Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear model predictive control for robust bipedal locomotion: exploring angular momentum and CoM height changes

Human beings can utilize multiple balance strategies, e.g. step location adjustment and angular momentum adaptation, to maintain balance when walking under dynamic disturbances. In this work, we propose a novel Nonlinear Model Predictive Control (NMPC) framework for robust gait pattern generation, with the capabilities of step location adjustment, Center of Mass (CoM) height variation, and angular momentum adaptation. These features are realized by constraining the Zero Moment Point within the support polygon. By employing the nonlinear inverted pendulum plus flywheel model, the effects of upper-body rotation and vertical height motion are considered. As a result, the NMPC is formulated as a quadratically constrained quadratic program problem, which is solved fast by sequential quadratic programming. Consequently, robust walking patterns that exploit reactive stepping, body inclination, and CoM height variation are generated. Adaptable walking in multiple scenarios has been demonstrated through simulation studies. GRAPHICAL ABSTRACT
Abundant non-A residues in the poly(A) tail orchestrate the mouse oocyte-to-embryo transition

Non-A (U, G, and C) residues can be added to the 5’-end, internal, and 3’-end positions of poly(A) tails of RNA transcripts1–3, and some of these have been shown to regulate mRNA stability4, 5. The mammalian oocyte-to-embryo transition (OET) relies on post-transcriptional regulation of maternal RNA, because transcription is silent during this process until the point of zygotic genome activation (ZGA)6–9. Although the regulation of mRNA translation by poly(A) tail length plays an important role in the mammalian OET, the dynamics and functions of non-A residues in poly(A) tails are completely unknown. In this study, we profiled the genome-wide presence, abundance, and roles of non-A residues during the OET in mice using PAIso-seq1 and PAIso-seq22, 10, two complementary methods of poly(A) tail analysis. We found that non-A residues are highly dynamic in maternal mRNA, following a general pattern of beginning to increase at the MII stage, becoming highly abundant after fertilization with U residues in about half of poly(A) tails in 1-cell embryos, and declining in 2-cell embryos. We revealed that Btg4-mediated global maternal mRNA deadenylation created the substrates for U residue addition by Tut4/7 at their 3’-ends and further re-polyadenylation. In addition, G residues can be added by Tent4a/b. Finally, we demonstrate that G residues stabilize the modified mRNA, while the U residues mark maternal RNA for faster degradation in 2-cell mouse embryos. Taken together, these findings demonstrate that non-A residues are abundant and re-sculpt the maternal transcriptome to initiate zygotic development, which reveals the functional importance of the post-transcriptional regulation mediated by non-A residues in mRNA poly(A) tails.
Robust designation of meiotic crossover sites by CDK-2 through phosphorylation of the MutSγ complex

Crossover formation is essential for proper segregation of homologous chromosomes during meiosis. Here we show that C. elegans Cyclin-dependent kinase 2 (CDK-2) forms a complex with cyclin-like protein COSA-1 and supports crossover formation by promoting conversion of meiotic double-strand breaks (DSBs) into crossover-specific recombination intermediates. Further, we identify MutSγ component MSH-5 as a CDK-2 phosphorylation target. MSH-5 has a disordered C-terminal tail that contains 13 potential CDK phosphosites and is required to concentrate crossover-promoting proteins at recombination sites. Phosphorylation of the MSH-5 tail appears dispensable in a wild- type background, but when MutSγ activity is partially compromised, crossover formation and retention of CDK-2/COSA-1 at recombination sites are exquisitely sensitive to phosphosite loss. Our data support a model in which robustness of crossover designation reflects a positive feedback mechanism involving CDK-2-mediated phosphorylation and scaffold-like properties of the MSH-5 C-terminal tail, features that combine to promote full recruitment and activity of crossover-promoting complexes.
A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

Glycans are critical to every facet of biology and medicine, from viral infections to embryogenesis. Tools to study glycans are rapidly evolving, however the majority of our knowledge is deeply dependent on binding by glycan binding proteins (e.g., lectins). The specificities of lectins, which are often naturally isolated proteins, have not been well- defined, making it difficult to leverage their full potential for glycan analysis. Herein, we use glycan microarray analysis of 116 commercially available lectins, including different preparations of the same lectin, to extract the specific glycan features required for lectin binding. Data was obtained using the Consortium for Functional Glycomics microarray (CFG v5.0) containing 611 glycans. We use a combination of machine learning algorithms to define lectin specificity, mapping inputs (glycan sequences) to outputs (lectin-glycan binding) for a large-scale evaluation of lectin-glycan binding behaviours. Our motif analysis was performed by integrating 68 manually defined glycan features with systematic probing of computational rules for significant binding motifs using mono- and disaccharides- and linkages. Using a combination of machine learning and manual annotation of the data, we created a detailed interpretation of glycan-binding specificity for 57 unique lectins, categorized by their major binding motifs: mannose, complex-type N-glycan, O-glycan, fucose, sialic acid and sulfate, GlcNAc and chitin, Gal and LacNAc, and GalNAc. Our work provides fresh insights into the complex binding features of commercially available lectins in current use, providing a critical guide to these important reagents.
Enzymatic Beacons for Specific Sensing of Dilute Nucleic Acid and Potential Utility for SARS-CoV-2 Detection.

