Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Non-Expert Robot Programming Through Crowdsourcing

A longstanding barrier to deploying robots in the real world is the ongoing need to author robot behavior. Remote data collection–particularly crowdsourcing—is increasingly receiving interest. In this paper, we make the argument to scale robot programming to the crowd and present an initial investigation of the feasibility of this proposed method. Using an off-the-shelf visual programming interface, non-experts created simple robot programs for two typical robot tasks (navigation and pick-and-place). Each needed four subtasks with an increasing number of programming statements (if statement, while loop, variables) for successful completion of the programs. Initial findings of an online study (N = 279) indicate that non-experts, after minimal instruction, were able to create simple programs using an off-the-shelf visual programming interface. We discuss our findings and identify future avenues for this line of research.
Identification, Characterization, and Expression Analysis Reveal Diverse Regulated Roles of Three MAPK Genes in Chlamys farreri Under Heat Stress

Mitogen-activated protein kinase (MAPK) cascades are fundamental signal transduction modules in all eukaryotic organisms, participating growth and development, as well as stress response. In the present study, three MAPK genes were successfully identified from the genome of Chlamys farreri, respectively, named CfERK1/2, CfJNK, and Cfp38, and only one copy of ERK, JNK, and p38 were detected. Domain analysis indicated that CfMAPKs possessed the typical domains, including S_TKc, Pkinase, and PKc_like domain. Phylogenetic analysis showed that three CfMAPKs of MAPK subfamilies exists in the common ancestor of vertebrates and invertebrates. All CfMAPKs specifically expressed during larval development and in adult tissues, and the expression level of CfERK1/2 and Cfp38 was apparently higher than that of CfJNK. Under heat stress, the expression of CfERK1/2 and Cfp38 were significantly downregulated and then upregulated in four tissues, while the expression of CfJNK increased in all tissues; these different expression patterns suggested a different molecular mechanism of CfMAPKs for bivalves to adapt to temperature changes. The diversity of CfMAPKs and their specific expression patterns provide valuable information for better understanding of the functions of MAPK cascades in bivalves.
Psychological Interventions for Healthcare Providers With PTSD in Life-Threatening Pandemic: Systematic Review and Meta-Analysis

Objective: This study aims to evaluate the effect of psychological interventions on healthcare providers (HCP) with post-traumatic stress disorder (PTSD) due to their necessary exposure in life-threatening pandemic. Methods: We performed a systematic research on Medline, Embase, Cochrane Central, PsycInfo, Cochrane Central Register of Controlled Trials, Clinicaltrials.gov, ProQuest PTSD Pubs ProQuest Dissertations & Theses Global, and other gray databases by January 2021. Randomized controlled trials involving therapeutic interventions for HCP with PTSD were included. The primary outcome was PTSD symptom severity. Summary standardized mean differences (SMDs) and 95% confidence intervals were estimated using inverse variance meta-analysis with fixed effects. Risks of bias were assessed using Cochrane methods. Results: Among 773 citations, this review includes six studies, randomizing 810 participants. A meta-analysis of the effect of interventions compared to placebo showed a significant reduction of PTSD symptom severity: Cognitive Behavioral Therapy-Brief (CBT-B) (M = 27.80, 95% CI: 17.12, 38.48), Cognitive Behavioral Therapy-Long (CBT-L) (M = 26.50, 95% CI: 15.75, 37.25), and Mindfulness-Based Stretching and Deep Breathing Exercise (MBX) (M = 17.2, 95% CI: 6.57, 27.83). CBT-L and CBT-B also showed a significant effect on depression severity. Conclusions: The most effective and feasible treatment option for HCP with PTSD is still unclear, but CBT and MBX have displayed the most significant effects based on current limited evidence. Future research in this area—preferably large robust randomized controlled trials—is much needed.
Hybridization With an Invasive Plant of Xanthium strumarium Improves the Tolerance of Its Native Congener X. sibiricum to Cadmium

