Miracle-dz/UniFAR-FTUs huggingface dataset:
Kmer-Node2Vec: a Fast and Efficient Method for Kmer Embedding from the Kmer Co-occurrence Graph, with Applications to DNA Sequences

Learning low-dimensional continuous vector representation for short k-mers divided from long DNA sequences is key to DNA sequence modeling that can be utilized in many bioinformatics investigations, such as DNA sequence classification and retrieval. DNA2Vec is the most widely used method for DNA sequence embedding. However, it poorly scales to large data sets due to its extremely long training time in kmer embedding. In this paper, we propose a novel efficient graph-based kmer embedding method, named Kmer-Node2Vec, to tackle this concern. Our method converts the large DNA corpus into one kmer co-occurrence graph and extracts kmer relation on the graph by random walks to learn fast and high-quality kmer embedding. Extensive experiments show that our method is faster than DNA2Vec by 29 times for training on a 4GB data set, and on par with DNA2Vec in terms of task-specific accuracy of sequence retrieval and classification.
Omega 3 fish oil suppress radiation induced hepato and renal toxicity in mice through modulation in Wnt canonical pathway combined with NHEJ and Intrinsic Apoptotic pathway

Radiation is associated with inflammation and oxidative stress, the latter of which contributes to activation of DNA damage and apoptosis. Omega 3 polyunsaturated fatty acids (PUFAs) have been reported to limit oxidative stress and DNA damage. The aim of this study was to evaluate the effect of the Omega 3 PUFA on antioxidant defence in male physiology on mice model. Liver and kidney tissues were obtained from whole body irradiated mice divided under 9 groups (Weight-10mg, 6-8 months old, n=5) and age-matched male controls (6-8 months old, n=5). 6 groups have been orally intubated with (50, 100 and 150) mg/kg BW with Omega 3 fish oil 1hr prior to the radiation exposure. Liver and kidney were surgically obtained after 24 hours and 30 days of radiation exposure. Omega 3 fish oil supplementation increased the level of mRNA expression of Lef1, Axin2, Survivin, Ku70, SOD1, SOD2, Cat, iNOS and decresed the level of Bax and Bcl2 in irradiated with omega 3 fish oil supplementation compare to irradiated alone. Omega 3 fish oil increased SOD scavenging, Catalase, Nitric oxide scavenging activity, Total antioxidant capacity and decrease the lipid peroxidation. The improvements in mRNA level of candidate genes of Wnt canonical pathway, NHEJ pathway, oxidative stress status serve as a stimulus for further investigation of Omega 3 fish oil as supplementation for patients undergo radiation therapy.
Host-specific subtelomere: structural variation and horizontal transfer in asexual filamentous fungal pathogens

Several asexual filamentous fungal pathogens contain supernumerary chromosomes carrying secondary metabolite (SM) or pathogenicity genes as well as transposons. Supernumerary chromosomes have been shown in in vitro experiments to transfer from pathogenic isolates to non-pathogenic ones and between isolates whose fusion can result in vegetative or heterokaryon incompatibility (HET). However, much is still unknown about the extent of horizontal transfer of supernumerary chromosomes within and between asexual pathogenic populations in adaptation to their hosts. We investigated several asexual fungal pathogens for genomic elements involved in maintaining telomeres for supernumerary and core chromosomes during vegetative reproduction. We found that in vegetative populations or lineages with a nearly complete telomere-to-telomere genome assembly (e.g. Fusarium equiseti and five formae speciales of the F. oxysporum species complex), core and supernumerary chromosomes were flanked by highly similar subtelomeric sequences on the 3’ side and by their reverse complements on the 5’ side. This subtelomere sequence structure was specific to the host. We detected instances of recent horizontal transfer of regions of a supernumerary chromosome between distant populations in the F. oxysporum species complex, and we also found field isolates with two structurally different copies of a supernumerary chromosome in a young asexual population, raising the possibility that those copies originated from different lineages by intrastrain anastomosis. A large number of HET domain genes were located in SM/pathogenicity gene clusters, with a potential role in marking these gene clusters during vegetative reproduction. The emergence of novel asexual pathogenic populations by horizontal transfer of transposon-rich supernumerary chromosomes within and between populations poses challenges to the control and management of these pathogens.
Long-term unsupervised recalibration of cursor BCIs

