Miracle-dz/UniFAR-FTUs huggingface dataset:
Screening of potential donors for anaerobic stress tolerance during germination in rice

The rising cost of transplanting rice has made direct seeding an affordable alternative for rice establishment, particularly in Africa. However, direct seeding, while cost-effective, faces crop establishment challenges due to flooding. Uncontrolled water, driven by erratic rains in low-lying areas or uneven fields, limit germination. Rice possesses the unique ability of anaerobic germination, enabling it to sprout and emerge in oxygen-deprived conditions. Understanding rice’s response to anaerobic stress during germination is crucial for resilience breeding. Africa, although relying on direct seeding, has made limited progress in addressing flooding during germination compared to Asia. Anaerobic stress tolerance ensures successful crop emergence even in oxygen-limited environments and can help suppress weeds, a significant challenge in direct-seeded rice cultivation. This study aims to contribute by screening for potential rice donors exhibiting anaerobic stress tolerance. We screened 200 rice genotypes at Sokoine University of Agriculture (SUA) in Morogoro, Tanzania, primarily focusing on landraces with untapped potential. Using an alpha lattice design, we conducted two anaerobic experiments in September and October 2022, adding 7 cm of standing water immediately after dry seeding for flooded and maintaining a 2 cm water level after germination in the control for duration of 21 days. We identified potential donors based on selection index computed from genomic estimated breeding values (GEBVs) using eight variables: germination at 14 DAS, germination at 21 DAS, seedling height at 14 DAS, seedling height at 21 DAS, shoot dry matter at 21 DAS, root dry matter at 21 DAS, culm diameter at 21 DAS, and root length at 21DAS. Ten genotypes emerged as the most promising, exhibiting at least 70% germination in floodwater at 21 DAS and greater selection indices. These genotypes were like: Afaa Mwanza 1/159, Rojomena 271/10, Kubwa Jinga, Wahiwahi, Magongo ya Wayungu, Mpaka wa Bibi, Mwangaza, Tarabinzona, IB126-Bug 2013A, and Kanamalia with respective percentages of 75, 74, 71, 86, 75, 80, 71, 80, 70, and 73. These findings contribute to global efforts to mitigate the impacts of flooding during germination. These donors, will be potential to enrich the gene pool for anaerobic germination, providing valuable resources for breeding for flooding tolerance.
A novel immune-related risk-scoring system associated with the prognosis and response of cervical cancer patients treated with radiation therapy

Objective: The tumor microenvironment plays a critical role in the radiotherapy and immunotherapy response of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Radioresistance is a key factor in treatment failure among patients who receive radical radiotherapy. Thus, new immune-related biomarkers associated with radiotherapy response in CESC are needed. Methods: In this study, the CIBERSORT and ESTIMATE methods were applied to determine the percentage of tumor-infiltrating cells and the number of immune components in 103 CESCs treated with radiotherapy from The Cancer Genome Atlas (TCGA) database. The main dysregulated genes were subjected to multivariate and univariate analyses. The prognostic value of this system was studied via receiver operating characteristic curve and survival analysis. For further confirmation, the biomarkers’ expression levels and predictive value were validated by immunohistochemistry (IHC) and qRT-PCR. The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in cervical cancer patients treated with radiation therapy. Results: Data for 17 radioresistant and 86 radiosensitive tumors were obtained from the The Cancer Genome Atlas database. 53 immune-related DEGs were identified. GO and KEGG analyses revealed that the DEGs were enriched in protein kinase B signaling, growth factors in cytokines, the MAPK pathway and the PI3K-Akt pathway. Then, 14 key immune-related genes built a risk scoring model were deemed prognostic in CESC with radiotherapy. The area under the curve (AUC) of the model was 0.723, and the high-risk group presented worse outcomes than the low-risk group. In addition, the high-risk group tended to have persistent tumors (p = 0.001). The high expression of WT1 and SPOUYT4 were associated with relapse, the high expression of Angiotensinogen and MIEN1 were associated with nonrelapse. Analysis of the immune microenvironment indicated that M0 macrophages, M2 macrophages, activated mast cells and resting memory CD4+ T cells were positively correlated with the risk score (p < 0.05). Conclusion: The novel immune-related risk scoring system has some advantages in predicting the prognosis and treatment response of cervical cancer patients treated with radiotherapy. Moreover, it might provide novel clues for providing targeted immune therapy to these patients.
Unidirectional gene pairs in archaea and bacteria require overlaps or very short intergenic distances for translational coupling via termination-reinitiation and often encode subunits of heteromeric complexes

