Miracle-dz/UniFAR-FTUs huggingface dataset:
Stand structure as the proximate driver of endemic biodiversity and ecosystem functions in tropical mosaic landscapes

Transformation of forests into agricultural lands threatens biodiversity and ecosystem functions globally. In the biodiversity hotspot Madagascar, key ecosystem functions along with highly endemic flora and fauna are under threat. Comprehensive studies identifying proximate drivers are lacking, with no studies accounting for endemic species richness across multiple taxa. We assess how plot-scale stand structural attributes (basal area, leaf area index, diameter diversity, and tree species richness) and landscape-scale forest cover affect biodiversity (species richness of butterflies, ants, birds, amphibians, reptiles, herbaceous plants, and multidiversity) and ecosystem functions (soil organic carbon, predation rate, acoustic diversity index, and multifunctionality) in the tropical mosaic landscape of northeastern Madagascar. Across a prevalent land-use gradient in the region, we sampled five woody land-use types: old-growth forest, forest fragment, woody fallow, forest-derived and fallow-derived vanilla agroforests. Complexly structured stands with a larger basal area and higher tree species richness promoted greater endemic multidiversity and certain ecosystem functions. Landscape-scale forest cover significantly favored, particularly, endemic bird species richness. Our models explained 70% of the variance in endemic multidiversity, 26% in multidiversity, and 43% in multifunctionality. Significant effects directions of our predictors differed between taxa but were univocally positive for endemic species richness. Our findings highlight that a simplified stand structure, resulting from land-use change, substantially reduces endemic biodiversity and ecosystem functions in this historically forested region. Conservation actions should aim at maintaining complex stand structure in forests and agroforests, while restoration interventions should focus on re-building such structures.
The L-lactate dehydrogenases of Pseudomonas aeruginosa are conditionally regulated but both contribute to survival during macrophage infection

Pseudomonas aeruginosa is an opportunistic pathogen that thrives in environments associated with human activity, including soil and water altered by agriculture or pollution. Because L-lactate is a significant product of plant and animal metabolism, it is available to serve as a carbon source for P. aeruginosa in the diverse settings it inhabits. Here, we evaluate P. aeruginosa’s production and use of its redundant L-lactate dehydrogenases, termed LldD and LldA. We confirm that the protein LldR represses lldD and identify a new transcription factor, called LldS, that activates lldA; these distinct regulators and the genomic contexts of lldD and lldA contribute to their differential expression. We demonstrate that the lldD and lldA genes are conditionally controlled in response to lactate isomers as well as to glycolate and ◻-hydroxybutyrate, which, like lactate, are ◻-hydroxycarboxylates. We also show that lldA is induced when iron availability is low. Our examination of lldD and lldA expression across depth in biofilms indicates a complex pattern that is consistent with the effects of glycolate production, iron availability, and cross-regulation on enzyme preference. Finally, macrophage infection assays revealed that both lldD and lldA contribute to persistence within host cells, underscoring the potential role of L-lactate as a carbon source during P. aeruginosa-eukaryote interactions. Together, these findings help us understand the metabolism of a key resource that may promote P. aeruginosa’s success as a resident of contaminated environments and animal hosts. Importance Pseudomonas aeruginosa is a major cause of lung infections in people with cystic fibrosis, hospital-acquired infections, and wound infections. It consumes L-lactate, which is found at substantial levels in human blood and tissues. In this study, we investigated the spatial regulation of two redundant enzymes, called LldD and LldA, which enable L-lactate metabolism in P. aeruginosa biofilms. We uncovered mechanisms and identified compounds that control P. aeruginosa’s LldD/LldA preference. We also showed that both enzymes contribute to its ability to survive within macrophages, a behavior that is thought to augment the chronicity and recalcitrance of infections. Our findings shed light on a key metabolic strategy used by P. aeruginosa and have the potential to inform the development of therapies targeting bacterial metabolism during infection.
A frosty genetic screen unmasks a major regulatory role for SHORT VEGETATIVE PHASE of flowering in response to a cold snap