Intracortical brain-computer interfaces (iBCIs) require frequent recalibration to maintain robust performance due to changes in neural activity that accumulate over time. Compensating for this nonstationarity would enable consistently high performance without the need for supervised recalibration periods, where users cannot engage in free use of their device. Here we introduce a hidden Markov model (HMM) to infer what targets users are moving toward during iBCI use. We then retrain the system using these inferred targets, enabling unsupervised adaptation to changing neural activity. Our approach outperforms the state of the art in large-scale, closed-loop simulations over two months and in closed-loop with a human iBCI user over one month. Leveraging an offline dataset spanning five years of iBCI recordings, we further show how recently proposed data distribution-matching approaches to recalibration fail over long time scales; only target-inference methods appear capable of enabling long-term unsupervised recalibration. Our results demonstrate how task structure can be used to bootstrap a noisy decoder into a highly-performant one, thereby overcoming one of the major barriers to clinically translating BCIs.
Early detection of white matter hyperintensities using SHIVA‐WMH detector

White matter hyperintensities (WMH) are well-established markers of cerebral small vessel disease (cSVD), and are associated with an increased risk of stroke, dementia, and mortality. Although their prevalence increases with age, small and punctate WMHs have been reported with surprisingly high frequency even in young, neurologically asymptomatic adults. However, most automated methods to segment WMH published to date are not optimized for detecting small and sparse WMH. Here we present the SHIVA-WMH tool, a deep-learning (DL)-based automatic WMH segmentation tool that has been trained with manual segmentations of WMH in a wide range of WMH severity. We show that it is able to detect WMH with high efficiency in subjects with only small punctate WMH as well as in subjects with large WMHs (i.e. with confluency) in evaluation datasets from three distinct databases: MRi-Share consisting of young university students, MICCAI 2017 WMH challenge dataset consisting of older patients from memory clinics, and UK Biobank with community-dwelling middle-aged and older adults. Across these three cohorts with a wide-ranging WMH load, our tool achieved voxel-level and individual lesion cluster-level Dice scores of 0.66 and 0.71, respectively, which were higher than for three reference tools tested: the lesion prediction algorithm implemented in the lesion segmentation toolbox (LST-LPA: Schmidt, 2017), PGS tool, a DL-based algorithm and the current winner of the MICCAI 2017 WMH challenge (Park et al, 2021), and HyperMapper tool (HPM: Mojiri Forooshani et al., 2022), another DL-based method with high reported performance in subjects with mild WMH burden. Our tool is publicly and openly available to the research community to facilitate investigations of WMH across a wide range of severity in other cohorts, and to contribute to our understanding of the emergence and progression of WMH. Highlights We propose a novel 3D Unet-based model, SHIVA-WMH detector, with much improved detection of small WMH across subjects with a wide range of WMH burden compared to existing methods We characterize microstructural properties of small white matter hyperintensities in young adults from MRi-Share study
Protein Sequence Design by Entropy-based Iterative Refinement

Inverse Protein Folding (IPF) is an important task of protein design, which aims to design sequences compatible with a given backbone structure. Despite the prosperous development of algorithms for this task, existing methods tend to leverage limited and noisy residue environment when generating sequences. In this paper, we develop an iterative sequence refinement pipeline, which can refine the sequence generated by existing sequence design models. It selects and retains reliable predictions based on the model’s confidence in predicted distributions, and decodes the residue type based on a partially visible environment. The proposed scheme can consistently improve the performance of a number of IPF models on several sequence design benchmarks, and increase sequence recovery of the SOTA model by up to 10%. We finally show that the proposed model can be applied to redesign Transposon-associated transposase B. 8 variants exhibit improved gene editing activity among the 20 variants we proposed. Our code and a demo of the refinement pipeline are provided in the online colab.
CLLE: A Benchmark for Continual Language Learning Evaluation in Multilingual Machine Translation

