Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Detection and Characterization of Blastocystis sp. and Enterocytozoon bieneusi in Cattle in Northern Spain

Some enteric parasites causing zoonotic diseases in livestock have been poorly studied or even neglected. This is the case in stramenopile Blastocystis sp. and the microsporidia Enterocytozoon bieneusi in Spain. This transversal molecular epidemiological survey aims to estimate the prevalence and molecular diversity of Blastocystis sp. and E. bieneusi in cattle faecal samples (n = 336) in the province of Álava, Northern Spain. Initial detection of Blastocystis and E. bieneusi was carried out by polymerase chain reaction (PCR) and Sanger sequencing of the small subunit (ssu) rRNA gene and internal transcribed spacer (ITS) region, respectively. Intra-host Blastocystis subtype diversity was further investigated by next generation amplicon sequencing (NGS) of the ssu rRNA gene in those samples that tested positive by conventional PCR. Amplicons compatible with Blastocystis sp. and E. bieneusi were observed in 32.1% (108/336, 95% CI: 27.2–37.4%) and 0.6% (2/336, 95% CI: 0.0–1.4%) of the cattle faecal samples examined, respectively. Sanger sequencing produced ambiguous/unreadable sequence data for most of the Blastocystis isolates sequenced. NGS allowed the identification of 10 Blastocystis subtypes including ST1, ST3, ST5, ST10, ST14, ST21, ST23, ST24, ST25, and ST26. All Blastocystis-positive isolates involved mixed infections of 2–8 STs in a total of 31 different combinations. The two E. bieneusi sequences were confirmed as potentially zoonotic genotype BEB4. Our data demonstrate that Blastocystis mixed subtype infections are extremely frequent in cattle in the study area. NGS was particularly suited to discern underrepresented subtypes or mixed subtype infections that were undetectable or unreadable by Sanger sequencing. The presence of zoonotic Blastocystis ST1, ST3, and ST5, and E. bieneusi BEB4 suggest cross-species transmission and a potential risk of human infection/colonization.
Identification of Arg32Ser, His92Tyr and Leu147Phe novel mutations in chromosomally mediated β-lactamase SHV and in silico characterization to understand their substrate activity imparting resistance

Abstract The emergence of β-lactam resistance is yearning for clinical significance in Enterobacteriaceae, which are categorized under global priority pathogen lists by the World Health Organization. Likewise, the prevalence of numerous β-lactamase enzymes, mutational propensity in such bacteria, and their role in accelerating resistance is still a major concern. Thus, the present work intends to characterize the β-lactamase producing bacteria isolated from acute diarrheal patients to understand their chromosomally acquired resistance pattern through molecular characterization and in silico approaches. The current study highlights the first identified Escherichia fergusonii and Escherichia marmotae species and their β-lactamase encoding genes, blaOKP-A, blaNDM and blaOXA from the unexplored Enterobacteriaceae family from North East India. First-ever reported point mutations such as Arg32Ser, His92Tyr, and Leu147Phe were observed in BlaSHV protein of two Klebsiella pneumoniae isolates S-35 and S-46. In molecular docking, non-catalytic site H-bond interactions of Arg 218, Ala 223, Asn 128, Ser 126, Gln 95, Asp 100, Tyr 101, Ser 102, Ala 274 with a low binding affinity towards BlaSHV was found. This correlates with the high imipenem, ceftazidime, cefuroxime, ceftriaxone, and cefpodoxime resistance in Klebsiella pneumoniae S-35 with the complementary effect of mutations Arg32Ser and Leu147Phe. Besides, the role of His92Tyr mutation in controlling the resistance in Klebsiella pneumoniae S-46 is also illustrated. Thus, our study highlights the novel mutations of β-lactamase and its clinical importance with altered resistance profiles. This could be useful to design better therapeutics and to readjust antibiotic treatment regimes against them and control to grow more resistance under selective pressure. Communicated by Ramaswamy H. Sarma
On the Efficacy of Handcrafted and Deep Features for Seed Image Classification

