Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing Machine Translation Engines for Multilingual Participatory Spaces

It is often a challenging task to build Machine Translation (MT) engines for a specific domain due to the lack of parallel data in that area. In this project, we develop a range of MT systems for 6 European languages (English, German, Italian, French, Polish and Irish) in all directions and in two domains (environment and economics).
Neural Speech Translation: From Neural Machine Translation to Direct Speech Translation

Speech-to-text translation, or simply speech translation (ST), is the task of translating automatically a spoken speech. The problem has classically been tackled by combining the technologies of automatic speech recognition (ASR) and machine translation (MT) with different degrees of coupling (Takezawa et al., 1998; Waibel et al., 1991). The most popular approach is to cascade ASR and MT systems, as it can make use of the state of the art in such mature fields (Black et al., 2002). The goal of this thesis was to develop the so-called approach of direct speech translation, which translates audio without intermediate transcription (Duong et al., 2016; Bérard et al., 2016; Weiss et al., 2017). Direct speech translation (DST) is based on the sequence-to-sequence learning technology that allowed the spectacular advances of the field of neural MT (NMT) but introducing its own challenges (Sutskever et al., 2014; Bahdanau et al., 2015). We started with a study about the effects of NMT in cascaded ST, where we analyzed the translation errors of NMT and phrase-based MT (PBMT) for automatically transcribed input text. Our results showed that NMT achieves an overall higher quality also in this setting, but its ability to model a theoretically-unlimited context can introduce subtle errors. Indeed, we found that in PBMT the errors are localized in correspondence to the source error, whereas NMT can introduce errors far from the source-side error position. Motivated by application needs, in a following work we studied how to use a single NMT system to translate effectively clean source text and automatic transcripts. We found that a simple training
POLENG MT: An Adaptive MT Platform

We introduce POLENG MT, an MT platform that may be used as a cloud web application or as an on-site solution. The platform is capable of providing accurate document translation, including the transfer of document formatting between the input document and the output document. The main feature of the on-site version is dedicated customer adaptation, which consists of training on specialized texts and applying forced terminology translation according to the user’s needs.
Automatic Video Dubbing at AppTek

Video dubbing is the activity of revoicing a video while offering a viewing experience equivalent to the original video. The revoicing usually comes with a changed script, mostly in a different language, and the revoicing should reproduce the original emotions, coherent with the body language, and lip synchronized. In this project, we aim to build an AD system in three phases: (1) voice-over; (2) emotional voice-over; (3) full dubbing, while enhancing the system with human-in-the-loop capabilities for a higher quality.
“Hi, how can I help you?” Improving Machine Translation of Conversational Content in a Business Context

This paper addresses the automatic translation of conversational content in a business context, for example support chat dialogues. While such use cases share characteristics with other informal machine translation scenarios, translation requirements with respect to technical and business-related expressions are high. To succeed in such scenarios, we experimented with curating dedicated training and test data, injecting noise to improve robustness, and applying sentence weighting schemes to carefully manage the influence of the different corpora. We show that our approach improves the performance of our models on conversational content for all 18 investigated language pairs while preserving translation quality on other domains - an indispensable requirement to integrate these developments into our MT engines at SAP.
MTee: Open Machine Translation Platform for Estonian Government

We present the MTee project - a research initiative funded via an Estonian public procurement to develop machine translation technology that is open-source and free of charge. The MTee project delivered an open-source platform serving state-of-the-art machine translation systems supporting four domains for six language pairs translating from Estonian into English, German, and Russian and vice-versa. The platform also features grammatical error correction and speech translation for Estonian and allows for formatted document translation and automatic domain detection. The software, data and training workflows for machine translation engines are all made publicly available for further use and research.
Oxford Nanopore Sequencing Reveals an Exotic Broad bean mottle virus Genome within Australian Grains Post-Entry Quarantine