Continual Language Learning (CLL) in multilingual translation is inevitable when new languages are required to be translated. Due to the lack of unified and generalized benchmarks, the evaluation of existing methods is greatly influenced by experimental design which usually has a big gap from the industrial demands. In this work, we propose the first Continual Language Learning Evaluation benchmark CLLE in multilingual translation. CLLE consists of a Chinese-centric corpus — CN-25 and two CLL tasks — the close-distance language continual learning task and the language family continual learning task designed for real and disparate demands. Different from existing translation benchmarks, CLLE considers several restrictions for CLL, including domain distribution alignment, content overlap, language diversity, and the balance of corpus. Furthermore, we propose a novel framework COMETA based on Constrained Optimization and META-learning to alleviate catastrophic forgetting and dependency on historical training data by using a meta-model to retain the important parameters for old languages. Our experiments prove that CLLE is a challenging CLL benchmark and that our proposed method is effective when compared with other strong baselines. Due to the construction of corpus, the task designing and the evaluation method are independent of the central language, we also construct and release the English-centric corpus EN-25 to facilitate academic research1.
The Signal Importance of Noise

Noise is widely regarded as a residual category—the unexplained variance in a linear model or the random disturbance of a predictable pattern. Accordingly, formal models often impose the simplifying assumption that the world is noise-free and social dynamics are deterministic. Where noise is assigned causal importance, it is often assumed to be a source of inefficiency, unpredictability, or heterogeneity. We review recent sociological studies that are noteworthy for demonstrating the theoretical importance of noise for understanding the dynamics of a complex system. Contrary to widely held assumptions, these studies identify conditions in which noise can increase efficiency and predictability and reduce diversity. We conclude with a methodological warning that deterministic assumptions are not an innocent simplification.
Dependence of crystal structure and work function of WNx films on the nitrogen content

The effect of nitrogen content on crystal structure (phase and grain size) and work function (Φm) of WNx films is investigated. The Φm of WNx films is extracted from the plot of flatband voltage versus SiO2 thickness. For W and WN0.4 films, the Φm are 4.67 and 4.39V, and their crystal phases are both body-centered-cubic W. For WN0.6 film, it contains W+W2N mixed phases and the Φm is 4.50V. On the other hand, the Φm of WN0.8 and WN1.5 films are 5.01 and 4.49V, and their crystal phases are both face-centered-cubic W2N. The grain size of W and W2N phases decreases with the increase of the nitrogen content in WNx. It is concluded that the Φm is affected by the crystal phase as well as the grain size of WNx film.
Mastery Learning and Productive Failure: Examining Constructivist Approaches to teach CS1

The struggles of novices taking introductory computer science courses to master basic constructs and develop an understanding of the notional machine continues to drive computer science education in the search of new pedagogical approaches. This work examines in depth two recent proposals: mastery learning and productive failure. Both approaches are grounded by constructivism, which should reduce the challenges that CS1 students face when learning to code. By exploring the concepts that drive these pedagogical approaches, this study aims to make constructivism more accessible to CS0/CS1 teachers. The two approaches illustrate and highlight key concepts that support constructive learning. The main outcomes from this work are the concept maps generated for each pedagogical approach, along with descriptive tables of their concepts. Both approaches support constructive learning by utilising (1) adaptive instruction that aligns with the current constructed knowledge of students, and (2) the use of student’s failure as key to identify knowledge gaps and improve learning.
ER-Test: Evaluating Explanation Regularization Methods for Language Models

By explaining how humans would solve a given task, human rationales can provide strong learning signal for neural language models (LMs). Explanation regularization (ER) aims to improve LM generalization by pushing the LM's machine rationales (Which input tokens did the LM focus on? ) to align with human rationales (Which input tokens would humans focus on? ). Though prior works primarily study ER via in-distribution (ID) evaluation, out-of-distribution (OOD) generalization is often more critical in real-world scenarios, yet ER's effect on OOD generalization has been underexplored. In this paper, we introduce ER-Test, a framework for evaluating ER models' OOD generalization along three dimensions: unseen dataset tests, contrast set tests, and functional tests. Using ER-Test, we extensively analyze how ER models' OOD generalization varies with different ER design choices. Across two tasks and six datasets, ER-Test shows that ER has little impact on ID performance but can yield large OOD performance gains. Also, we find that ER can improve OOD performance even with limited rationale supervision. ER-Test's results help demonstrate ER's utility and establish best practices for using ER effectively.
HeLo: Learning-Free Lookahead Decoding for Conversation Infilling

