Miracle-dz/UniFAR-FTUs huggingface dataset:
Robotic hand augmentation drives changes in neural body representation

Skillful Third Thumb hand augmentation can be readily learned but may influence user’s body representation and motor control. Humans have long been fascinated by the opportunities afforded through augmentation. This vision not only depends on technological innovations but also critically relies on our brain’s ability to learn, adapt, and interface with augmentation devices. Here, we investigated whether successful motor augmentation with an extra robotic thumb can be achieved and what its implications are on the neural representation and function of the biological hand. Able-bodied participants were trained to use an extra robotic thumb (called the Third Thumb) over 5 days, including both lab-based and unstructured daily use. We challenged participants to complete normally bimanual tasks using only the augmented hand and examined their ability to develop hand-robot interactions. Participants were tested on a variety of behavioral and brain imaging tests, designed to interrogate the augmented hand’s representation before and after the training. Training improved Third Thumb motor control, dexterity, and hand-robot coordination, even when cognitive load was increased or when vision was occluded. It also resulted in increased sense of embodiment over the Third Thumb. Consequently, augmentation influenced key aspects of hand representation and motor control. Third Thumb usage weakened natural kinematic synergies of the biological hand. Furthermore, brain decoding revealed a mild collapse of the augmented hand’s motor representation after training, even while the Third Thumb was not worn. Together, our findings demonstrate that motor augmentation can be readily achieved, with potential for flexible use, reduced cognitive reliance, and increased sense of embodiment. Yet, augmentation may incur changes to the biological hand representation. Such neurocognitive consequences are crucial for successful implementation of future augmentation technologies.
Writing RSS Feeds in a Machine-Processable Controlled Natural Language

In this paper, we present PENG Online, a web-based authoring tool which allows authors to write RSS feeds in a machine-processable controlled natural language. The authoring tool is implemented as a Java applet and communicates in near real-time with a remote server which runs a controlled natural language processor and an inference engine. The authoring tool provides browser functionality for viewing web pages which can then be summarised and augmented in controlled natural language. The writing process is guided via predictive interface techniques which guarantee that the text conforms to the rules of the controlled natural language. The resulting descriptions in RSS format look informal at first glance and are easy to read and understand by humans, but they have the same formal properties as the underlying logic-based representation language. These properties build an ideal starting point for making inferences over the represented knowledge and for using the RSS feeds as a source for question answering.
Guarani: A Case Study in Resource Development for Quick Ramp-Up MT

In this paper we describe a set of processes for the acquisition of resources for quick rampup machine translation (MT) from any language lacking significant machine tractable resources into English, using the Paraguayan indigenous language Guarani as well as Amharic and Chechen, as examples. Our task is to develop a 250,000 monolingual corpus, a 250,000 bilingual parallel corpus, and smaller corpora tagged with part of speech, named entity, and morphological annotations.
DIFFERENCES IN CONE AND SEED MORPHOLOGY OF PINUS STROBIFORMIS AND PINUS AYACAHUITE

Abstract For decades there has been confusion and uncertainty on how to clearly identify the two distinct species, Pinus strobiformis Engelm. and Pinus ayacahuite Ehrenberg. Pinus ayacahuite is further defined as two varieties, var. ayacahuite and var. veitchii. These species are of ecological importance throughout much of Mexico because they offer valuable ecosystem services. The objective in this work was to examine the morphological characteristics of cones and seeds from parent trees from six sites in northern Mexico and three sites in southern Mexico. The results show that the mean seed width and length per tree, mean cone weight per tree, and the 100-seed weight per tree were the best variables to accurately separate P. strobiformis from P. ayacahuite. Using these criteria, we found that P. ayacahuite var. veitchii is more similar to P. strobiformis than to P. ayacahuite var. ayacahuite.
FluoSTEPs: Fluorescent biosensors for monitoring compartmentalized signaling within endogenous microdomains