Hybridization is one of the important factors influencing the adaptive evolution of invasive plants. According to previous studies, hybridization with an invasive plant reduces the adaptability of its native congener to environment. However, in this study, the hybridization with an invasive plant of Xanthium strumarium (LT) improves the tolerance and accumulation of its native congener Xanthium sibiricum (CR) to cadmium (Cd). Under Cd stress, X. sibiricum♀ × X. strumarium♂ (ZCR) showed higher biomass and Cd accumulation. Compared with CR, ZCR has longer vegetative and reproductive growth time. Moreover, ZCR adopted more reasonable biomass allocation strategy. ZCR increased the proportion of reproductive allocation and ensured its own survival with the increase of Cd stress. Furthermore, ZCR increased the translocation of Cd to aboveground parts and changed the distribution of Cd. A large amount of Cd is stored in senescent leaves and eliminated from the plant when the leaves fall off, which not only reduces the Cd content in the plant, but also reduces the toxicity of Cd in the normal leaves. Transcriptome analysis shows a total of 2055 (1060 up and 995 down) differentially expressed genes (DEGs) were detected in the leaves of Cd-stressed ZCR compared with CR, while only 792 (521 up and 271 down) were detected in X. strumarium♀ × X. sibiricum♂ (ZLT) compared with LT. A large number of DGEs in ZCR and ZLT are involved in abscisic acid (ABA) synthesis and signal transduction. The genes induced by ABA in ZCR, including CNGC5/20, CPK1/28, CML, PTI1-like tyrosine-protein kinase 3, respiratory burst oxidase homolog protein C, and WRKY transcription factor 33 were found differentially expressed compared CR. carotenoid cleavage dioxygenase 4, NCED1/2, phytoene synthase 2, and CYP707A involved in ABA synthesis and decomposition in ZLT were found differentially expressed compared LT. We speculated that ABA played an important role in Cd transportation of hybrids and Cd distribution in senescent and normal leaves. The results demonstrate that hybridization with an invasive plant improves the adaptability of the hybrid to Cd stress and may enhance the extinction risk of native congener in pollution environment.
Satellite Tracking Reveals Nesting Patterns, Site Fidelity, and Potential Impacts of Warming on Major Green Turtle Rookeries in the Red Sea

Major aggregations of nesting green turtles (Chelonia mydas) occur in the northern Red Sea, although little is known about the reproductive ecology of this endangered species in the region. To address this issue, we satellite-tracked 30 female green turtles to document their movements and to identify factors driving habitat use at two major rookeries in the Red Sea, Jazirat Mashabah (Mashabah Island) and Ras Al Baridi in Saudi Arabia. Between successive nesting events, turtles displayed high fidelity to nesting beaches and adjacent in-water habitats (inter-nesting habitats). Using generalized linear mixed models, we estimated the mean probability of nesting per beach emergence (nesting success rate) to be 0.628, and the mean duration between a successful nesting event and the successive emergence onto the beach (re-nesting interval) to be 10.8 days at each site. The nesting success rate was relatively high (>0.8) when the preceding daytime land surface temperature (LST) was lower than 37°C but decreased with elevated daytime LST (<0.4 when >47°C). Re-nesting interval was longer at lower water temperatures and towards the end of the nesting season of individuals. Our study improves the robustness of abundance estimates from census data (e.g., track counts) and shows that the protection of nesting and inter-nesting habitats during a breeding season would be an effective conservation strategy for the species. We discuss how global warming could increase energy expenditure due to lowered nesting success, ultimately compromising the reproductive fitness of these populations.
Effects of Wave–Current Interaction on Storm Surge in the Pearl River Estuary: A Case Study of Super Typhoon Mangkhut

This study explored the effects of interactions between waves and current on storm surge in the Pearl River Estuary (PRE) using a fully coupled wave–current model. The model was validated based on in situ observations during the traverse of super typhoon Mangkhut. The results indicated that the model could reproduce the storm surge and wave setup processes. Numerical experiments showed that simulations of storm surge are minimally affected by wave setup. The wave setup during super typhoon Mangkhut reached up to 0.23 m and contributed to the total near shore storm surge by up to 8%. The simulations of the coupled model showed a better correlation with observations compared to those of an uncoupled model. The storm surge increased with transport upstream in a tidal-dominated outlet, whereas it decreased in a river-dominated outlet. The storm surge and wave setup increased and decreased, respectively, during spring tide as compared to that during a neap tide. The storm surge increased with increasing runoff in the upper river reaches, whereas there was little change in the tidal-dominated lower river reaches. This research emphasizes the importance of integrating the effects of multiple dynamic factors in the forecasting of storm surge and provides a reference for similar studies in other estuaries with multiple outlets and a complex river network.
A Novel Model for Identifying Essential Proteins Based on Key Target Convergence Sets