Genomes of bacteria and archaea contain a much larger fraction of unidirectional (serial) gene pairs than convergent or divergent gene pairs. Many of the unidirectional gene pairs have short overlaps of −4 nt and −1 nt. As shown previously, translation of the genes in overlapping unidirectional gene pairs is tightly coupled. Two alternative models for the fate of the post-termination ribosome predict either that overlaps or very short intergenic distances are essential for translational coupling or that the undissociated post-termination ribosome can scan through long intergenic regions, up to hundreds of nucleotides. We aimed to experimentally resolve the contradiction between the two models by analyzing three native gene pairs from the model archaeon Haloferax volcanii and three native pairs from Escherichia coli. A two reporter gene system was used to quantify the reinitiation frequency, and several stop codons in the upstream gene were introduced to increase the intergenic distances. For all six gene pairs from two species, an extremely strong dependence of the reinitiation efficiency on the intergenic distance was unequivocally demonstrated, such that even short intergenic distances of about 20 nt almost completely abolished translational coupling. Bioinformatic analysis of the intergenic distances in all unidirectional gene pairs in the genomes of H. volcanii and E. coli and in 1,695 prokaryotic species representative of 49 phyla showed that intergenic distances of −4 nt or −1 nt (= short gene overlaps of 4 nt or 1 nt) were by far most common in all these groups of archaea and bacteria. A small set of genes in E. coli, but not in H. volcanii, had intergenic distances of around +10 nt. Our experimental and bioinformatic analyses clearly show that translational coupling requires short gene overlaps, whereas scanning of intergenic regions by the post-termination ribosome occurs rarely, if at all. Short overlaps are enriched among genes that encode subunits of heteromeric complexes, and co-translational complex formation requiring precise subunit stoichiometry likely confers an evolutionary advantage that drove the formation and conservation of overlapping gene pairs during evolution.
Molecular Dynamics (MD) Applications in Materials Science and Engineering and Nanotechnology

Molecular dynamics (MD) is a computer simulation technique that helps to explore the behavior and properties of molecules and atoms. MD has been used in research and development in many spaces, including materials science and engineering and nanotechnology. MD has been proven useful in topics like the nano-engineering of construction materials, correcting graphene planar defects, studying self-assembling bio-materials, and the densifi-cation, consolidation, and sintering of nanocrystalline materials
Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning

Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high‐latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground‐based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non‐linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine‐learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM‐H index characterizing geomagnetic storms multiple‐hour ahead, using public interplanetary magnetic field (IMF) data from the Sun‐Earth L1 Lagrange point and SYM‐H data. We implement a type of machine‐learning model called long short‐term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep‐learning model in the context of forecasting the SYM‐H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper‐parameters of the LSTM network and robustness tests.
“They’re not going to do all the tasks we do”: Understanding Trust and Reassurance towards a UV-C Disinfection Robot

Increasingly, robots are adopted for routine tasks such as cleaning and disinfection of public spaces, raising questions about attitudes and trust of professional cleaners who might in future have robots as teammates, and whether the general public feels reassured when disinfection is carried out by robots. In this paper, we present the results of a mixed-methods user study exploring how trust and reassurance by both professional cleaners and members of the public is affected by the use of a UV-C disinfection robot and information about its performance after disinfecting a simulated classroom. The results show a range of insights for those designing and wishing to deploy UV-C robots: we found that trust and reassurance are affected by information about the UV-C robot’s task performance, with more information coinciding with significantly more agreement to be able to judge that the robot is doing a good job. However, care should be taken when designing information about task performance to avoid misinterpretation. Overall, the results suggest a generally positive picture regarding the use of UV-C disinfecting robots and that cleaning professionals would be happy to have them as their teammates; however, there were also some concerns regarding the effect on less-skilled jobs. Taken together, our results provide considerations to make UV-C robots welcomed by cleaning teams as well as to provide reassurance to space users.
Development of the Pedestrian Awareness model for mobile robots*