Fluorescent sensors targeted to endogenous proteins measure native signaling dynamics within signaling compartments. Growing evidence suggests that many essential intracellular signaling events are compartmentalized within kinetically distinct microdomains in cells. Genetically encoded fluorescent biosensors are powerful tools to dissect compartmentalized signaling, but current approaches to probe these microdomains typically rely on biosensor fusion and overexpression of critical regulatory elements. Here, we present a novel class of biosensors named FluoSTEPs (fluorescent sensors targeted to endogenous proteins) that combine self-complementing split green fluorescent protein, CRISPR-mediated knock-in, and fluorescence resonance energy transfer biosensor technology to probe compartmentalized signaling dynamics in situ. We designed FluoSTEPs for simultaneously highlighting endogenous microdomains and reporting domain-specific, real-time signaling events including kinase activities, guanosine triphosphatase activation, and second messenger dynamics in live cells. A FluoSTEP for 3′,5′-cyclic adenosine monophosphate (cAMP) revealed distinct cAMP dynamics within clathrin microdomains in response to stimulation of G protein–coupled receptors, showcasing the utility of FluoSTEPs in probing spatiotemporal regulation within endogenous signaling architectures.
Scoring Dimension-Level Job Performance From Narrative Comments: Validity and Generalizability When Using Natural Language Processing

Performance appraisal narratives are qualitative descriptions of employee job performance. This data source has seen increased research attention due to the ability to efficiently derive insights using natural language processing (NLP). The current study details the development of NLP scoring for performance dimensions from narrative text and then investigates validity and generalizability evidence for those scores. Specifically, narrative valence scores were created to measure a priori performance dimensions. These scores were derived using bag of words and word embedding features and then modeled using modern prediction algorithms. Construct validity evidence was investigated across three samples, revealing that the scores converged with independent human ratings of the text, aligned numerical performance ratings made during the appraisal, and demonstrated some degree of discriminant validity. However, construct validity evidence differed based on which NLP algorithm was used to derive scores. In addition, valence scores generalized to both downward and upward rating contexts. Finally, the performance valence algorithms generalized better in contexts where the same qualitative survey design was used compared with contexts where different instructions were given to elicit narrative text.
Soft anharmonic phonons and ultralow thermal conductivity in Mg3(Sb, Bi)2 thermoelectrics

The atomistic origin of ultralow thermal conductivity in promising new thermoelectrics is revealed by experiments and simulations. The candidate thermoelectric compounds Mg3Sb2 and Mg3Bi2 show excellent performance near ambient temperature, enabled by an anomalously low lattice thermal conductivity (κl) comparable to those of much heavier PbTe or Bi2Te3. Contrary to common mass-trend expectations, replacing Mg with heavier Ca or Yb yields a threefold increase in κl in CaMg2Sb2 and YbMg2Bi2. Here, we report a comprehensive analysis of phonons in the series AMg2X2 (A = Mg, Ca, and Yb; X = Bi and Sb) based on inelastic neutron/x-ray scattering and first-principles simulations and show that the anomalously low κl of Mg3X2 has inherent phononic origins. We uncover a large phonon softening and flattening of low-energy transverse acoustic phonons in Mg3X2 compared to the ternary analogs and traced to a specific Mg-X bond, which markedly enlarges the scattering phase-space, enabling the threefold tuning in κl. These results provide key insights for manipulating phonon scattering without the traditional reliance on heavy elements.
Hydrobiochemical balance of total mercury in a forest catchment area at former cinnabar mining locality

Abstract We studied the hydrobiochemical balance of total mercury (THg) in a forest ecosystem covering an area affected by mining activity in the past (14th – 18th cent.) in the Kremnické vrchy Mts. (central Slovakia). A reference plot was located in an undisturbed area very close to primeval forest of Badínsky prales natural reserve. We analysed THg in bulk precipitation, throughfall, litterfall, forest floor percolate, forest soil and assimilatory organs of tree species. Results pointed out to high wet mercury deposition at both plots (51 μg·m−2·yr−1 an area near a cinnabar mining (MP1) and 37 μg·m−2·yr−1, in a reference catchment area near the protected primary forest (MP2)) as well as high THg deposition by throughfall (74 μg·m−2·yr−1 and 51 μg·m−2·yr−1, respectively in MP1 and MP2). Litterfall does not represent the main THg flux into forest soil but together with throughfall doubles the THg input compared to open space deposition. Forest ecosystem has ability to capture atmospheric Hg and thus makes new sources of mercury inputs (throughfall and litterfall) into soil.
Recommendations of the Polish Association of Anaesthesia and Intensive Care Nurses on pain monitoring in Intensive Care Units using a Polish version of the Behavioural Pain Scale (BPS)