The control of flowering in plants is intricately governed by a combination of internal and environmental signals, with temperature playing a critical role. Thus, Arabidopsis thaliana plants display temperature-dependent variations in flowering time. As unexpected periods of cold temperatures can occur at any time, plants have evolved mechanisms to detect such cold snaps and to respond by delaying flowering. Plants are more tolerant to cold temperatures in the vegetative stage, while flowers are more sensitive and have reduced reproductive success due to damage to floral structures and gametes. At the molecular level, delayed flowering can be caused by repressing the FLOWERING LOCUS T (FT) gene, and several MADS box transcription factors have been shown to repress FT expression in response to cold and in this way prevent flowering. Here, we employed a forward genetic screen aimed at understanding the effect of a cold snap on the transition to flowering. We germinated a population of A. thaliana EMS M2 plants at 20°C and then gradually lowered the temperature to 10°C and selected early flowering mutants. Using whole-genome sequencing, we identified seven mutant alleles of the SHORT VEGETATIVE PHASE (SVP) gene. This finding establishes a central role for SVP in repressing flowering in response to a cold snap and provides novel alleles, several of which affect splice junctions. Our research thus presents valuable insights into the nuanced molecular mechanisms governing temperature-responsive flowering in Arabidopsis and sheds light on the dynamic interplay between SVP and environmental cues.
Augmenting Physical Tools: Bridging the Chasm of Late Adoption with Multimodal Language

Computing systems that attempt to automate safety-critical operations, such as those found in hospitals, traffic control centers, and military command posts, often do not account for the way that physical artifacts and human language constitute a medium for collaborative activity in those environments. Consequently, these approaches fail to win the favor of these naturally conservative end-users. In this paper we examine ethnographies of these three environments to understand their common characteristics and the artifacts used in them. Based on these comparisons, we argue that when automating these types of environments, designers must begin to deliver tools that: (1) support co-present collaboration, and (2) are reliable in the extreme. Otherwise, our solutions will continue to fall into the chasm that separates early and late-adopters of technology. Consequently, we propose a technique for augmenting physical artifacts by observing the use of multimodal language coincident with them . This approach blends the benefits of computation with those of physical artifacts, thereby bridging a technology chasm which separates early adopters from conservative users.
Bone-forming capacity of adult human nasal chondrocytes

Nasal chondrocytes (NC) derive from the same multipotent embryological segment that gives rise to the majority of the maxillofacial bone and have been reported to differentiate into osteoblast‐like cells in vitro. In this study, we assessed the capacity of adult human NC, appropriately primed towards hypertrophic or osteoblastic differentiation, to form bone tissue in vivo. Hypertrophic induction of NC‐based micromass pellets formed mineralized cartilaginous tissues rich in type X collagen, but upon implantation into subcutaneous pockets of nude mice remained avascular and reverted to stable hyaline‐cartilage. In the same ectopic environment, NC embedded into ceramic scaffolds and primed with osteogenic medium only sporadically formed intramembranous bone tissue. A clonal study could not demonstrate that the low bone formation efficiency was related to a possibly small proportion of cells competent to become fully functional osteoblasts. We next tested whether the cues present in an orthotopic environment could induce a more efficient direct osteoblastic transformation of NC. Using a nude rat calvarial defect model, we demonstrated that (i) NC directly participated in frank bone formation and (ii) the efficiency of survival and bone formation by NC was significantly higher than that of reference osteogenic cells, namely bone marrow‐derived mesenchymal stromal cells. This study provides a proof‐of‐principle that NC have the plasticity to convert into bone cells and thereby represent an easily available cell source to be further investigated for craniofacial bone regeneration.
Snapshots of Pseudomonas aeruginosa SOS response activation complex reveal structural prerequisites for LexA engagement and cleavage