In recent years, many computational models have been designed to detect essential proteins based on protein-protein interaction (PPI) networks. However, due to the incompleteness of PPI networks, the prediction accuracy of these models is still not satisfactory. In this manuscript, a novel key target convergence sets based prediction model (KTCSPM) is proposed to identify essential proteins. In KTCSPM, a weighted PPI network and a weighted (Domain-Domain Interaction) network are constructed first based on known PPIs and PDIs downloaded from benchmark databases. And then, by integrating these two kinds of networks, a novel weighted PDI network is built. Next, through assigning a unique key target convergence set (KTCS) for each node in the weighted PDI network, an improved method based on the random walk with restart is designed to identify essential proteins. Finally, in order to evaluate the predictive effects of KTCSPM, it is compared with 12 competitive state-of-the-art models, and experimental results show that KTCSPM can achieve better prediction accuracy. Considering the satisfactory predictive performance achieved by KTCSPM, it indicates that KTCSPM might be a good supplement to the future research on prediction of essential proteins.
Diethyl Aminoethyl Hexanoate Priming Ameliorates Seed Germination via Involvement in Hormonal Changes, Osmotic Adjustment, and Dehydrins Accumulation in White Clover Under Drought Stress

Drought is a serious outcome of climate change reducing the productivity of forage species under arid and semi-arid conditions worldwide. Diethyl aminoethyl hexanoate (DA-6), a novel plant growth regulator, has proven to be involved in the amelioration of critical physiological functions in many agricultural crops under various abiotic stresses, but the role of the DA-6 in improving seed germination has never been investigated under drought stress. The present study was carried out to elucidate the impact of the DA-6 priming on seeds germination of white clover under drought stress. Results showed that seed priming with the DA-6 significantly mitigated the drought-induced reduction in germination percentage, germination vigor, germination index, seed vigor index, root length, shoot length, and fresh weight after 7 days of seed germination. The DA-6 significantly increased the endogenous indole-3-acetic acid, gibberellin, and cytokinin content with marked reduction in abscisic acid content in seedlings under drought stress. In addition, the DA-6 significantly accelerated starch catabolism by enhancing the activities of hydrolases contributing toward enhanced soluble sugars, proline content and ameliorated the antioxidant defense system to enhance the ability of reactive oxygen species scavenging under drought stress. Furthermore, exogenous DA-6 application significantly increased dehydrins accumulation and upregulated transcript levels of genes encoding dehydrins (SK2, Y2SK, or DHNb) during seeds germination under water deficient condition. These findings suggested that the DA-6 mediated seeds germination and drought tolerance associated with changes in endogenous phytohormones resulting in increased starch degradation, osmotic adjustment, antioxidants activity, and dehydrins accumulation during seed germination under water deficient condition.
COVID-19 Impacts on Teaching and Learning: A Collaborative Autoethnography by Two Higher Education Lecturers