Abstract Introduction. In 2018, another update of the Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobilization and Sleep Disorders in Adult Patients Treated in Intensive Care Units (ICUs) was released. Aim. The study is aimed at presenting current recommendations concerning pain management in patients treated in ICU, and presenting the algorithm of pain assessment and monitoring in patients treated in ICU, using a Polish version of the BPS (Behavioural Pain Scale). The guidelines were prepared based on a systematic review of the literature published in the years 2013-2018. Material and methods. The search for scientific publications was carried out using electronic databases in English and Polish. The following keywords and their combinations were used in the searches: pain, assessment, monitoring, nurse, intensive care, adult patient, unable to communicate. Initially, 758 papers were identified with the use of keywords. After excluding duplicates and preliminary checking and selecting the titles of publications and abstracts, 85 papers were qualified for the analysis of full text. Conclusions. Access to effective pain treatment is a fundamental human right. Recommendations of the Polish Association of Anaesthesia and Intensive Care Nurses, concerning pain monitoring in ICU using a Polish version of the Behavioural Pain Scale (BPS), developed by the Task Force for Practice, are intended to provide a specific guideline for developing effective local pain management strategies in ICU.
Evaluation of Oxidative Stress Parameters in Dogs with Brachycephalic Obstructive Airway Syndrome Before and after Surgery

Abstract Introduction Canine brachycephalic obstructive airway syndrome (BOAS) is a conformation-related respiratory disorder of dog breeds having congenitally flattened facial and skull anatomy. The aim of the study was to determine oxidative stress parameters, the lipid peroxidation product malondialdehyde, and antioxidant enzymes superoxide dismutase (SOD) and glutathione peroxidase in BOAS patients before and after surgical treatment and in healthy brachycephalic dogs. Material and Methods Nine healthy brachycephalic dogs that had not undergone surgery and 39 BOAS patients were included in the study. The BOAS patients were classified as grade 1 (5/34), grade 2 (16/34), and grade 3 (13/34) based on the decrease in the radius of the airway in the larynx. In BOAS patients, oxidative stress parameters were determined before and two weeks after surgery, while in control dogs, blood samples were collected only on inclusion to the study. Results All BOAS patients showed various degrees of improvement in clinical signs after surgery. Significantly lower (P < 0.05) SOD activity was found in grade 2 and 3 BOAS patients than in grade 1 patients. Two weeks after surgery, a significant (P < 0.05) increase in SOD activity in grade 2 and 3 patients was observed. Conclusion Antioxidant enzyme SOD may play an important role in BOAS and can be used as a biomarker of antioxidant status assessment in BOAS patients.
Remdesivir Alleviates Acute Kidney Injury by Inhibiting the Activation of NLRP3 Inflammasome

Acute kidney injury (AKI) is a frequent clinical complication in critically ill patients, and it rapidly develops into renal failure with high morbidity and mortality. However, other than dialysis, no effective therapeutic interventions can offer reliable treatment to limit renal injury and improve survival. Here, we firstly reported that remdesivir (RDV, GS-5734), a broad-spectrum antiviral nucleotide prodrug, alleviated AKI by specifically inhibiting NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome activation in macrophages. Mechanically, RDV effectively suppressed the activities of nuclear transcription factor (NF)-κB, mitogen-activated protein kinase (MAPK), which further led to the reduction of the inflammasome genes of NLRP3 transcription, limiting the activation of NLRP3 inflammasome in vivo and in vitro. RDV also inhibited other pro-inflammatory genes including tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), IL-12, IL-1β, and interferon–β (IFN-β), leading to the reduction of inflammatory factors release. Thus, RDV can ameliorate AKI via modulating macrophage inflammasome activation and inflammatory immune responses and may have a therapeutic potential for patients with AKI in clinical application.
Screening for Mutations in Isolated Central Hypothyroidism Reveals a Novel Mutation in Insulin Receptor Substrate 4

