it is shown that capsule networks can be used for continuous learning utilising already learned basic geometric shapes to learn more complex objects. As shown by our experiments, our approach allows for distinct explainability making it possible to use capsule networks where explainability is required.
Compact Planar Tunable Filter With Constant Absolute Bandwidth and Wide-Frequency Tuning Range Using DGS Coupling Structure

In this study, defected ground structures (DGSs) are applied in the coupling schemes of a planar tunable filter to achieve constant absolute bandwidth (CAB). The filter consists of parallel-coupled quarter-wavelength resonators loaded with varactor diodes, and the DGSs are implemented to enhance the coupling at a certain part. This method enables controlling the ratio between electric coupling and magnetic coupling and makes the total coupling coefficient inversely proportional to frequency, as required to achieve CAB. With the DGSs, the tunable resonators can be equalized to stepped-impedance tunable resonators, which bring wider-frequency tuning range. Moreover, due to the help of the DGS in adjusting the coupling coefficient curve versus frequency, the resonators maintain their universal widths and are coupled at full length. Thus, the tunable filter is as compact as a traditional combline filter. Meanwhile, each external coupling scheme contains a series capacitor and a short-ended stub that is parallel coupled to the first or last resonator, resulting in external $Q$ factor being proportional to frequency. A second-order tunable filter is designed and measured, and a wide tuning range from 0.63 GHz to 1.09 GHz together with a constant bandwidth of 65±4 MHz are achieved. Besides, a transmission zero generated by coupling zero of the DGS-loaded coupling structure can be observed at the high stopband. The total dimension of the filter is 0.05 $\lambda _{\mathrm {g}}^{\ast }~0.15 \lambda _{\mathrm {g}}$ , which is more compact than solutions with partial-length coupling schemes. Owing to the simple structures of the resonators and coupling schemes, the filter solution has the potential to design high-order tunable filters with CAB, and a compact fourth-order tunable filter with ABC is given with simulation results.
Integration of GWAS and TWAS to elucidate the genetic architecture of natural variation for leaf cuticular conductance in maize

The cuticle, a hydrophobic layer of cutin and waxes synthesized by plant epidermal cells, is the major barrier to water loss when stomata are closed. Dissecting the genetic architecture of natural variation for maize leaf cuticular conductance (gc) is important for identifying genes relevant to improving crop productivity in drought-prone environments. To this end, we performed an integrated genome- and transcriptome-wide association study (GWAS/TWAS) to identify candidate genes putatively regulating variation in leaf gc. Of the 22 plausible candidate genes identified, five were predicted to be involved in cuticle precursor biosynthesis and export, two in cell wall modification, nine in intracellular membrane trafficking, and seven in the regulation of cuticle development. A gene encoding an INCREASED SALT TOLERANCE1-LIKE1 (ISTL1) protein putatively involved in intracellular protein and membrane trafficking was identified in GWAS and TWAS as the strongest candidate causal gene. A set of maize nested near-isogenic lines that harbor the ISTL1 genomic region from eight donor parents were evaluated for gc, confirming the association between gc and ISTL1 in a haplotype-based association analysis. The findings of this study provide novel insights into the role of regulatory variants in the development of the maize leaf cuticle, and will ultimately assist breeders to develop drought-tolerant maize for target environments. Sentence summary We performed an integrated GWAS/TWAS and identified 22 candidate genes putatively regulating variation in maize leaf gc. The association between gc and the strongest candidate causal gene, ISTL1, was validated with maize nested near-isogenic lines.
On Architectural Decay Prediction in Real-Time Software Systems

As the number of software applications including the widespread of real-time and embedded systems are constantly increasing and tend to grow in complexity, the architecture tends to decay over the years, leading to the occurrence of a spectrum of defects and bad smells (i.e., instances of architectural decay) that are manifested and sustained over time in a software system’s life cycle. Thus, the implemented system is not compliant to the specified architecture and such architectural decay becomes an increasing challenge for the developers. We propose a set of constructive architecture views at different levels of granularity, which monitor and ensure that the modifications made by developers at the implementation level are in compliance with those of the different architectural timed-event elements of real-time systems. Thus, we investigated a set of orthogonal architectural decay paradigms timed-event component decay, timed-event interface decay, timed-event connector decay and timed-event port decay. All of this has led to predicting, forecasting, and detecting architectural decay with a greater degree of structure, abstraction techniques, architecture reconstruction; and hence offered a series of potential effectiveness and enhancement in gaining a deeper understanding of implementation-level bad smells in real-time systems. Furthermore, to support this research towards an effective architectural decay prediction and detection geared towards real-time and embedded systems, we investigated and evaluated the effect of our approach through a real-time Internet of Things (IoT) case study.
Bayesian inference of neuronal assemblies