The phenomenon of the Covid-19 lockdown in New Zealand during 2020 enabled two Higher Education (HE) lecturers to reflect on grappling with new technologies, changes in lifestyle and livelihoods, and the impact that social isolation had on Bachelor of Sport and Recreation (BSR) students as they shifted to emergency “remote” teaching and learning. This paper presents personal narratives, authored collaboratively by lecturers Anna and Hana (pseudonyms), engaging with a socio-ecological systems framework. The systems framework presents a layered, multi-faceted approach to reveal the complexity of the impacts of Covid-19 on HE teaching and learning. In-depth analysis of the microsystems, mesosystems, and macrosystems making up their systems framework, serve to highlight specifically how Anna and Hana interpreted their own and their university students’ responses to the unprecedented measures imposed on their lifestyle (home), livelihood (employment), and HE experience (online learning). By applying an autoethnographic methodology, this paper acknowledges and celebrates the lecturers’ subjectivity, emotionality, and influence on the presented research. As educators, their critical self-reflections are authentic and timely, expressing key concerns and considerations, while searching for optimal solutions to deliver equal and equitable learning opportunities for all students. A unique characteristic of this phenomenon was the inability (due to COVID-19 restrictions) of students who learn through practical contexts, to enact kinesthetically in a meaningful manner, and the subsequent implications on their learning. This paper presents a snippet of the lecturers’ reflective practice, co-constructed from recollections, memories, and anecdotal evidence, against a backdrop of current Covid-19 research on the effects of the pandemic, on teaching and learning globally. Whilst this paper sheds light on the experiences of two HE lecturers during the COVID-19 lockdown, a collection and analysis of “student” voice, is recommended. This paper concludes that a collaborative autoethnographic approach during exceptional circumstances, such as natural disasters, pandemics, and other disruptive situations, provides an opportunity for professional self-observation and self-reflective practice that is mutually beneficial, and empowering. These insights provide shared critical knowledge to sustain achievement while averting negative impacts, for students and lecturers alike.
A Novel Estimation of Unobserved Pig Growth Traits for the Purposes of Precision Feeding Methods

Recent technological advances make it possible to deliver feeding strategies that can be tailored to the needs of individual pigs in order to optimise the allocation of nutrient resources and contribute toward reducing excess nutrient excretion. However, these efforts are currently hampered by the challenges associated with: (1) estimation of unobserved traits from the available data on bodyweight and feed consumption; and (2) characterisation of the distributions and correlations of these unobserved traits to generate accurate estimates of individual level variation among pigs. Here, alternative quantitative approaches to these challenges, based on the principles of inverse modelling and separately inferring individual level distributions within a Bayesian context were developed and incorporated in a proposed precision feeding modelling framework. The objectives were to: (i) determine the average and distribution of individual traits characterising growth potential and body composition in an empirical population of growing-finishing barrows and gilts; (ii) simulate the growth and excretion of nitrogen and phosphorus of the average pig offered either a commercial two-phase feeding plan, or a precision feeding plan with daily adjustments; and (iii) simulate the growth and excretion of nitrogen and phosphorus across the pig population under two scenarios: a two-phase feeding plan formulated to meet the nutrient requirements of the average pig or a precision feeding plan with daily adjustments for each and every animal in the population. The distributions of mature bodyweight and ratio of lipid to protein weights at maturity had median (IQR) values of 203 (47.8) kg and 2.23 (0.814) kg/kg, respectively; these estimates were obtained without any prior assumptions concerning correlations between the traits. Overall, it was found that a proposed precision feeding strategy could result in considerable reductions in excretion of nitrogen and phosphorus (average pig: 8.07 and 9.17% reduction, respectively; heterogenous pig population: 22.5 and 22.9% reduction, respectively) during the growing-finishing period from 35 to 120 kg bodyweight. This precision feeding modelling framework is anticipated to be a starting point toward more accurate estimation of individual level nutrient requirements, with the general aim of improving the economic and environmental sustainability of future pig production systems.
Prognostic Value of an Immunohistochemical Signature in Patients With Head and Neck Mucosal Melanoma