Background Central hypothyroidism (CeH) is a rare condition affecting approximately 1:16 000- 100 000 individuals. Congenital forms can harm normal development if not detected and treated promptly. Clinical and biochemical diagnosis, especially of isolated CeH, can be challenging. Cases are not usually detected in neonatal screening, which, in most countries, is focused on detection of the more prevalent primary hypothyroidism. Until now, five genetic causes for isolated CeH have been identified. Here we aimed to identify the genetic cause in two brothers with impaired growth diagnosed with CeH at the age of 5 years. We further evaluated the candidate gene variants in a large genetic database. Methods Clinical and biochemical characterization together with targeted next-generation sequencing (NGS) was used to identify the genetic cause in a family of two brothers presenting with CeH. Screening of insulin receptor substrate 4 (IRS4) variants was carried out in the FinnGen database. Results A novel monoallelic frameshift mutation c. 1712_1713insT, p.Gly572Trp fs*32 in the X-linked IRS4 gene was identified by NGS analysis in both affected males and confirmed using Sanger sequencing. Their mother was an unaffected carrier. In addition to the declined growth at presentation, central hypothyroidism and blunted TRH test, no other phenotypic alterations were found. Diagnostic tests included head MRI, thyroid imaging, bone age, and laboratory tests for thyroid autoantibodies, glucose, insulin and glycosylated hemoglobin levels. Examination of the IRS4 locus in FinnGen (R5) database revealed the strongest associations to a rare Finnish haplotype associated with thyroid disorders (p = 1.3e-7) and hypothyroidism (p = 8.3e-7). Conclusions Here, we identified a novel frameshift mutation in an X-linked IRS4 gene in two brothers with isolated CeH. Furthermore, we demonstrate an association of IRS4 gene locus to a general thyroid disease risk in the FinnGen database. Our findings confirm the role of IRS4 in isolated central hypothyroidism.
Feasibility of Different Tumor Delineation Approaches for 18F-PSMA-1007 PET/CT Imaging in Prostate Cancer Patients

Background Delineation of PSMA-positive tumor volume on PET using PSMA-ligands is of highest clinical interest as changes of PSMA-PET/CT-derived whole tumor volume (WTV) have shown to correlate with treatment response in metastatic prostate cancer patients. So far, WTV estimation was performed on PET using 68Ga-labeled ligands; nonetheless, 18F-labeled PET ligands are gaining increasing importance due to advantages over 68Ga-labeled compounds. However, standardized tumor delineation methods for 18F-labeled PET ligands have not been established so far. As correlation of PET-based information and morphological extent in osseous and visceral metastases is hampered by morphological delineation, low contrast in liver tissue and movement artefacts, we correlated CT-based volume of lymph node metastases (LNM) and different PET-based delineation approaches for thresholding on 18F-PSMA-1007 PET. Methods Fifty patients with metastatic prostate cancer, 18F-PSMA-1007 PET/CT and non-bulky LNM (short-axis diameter ≥10mm) were included. Fifty LNM were volumetrically assessed on contrast-enhanced CT (volumetric reference standard). Different approaches for tumor volume delineation were applied and correlated with the reference standard: I) fixed SUV threshold, II) isocontour thresholding relative to SUVmax (SUV%), and thresholds relative to III) liver (SUVliver), IV) parotis (SUVparotis) and V) spleen (SUVspleen). Results A fixed SUV of 4.0 (r=0.807, r2 = 0.651, p<0.001) showed the best overall association with the volumetric reference. 55% SUVmax (r=0.627, r2 = 0.393, p<0.001) showed highest association using an isocontour-based threshold. Best background-based approaches were 60% SUVliver (r=0.715, r2 = 0.511, p<0.001), 80% SUVparotis (r=0.762, r2 = 0.581, p<0.001) and 60% SUVspleen (r=0.645, r2 = 0.416, p<0.001). Background tissues SUVliver, SUVparotis & SUVspleen did not correlate (p>0.05 each). Recently reported cut-offs for intraprostatic tumor delineation (isocontour 44% SUVmax, 42% SUVmax and 20% SUVmax) revealed inferior association for LNM delineation. Conclusions A threshold of SUV 4.0 for tumor delineation showed highest association with volumetric reference standard irrespective of potential changes in PSMA-avidity of background tissues (e. g. parotis). This approach is easily applicable in clinical routine without specific software requirements. Further studies applying this approach for total tumor volume delineation are initiated.
Cross-site Prediction on Social Influence for Cold-start Users in Online Social Networks