A Broad bean mottle virus (BBMV) isolate (S52) obtained from an infected Vicia faba leaf sample from Syria was sequenced using Oxford Nanopore long-read sequencing at the Australian border. The genome had 95.6%, 98.2%, and 93.4% nucleotide sequence identity to BBMV strains RNA1 (Bawden), RNA2 (Mo), and RNA3 (Bawden). ABSTRACT A Broad bean mottle virus (BBMV) isolate (S52) obtained from an infected Vicia faba leaf sample from Syria was sequenced using Oxford Nanopore long-read sequencing at the Australian border. The genome had 95.6%, 98.2%, and 93.4% nucleotide sequence identity to BBMV strains RNA1 (Bawden), RNA2 (Mo), and RNA3 (Bawden).
nEYron: Implementation and Deployment of an MT System for a Large Audit & Consulting Corporation

This paper reports on the implementation and deployment of an MT system in the Polish branch of EY Global Limited. The system supports standard CAT and MT functionalities such as translation memory fuzzy search, document translation and post-editing, and meets less common, customer-specific expectations. The deployment began in August 2018 with a Proof of Concept, and ended with the signing of the Final Version acceptance certificate in October 2021. We present the challenges that were faced during the deployment, particularly in relation to the security check and installation processes in the production environment.
The PASSAGE project : Standard German Subtitling of Swiss German TV content

We present the PASSAGE project, which aims at automatic Standard German subtitling of Swiss German TV content. This is achieved in a two step process, beginning with ASR to produce a normalised transcription, followed by translation into Standard German. We focus on the second step, for which we explore different approaches and contribute aligned corpora for future research.
In vivo and in silico approaches to assess surface water genotoxicity from Tocantins River, in the cities of Porto Nacional and Palmas, Brazil

Abstract The main environmental problem in urban areas, especially in Brazil, is the discharge of untreated sewage. The in vivo Drosophila melanogaster Somatic Mutation and Recombination Test (SMART) was used to assess the genotoxicity of surface waters from three different sites in the Tocantins River, Brazil. The in silico approach was used to search for known and predicted interactions between environmental chemicals found in our samples and Drosophila and human proteins. The genotoxicity tests were performed in standard (ST) and high bioactivation (HB) crosses with samples collected at two periods, the rainy and dry seasons. Mutant spot frequencies found in treatments with unprocessed water from the test sites were compared with the frequencies observed in negative controls. The collection points were represented as sites A, B and C along Tocantins River. Sites A and B are located in Porto Nacional City, whereas site C is located in Palmas City. Considering the rainy season collection, positive responses in the ST cross were observed for sites A and C (89.47% and 85% of recombination, respectively) and in the HB cross for sites A, B and C (88.24%, 84.21% and 82.35% of recombination, respectively). The positive results in the dry season were restricted to sites A and B (88.89% and 85.71% of recombination, respectively) in the HB cross. In accordance with in vivo and in silico results, we hypothesize that ribosomal proteins (RPs) in fruit fly and humans are depleted in cells exposed to heavy metal causing DNA damage and chromosome instability, increasing homologous recombination.
Breath and the dynamics of connection and disconnection: a neuro-scientifically informed perspective

ABSTRACT This article, which is based on a keynote speech delivered to PCE2021, takes the first theme of the conference, Tihei mauri ora, as a framework with which to examine the role of breath in well-being and the ways in which we connect and disconnect from ourselves and others. The theoretical context of the article is the application of a neuroscientifically-informed perspective on and in person-centered and experiential psychotherapy. The cultural context of the article is the experience of therapeutic practice and life in contemporary Aotearoa New Zealand.
Basketball shooting performance is maximized by individual-specific optimal release strategies

