Miracle-dz/UniFAR-FTUs huggingface dataset:
An Exploration of Failures in Visual Working Memory: A Steady-State Visual Evoked Potential Study

Working memory consists of three stages: encoding, maintenance, and retrieval. It has been demonstrated that working memory (WM) capacity is limited to about four items (Cowan 2001). However, there are ambiguities regarding why some items are correctly retrieved and why others are subsequently lost. Previous studies have not been able to demonstrate at which stage these items are lost because these studies only measure the processing of all items shown in a memory array. This investigation employs a novel paradigm pairing frequency tagging and a full report paradigm. This paradigm allowed us to disentangle individual items that were encoded and compare these items to the items that were actually retrieved. Two attentional models were tested in regards to encoding: the ‘graded attention’ model and the ‘all or nothing’ model. These two models describe how neural resources are allocated to items in a memory array. This study found that frequency tag amplitudes were larger for items correctly retrieved as compared to items subsequently forgotten. The data were also found to be consistent with the ‘all or nothing’ attentional model that states that attentional resources are spread to all items during encoding. The results indicate how important WM encoding is to explaining underlying mechanisms for why WM fails.
Design and Implementation of Vision Based Safety Detection Algorithm for Personnel in Construction Site

The failure of construction workers to wear safety equipment as required is an important cause of safety accidents. In fortunate cases people are injured and severe cases can cause death. In order to prevent this from happening, this paper proposes an algorithm consist of data augmentation for complex environments and object occlusion, more than 17,000 sample images and an advanced neural network model faster R-CNN[1] . The experimental results show that the method can identify the personnel and helmets in the surveillance video in real time, and the average recognition accuracy is up to 90.3%, and the detection time is up to 0.037s per image. It satisfies the safety requirements of real-time detection of construction sites.
Prototype of a Compact Assistant Surveillance Robot for Search and Rescue Operations

This paper presents a prototype of a compact, affordable mobile rescue robot that can be used to gather real-time information on difficult to reach locations during rescue operations. The prototype uses Arduino Mega 2560 as the main microcontroller, FPV camera for real-time video streaming mounted on a tilt assembly. Continuous track differential wheels were utilized for all-terrain navigation. The robot can be used in simple rescue operations such as for detecting, locating injured and characterizing obstacles in collapsed structures.
An ERP success model based on agency theory and IS success model: The case of a banking institution in Africa

The purpose of this paper is to propose an enterprise resource planning (ERP) implementation model based on the agency theory and the Delone and McLean information systems (IS) success model. This paper answers two major research questions: (i) how does client–consultant interaction affect the outcome of ERP implementation projects; and (ii) how can this interaction be managed effectively to ensure successful project outcomes? ,An electronic banking institution in Africa was used to conduct a case study research and examine the validity of the proposed conceptual framework. ,Based on the constructs of the conceptual framework, the study found that client–consultant relationships/interactions mediate the effect of human, organizational, and technological critical success factors (CSFs) on information quality, service quality, and information quality. Agency conflicts in client–consultant relationships can be managed using outcome incentive-based contracts and a conflict management committee. ,This is a single case study research. Thus, despite its analytical validity and generalizability, there is a need for more studies on the statistical validity of the model in other contexts. ,This paper provides practical information needed to manage conflicts between clients and consultants, as well as factors that must be considered in order to keep the interest of both parties aligned. ,No research has been conducted on how to manage client–consultant interactions and related conflicts in ERP implementation projects. This study fills this gap using a well-established theoretical foundation to propose a conceptual framework that would guide and drive further discussions on the topic. This is also one of the few studies in the context of developing countries.
Alignment-free Phylogeny Reconstruction Based On Quartet Trees