Autonomous mobile robots are now being perceived as natural objects in real environments such as warehouses or restaurants. Naturally, These robots must consider the indeterminate behaviors of people, especially those unaware of their surroundings, such as those texting while walking (awareness). Although the risk of nonawareness has been studied extensively, much less work has been done on developing the pedestrian awareness model for an autonomous mobile robot. This study uses three factors: viewing angle, distance, and updating cycle to replicate the pedestrian awareness model mathematically. We collect data from five participants with high and low-workload texting tasks to identify their parameters. In this data collection, one pedestrian is walking freely in a $6-\mathrm{m}^{2}$ room with three walking experimenters. Meanwhile, they carry out a task that requires repeating a given sentence, and gazing information and head position are measured. In consequence, the distance probability of pedestrian awareness can be approximated by the sigmoid. Other parameters are estimated by the time ratio of awareness time to the overall time from the gazing information. Due to the difficulty of producing the generic parameters, we verified the proposed method using the calculated parameters of each participant. The simulation evaluation result indicates that our model leads to fewer errors than the simple social force model by comparing it with the collected walking trajectories. The result indicates that the proposed model could reproduce nonawareness pedestrians with higher accuracy, and our proposed model contributes to the mobile robot and the more realistic pedestrian simulation.
Exogenous dsRNA-Induced Silencing of the Phytophthora infestans Elicitin Genes inf1 and inf4 Suppresses Its Pathogenicity on Potato Plants

Phytophthora infestans, an Oomycete pathogen, has a devastating impact on potato agriculture, leading to the extensive use of chemical fungicides to prevent its outbreaks. Spraying double-stranded RNAs to suppress specific genes of the pathogen via the RNA interference (RNAi) pathway may provide an environmentally friendly alternative to chemicals. However, this novel approach will require various target genes and application strategies to be tested. Using the L4440 backbone, we have designed two plasmids to express dsRNA targeting inf1 and inf4 genes of P. infestans that are known to contribute to the disease development at different stages. The dsRNA produced by the bacteria was tested on potato explants and demonstrated a statistically significant reduction in lesions five days after inoculation compared to water treatment. The study results allow us to consider our approach to be promising for potato late blight control.
Balanced biogeographic and local environmental effects determine the patterns of microbial diversity in biocrusts at multi-scales

Introduction Biodiversity maintenance and its underlying mechanisms are central issues of ecology. However, predicting the composition turnovers of microbial communities at multiple spatial scales remains greatly challenging because they are obscured by the inconsistent impacts of climatic and local edaphic conditions on the assembly process. Methods Based on the Illumina MiSeq 16S/18S rRNA sequencing technology, we investigated soil bacterial and eukaryotic communities in biocrusts with different successional levels at a subcontinental scale of Northern China. Results Results showed that irrespective of spatial scale, bacterial α diversity increased but eukaryotic diversity decreased with the primary succession, whereas both β diversities decreased at the subcontinental scale compared with smaller scales, indicating that the biogeographic pattern of soil microorganisms was balanced by successional convergence and distance decay effect. We found that the convergence of bacterial and eukaryotic communities was attributed to the turnovers of generalist and specialist species, respectively. In this process, edaphic and climatic factors showed unique roles in the changes of diversity at local/subcontinental scales. Moreover, the taxonomic diversity tended to be more susceptible to climatic and edaphic conditions, while biotic factors (photosynthesis and pigments) were more important to phylogenetic diversity. Conclusion Taken together, our study provided comprehensive insights into understanding the pattern of microbial diversity at multiple spatial scales of drylands.
Theoretical Study of Doping in GaOOH for Electronics Applications