ABSTRACT This study investigated the relationship between optimal basketball release angles and individual release distributions and whether individuals seek their optimal or minimum velocity release strategy. Sixteen male basketball players (height 183 ± 9 cm, age 22.6 ± 7 years) were recorded shooting 75 three-point shots. Ball release angle and velocity estimates were used in a nonparametric kernel density estimator (KDE) to identify individual-specific release distributions and optimal release angles. Optimal releases varied among individuals and were 4.3 ± 2.1° higher than minimum velocity releases. Mean release angles were 3.9° higher than the minimum velocity angle (p < 0.001) and only 0.4° below the optimal (p = 0.5). Participants skewed their probability density function (PDF) peaks 0.24° towards the optimal (p = 0.044) further indicating participants seek optimal rather than minimum velocity releases. Individual-specific optimal release angles were strongly correlated with their PDF covariance (r = 0.78, p < 0.001) and weakly correlated to the principal axis aspect ratio (r = −0.40, p = 0.137). These findings illustrate that optimal releases varied among participants and performance may be maximised by each athlete matching their release strategy to their PDF characteristics rather than matching a predetermined optimal release angle.
Analysis of blood flow through a catheterized stenosed artery using Mathematica

A mathematical analysis on blood flowing through a catheterized stenosed artery is carried out using Mathematica, where a package has been developed to solve a Newtonian model of blood flow. This package can be extended to solve and simulate other fluid models and boundary conditions. Investigation centres on the effect of inserting a catheter, which is a tube, used amongst others in patients who are bedridden and whose blood pressure needs to be measured and monitored continuously. Inserting a catheter in an artery is expected to alter some characteristics of blood flow such as velocity, the wall shear stress and the streamlines. The present model considers the catheter and the artery to be in an eccentric position which is more realistic physically compared to the usual model which considers concentric position. The governing equations are solved analytically by a perturbation method. A problem to be tackled is the intimidating and horrendous mathematics involved in the solution procedure. An algorithm to circumvent this difficulty ought to be developed and it is conjectured that Mathematica based algorithm would be able alleviate such problem. Results show that the eccentricity causes the axial velocity and wall shear stress to increase. There is also a trapping bolus which occurs in the region between the wall of stenosis and the wall of catheter for small values of eccentricity parameter.
Experiences of Teaching an English for Specific Purposes Course to Students with Disabilities

To complete the master’s program in Teaching English as a Foreign Language at the University of Costa Rica, the teachers designed and taught an ESP course for ten students enrolled in a master’s program in Disability Studies. Three learners have visual impairments, and one has hypoacusis. Different curricular accommodations were made for them to work autonomously, but the results show that some could not always do so. However, their attitude towards learning English improved. This paper presents the challenges and outcomes of the lessons and materials used to raise awareness about the importance of inclusive classes, as well as recommendations to work with this population.
Randomised controlled trial of a behaviour change physiotherapy intervention to increase physical activity following hip and knee replacement: the PEP-TALK trial

Objective To test the effectiveness of a behaviour change physiotherapy intervention to increase physical activity compared with usual rehabilitation after total hip replacement (THR) or total knee replacement (TKR). Design Multicentre, pragmatic, two-arm, open, randomised controlled, superiority trial. Setting National Health Service providers in nine English hospitals. Participants 224 individuals aged ≥18 years, undergoing a primary THR or TKR deemed ‘moderately inactive’ or ‘inactive’. Intervention Participants received either six, 30 min, weekly, group-based exercise sessions (usual care) or the same six weekly, group-based, exercise sessions each preceded by a 30 min cognitive behaviour discussion group aimed at challenging barriers to physical inactivity following surgery (experimental). Randomisation and blinding Initial 75 participants were randomised 1:1 before changing the allocation ratio to 2:1 (experimental:usual care). Allocation was based on minimisation, stratifying on comorbidities, operation type and hospital. There was no blinding. Main outcome measures Primary: University of California Los Angeles (UCLA) Activity Score at 12 months. Secondary: 6 and 12-month assessed function, pain, self-efficacy, kinesiophobia, psychological distress and quality of life. Results Of the 1254 participants assessed for eligibility, 224 were included (139 experimental: 85 usual care). Mean age was 68.4 years (SD: 8.7), 63% were women, 52% underwent TKR. There was no between-group difference in UCLA score (mean difference: −0.03 (95% CI −0.52 to 0.45, p=0.89)). There were no differences observed in any of the secondary outcomes at 6 or 12 months. There were no important adverse events in either group. The COVID-19 pandemic contributed to the reduced intended sample size (target 260) and reduced intervention compliance. Conclusions There is no evidence to suggest attending usual care physiotherapy sessions plus a group-based behaviour change intervention differs to attending usual care physiotherapy alone. As the trial could not reach its intended sample size, nor a proportion of participants receive their intended rehabilitation, this should be interpreted with caution. Trial registration number ISRCTN29770908.
Research on micro-EDM machine tool and its key technologies