Antimicrobial resistance represents a major threat to human health and Pseudomonas aeruginosa stands out among the pathogens responsible for this emergency. The SOS response to DNA damage plays a pivotal role in bacterial evolution, driving the development of resistance mechanisms and influencing the adaptability of bacterial populations to challenging environments, particularly in the context of antibiotic exposure. Recombinase A (RecA) and the transcriptional repressor LexA are the key players that orchestrate this process, determining either the silencing or the active transcription of the genes under their control. By integrating state-of-the-art structural approaches with binding and functional assays in vitro, we elucidated the molecular events governing the SOS response activation in P. aeruginosa, focusing on the RecA-LexA interaction. Our findings identify the conserved determinants and strength of the interactions that let RecA trigger the autocleavage and inactivation of the LexA repressor. These results provide the groundwork for designing novel antimicrobial strategies and for exploring the potential translation of Escherichia coli-derived approaches, to address the health-threatening implications of bacterial infections. Graphical Abstract
Interactions between Pseudomonas aeruginosa and six opportunistic pathogens cover a broad spectrum from mutualism to antagonism

Bacterial infections often involve more than one pathogen. While it is known that polymicrobial infections can impact disease outcomes, we have a poor understanding about how pathogens affect each other’s behaviour and fitness. Here, we used a microscopy approach to explore interactions between Pseudomonas aeruginosa and six opportunistic human pathogens that often co-occur in polymicrobial infections: Acinetobacter baumannii, Burkholderia cenocepacia, Escherichia coli, Enterococcus faecium, Klebsiella pneumoniae, and Staphylococcus aureus. When following growing micro-colonies on agarose pads over time, we observed a broad spectrum of species-specific ecological interactions, ranging from mutualism to antagonism. For example, P. aeruginosa engaged in a mutually beneficial interaction with E. faecium but suffered from antagonism by E. coli and K. pneumoniae. While we found little evidence for active directional growth towards or away from cohabitants, we observed that certain species increased growth in double layers in co-cultures and that physical forces due to fast colony expansion had a major impact on fitness and interaction patterns. Overall, our work provides an atlas of pathogen interactions, potentially useful to understand species dynamics in polymicrobial infections. We discuss possible mechanisms driving pathogen interactions and offer predictions of how the different ecological interactions could affect virulence.
Caching Techniques for Streaming Multimedia over the Internet

—Existing solutions for streaming multimedia in the Internet do not scale in terms of object size and number of supported streams. Using separate unicast streams, for example, will overload both network and servers. While caching is the standard technique for improving scalability, existing caching schemes do not support streaming media well. In this paper, we propose a complete solution for caching multimedia streams in the Internet by extending existing techniques and proposing new techniques to support streaming media. These include segmentation of streaming objects, dynamic caching, and self-organizing cooperative caching. We consider these techniques in an integrated fashion. We implemented a complete caching architecture called SOCCER using the network simulator ns-2 and evaluate the effectiveness of each proposed technique and compare them to alternative caching solutions.
Cryptanalysis and Improvement of a Remote User Authentication Scheme

Smart card based remote user authentication is receiving more and more attention than ever with the popularization of computer network. Recently, Yoon et al. proposed a remote user authentication scheme using smart cards based on Hwang et al.’s. Its security depends on the one-way hash function. They claim that the scheme provides mutual authentication between the user and the remote system and can avoid the security problems of Hwang et al.’s. Nevertheless, in this paper we give a cryptanalysis of Yoon et al.’s scheme and point out that there exist several security flaws in their scheme. The scheme is also vulnerable and insecure. Then we propose an improved one which can avoid such flaws in Yoon et al’s scheme.
Generalize for Future: Slow and Fast Trajectory Learning for CTR Prediction