Traditional methods for phylogeny reconstruction are based on multiple sequence alignments and character-based methods. This combination of computationally expensive methods leads to very accurate results, but it is ill-suited to handle the enormous amount of sequence data that is available today. As a consequence, very fast alignment-free methods have been developed. These methods calculate pairwise distances in order to build phylogenetic trees. However, current alignment-free methods are generally less accurate than traditional methods. In this thesis, I developed Multi-SpaM which is a novel alignment-free approach that tries to combine the best of both worlds. This method quickly finds small gap-free ‘microalignments’ – so-called blocks – involving four sequences. A binary pattern defines at which positions the nucleotides have to match. At the remaining don’t care positions, the possibly mismatching nucleotides are first used to remove random matches with a filtering procedure previously introduced by Filtered Spaced-Word Matches (FSWM). Then, the character-based method RAxML is used to find the optimal quartet tree for each block. Subsequently, all quartet trees are amalgamated into a supertree with Quartet MaxCut. This approach can be used to build phylogenetic trees of high quality. Furthermore, I showed multiple ways that could help to improve Multi-SpaM. The distances between two adjacent blocks involving the same four sequences can be used to identify putative insertions and deletions from which accurate quartet trees can be derived. These trees could be used both on their own and in combination with the quartet trees produced by Multi-SpaM to build or improve phylogenetic trees using Quartet MaxCut. As an alternative, we also used Maximum-Parsimony to infer accurate phylogenies from these putative insertions and deletions. In other experiments, I tried to give the individual quartet trees weights based on SH-like support values and tried to use Neighbor-Joining in order to speed up Multi-SpaM. Moreover, I contributed to another extension of the FSWM approach. Here, we used these matches as anchor points for a genome alignment tool called mugsy. We found that a higher number of homologous pairs could be aligned for more distantly related species in comparison to other anchor points used with the same alignment program.
Functional control of HIV-1 post-transcriptional gene expression by host cell factors

RNA helicases are encoded by all eukaryotic and prokaryotic cells and a minority of viruses. Activity of RNA helicases is necessary for all steps in the expression of cells and viruses and the host innate response to the infectious pathogens including viruses. Their vast functional repertoire is attributable to the core ATPase-dependent helicase domain in conjunction with flanking domains that are interchangeable and engage viral and cellular cofactors. This chapter evaluates the experimental approaches to dissect the functions of the host RNA helicases that are necessary for virus replication. The chapter presents multiple approaches for the identification and characterization of candidate helicase and methods to define the biochemical and biophysical parameters of specificity and functional activity. The methods presented are in the context of the cell-intrinsic RNA helicase activity and virion-associated RNA helicase function. In order to determine the virologic scope of RNA helicase superfamily members across divergent cell lineages and viral replication cycles, the methodology and the choice of controls presented in this chapter can be effectively employed.
Morphometric comparison of native and non-native populations of round goby Neogobius melanostomus from the River Danube

Abstract. The external morphology of native (Bulgarian) and non-native (Slovak) populations of Neogobius melanostomus was examined using standard distance-based measurements and, in addition, comparison of fin ray number between populations was made. Five of the 29 morphological characters measured differed between populations, both for males and females. The non-native population was characterised by a smaller mouth and eye, shorter pre-dorsal distance and greater inter-orbital distance. Three characters, post-orbital distance, head depth and minimal body depth, differed between populations only in females, though the overall trend was the same in both sexes. A lower head depth value, greater post-orbital distance and minimal body depth was recorded for females from the non-native population. The range in fin ray numbers was similar between native and non-native populations. Populations differed, however, in the frequency of pectoral fin rays. Individuals with 17 pectoral fin rays were more common in the non-native range, their proportion in the native range being low. In contrast, individuals with 19 pectoral fin rays occurred more commonly in the native range. This difference was consistent for both sexes. The differences between populations are discussed within the context of differing environments and the “ship transport” hypothesis.
Beneficial Effects of Pentoxifylline in Patients With Idiopathic Dilated Cardiomyopathy Treated With Angiotensin-Converting Enzyme Inhibitors and Carvedilol

Background—We previously reported beneficial effects of pentoxifylline, a xanthine-derived agent known to inhibit the production of tumor necrosis factor-α, in patients with idiopathic dilated cardiomyopathy treated with diuretics, digoxin, and ACE inhibitors. Since then, 3 large clinical trials showed important clinical benefits of β-blockers in this population. Therefore, we designed the present study to establish whether in patients with heart failure already receiving treatment with ACE inhibitors and β-blockers, the addition of pentoxifylline would have an additive beneficial effect. Methods and Results—In a single-center, prospective, double-blind, randomized, placebo-controlled study, 39 patients with idiopathic dilated cardiomyopathy were randomized to pentoxifylline 400 mg TID (n=20) or placebo (n=19) if they had a left ventricular ejection fraction <40% after 3 months of therapy with digoxin, ACE inhibitors, and carvedilol. Primary end points were New York Heart Association functional class, exe.
Vaccinia virus as a tool to study novel mechanisms of host cell contraction and blebbing