In order to use electro discharge machining(EDM) technology to manufacture micro-machines,analyzed the key technologies of micro EDM,and developed a micro EDM machine tool.The machine tool is made up of precise feed stages,spindle,wire electrical discharge grinding(WEDG) device,pulse power supply of micro EDM,granite worktable,servo and control system and so on.It has the function of linked 3-axes NC.The feeding resolution of each axis is 0.1 μm. The rotation run-out of spindle is less than 1 μm. The rotation speed is 1 000-2 5000 r/min,and can be changed continuously.The machine tool can be placed on a desk.With the machine tool,some elementary experiments have been carried out.Micro rod less than 15 μm in diameter and micro holes with diameter of 25 μm were stably obtained.The 3D micro-configurations were also machined.
BuMA: Non-Intrusive Breathing Detection using Microphone Array

Breath monitoring is important for monitoring illnesses, such as sleep apnea, for people of all ages. One cause of concern for parents is sudden infant death syndrome (SIDS), where an infant suddenly passes away during sleep, usually due to complications in breathing. There are a variety of works and products on the market for monitoring breathing, especially for children and infants. Many of these are wearables that require you to attach an accessory onto the child or person, which can be uncomfortable. Other solutions utilize a camera, which can be privacy-intrusive and function poorly during the night, when lighting is poor. In this work, we introduce BuMA, an audio-based, non-intrusive, and contactless, breathing monitoring system. BuMA utilizes a microphone array, beamforming, and audio filtering to enhance the sounds of breathing by filtering out several common noises in or near home environments, such as construction, speech, and music, that could make detection difficult. We show that BuMA improves breathing detection accuracy by up to 12%, within 30cm from a person, over existing audio filtering algorithms or platforms that do not leverage filtering.
SoftVN: efficient memory protection via software-provided version numbers

Trusted execution environments (TEEs) in processors protect off-chip memory (DRAM), and ensure its confidentiality and integrity using memory encryption and integrity verification. However, such memory protection can incur significant performance overhead as it requires additional memory accesses for protection metadata such as version numbers (VNs) and MACs. This paper proposes SoftVN, an extension to the current memory protection schemes, which significantly reduces the overhead of today's state-of-the-art by allowing software to provide VNs for memory accesses. For memory-intensive applications with simple memory access patterns for large data structures, the VNs only need to be maintained for data structures instead of individual cache blocks and can be tracked in software with low efforts. Off-chip VN accesses for memory reads can be removed if they are tracked and provided by software. We evaluate SoftVN by simulating a diverse set of memory-intensive applications, including deep learning, graph processing, and bioinformatics algorithms. The experimental results show that SoftVN reduces the memory protection overhead by 82% compared to the baseline similar to Intel SGX, and improves the performance by 33% on average. The maximum performance improvement can be as high as 65%.
X-cache: a modular architecture for domain-specific caches