Deep neural networks (DNNs) have achieved significant advancements in click-through rate (CTR) prediction by demonstrating strong generalization on training data. However, in real-world scenarios, the assumption of independent and identically distributed (i.i.d.) conditions, which is fundamental to this problem, is often violated due to temporal distribution shifts. This violation can lead to suboptimal model performance when optimizing empirical risk without access to future data, resulting in overfitting on the training data and convergence to a single sharp minimum. To address this challenge, we propose a novel model updating framework called Slow and Fast Trajectory Learning (SFTL) network. SFTL aims to mitigate the discrepancy between past and future domains while quickly adapting to recent changes in small temporal drifts. This mechanism entails two interactions among three complementary learners: (i) the Working Learner, which updates model parameters using modern optimizers (e.g., Adam, Adagrad) and serves as the primary learner in the recommendation system, (ii) the Slow Learner, which is updated in each temporal domain by directly assigning the model weights of the working learner, and (iii) the Fast Learner, which is updated in each iteration by assigning exponentially moving average weights of the working learner. Additionally, we propose a novel rank-based trajectory loss to facilitate interaction between the working learner and trajectory learner, aiming to adapt to temporal drift and enhance performance in the current domain compared to the past. We provide theoretical understanding and conduct extensive experiments on real-world CTR prediction datasets to validate the effectiveness and efficiency of SFTL in terms of both convergence speed and model performance. The results demonstrate the superiority of SFTL over existing approaches.
Adverse respiratory effect of acute β-blocker exposure in asthma: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND β-Blockers are avoided in asthma over concerns regarding acute bronchoconstriction. Risk is greatest following acute exposure, including the potential for antagonism of β2-agonist rescue therapy. METHODS A systematic review of databases was performed to identify all randomized, blinded, placebo-controlled clinical trials evaluating acute β-blocker exposure in asthma. Effect estimates for changes in respiratory function, symptoms, and β2-agonist response were pooled using random effects meta-analysis with heterogeneity investigated. RESULTS Acute selective β-blockers in the doses given caused a mean change in FEV1 of −6.9% (95% CI, −8.5 to −5.2), a fall in FEV1 of ≥20% in one in eight patients (P=.03), symptoms affecting one in 33 patients (P=.18), and attenuation of concomitant β2-agonist response of −10.2% (95% CI, −14.0 to −6.4). Corresponding values for acute nonselective β-blockers in the doses given were −10.2% (95% CI, −14.7 to −5.6), one in nine patients (P=.02), one in 13 patients (P=.14), and −20.0% (95% CI, −29.4 to −10.7). Following investigation of heterogeneity, clear differences were found for celiprolol and labetalol. A dose-response relationship was demonstrated for selective β-blockers. CONCLUSIONS Selective β-blockers are better tolerated but not completely risk-free. Risk from acute exposure may be mitigated using the smallest dose possible and β-blockers with greater β1-selectivity. β-Blocker-induced bronchospasm responded partially to β2-agonists in the doses given with response blunted more by nonselective β-blockers than selective β-blockers. Use of β-blockers in asthma could possibly be based upon a risk assessment on an individual patient basis.
Conformal Crystal Graph Transformer with Robust Encoding of Periodic Invariance

Machine learning techniques, especially in the realm of materials design, hold immense promise in predicting the properties of crystal materials and aiding in the discovery of novel crystals with desirable traits. However, crystals possess unique geometric constraints—namely, E(3) invariance for primitive cell and periodic invariance—which need to be accurately reflected in crystal representations. Though past research has explored various construction techniques to preserve periodic invariance in crystal representations, their robustness remains inadequate. Furthermore, effectively capturing angular information within 3D crystal structures continues to pose a significant challenge for graph-based approaches. This study introduces novel solutions to these challenges. We first present a graph construction method that robustly encodes periodic invariance and a strategy to capture angular information in neural networks without compromising efficiency. We further introduce CrystalFormer, a pioneering graph transformer architecture that emphasizes angle preservation and enhances long-range information. Through comprehensive evaluation, we verify our model's superior performance in 5 crystal prediction tasks, reaffirming the efficiency of our proposed methods.
Comparison of Behaviour in Different Liquids and in Cells of Gold Nanorods and Spherical Nanoparticles Modified by Linear Polyethyleneimine and Bovine Serum Albumin