Purpose We aimed to develop a prognostic immunohistochemistry (IHC) signature for patients with head and neck mucosal melanoma (MMHN). Methods In total, 190 patients with nonmetastatic MMHN with complete clinical and pathological data before treatment were included in our retrospective study. Results We extracted five IHC markers associated with overall survival (OS) and then constructed a signature in the training set (n=116) with the least absolute shrinkage and selection operator (LASSO) regression model. The validation set (n=74) was further built to confirm the prognostic significance of this classifier. We then divided patients into high- and low-risk groups according to the IHC score. In the training set, the 5-year OS rate was 22.0% (95% confidence interval [CI]: 11.2%- 43.2%) for the high-risk group and 54.1% (95% CI: 41.8%-69.9%) for the low-risk group (P<0.001), and in the validation set, the 5-year OS rate was 38.1% (95% CI: 17.9%-81.1%) for the high-risk group and 43.1% (95% CI: 30.0%-61.9%) for the low-risk group (P=0.26). Multivariable analysis revealed that IHC score, T stage, and primary tumor site were independent variables for predicting OS (all P<0.05). We developed a nomogram incorporating clinicopathological risk factors (primary site and T stage) and the IHC score to predict 3-, 5-, and 10-year OS. Conclusions A nomogram was generated and confirmed to be of clinical value. Our IHC classifier integrating five IHC markers could help clinicians make decisions and determine optimal treatments for patients with MMHN.
Low Virulence of the Fungi Escovopsis and Escovopsioides to a Leaf-Cutting Ant-Fungus Symbiosis

Eusocial insects interact with a diversity of parasites that can threaten their survival and reproduction. The amount of harm these parasites cause to their hosts (i.e., their virulence) can be influenced by numerous factors, such as the ecological context in which the parasite and its host are inserted. Leaf-cutting ants (genera Atta, Acromyrmex and Amoimyrmex, Attini: Formicidae) are an example of a eusocial insect whose colonies are constantly threatened by parasites. The fungi Escovopsis and Escovopsioides (Ascomycota: Hypocreales) are considered a highly virulent parasite and an antagonist, respectively, to the leaf-cutting ants’ fungal cultivar, Leucoagaricus gongylophorus (Basidiomycota: Agaricales). Since Escovopsis and Escovopsioides are common inhabitants of healthy colonies that can live for years, we expect them to have low levels of virulence. However, this virulence could vary depending on ecological context. We therefore tested two hypotheses: (i) Escovopsis and Escovopsioides are of low virulence to colonies; (ii) virulence increases as colony complexity decreases. For this, we used three levels of complexity: queenright colonies (fungus garden with queen and workers), queenless colonies (fungus garden and workers, without queen) and fungus gardens (without any ants). Each was inoculated with extremely high concentrations of conidia of Escovopsis moelleri, Escovopsioides nivea, the mycoparasitic fungus Trichoderma longibrachiatum or a blank control. We found that these fungi were of low virulence to queenright colonies. The survival of queenless colonies was decreased by E. moelleri and fungus gardens were suppressed by all treatments. Moreover, E. nivea and T. longibrachiatum seemed to be less aggressive than E. moelleri, observed both in vivo and in vitro. The results highlight the importance of each element (queen, workers and fungus garden) in the leaf-cutting ant-fungus symbiosis. Most importantly, we showed that Escovopsis may not be virulent to healthy colonies, despite commonly being described as such, with the reported virulence of Escovopsis being due to poor colony conditions in the field or in laboratory experiments.
Prosodic Differences in Human- and Alexa-Directed Speech, but Similar Local Intelligibility Adjustments

The current study tests whether individuals (n = 53) produce distinct speech adaptations during pre-scripted spoken interactions with a voice-AI assistant (Amazon’s Alexa) relative to those with a human interlocutor. Interactions crossed intelligibility pressures (staged word misrecognitions) and emotionality (hyper-expressive interjections) as conversation-internal factors that might influence participants’ intelligibility adjustments in Alexa- and human-directed speech (DS). Overall, we find speech style differences: Alexa-DS has a decreased speech rate, higher mean f0, and greater f0 variation than human-DS. In speech produced toward both interlocutors, adjustments in response to misrecognition were similar: participants produced more distinct vowel backing (enhancing the contrast between the target word and misrecognition) in target words and louder, slower, higher mean f0, and higher f0 variation at the sentence-level. No differences were observed in human- and Alexa-DS following displays of emotional expressiveness by the interlocutors. Expressiveness, furthermore, did not mediate intelligibility adjustments in response to a misrecognition. Taken together, these findings support proposals that speakers presume voice-AI has a “communicative barrier” (relative to human interlocutors), but that speakers adapt to conversational-internal factors of intelligibility similarly in human- and Alexa-DS. This work contributes to our understanding of human-computer interaction, as well as theories of speech style adaptation.