With Dennard scaling ending, architects are turning to domain-specific accelerators (DSAs). State-of-the-art DSAs work with sparse data [37] and indirectly-indexed data structures [18, 30]. They introduce non-affine and dynamic memory accesses [7, 35], and require domain-specific caches. Unfortunately, cache controllers are notorious for being difficult to architect; domain-specialization compounds the problem. DSA caches need to support custom tags, data-structure walks, multiple refills, and preloading. Prior DSAs include ad-hoc cache structures, and do not implement the cache controller. We propose X-Cache, a reusable caching idiom for DSAs. We will be open-sourcing a toolchain for both generating the RTL and programming X-Cache. There are three key ideas: i) DSA-specific Tags (Meta-tag): The designer can use any combination of fields from the DSA-metadata as the tag. Meta-tags eliminate the overhead of walking and translating metadata to global addresses. This saves energy, and improves load-to-use latency. ii) DSA-programmable walkers (X-Actions): We find that a common set of microcode actions can be used to implement the DSA-specific walking, data block, and tag management. We develop a programmable microcode engine that can efficiently realize the data orchestration. iii) DSA-portable controller (X-Routines): We use a portable abstraction, coroutines, to let the designer express walking and orchestration. Coroutines capture the block-level parallelism, remain lightweight, and minimize controller occupancy. We create caches for four different DSA families: Sparse GEMM [35, 37], GraphPulse [30], DASX [22], and Widx [18]. X-Cache outperforms address-based caches by 1.7 × and remains competitive with hardwired DSAs (even 50% improvement in one case). We demonstrate that meta-tags save 26--79% energy compared to address-tags. In X-Cache, meta-tags consume 1.5--6.5% of data RAM energy and the programmable microcode adds a further 7%.
ROS-SF: A Transparent and Efficient ROS Middleware using Serialization-Free Message

In recent years, ROS becomes the dominant middleware for robotic systems. The performance of its message-passing paradigm is crucial to the robot's reaction time. However, previous works only focus on efficiency, but ignore the requirement for transparency. We present ROS-SF framework, which can transparently eliminate serialization and de-serialization under the ROS APIs. The key contributions are a new serialization format called SFM and a life-cycle management method for serialization-free messages. Evaluation results show that our ROS-SF framework can improve the message-passing performance of ROS by up to 76.3\%. Application case study and applicability study show that our ROS-SF framework can be transparently applied to many existing ROS-based systems and packages. Even in the failure cases, our ROS-SF framework can provide modification guidance.
Learnersourcing in Theory and Practice: Synthesizing the Literature and Charting the Future

Given the growing interest in learnersourcing -- a pedagogically supported form of crowdsourcing that harnesses the knowledge and creativity of learners for the creation of learning resources -- we propose a theoretical framework to study, design, and deploy learnersourcing systems. By integrating ideas from crowdsourcing and learning theories focusing on learner-centered pedagogy, this work provides a review and classification of learnersourcing systems from the perspective of its three groups of stakeholders: (1) contributors, who are the learners who contribute new learning artifacts, (2) beneficiaries, who are the learners who learn from these artifacts, and (3) the instructional team who design and deploy learnersourcing tasks. The framework serves as a heuristic device for designing new learnersourcing systems and for considering the broader implications for learnersourcing in terms of workflow design, incentivizing contributors, quality-control, learning outcomes, delivering personalized learning experiences, ethical considerations, and its complementary relationship with AI in education.
An automated segmentation model based on CBAM for MR image of glioma tumors

As a serious disease endangering human life, the incidence of glioma is increasing in recent years. A semantic segmentation model of glioma based on the deep separable convolution of the attention mechanism is proposed. The model uses an encoder-decoder structure, where the encoder part uses an improved Xception backbone network. In the improved Xception backbone network, CBAM is added after each convolutional layer, thereby improving the segmentation accuracy. In the entire network structure, the Mish activation function is used instead of the ReLU activation function to ensure a smooth gradient descent during training and optimize network performance. The segmentation results of magnetic resonance image slices obtained based on the BraTS2019 data set show that the joint intersection is 83.68%, the Kappa coefficient is 90.74%, and the Dice coefficient is 0.9111, which is better than mainstream semantic segmentation models. The semantic segmentation model proposed in this paper has a high accuracy rate for glioma segmentation. This work can effectively alleviate the complex recognition work of doctors on tumors, and is of practical significance to the medical diagnosis process.