In many areas of the brain, both spontaneous and stimulus-evoked activity can manifest as synchronous activation of neuronal assemblies. The characterization of assembly structure and dynamics provides important insights into how brain computations are distributed across neural networks. The proliferation of experimental techniques for recording the activity of neuronal assemblies calls for a comprehensive statistical method to describe, analyze and characterize these high dimensional datasets. The performance of existing methods for defining assemblies is sensitive to noise and stochasticity in neuronal firing patterns and assembly heterogeneity. To address these problems, we introduce a generative hierarchical model of synchronous activity to describe the organization of neurons into assemblies. Unlike existing methods, our analysis provides a simultaneous estimation of assembly composition, dynamics and within-assembly statistical features, such as the levels of activity, noise and assembly synchrony. We have used our method to characterize population activity throughout the tectum of larval zebrafish, allowing us to make statistical inference on the spatiotemporal organization of tectal assemblies, their composition and the logic of their interactions. We have also applied our method to functional imaging and neuropixels recordings from the mouse, allowing us to relate the activity of identified assemblies to specific behaviours such as running or changes in pupil diameter.
Rethinking a new transition finance paradigm for addressing the climate crisis in Africa

This policy brief uncovers the investment-ready instruments and policy packages that can unlock the energy transition in Sub-Saharan Africa. These are summarised around three key messages. First, transition finance vehicles in Africa should aim to transform ‘brown’ (polluting) into ‘green’ (renewable) industries. Second, key instruments include green bonds for specific environmental projects, grants/guaranties to support private investments that target access to energy for the poor, and patient capital investments into growth sectors focused on environmental, social, and governance targets. Third, national energy policy should connect innovative market-based solutions (e.g., mini grids) to centralized (e.g., national grid) systems to strengthen governance.
Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics

During spatial exploration, neural circuits in the hippocampus store memories of sequences of sensory events encountered in the environment. When sensory information is absent during “offline” resting periods, brief neuronal population bursts can “replay” sequences of activity that resemble bouts of sensory experience. These sequences can occur in either forward or reverse order, and can even include spatial trajectories that have not been experienced, but are consistent with the topology of the environment. The neural circuit mechanisms underlying this variable and flexible sequence generation are unknown. Here we demonstrate in a recurrent spiking network model of hippocampal area CA3 that experimental constraints on network dynamics such as population sparsity, stimulus selectivity, rhythmicity, and spike rate adaptation enable additional emergent properties, including variable offline memory replay. In an online stimulus-driven state, we observed the emergence of neuronal sequences that swept from representations of past to future stimuli on the timescale of the theta rhythm. In an offline state driven only by noise, the network generated both forward and reverse neuronal sequences, and recapitulated the experimental observation that offline memory replay events tend to include salient locations like the site of a reward. These results demonstrate that biological constraints on the dynamics of recurrent neural circuits are sufficient to enable memories of sensory events stored in the strengths of synaptic connections to be flexibly read out during rest and sleep, which is thought to be important for memory consolidation and planning of future behavior.
Inventory of child bicycle education programs reveals need for age, development, and skill-level considerations.

Objective: There are a plethora of child bicycle safety education programs worldwide. However, the content and durations vary widely from program to program and no gold standard has been established. The main objective of this project was to create an inventory of youth bicycle safety education programs and their content, approaches, and age and developmental considerations.Methods: Methods used to gather program information included web and online database searches, extraction from personal lists, and a widely distributed online survey. A total of 89 programs met inclusion criteria and were reviewed (78 from the United States and 11 from other countries). Results: Over half (56.2%) of the included programs were not explicitly age specific, meaning that the content was not appropriately designated by age and developmental cut points. Many programs had target age groups, but these were often very wide age ranges (e.g., all elementary school-age children) resulting in content too advanced for the youngest children. Only 12.4% of included programs had published program evaluations and their scientific rigor varied widely. Main results from this inventory revealed a weak evidence base for program effectiveness due to lack of program evaluations. Results also highlighted a need for age, development, and skill-level considerations in youth bicycle education programs.Conclusions: This study provides a comprehensive list of program components and approaches that can be used as a foundation upon which child bicycle education standards can be evaluated and built, with the long-term goal of increased childhood safety.
An Overview of Surgical Treatment of Perforated Peptic Ulcer