Computer vision techniques have become important in agriculture and plant sciences due to their wide variety of applications. In particular, the analysis of seeds can provide meaningful information on their evolution, the history of agriculture, the domestication of plants, and knowledge of diets in ancient times. This work aims to propose an exhaustive comparison of several different types of features in the context of multiclass seed classification, leveraging two public plant seeds data sets to classify their families or species. In detail, we studied possible optimisations of five traditional machine learning classifiers trained with seven different categories of handcrafted features. We also fine-tuned several well-known convolutional neural networks (CNNs) and the recently proposed SeedNet to determine whether and to what extent using their deep features may be advantageous over handcrafted features. The experimental results demonstrated that CNN features are appropriate to the task and representative of the multiclass scenario. In particular, SeedNet achieved a mean F-measure of 96%, at least. Nevertheless, several cases showed satisfactory performance from the handcrafted features to be considered a valid alternative. In detail, we found that the Ensemble strategy combined with all the handcrafted features can achieve 90.93% of mean F-measure, at least, with a considerably lower amount of times. We consider the obtained results an excellent preliminary step towards realising an automatic seeds recognition and classification framework.
Pain in cervical dystonia: mechanisms, assessment and treatment

ABSTRACT Introduction In patients with cervical dystonia (CD), pain is a major contributor to disability and social isolation and is often the main reason patients seek treatment. Surveys evaluating patient perceptions of their CD symptoms consistently highlight pain as a troublesome and disabling feature of their condition with significant impact on daily life and work. Areas covered In this article, the authors review the epidemiology, assessment, possible mechanisms and treatment of pain in CD, including a meta-analysis of randomized controlled trial data with abobotulinumtoxinA. Expert opinion Mechanisms of pain in CD may be muscle-based and non-muscle based. Accumulating evidence suggests that non-muscle-based mechanisms (such as abnormal transmission and processing of nociceptive stimuli, dysfunction of descending pain inhibitory pathways as well as structural and network changes in the basal ganglia, cortex and other areas) may also contribute to pain in CD alongside prolonged muscle contraction. Chemodenervation with botulinum toxin is considered the first-line treatment for CD. Treatment with botulinum toxin is usually effective, but optimization of the injection parameters should include consideration of pain as a core symptom in addition to the motor problems
Montelukast attenuates interleukin IL-1β-induced oxidative stress and apoptosis in chondrocytes by inhibiting CYSLTR1 (Cysteinyl Leukotriene Receptor 1) and activating KLF2 (Kruppel Like Factor 2)

ABSTRACT Montelukast is a cysteinyl leukotriene receptor 1 (CysLTR1) antagonist widely used to suppress the inflammatory response in asthma and allergic rhinitis. This study aimed to investigate the potential impacts of montelukast on osteoarthritis (OA) progression. To determine the role of montelukast in OA, the expression of CysLTR1 was first examined by quantitative reverse transcription PCR (RT-qPCR) and western blot in IL-1β-induced ATDC5 cells treated with or without montelukast. Subsequently, the impacts of montelukast on cell viability and oxidative stress were measured by Cell-Counting-Kit-8 (CCK-8), commercial kits and western blot. Oxidative stress-related protein expressions were determined by western blot analysis in Il-1β-induced ATDC5 cells. Cell apoptosis and cartilage degradation were examined by TdT-mediated dUTP Nick-End Labeling (TUNEL) assay, western blot and RT-qPCR. KLF2 expression was measured in IL-1β-induced ATDC5 cells treated with montelukast. After interference with small interfering RNA (siRNA)-KLF2 in ATDC5 cells, the loss-of-function assays were also performed in same ways. CysLTR1 expression was elevated in IL-1β-induced ATDC5 cells but inhibited significantly by montelukast. Montelukast attenuated the oxidative stress and apoptosis, improved cell viability. Moreover, montelukast enhanced KLF2 expression. After transfected with siRNA-KLF2, montelukast attenuated cell injury, oxidative stress, apoptosis and cartilage degradation in IL-1β-induced ATDC5 cells by activating KLF2.In summary, this work elaborates the evidence that montelukast could attenuate oxidative stress and apoptosis in IL-1β-induced chondrocytes by inhibiting CysLTR1 and activating KLF2, which can guide the therapeutic strategies of montelukast for OA development in the future.
Deciphering two rounds of cell lineage segregations during bovine preimplantation development