Enzymatic beacons, or E-beacons, are 1:1 bioconjugates of the nanoluciferase enzyme linked covalently at its C-terminus to hairpin forming DNA oligonucleotides equipped with a dark quencher. We prepared E-beacons biocatalytically using the promiscuous “hedgehog” protein-cholesterol ligase, HhC. Instead of cholesterol, HhC attached nanoluciferase site-specifically to mono-sterylated hairpin DNA, prepared in high yield by solid phase synthesis. We tested three potential E-beacon dark quenchers: Iowa Black, Onyx-A, and dabcyl. Prototype E-beacon carrying each of those quenchers provided sequence-specific nucleic acid sensing through turn-on bioluminescence. For practical application, we prepared dabcyl-quenched E-beacons for potential use in detecting the COVID-19 virus, SARS-CoV-2. Targeting the E484 codon of the SARS-CoV-2 Spike protein, E-beacons (80 × 10−12 M) reported wild-type SARS-CoV-2 nucleic acid at ≥1 × 10−9 M with increased bioluminescence of 8-fold. E-beacon prepared for the E484K variant of SARS-CoV-2 functioned with similar sensitivity. These E-beacons could discriminate their complementary target from nucleic acid encoding the E484Q mutation of the SARS-CoV-2 Kappa variant. Along with specificity, detection sensitivity with E-beacons is two to three orders of magnitude better than synthetic molecular beacons, rivaling the most sensitive nucleic acid detection agents reported to date.
The effect of prior incarceration on trust and social support: results from two factorial vignette studies

Abstract Social capital can help formerly incarcerated individuals navigate the challenges of life after prison. Yet, these individuals are unlikely to receive the trust from others that is necessary to build the relationships from which social capital and social support flow. To date, little research has examined individuals’ willingness to extend trust and provide social support to those who are reentering society. To help fill this void, two independent factorial vignette studies were conducted using university-based samples. Study 1 tested the effect of prior incarceration on participants’ willingness to trust. Study 2 examined whether participants provided more social support to recently incarcerated kin as opposed to recently incarcerated friends. Findings from both studies highlight some of the disadvantages formerly incarcerated individuals face when reentering society.
The impact of cannabis smoke on the performance of pulmonary surfactant under physiologically relevant conditions

The principal site for gaseous exchange within the lung is the alveolar space, which is bathed in a lipid‐protein blend called pulmonary surfactant. This material is the initial contacting site for orally inhaled products and environmental toxins. Using the lung biosimulator, this study investigates the influence of cannabis smoke on the activity of the lung surfactant replacement product, Curosurf. Initially, 50‐mg cannabis material was pyrolysed and the smoke collected. Cannabis smoke profiling was conducted via gas chromatography–mass spectroscopy, with a mean concentration of 1% Δ9‐tetrahydrocannabinol determined. The smoke aliquots were transferred to the lung biosimulator and expansion—contraction cycles were then initiated to mimic tidal breathing. Baseline data confirmed that Curosurf works effectively under physiologically relevant conditions. Exposure to cannabis smoke from 2 independent batches reduced the Langmuir maximum surface pressure values by approximately 20% and increased the compressibility term; interbatch variation was detected. Cannabis smoke impaired the ability of Curosurf to lower the surface tension term. This was ascribed to the penetration of the planar, hydrophobic drug into the two‐dimensional film, and destructive interaction with polar functionalities. The net effect would be increased work of breathing for the individual.
Age heaping pattern and data quality: evidence from Indian Household Survey Data (1991–2016)