We propose Heuristic Guided Lookahead De-coding (HeLo), a novel decoding strategy for conversation infilling. Conversation infilling aims to generate a seamless bridge of utterances connecting a given pair of source and target utterances. HeLo does not require fine-tuning or extra models – only the generating model itself. Instead, HeLo leverages a greedy lookahead phase before committing to any token. The HeLo framework is simple and can augment conventional decoding strategies paired with any autoregressive language model. Smooth transitions between utterances are encouraged with an annealing schedule. Our experiments show HeLo outperforms several baselines when evaluated with both automatic and human evaluation metrics, which, we argue, are appropriate for the task. 1
Influence of late pruning practice on two red skin grapevine cultivars in a semi-desert climate

Continually increasing global temperature could severely affect grape berry metabolite accumulation and ultimately wine polyphenol concentration and color intensity. To explore the effect of late shoot pruning on grape berry and wine metabolite composition, field trials were carried out on Vitis vinifera cv. Malbec and cv. Syrah grafted on 110 Richter rootstock. Fifty-one metabolites were detected and unequivocally annotated employing UPLC-MS based metabolite profiling. Integrating the data using hierarchical clustering showed a significant effect of late pruning treatments on must and wine metabolites. Syrah metabolite profiles were characterized by a general trend of higher metabolite content in the late shoot pruning treatments, while Malbec profiles did not show a consistent trend. In summary, late shoot pruning exerts a significant effect, though varietal specific, on must and wine quality-related metabolites, possibly related to enhanced photosynthetic efficiency, which should be taken into consideration when planning mitigating strategies in warm climates.
Suppression of top-down influence decreases both behavioral and V1 neuronal response sensitivity to stimulus orientations in cats

How top-down influence affects behavioral detection of visual signals and neuronal response sensitivity in the primary visual cortex (V1) remains poorly understood. This study examined both behavioral performance in stimulus orientation identification and neuronal response sensitivity to stimulus orientations in the V1 of cat before and after top-down influence of area 7 (A7) was modulated by non-invasive transcranial direct current stimulation (tDCS). Our results showed that cathode (c) but not sham (s) tDCS in A7 significantly increased the behavioral threshold in identifying stimulus orientation difference, which effect recovered after the tDCS effect vanished. Consistently, c-tDCS but not s-tDCS in A7 significantly decreased the response selectivity bias of V1 neurons for stimulus orientations, which effect could recover after withdrawal of the tDCS effect. Further analysis showed that c-tDCS induced reduction of V1 neurons in response selectivity was not resulted from alterations of neuronal preferred orientation, nor of spontaneous activity. Instead, c-tDCS in A7 significantly lowered the visually-evoked response, especially the maximum response of V1 neurons, which caused a decrease in response selectivity and signal-to-noise ratio. By contrast, s-tDCS exerted no significant effect on the responses of V1 neurons. These results indicate that top-down influence of A7 may enhance behavioral identification of stimulus orientations by increasing neuronal visually-evoked response and response selectivity in the V1.
Electric Field Poling of Lithium Niobate Crystals after Proton-Exchanged Channel Waveguide Fabrication

An electric field poling and domain evolution in congruent lithium niobate wafers with α phase proton exchanged channel waveguides were studied experimentally. A piezoresponse force microscopy and the study of an etching rate showed a presence of a spontaneous polarization in the waveguide region and an ability to create tailored domain structures inside the proton exchanged channel waveguides. It was shown by the in situ visualization of the domain evolution that the proton exchanged channel waveguide acted as a region with an increased value of a threshold field for domain growth.
Associations between maternal dietary scores during early pregnancy with placental outcomes