Vaccinia is a widely studied member of the poxvirus family. Throughout its life cycle, vaccinia manipulates cellular processes of the host to aid its replication and spread. Early in infection vaccinia stimulates transient host cell contraction, associated with dynamic plasma membrane blebbing and migration, reminiscent of the RhoA-ROCK regulated amoeboid migration of cancer cells. Cell contraction required the expression of early vaccinia genes whilst subsequent re-spreading required late vaccinia genes. Using a virus that does not express the vaccinia protein F11, I showed that F11 was required for virus infection to stimulate contraction. However, using a highly attenuated vaccinia strain rescued with wild type F11, MVA-F11, I found that cell contraction additionally required other vaccinia proteins. Live cell imaging of F11-GFP revealed that F11 is recruited to the plasma membrane during blebbing, further supporting a role for F11 in regulating these membrane events. Despite previous evidence from this laboratory showing F11 interacts with RhoA, I found that cell contraction was independent of RhoA. Instead vaccinia induced contraction required RhoC to ROCK signalling. Furthermore, using a small siRNA screen of several Rho GTPases, I discovered that RhoD negatively regulates vaccinia-induced contraction. I suggest that RhoD can supress cell contraction in uninfected and ∆F11L-infected cells by inhibiting RhoC activation, and suggest that RhoD signalling is inhibited during infection to allow for efficient cell contraction.
Embodiment Effects in Interactions with Failing Robots

The increasing use of robots in real-world applications will inevitably cause users to encounter more failures in interactions. While there is a longstanding effort in bringing human-likeness to robots, how robot embodiment affects users' perception of failures remains largely unexplored. In this paper, we extend prior work on robot failures by assessing the impact that embodiment and failure severity have on people's behaviours and their perception of robots. Our findings show that when using a smart-speaker embodiment, failures negatively affect users' intention to frequently interact with the device, however not when using a human-like robot embodiment. Additionally, users significantly rate the human-like robot higher in terms of perceived intelligence and social presence. Our results further suggest that in higher severity situations, human-likeness is distracting and detrimental to the interaction. Drawing on quantitative findings, we discuss benefits and drawbacks of embodiment in robot failures that occur in guided tasks.
Fine-Grained Gating Based on Question-Summary for Machine Comprehension

Currently, Deep Learning (DL) models for performing Machine Comprehension are very focused on Interaction Encoders, which are mostly based on attention mechanisms. DL models for encoding context, usually include pre-trained features into the initial embeddings, such as: Part-of-Speech, Named Entity Recognition, Term Frequency, etc. In this paper, we propose to use a ﬁne-grained gating mechanism that controls the ﬂow of information from the Context Encoder towards the Interaction Encoder. This gate is based on the Question-summary and the input vector at some time step. This simple structure has been shown to improve the performance of a given baseline model. Our model achieved 68.70% of exact match and 78.25% of F1 measure, on the Stanford question answering benchmark.
Safety comparison of over the counter bleaching with professionally prescribed home bleaching agent

Aims: This aimed to compare the colour changes, microhardness, and surface roughness of the human natural tooth after bleaching treatment with a professional home bleaching agent and over-the-counter (OTC) bleaching agent. Settings and Design: This was an in vitro study using extracted human teeth stained with human blood as specimens. Materials and Methods: Fifty-seven human natural teeth were embedded in acrylic of 2.5 mm thickness and 14 mm × 8 mm surface area. The samples were stained with human blood before they were divided into three groups (n = 19 per group) of control (C), Professional Bleaching Opalescence PF 15% (PB), and OTC Whitelight Tooth Whitening set (WL) before being treated with the respective bleaching agents for 10 days. Color changes were measured as colorimetric measurements (L*, a*, and b* values) were recorded during prestaining, poststaining, and postbleaching, while microhardness and surface roughness measurements were recorded for pre- and postbleaching. Statistical Analysis: Statistical analysis was done with SPSS (IBM Statistic, California, USA) version 22.0. Paired t-test and nonparametric analysis (Wilcoxon Signed-Rank Test) were used to analyze the data. P value was set as significant at P < 0.05. Results: The color changes in PB group was not significantly better compared with WL group (PB: 12.2 [4.07] and WL: 12.2 [4.32]). Whereas significant difference was noticed in microhardness after bleaching in PB group with a higher VHN number (500.4 [121.10]) compared with WL group (471.0 [114.47]) . The surface roughness (Ra) remain the same for all experimental groups. Conclusions: Both professional home bleaching agent and OTC bleaching agents showed similar efficacy, with no effect on surface roughness, and both caused an increase in microhardness.
Feasibility study of an Online 24-hr Dietary Assessment Tool: myfood24, in a clinical population