Abstract Age structure is crucial to various socio-economic and demographic factors. Better age quality data are critical to determine the reliability of large scale household surveys and the estimates they provide. Considering the importance and large sample these household surveys represent, we examined one of India’s largest household survey (NFHS) to determine its data quality and accuracy. Using multiple indices we also made a comparison of various age reporting measures to assess pattern of age heaping. Our results found that age heaping is a gray concern for household surveys in India. Though there has been some improvement, but over all age quality data are still very rough, affecting likely the survey estimates. Females are performing better on contrary to what earlier studies have found, which is likely due to improving socio-cultural and living norms in Indian settings. It is clear that age preference can likely cause the substantial biases in demographic factors and survey estimates. Thus studies examining age structure or any such methods where age is significantly important should adjust the age bias before carrying out further analysis. Furthermore, a single approach for age adjustment techniques is must to improve the age quality data for better policy implications.
Work-Related Stress and the Relationship with the Health Belief Model among Medical Doctors in a Tertiary Hospital in Port-Harcourt, Nigeria

Background: Work-Related Stress (WRS) is a harmful physical and/or emotional response resulting from a mismatch between the requirements of a job and the capabilities, resources, or needs of the worker in the work environment. The health belief model (HBM) is a psychological health behaviour change model established to describe and predict health-related behaviours regarding the uptake of health services. This study sought to determine the prevalence of WRS and to assess WRS among medical doctors in the University of Port Harcourt Teaching Hospital (UPTH), Rivers State, using the Health Belief Model (HBM). Methods: The study design was descriptive cross-sectional conducted among medical doctors in the UPTH. A proportionate stratified and random sampling method was used to recruit 363 medical doctors in two stages. Data was collected using a self-administered questionnaire which assessed respondents’ socio-demographics, Work-related Stress and Health Belief Model domains. Data was analysed using SPSS version 23.0. The Pearson’s correlation coefficient was used to assess Original Research Article Okechukwu and Babatunde; JESBS, 34(4): 10-21, 2021; Article no.JESBS. 69249 11 relationship between WRS and the HBM components, while the multiple linear regression analysis was used to identify the HBM components that significantly predicted work-related stress. The level of significance was set at p= 0.05. Results: Most of the respondents were females (56.5%), married (90.1%), Christians (93.7%) and ≥36 years (71.6%). The mean age of respondents was 39.7±0.45 years. The prevalence of workrelated stress was 66%, (Overall mean score ± SD=3.30±0.27). All components of the HBM were significantly correlated with Work-related Stress, and perceived severity showed the strongest positive correlation (r=0.687; p<0.001). All components of the HBM significantly predicted workrelated stress except perceived susceptibility. Conclusion: All the components of the health belief model significantly predict Work-related Stress except perceived susceptibility. Measures to address stress among doctors in the workplace should put into consideration these domains of the health belief model.
Statistical Downscaling and Projection of Future Temperature and Precipitation Change in Gandaki Basin

Understanding the present and future spatial and temporal variations of precipitation and temperature is important for monitoring climate-induced disasters. Satellite and global reanalysis data can provide evenly distributed climate data; however, they are still too coarse to resolve fundamental processes over complex terrains. The study applies global climate model CGCM4/CANESM2, to project future maximum temperature, minimum temperature, and precipitation across the cross-section of the Gandaki River basin, Nepal. Large scale atmospheric variables of the National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis (NCEP/NCAR) datasets are downscaled using Statistical Downscaling Model (SDSM) under different emission scenarios. For the variability and changes in maximum temperature (Tmax), minimum temperature (Tmin), and precipitation for future periods (2020s, 2050s, and 2080s), three different scenarios RCP2.6, RC4.5, and RCP8.5 of CGCM4 model were performed. The study revealed that both the temperature and precipitation would increase for three RCPs (representative concentration pathways) in the future. The highest increase in precipitation was found in the arid region compared to humid and sub-humid regions by the end of 2100. Similarly, the increase in mean monthly Tmin and Tmax was more pronounced in Jomsom station than Baglung and Dumkauli stations. Overall, a decrease in summer temperature and increase in winter temperature was expected for future periods across all regions. Further, spatial consistency was observed for Tmax and Tmin, whereas spatial consistency was not found for precipitation.
The Retrieval-Related Anterior Shift Is Moderated by Age and Correlates with Memory Performance