Blastocyst formation gives rise to the inner cell mass (ICM) and trophectoderm (TE) and is followed by the differentiation of the epiblast (Epi) and primitive endoderm (PrE) within the ICM. Although these two‐round cell lineage differentiations underpin proper embryogenesis in every mammal, their spatiotemporal dynamics are quite diverse among species. Here, molecular details of the blastocyst stage in cattle were dissected using an optimized in vitro culture method. Blastocyst embryos were placed on agarose gel filled with nutrient‐rich media to expose embryos to both gaseous and liquid phases. Embryos derived from this “on‐gel” culture were transferred to surrogate mothers on day (D) 10 after fertilization and successfully implanted. Immunofluorescent studies using on‐gel‐cultured embryos revealed that the proportion of TE cells expressing the pluripotent ICM marker, OCT4, which was beyond 80% on D8, was rapidly reduced after D9 and reached 0% on D9.5. This first lineage segregation process was temporally parallel with the second one, identified by the spatial separation of Epi cells expressing SOX2 and PrE cells expressing SOX17. RNA‐seq comparison of TE cells from D8 in vitro fertilized embryos and D14 in vivo embryos revealed that besides drastic reduction of pluripotency‐related genes, TE cells highly expressed Wnt, FGF, and VEGF signaling pathways‐related genes to facilitate the functional maturation required for feto‐maternal interaction. Quantitative PCR analysis of TE cells derived from on‐gel culture further confirmed time‐dependent increments in the expression of key TE markers. Altogether, the present study provides platforms to understand species‐specific strategies for mammalian preimplantation development.
Anti-HIV and anti-HCV small molecule protease inhibitors in-silico repurposing against SARS-CoV-2 Mpro for the treatment of COVID-19

Abstract The COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is a global health emergency warranting development and implementation of targeted treatment. The enzyme main protease (Mpro; also known as 3C-like protease) is emerging as an attractive drug target. This enzyme plays an indispensable role in processing the translated polyproteins of viral RNA. Inhibiting the activity of Mpro would wedge viral replication. To facilitate the discovery of targeted therapy for COVID-19, we carried out the structure-assisted repurposing of existing protease inhibiting small molecules to target SARS-CoV-2 Mpro. Based on the structure of SARS-CoV-2 Mpro, here we report the small drug molecule namely saquinavir as its potent inhibitor. Findings support the premise that this promising antiviral protease inhibiting small drug molecule can be validated and implemented for the treatment and clinical management of COVID-19 pandemic disease. Communicated by Ramaswamy H. Sarma.
Mercury fractionation in gypsum using temperature desorption and mass spectrometric detection

Abstract A quadrupole mass spectrometer was used to study the thermal release of mercury from wet flue gas desulphurization (WFGD) gypsum using temperature-programmed desorption/decomposition (TPD). The inability in direct detection of low concentrations of mercury halogenides in gypsum by mass spectrometry is discussed in detail. The hydrolysis of HgCl2 vapours under specific experimental conditions in the mass spectrometer was considered theoretically and proved experimentally. The mercury concentration in different gypsum fractions varies from 0.22 mg kg-1 (3.27-148 μm, coarse particles) to 20.6 mg kg-1 (0.41-88.0 μm, fine particles). All samples had a similar, symmetrical, single-peak (peak maximum 253–266°C) in the TPD spectra. In the present study, the use of ‘wet’ methods for preparing mercury compounds is introduced in addition to the mercury standards prepared using the ‘dry’ method, as commonly found in TPD. The study showed that selected metals, such as Fe enriched in gypsum samples, significantly influence the shape and the maximum temperature of the Hg TPD curves and that during the mercury compound preparation and the TPD process, Hg species undergo transformations that prevent the identification of their original identity.
Large-scale fabrication of colloidal nano-sized CuCl solution with high concentration for using as fungicide for plant