A number of advancements in the therapy of perforated duodenal ulcers have been made in the recent two decades, suggesting that the disease's morbidity and mortality may be reduced. Recently, there has been a return to a more conservative first approach, with reports of either delayed resection or two-stage surgery, in which a non-radical resection is performed first, followed by lymphadenectomy at a later date. Furthermore, because gastric lymphoma can be cured without resection, many upper GI surgeons recommend performing a biopsy and repair at the index operation and then considering how best to continue if adenocarcinoma is discovered later.
Using a Two-Stage Method to Reject False Loop Closures and Improve the Accuracy of Collaborative SLAM Systems

Loop-closure detection is an essential means to reduce accumulated errors of simultaneous localization and mapping (SLAM) systems. However, even false positive loop closures could seriously interfere and even corrupt the back-end optimization process. For a collaborative SLAM system that generally uses both intra-robot and inter-robot loop closures to optimize the pose graph, it is a tough job to reject those false positive loop closures without a reliable a priori knowledge of the relative pose transformation between robots. Aiming at this solving problem, this paper proposes a two-stage false positive loop-closure rejection method based on three types of consistency checks. Firstly, a multi-robot pose-graph optimization model is given which transforms the multi-robot pose optimization problem into a maximum likelihood estimation model. Then, the principle of the false positive loop-closure rejection method based on test is proposed, in which clustering is used to reject those intra-robot false loop-closures in the first step, and a largest mutually consistent loop-based test is constructed to reject inter-robot false loop closures in the second step. Finally, an open dataset and synthetic data are used to evaluate the performance of the algorithms. The experimental results demonstrate that our method improves the accuracy and robustness of the back-end pose-graph optimization with a strong ability to reject false positive loop closures, and it is not sensitive to the initial pose at the same time. In the Computer Science and Artificial Intelligence Lab (CSAIL) dataset, the absolute position error is reduced by 55.37% compared to the dynamic scaling covariance method, and the absolute rotation error is reduced by 77.27%; in the city10,000 synthetic dataset, the absolute position error is reduced by 89.37% compared to the pairwise consistency maximization (PCM) and the absolute rotation error is reduced by 97.9%.
Acquired Thrombotic Purpura Successfully Treated with Caplacizumab without Plasma Transfusion in a Jehovah’s Witness Patient

DOI: 10.46998/IJCMCR.2021. 10.000245 Abstract Acquired Thrombotic Thrombocytopenic Purpura (TTP) is a hematologic emergency characterized by auto-antibody mediated inhibition or clearance of ADAMTS13, a von Willebrand Factor (vWF) cleaving metalloprotease, thrombocytopenia, microvascular thrombosis, and hemolytic anemia. The primary treatment of TTP is therapeutic plasma exchange with human plasma transfusion, a procedure known as PLEX. Caplacizumab, an immunoglobulin fragment that inhibits vWF and platelet interaction, has been shown to improve outcomes when used in conjunction with PLEX and immunosuppression. For Jehovah’s Witness patients who do not accept plasma transfusion, optimal treatment is uncertain. We present a case of TTP successfully treated with delayed caplacizumab without plasma transfusion. Our patient’s experience provides evidence that caplacizumab with immunosuppression even in the absence of PLEX may be a feasible alternative for treatment of TTP in patients who are unwilling or unable to accept plasma transfusion. Our case also provides evidence for use of caplacizumab as a step-up therapy in patients who fail initial treatment with therapeutic plasma exchange.
Cell Fate Control by Translation: mRNA Translation Initiation as a Therapeutic Target for Cancer Development and Stem Cell Fate Control

Translation of mRNA is an important process that controls cell behavior and gene regulation because proteins are the functional molecules that determine cell types and function. Cancer develops as a result of genetic mutations, which lead to the production of abnormal proteins and the dysregulation of translation, which in turn, leads to aberrant protein synthesis. In addition, the machinery that is involved in protein synthesis plays critical roles in stem cell fate determination. In the current review, recent advances in the understanding of translational control, especially translational initiation in cancer development and stem cell fate control, are described. Therapeutic targets of mRNA translation such as eIF4E, 4EBP, and eIF2, for cancer treatment or stem cell fate regulation are reviewed. Upstream signaling pathways that regulate and affect translation initiation were introduced. It is important to regulate the expression of protein for normal cell behavior and development. mRNA translation initiation is a key step to regulate protein synthesis, therefore, identifying and targeting molecules that are critical for protein synthesis is necessary and beneficial to develop cancer therapeutics and stem cells fate regulation.