Recent research suggests that episodic memory is associated with systematic differences in the localization of neural activity observed during memory encoding and retrieval. The retrieval-related anterior shift is a phenomenon whereby the retrieval of a stimulus event (e.g., a scene image) is associated with a peak neural response which is localized more anteriorly than the response elicited when the stimulus is experienced directly. Here, we examine whether the magnitude of the anterior shift (i.e., the distance between encoding- and retrieval-related response peaks) is moderated by age, and also whether the shift is associated with memory performance. Younger and older human subjects of both sexes underwent fMRI as they completed encoding and retrieval tasks on word-face and word-scene pairs. We localized peak scene and face selectivity for each individual participant within the face-selective precuneus and in three scene-selective (parahippocampal place area [PPA], medial place area, occipital place area) ROIs. In line with recent findings, we identified an anterior shift in the PPA and occipital place area in both age groups and, in older adults only, in the medial place area and precuneus also. Of importance, the magnitude of the anterior shift was larger in older than in younger adults. The shift within the PPA exhibited an age-invariant across-participant negative correlation with source memory performance, such that a smaller displacement between encoding- and retrieval-related neural activity was associated with better performance. These findings provide novel insights into the functional significance of the anterior shift, especially in relation to memory decline in older age. SIGNIFICANCE STATEMENT Cognitive aging is associated with reduced ability to retrieve precise details of previously experienced events. The retrieval-related anterior shift is a phenomenon in which category-selective cortical activity at retrieval is localized anterior to the peak activity at encoding. The shift is thought to reflect a bias at retrieval in favor of semantic and abstract information at the expense of low-level perceptual detail. Here, we report that the anterior shift is exaggerated in older relative to younger adults, and we demonstrate that a larger shift in the parahippocampal place area is associated with poorer memory performance. These findings suggest that the shift is sensitive to increasing age and that it is moderated by the quality and content of the retrieved episode.
Utilization of multilayer perceptron for determining the inverse kinematics of an industrial robotic manipulator

Inverse kinematic equations allow the determination of the joint angles necessary for the robotic manipulator to place a tool into a predefined position. Determining this equation is vital but a complex work. In this article, an artificial neural network, more specifically, a feed-forward type, multilayer perceptron (MLP), is trained, so that it could be used to calculate the inverse kinematics for a robotic manipulator. First, direct kinematics of a robotic manipulator are determined using Denavit–Hartenberg method and a dataset of 15,000 points is generated using the calculated homogenous transformation matrices. Following that, multiple MLPs are trained with 10,240 different hyperparameter combinations to find the best. Each trained MLP is evaluated using the R 2 and mean absolute error metrics and the architectures of the MLPs that achieved the best results are presented. Results show a successful regression for the first five joints (percentage error being less than 0.1%) but a comparatively poor regression for the final joint due to the configuration of the robotic manipulator.
Unsupervised machine learning framework for early machine failure detection in an industry

Abstract This article describes a credible and prognostic analysis in this study for failure detection of a machine in the industry. An interpretable methodology and an informative functionality are portrayed, trained with the dataset and their explicatory implementation is compared and evaluated. In this paper, we will design a deployable end-to-end grading model to forecast whether or not the machine will fail. We will train state-of-the-art algorithms for gradient enhanced decision trees (GBDT) and compare their performance.
Analyse du rôle de la dégradation du facteur CIITA (class II transactivator) sur son potentiel d'activation des gènes de classe II du complexe majeur d'histocompatibilité

The relationship between protein turnover and transcriptional activation is well documented, but still poorly understood. One mechanism to induce degradation is via ubiquitination of the N-terminal a-amino group of proteins. The major histocompatibility complex (MHC) class II transactivator CIITA is the master regulator of MHC-II gene expression and we showed earlier that CIITA is a short-lived protein. We show here that the extreme N-terminal end of CIITA isoform III induces both rapid degradation and transactivation. It is essential that this sequence resides at the N-terminal end of the protein. The first ten amino acids of CIITA isoform III act as a portable degron and transactivation sequence, as do the N-terminal ends of several known N-terminal ubiquitination substrates, such as Id2, Cdtl and MyoD. Arginine and proline residues within the N-terminal ends contribute to rapid turnover. The N-terminal end of CIITA isoform III is responsible for efficient in vivo recruitment to the HLA-DRA promoter and increased interaction with components of the transcription machinery, such as TBP, p300, p400/Domino, the 19S ATPase S8, and the MHC-II promoter binding complex RFX. These experiments reveal a novel ftmction of free N-terminal ends of proteins in degradation-dependent transcriptional activation.
Modeling the relations among task value, strategies, social factors, and English achievement

Abstract Task value has a considerable effect on one’s interest, motivation, and strategies in learning. Additionally, the social contexts in which a learner studies, such as subject specialization and gender, may potentially influence how successfully one learns. The purpose of this quantitative study is to examine the relationship between task value and social factors, which were mediated by three types of learning strategy, and students’ test performance in English. A questionnaire survey was conducted with 776 Grade 11 EFL vocational high school students in Taiwan. The path model revealed that the participants’ English test scores were strongly influenced by the task value. Only metacognitive and cognitive strategies mediated the relationship between task value and English test score. Emotion control strategies did not mediate the relationship between them. Students’ subject specialization had a direct influence on students’ English test score, but the learning strategies did not play a mediating role between them.