Synthesis of nano-sized CuCl with Cu concentration from 4,000 to 6,000 ppm dispersed in chitosan solution (nanosized CuCl/CTS) using CuSO4.5H2O as the precursor and NaHSO3 as the reducing agent in HCl acid medium on large scale of 1.000 kg/batch was carried out. The obtained nano-sized CuCl/CTS samples were characterized by transmission electron microscopy (TEM) and X-ray powder diffraction (XRD). Based on the obtained results, the reaction factors for fabrication of the colloidal nano-sized CuCl/CTS solution with Cu concentration of 5,000 ppm and CuCl nanoparticle size of about 7.7 nm dispersed in 1 % chitosan solution were selected for application in agriculture as a fungicide for plant protection.
“The vaccination is positive; I don’t think it’s the panacea”: A qualitative study on COVID-19 vaccine attitudes among ethnically diverse healthcare workers in the United Kingdom

Background Globally, healthcare workers (HCWs) are prioritised for receiving vaccinations against the coronavirus disease-2019 (COVID-19). Previous research has shown disparities in COVID-19 vaccination uptake among HCWs based on ethnicity, job role, sex, age, and deprivation. However, vaccine attitudes underpinning these variations are yet to be fully explored. Methods We conducted a qualitative study with 164 HCWs from different ethnicities, sexes, job roles, migration statuses, and regions in the United Kingdom (UK). Interviews and focus groups were conducted using Microsoft Teams or telephone, and recorded with participants' permission. Recordings were transcribed and thematically analysed following an inductive approach. Findings We conducted an in-depth analysis of 53 randomly selected transcripts (involving 82 participants) to generate rapid evidence. Four different vaccine attitudes were identified: Active Acceptance, Passive Acceptance, Passive Decline, and Active Decline. Factors influencing vaccine acceptance include: knowledge of vaccine; risk perception; positive attitude towards other vaccines; social influences; and considerations about the future. Correspondingly, barriers to vaccine acceptance were identified as, low trust in the vaccine and historical (mis)trust, inadequate communication, and inequities in delivery and access. Opinion on mandatory vaccination was divided. Interpretation Our data show that vaccine attitudes are diverse and elements of hesitancy may remain even after vaccine acceptance. This has implications for the sustainability of the vaccine programme, particularly as new components (e.g. boosters) are being added. Based on our findings we recommend trust-building, designing inclusive and accessible information, and addressing structural inequities for improving vaccine uptake among HCWs. Funding UKRI-MRC and NIHR.
Towards a balanced annotated Low Saxon dataset for diachronic investigation of dialectal variation

We describe a new annotated dataset for Low Saxon with the intention to complement existing corpora. This corpus covers the period from the 15 th to the 21 st century and is annotated with PoS and morphosyntactic tags as well as century and region information. This dataset will be used for diachronic dialecto-metry, but can lend itself to other NLP tasks as well. The target size is around 2000 sentences per dialect and century and at the time of writing, 798 texts have been selected for inclusion in the corpus. They will be gradually added as the annnotation progresses.
Automatic Phrase Recognition in Historical German

Due to a lack of annotated data, theories of historical syntax are often based on very small, manually compiled data sets. To enable the empirical evaluation of existing hypotheses, the present study explores the automatic recognition of phrases in historical German. Using modern and historical treebanks, training data for a neural sequence labeling tool and a probabilistic parser is created, and both methods are compared on a variety of data sets. The evaluation shows that the unlexicalized parser outperforms the sequence labeling approach, achieving F 1 -scores of 87%–91% on modern German and between 73% and 85% on different historical corpora. An error analysis indicates that accuracy decreases especially for longer phrases, but most of the errors concern incorrect phrase boundaries, suggesting further potential for improvement.
An Automated Driving Strategy Generating Method Based on WGAIL–DDPG

Abstract Reliability, efficiency and generalization are basic evaluation criteria for a vehicle automated driving system. This paper proposes an automated driving decision-making method based on the Wasserstein generative adversarial imitation learning–deep deterministic policy gradient (WGAIL–DDPG(λ)). Here the exact reward function is designed based on the requirements of a vehicle’s driving performance, i.e., safety, dynamic and ride comfort performance. The model’s training efficiency is improved through the proposed imitation learning strategy, and a gain regulator is designed to smooth the transition from imitation to reinforcement phases. Test results show that the proposed decision-making model can generate actions quickly and accurately according to the surrounding environment. Meanwhile, the imitation learning strategy based on expert experience and the gain regulator can effectively improve the training efficiency for the reinforcement learning model. Additionally, an extended test also proves its good adaptability for different driving conditions.
Hand Guiding a Virtual Robot Using a Force Sensor