Background and aims Individual macronutrient and micronutrient effects on placental growth have been widely investigated. However, the influence of overall maternal diet is relatively unknown. Therefore, the aim of this study is to examine associations between a range of maternal dietary scores during early pregnancy with placental outcomes, and to investigate whether there is evidence of sexual dimorphism. Methods This analysis of the Lifeways Cross-Generational Cohort includes 276 mother–child pairs. A validated 148-item semi-quantitative food frequency questionnaire assessed maternal diet in early pregnancy. Dietary scores reflecting dietary quality [Healthy Eating Index (HEI-2015), Dietary Approaches to Stop Hypertension (DASH)], dietary inflammatory potential [Dietary Inflammatory Index (DII) and the energy adjusted DII (E-DII)], dietary antioxidant status [Dietary Antioxidant Quality (DAQ)], and glycemic and insulinemic loads/indices (GL/GI, IL/II) were calculated. Linear regression analyses assessed maternal dietary score relationships with untrimmed placental weight (PW) and birth weight:placental weight (BW:PW) ratio. Results In fully adjusted models, maternal E-DII and GI were positively associated, and HEI-2015 and DAQ were negatively associated with PW (B: 12.31, 95% CI: 0.41, 24.20, p = 0.04, B: 4.13, 95% CI: 0.10, 8.17, p = 0.04, B: −2.70, 95% CI: −5.03, −0.35, p = 0.02 and B: −15.03, 95% CI: −28.08, −1.98, p = 0.02, for E-DII, GI, HEI-2015 and DAQ respectively). Maternal DAQ associations with BW:PW ratio were attenuated. When stratified by sex, maternal GI and pregnancy-specific DAQ were associated with PW in female offspring (B: 5.61, 95% CI: 0.27, 10.96, p = 0.04 and B: −15.31, 95% CI: −30.35, −0.27, p = 0.046). Maternal E-DII and HEI-2015 were associated with PW in males (B: 24.31, 95% CI: 5.66, 42.96, p = 0.01 and B: −3.85, 95% CI: −7.47, −0.35, p = 0.03 respectively). Conclusion The results of this novel investigation suggest that maternal diet may influence placental development. Female fetuses may be more sensitive to increased glucose levels whereas male fetuses may be more susceptible to in-utero stresses that are regulated by inflammatory pathways and overall diet quality. Hence, early pregnancy offers an opportune time for a mother to prioritize dietary changes that focus on reducing inflammatory and glycemic responses.
Ichthyoplankton and plastic waste drift in a river in the Amazon Basin, Brazil

Egg and larvae drift is a key mechanism for early fish stages to colonize nursery and growth areas and provides insights into ichthyofauna spawning times and spawning locations—crucial information for understanding fish biology. In the Tapajós River, Amazon Basin, no study has investigated the drift of ichthyoplankton along the hydrological phases nor the occurrence and dispersion of plastic waste associated with plankton. Thus, we aimed to present an overview of the spatio-temporal drift of ichthyoplankton and plastic waste in this river. Temporal sampling was carried out along a spatial gradient of approximately 300 km, covering different sectors of the river. Ichthyoplankton and plastic waste were captured through horizontal trawls on the subsurface of the water column for 10 min. Fish larvae belonging to 10 taxonomic orders and with an average size of 4.98 mm ± 3.14 mm were captured. Clupeiformes larvae occurred in all hydrological phases and reproductive peaks for other orders were recorded. Plastic waste was classified into 20 types according to color and shape and an average size of 1.55 mm ± 1.27 mm. Green fragments and blue filaments were the most abundant. We found the highest density of fish eggs and larvae drifting during the drought phase in stretches with greater environmental structure, whereas plastics were more abundant during the receding water phase in more turbulent stretches that have impacts from illegal mining. Simultaneous drift of ichthyoplankton and plastic waste was recorded in all hydrological phases and sampled sectors. This is worrying because, although we did not analyze the ingestion of plastics by fish larvae, plastic waste can enter the nursery areas of the Tapajós River and reduce the function of these areas for fish. Here we discover through the high densities of fish eggs and larvae deriving that the Tapajós River is an important reproduction site for ichthyofauna and that the presence of different landscape configurations prove to be a key factor in the dispersion, retention and development of ichthyoplankton and plastic waste.