myfood24 is a comprehensive self-completed online 24-hour dietary recall tool currently used for nutritional assessments in epidemiological research. However, its clinical application has been unexplored. This mixed methods prospective observational study explores the acceptability and usability of myfood24 in a clinical population, women with gestational diabetes (GDM). Women were recruited at their first diabetes antenatal clinic appointment. To assess acceptability and usability, they were asked to complete five 24-hour dietary recalls using myfood24 over two weeks and a user experience questionnaire; with a subset invited to participate in a one-to-one semi-structured interview. Of the 199 participants, mean maternal age was 33 years, mean booking BMI 29.7kg/m2, 36% primiparous, 57% White, 33% Asian. Of these 121 (61%) completed myfood24 at least once and 73 (37%) completed the user questionnaire; 15 were interviewed. Usability of myfood24 was measured using the System Usability Scale (SUS) and found to be good (mean 70.9, 95%CI 67.1, 74.6). Interviews identified several areas for improvement, including optimising its use for mobile devices. myfood24 appears to be acceptable and have potential to support self-management and behaviour change for women with GDM but requires adaptation to record blood glucose results alongside real-time tracking of diet.
Enriching Neural MT through Multi-Task Training

The Transformer model is a very recent, fast and powerful discovery in neural machine translation. We experiment with multi-task learning for enriching the source side of the Transformer with linguistic resources to provide it with additional information to learn linguistic and world knowledge better. We analyze two approaches: the basic shared model with multi-tasking through simple data manipulation, and multi-decoder models. We test joint models for machine translation (MT) and POS tagging, dependency parsing and named entity recognition as the secondary tasks. We evaluate them in comparison with the baseline and with dummy, linguistically unrelated tasks. We focus primarily on the standard-size data setting for German-to-Czech MT. Although our enriched models did not significantly outperform the baseline, we empirically document that (i) the MT models benefit from the secondary linguistic tasks; (ii) considering the amount of training data consumed, the multi-tasking models learn faster; (iii) in low-resource conditions, the multi-tasking significantly improves the model; (iv) the more fine-grained annotation of the source as the secondary task, the higher benefit to MT.
Support vector machine filtering data aid on fatigue driving detection

This paper proposes an assumption that filtering out the confusing “awake” data from fatigue driving detection model promotes the accuracy of detection of “drowsy” status under real driving situation. Instead of focus on both “drowsy” and “awake” driving status, we set our first priority to alarm “drowsy” and temporarily ignore the accuracy of “awake” status recognition. The Support Vector Machine as a good classifier is employed for data filtering, provides more efficient training data and removes the data that may confuse the detection model. The results prove our assumption by 72% accuracy on “drowsy” recognition, which is higher than 38% recognition performed by detection without SVM filtering. In addition, the size of training samples after filtering for conducting detection model is extremely smaller than no filtering.
High throughput physiological micro-models for in vitro pre-clinical drug testing: a review of engineering systems approaches

To address the low success rate of new drug discovery, there has been significant growth of in vitro physiological micro-models based on human cells. These may be in the form of cell spheroids, organs-on-a-chip, or multi-cellular tissue cultures, and it is expected that the more biomimetic environment they create will be more accurate than standard cell culture in drug screening prior to clinical testing. However, commercial use of complex co-cultures is still limited. This is due to a lack of validation, low throughput rates, and a lack of compatibility with standard assessment techniques. This review paper focusses specifically on the different engineering approaches used to create, mature and analyse these micro-models, with the aim of exploring which approaches have the potential for high throughput. Active and passive pumping and nozzle based dispensing techniques are considered for fluid handling, with transwells, cell patterning, spheroid cultures and microfluidics considered for establishing and maintaining co-cultures, together with conventional analysis techniques (proteomic and genomic approaches, and immunohistochemistry) and novel sensor systems for downstream analysis are considered. It is concluded that (i) throughput is essential for validation as well as exploitation of the models, and (ii) an integrated approach to model re-design for high throughput is key, with the limitations on throughput at each stage considered in order to develop a system which can deliver and analyse at high throughput rates at all stages of the process.
An iterative transfer learning framework for cross‐domain tongue segmentation

Tongue diagnosis is an important clinical examination in Traditional Chinese Medicine. As the first step of the diagnosis, the accuracy of tongue image segmentation directly affects the subsequent diagnosis. Recently, deep learning‐based methods have been applied for tongue image segmentation and achieve promising results. However, these methods usually work well on one dataset and degenerate significantly on different distributed datasets. To deal with this issue, we propose a framework named Iterative cross‐domain tongue segmentation in the study. First, we train a tongue image segmentation U‐Net model on the source dataset. Then, we propose a tongue assessment filter to select satisfying samples based on predictions of the U‐Net model from the target dataset. Following, we fine‐tune the model on the selected samples along with the source domain. Finally, we iterate between the filtering and the fine‐tuning steps until the model is converged. Experimental results on two tongue datasets show that our proposed method can improve the dice score on the target domain from 70.11% to 98.26%, as well as outperform state‐of‐the‐art comparing methods.