Gold nanorods (GNRs) are considered one of the most promising forms of nanoparticles for nanobiotechnology; however, the problem of their toxicity is currently not resolved. We synthesised GNRs, modified with linear polyethyleneimine (PEI-GNRs), and examined their physicochemical and some biological properties in comparison with GNRs modified with BSA and spherical gold nanoparticles (sGNPs) modified with the same agents. The influence of the buffer, cell culture media, and serum on hydrodynamic diameter and zeta potential of all GNPs was studied. Simultaneously, the size, shape, and formation of a corona were examined by transmission electron microscopy (TEM). PEI-GNRs and GNPs were nontoxic for BHK-21 and HeLa cells (MTT test). Penetration of all GNPs into BHK-21, melanoma B16, and HeLa cells was examined after 30 min, 3 h, and 24 h of incubation using TEM ultrathin sections. PEI-GNRs and PEI-sGNPs demonstrated fast and active penetration into cells by caveolin-dependent and lipid raft-mediated endocytosis and accumulated in endosomes and lysosomes. BSA-modified GNPs showed prolonged flotation and a significant delay in cell penetration. The results show that the charge of initial NPs determines penetration into cells. Thus, the designed PEI-GNRs were nontoxic and stable in cell culture media and could efficiently penetrate cells.
Post-Military Areas in the Czech Republic and theirRevitalization - Examples of the Towns of Hodonín and UherskéHradiště

One of the basic transforming processes of the period after 1989 is the process of demilitarization. Among other things, one of its consequences is the emergence of abandoned military buildings and areas – so-called military brownfields. This kind of brownfield has a large number of specifics, to which subsequent revitalization necessarily must be adapted. As a large portion of these areas is situated within municipalities or is directly adjacent, it is essential that the revitalization of these sites must be approached with great sensitivity. Two examples of an approach to the revitalization of former barracks sites located within cities are shown in this article.
Exploring Temporal Feature Correlation for Efficient and Stable Video Semantic Segmentation

This paper tackles the problem of efficient and stable video semantic segmentation. While stability has been under-explored, prevalent work in efficient video semantic segmentation uses the keyframe paradigm. They efficiently process videos by only recomputing the low-level features and reusing high-level features computed at selected keyframes. In addition, the reused features stabilize the predictions across frames, thereby improving video consistency. However, dynamic scenes in the video can easily lead to misalignments between reused and recomputed features, which hampers performance. Moreover, relying on feature reuse to improve prediction consistency is brittle; an erroneous alignment of the features can easily lead to unstable predictions. Therefore, the keyframe paradigm exhibits a dilemma between stability and performance. We address this efficiency and stability challenge using a novel yet simple Temporal Feature Correlation (TFC) module. It uses the cosine similarity between two frames’ low-level features to inform the semantic label’s consistency across frames. Specifically, we selectively reuse label-consistent features across frames through linear interpolation and update others through sparse multi-scale deformable attention. As a result, we no longer directly reuse features to improve stability and thus effectively solve feature misalignment. This work provides a significant step towards efficient and stable video semantic segmentation. On the VSPW dataset, our method significantly improves the prediction consistency of image-based methods while being as fast and accurate.
Computationally predicted IgE epitopes of walnut allergens contribute to cross‐reactivity with peanuts

To cite this article: Maleki SJ, Teuber SS, Cheng H, Chen D, Comstock SS, Ruan S, Schein CH. Computationally predicted IgE epitopes of walnut allergens contribute to cross‐reactivity with peanuts. Allergy 2011; 66: 1522–1529.