Abstract The research behind this paper arose out of a need to use an open-source system that enables hand guiding of the robot effector using a force sensor. The paper deals with some existing solutions, including the solution based on the open-source framework Robot Operating System (ROS), in which the built-in motion planner MoveIt is used. The proposed concept of a hand-guiding system utilizes the output of the force–torque sensor mounted at the robot effector to obtain the desired motion, which is thereafter used for planning consequential motion trajectories. Some advantages and disadvantages of the built-in planner are discussed, and then the custom motion planning solution is proposed to overcome the identified drawbacks. Our planning algorithm uses polynomial interpolation and is suitable for continuous replanning of the consequential motion trajectories, which is necessary because the output from the sensor changes due to the hand action during robot motion. The resulting system is verified using a virtual robot in the ROS environment, which acts on the real Optoforce force–torque sensor HEX-70-CE-2000N. Furthermore, the workspace and the motion of the robot are restricted to a greater extent to achieve more realistic simulation.
Thermal-magneto-mechanical stability analysis of nanofluid conveying carbon nanotubes based on nonlocal couple stress theory

Abstract Carbon nanotubes (CNTs) have extensive biomedical applications in which a heat pulse is applied to the CNTs. The present study encompasses the novelty by focusing on the complicated effect of thermal loads and heat generation on the CNT stability with the aim of preserving and improving the stability. There is also a lack of research that evaluates the size-dependence using appropriate robust non-classic theory, which is incorporated by employing a hybrid method of nonlocal couple stress theory and nonlocal elasticity theory. Additionally, Euler–Bernoulli beam theory is employed for coupling the Navier–Stokes equation of magnetic-fluid flow with the CNT deformation. The CNT stability is evaluated by considering nonlocal and couple-stress sizing effect parameters, Knudsen number, magnetic field intensity, thermal effect, heat generation, and fluid flow velocity. Results indicate that, by rising the temperature gradient and the couple stress sizing effect parameter, the system stability is improved up to 19.07% and 16.58%. Whereas, by increasing the heat generation, the dimensionless critical velocity shows 6.91% decrease, which deteriorates the CNT stability. Results of the present study demonstrates that in CNT applications with the presence of thermal loads, neglect of thermal effects leads to misinterpretation of the system stability.
Fixed-time output tracking control for a class of uncertain nonlinear MIMO systems

This article proposed a new fixed-time output tracking control scheme for a class of high-order MIMO nonlinear systems with unknown nonlinearities, parameter uncertainties and external disturbances. Firstly, a novel nonsingular recursive integral terminal sliding mode (ITSM) surface is designed by employing appropriate integral function and integer orders. Then the lumped system matched and mismatched uncertainties are estimated by developing a new adaptive fixed-time disturbance observer (AFTDO) based on super-twisting technique. The chattering problem existed in traditional disturbance observer (DO) can be reduced with the proposed AFTDO allowing the gains to adapt the changed derivative of lumped disturbances, effectively. Furthermore, semi-global fixed-time stability analysis is presented by means of Lyapunov stability theorem and it is proved that the system convergence time is independent of the system initial states and allowed to be arbitrarily adjusted based on practical demands. Finally, theoretical results are supported by numerical simulation and experimental results.
Assessing the impact of sharing economy through adoption of ICT based crowdshipping platform for last-mile delivery in urban and semi-urban India

ABSTRACT Crowdshipping and Item sharing are the concepts of sharing economy being increasingly adopted by various retailers to address the problem of last-mile delivery. Moreover crowdshipping platform has not yet been introduced commercially in developing countries successfully. Thus the purpose of this study is to investigate the Indian urban and semi-urban participant's intention toward crowdshipping platform for last-mile delivery through the use of sharing economy. A sociotechnical framework is adopted to analyse and assess the impact of sharing platform intension by considering the mediating roles of ‘trust' and ‘attitude’. The theoretical model has been validated empirically using a survey of 310 participants and subsequent analysis have been carried out using structured equation modelling. The result indicate increasing participation of the next generation. The research also highlights impacts of potential for collaboration with various stakeholders. As a result, it can lead to generate employment opportunities and revenue generation.