Online social networks (OSNs) have become a commodity in our daily life. As an important concept in sociology and viral marketing, the study of social influence has received a lot of attentions in academia. Most of the existing proposals work well on dominant OSNs, such as Twitter, since these sites are mature and many users have generated a large amount of data for the calculation of social influence. Unfortunately, cold-start users on emerging OSNs generate much less activity data, which makes it challenging to identify potential influential users among them. In this work, we propose a practical solution to predict whether a cold-start user will become an influential user on an emerging OSN, by opportunistically leveraging the user’s information on dominant OSNs. A supervised machine learning-based approach is adopted, transferring the knowledge of both the descriptive information and dynamic activities on dominant OSNs. Descriptive features are extracted from the public data on a user’s homepage. In particular, to extract useful information from the fine-grained dynamic activities that cannot be represented by the statistical indices, we use deep learning technologies to deal with the sequential activity data. Using the real data of millions of users collected from Twitter (a dominant OSN) and Medium (an emerging OSN), we evaluate the performance of our proposed framework to predict prospective influential users. Our system achieves a high prediction performance based on different social influence definitions.
Work volition, decent work, and work fulfilment, in the formal and informal economy in Burkina Faso

ABSTRACT Decent work is crucial for an individual’s life development and well-being. The psychology of working theory defines the relationship between micro and macro factors that might be strongly influenced by the context. The aim of this research was to study how people working in the formal and informal economy in Burkina Faso describe their working conditions and the notion of decent work and how economic constraints and marginalisation influence work volition, decent work and work fulfilment using a mixed method approach. A study shows that above and beyond the usual components, social recognition is an especially important aspect of decent work in this context (N = 51). A second study shows that economic constraints and marginalisation factors have an impact on obtaining a decent work, mediated by work volition, both being related to work fulfilment outcomes (N = 501). Results suggest that the objective and subjective components of decent work might refer to two aspects of the same reality.
Dynamic Natural Language User Interfaces Using Microservices

Microservices have become a popular way to build and deploy software systems as they allow engineers to break down systems into smaller components that can be deployed and maintained independently. Interactions with these systems typically employ a Graphical User Interface (GUI) that weaves and orchestrates the services together to perform use cases. However, each time the requirements change or the underlying services change, the logic in the GUI must be updated, increasing maintenance costs. There is a need for the orchestration logic to be more flexible. We present an automated approach to build user interfaces using natural language that can augment or replace these types of graphical interfaces. Our approach creates the user interface by extracting intents from requirement statements and satisfying them by dynamically orchestrating the underlying microservices. We are able to handle requirement changes as well as adding, removing, or updating services on the fly without additional development.
Snippets of Folk Legends: Adapting a Text Mining Tool to a Collection of Folk Legends

A topic modelling tool was adapted to requirements for a collection of Swedish folk legends. To offer an overview of a list of folk legend texts, which had been automatically extracted by the topic modelling tool, snippet text versions of the folk legends were displayed. The snippets were constructed from the full-text versions of the legends using the sentences most relevant to the topics extracted by the topic modelling algorithm. In addition, collection-adapted data was constructed for performing a pre-processing of the folk legend texts, before they were submitted to the topic modelling algorithm. This data consisted of a collection-adapted stop word list and word lists for improving the quality of clusters of semantically similar words.