GaOOH, having a bandgap of 4.7–4.9 eV, can be regarded as one of several ultrawide-bandgap (UWBG) semiconductors, although it has so far mainly been used as a precursor material of Ga2O3. To examine the possibility of valence control and application in electronics, impurity levels in GaOOH are investigated using the first-principles density-functional theory calculation. The density values of the states of a supercell including an impurity atom are calculated. According to the results, among the group 14 elements, Si is expected to introduce a shallow donor level, i.e., a free electron is introduced. On the other hand, Ge and Sn introduce a localized state about 0.7 eV below the conduction band edge, and thus cannot act as an effective donor. While Mg and Ca can introduce a free hole and act as a shallow acceptor, Zn and Cd introduce acceptor levels away from the valence band. The transition metal elements (Fe, Co, Ni, Cu) are also considered, but none of them are expected to act as a shallow dopant. Thus, the results suggest that the carrier concentration can be controlled if Si is used for n-type doping, and Mg and Ca for p-type doping. Since GaOOH can be easily deposited using various chemical techniques at low temperatures, GaOOH will potentially be useful for transparent electronic devices.
Estimation of the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional climate model MAR

Our results indicate that in warmer climates, the mass gained due to increased winter snowfall over GrIS does not compensate the mass lost through increased meltwater run-off in summer. All the MAR projections shows similar non-linear melt increases with rising temperatures as a result of the positive surface albedo feedback, because no change is projected in the general atmospheric circulation over Greenland. Nevertheless, MAR exhibits a large range in its future projections.
New fixed point results of some enriched contractions in CAT(0) spaces

Enriched contraction, a class that contains the Picard -Banach contractions and some nonexpansive mappings, are generalized from Banach space framework into a nonlinear context, namely, geodesic metric spaces of nonpositive curvature. We establish general implications that extend the well-known results for enriched mappings formed on Banach spaces. We also look at the results for ﬁxed points involving the contractions i
Anthracycline’s Effects on Heart Rate Variability in Children with Acute Lymphoblastic Leukemia: Early Toxicity Signs—Pilot Study

Anthracycline treatments are known to cause cardiotoxic long-term side effects in cancer survivors. Recently, a decrease in heart rate variability (HRV) has been identified in these patients, signaling autonomic dysfunction and altered cardiac fitness. This study aimed at evaluating changes in HRV in children treated with anthracyclines. A total of 35 pediatric patients with acute lymphoblastic leukemia were evaluated by means of a 24 h Holter ECG, at baseline and after reaching half the total cumulative dose of doxorubicin equivalent (120 mg/m2). Parameters of HRV were assessed, as well as any arrhythmic episodes, bradycardia and tachycardia percentages. The results showed a significant decrease in both time-domain and frequency-domain HRV parameters, following anthracycline treatment. The low-frequency (LF) to high-frequency (HF) parameters’ ratio also displayed a significant difference (p = 0.035), suggestive of early cardiac autonomic dysfunction. Of note, none of the patients presented symptoms of heart disease or elevated troponins, and only two patients presented echocardiographic signs of diastolic dysfunction. The present study showed that cardiac autonomic nervous system regulation is compromised in children treated with anthracyclines even before reaching the total cumulative dose. Therefore, HRV parameters could be the first indicators of subclinical cardiac toxicity, making Holter ECG monitoring of the oncological patient a necessity.
Fast Coupled Thermoelectric and Magnetic Model to Simulate the Transient Behavior of Inductive and Resistive Superconducting Fault-Current Limiters

The nonlinear dependence of the resistance of high-temperature superconductors (HTSs) on current, temperature, and magnetic flux density is the basis of the operation of some superconducting power equipment. By modeling the resistance, to simulate in detail the transient behavior of such devices in power systems. In that regard, the finest and most accurate models employ the finite-element method (FEM). Nevertheless, the most common approach in power systems remains the lumped parameters using a classic thermal–electrical analogy. Thus far, there has not been a general method that can combine fine geometrical features of the superconducting device given by finite-element models and the flexibility and computational speed of lumped-parameter models (LPMs). A new model is proposed here to bridge both modeling philosophies and benefit from their advantages. This model, referred to as finite-element lumped-parameter model (FELPM), couples an FEM with an LPM in the same framework. The resulting FELPM is compared with two existing LPMs for the two main topologies of superconducting fault-current limiters (SFCL): resistive (RSFCL) and inductive (ISFCL). All the models are validated against experimental data from the literature when available. It is shown that the new approach yields reasonable computation times, especially in the case of inductive superconducting fault-current limiters. It is argued that such a proposal could be expanded to analyze transients of superconducting power components in more complex electrical networks.