Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential biodiversity responses between kingdoms (plants, fungi, bacteria and metazoa) along an Alpine succession gradient

Biological diversities of multiple kingdoms potentially respond in similar ways to environmental changes. However, studies either compare details of microbial diversity across general vegetation or land use classes or relate details of plant community diversity with the extent of microbially governed soil processes, via physiological profiling. Here, we test the hypothesis of shared responses of plant and rhizosphere bacterial, fungal and metazoan biodiversities (especially across‐habitat β‐diversity patterns) along a disturbance gradient encompassing grazed to abandoned Alpine pasture, on acid soil in the European Central Alps. Rhizosphere biological diversity was inferred from eDNA fractions specific to bacteria, fungi and metazoans from contrasting plant habitats indicative of different disturbance levels. We found that soil β‐diversity patterns were weakly correlated with plant diversity measures and similarly ordinated along an evident edaphic (pH, C:N, assimilable P) and disturbance gradient but, contrary to our hypothesis, did not demonstrate the same diversity patterns. While plant communities were well separated along the disturbance gradient, correlating with fungal diversity, the majority of bacterial taxa were shared between disturbance levels (75% of bacteria were ubiquitous, cf. 29% plant species). Metazoa exhibited an intermediate response, with communities at the lowest levels of disturbance partially overlapping. Thus, plant and soil biological diversities were only loosely dependent and did not exhibit strictly linked environmental responses. This probably reflects the different spatial scales of organisms (and their habitats) and capacity to invest resources in persistent multicellular tissues, suggesting that vegetation responses to environmental change are unreliable indicators of below‐ground biodiversity responses.
"Should I Worry?" A Cross-Cultural Examination of Account Security Incident Response

Digital security technology is able to identify and prevent many threats to users accounts. However, some threats remain that, to provide reliable security, require human intervention: e.g., through users paying attention to warning messages or completing secondary authentication procedures. While prior work has broadly explored people's mental models of digital security threats, we know little about users' precise, in-the-moment response process to in-the-wild threats. In this work, we conduct a series of qualitative interviews (n=67) with users who had recently experienced suspicious login incidents on their real Facebook accounts in order to explore this process of account security incident response. We find a common process across participants from five countries -- with differing online and offline cultures -- allowing us to identify areas for future technical development to best support user security. We provide additional insights on the unique nature of incident-response information seeking, known attacker threat models, and lessons learned from a large, cross-cultural qualitative study of digital security.
XML Skeleton Definitions for Human Posture Assessments

In this paper, we show how the XML dialect SKAML (Skeletal Assessment Markup Language) can be used to use data from one or more Motion Capture systems to perform human posture assessments with multiple assessment methods. We show an implementation example using an inertial measuring suit and both OWAS and REBA assessment methods. SKAML makes it possible to implement classifiers for a Motion Capture system once and adapt the classifier by-configuration to various ergonomics assessment methods. We anticipate our work as help for researchers and developers that implement new assessment methods or motion capture systems.
Measurement Invariance of the Student Risk Screening Scale Across Time and Gender

Universal screening for behavioral/mental health risk is a critical component of multitiered systems of support, allowing for early identification of students in need of prevention and/or intervention services. The Student Risk Screening Scale (SRSS; Drummond, 1994) is one commonly used universal screening tool intended to measure externalizing behavior difficulties. Although the reliability and criterion-related validity of the SRSS has been studied extensively, there are limited data supporting its construct validity. To this end, the current study investigated the internal structure of the SRSS and the degree to which it demonstrated measurement invariance across time (i.e., fall, winter, spring) and gender (i.e., male, female). Fifty-five teachers completed the SRSS for 1,220 students in kindergarten through 5th grade across three elementary schools during fall, winter, and spring benchmarking periods. Results of a confirmatory factor analysis provided support for the SRSS as a single-factor measure of externalizing behavior difficulties. Results of multigroup confirmatory factor analyses supported its measurement invariance across time and gender. These findings further establish the psychometric defensibility of the SRSS as used within multitiered systems of support. Implications, limitations, and future directions are discussed for practitioners and researchers.
Effects of adaptation time and inclusion level of sugar beet pulp on nutrient digestibility and evaluation of ileal amino acid digestibility in pigs

Objective Two experiments were conducted to determine the effects of adaptation time and inclusion level of sugar beet pulp (SBP) on nutrient digestibility and to evaluate the ileal amino acid digestibility of SBP fed to pigs. Methods In Exp. 1, thirty-six crossbred barrows (85.0±2.1 kg) were allotted to 6 diets in a completely randomized design with six replicates per diet. Diets included a corn-soybean meal diet and 5 test diets containing 14.6%, 24.4%, 34.2%, 43.9%, or 53.7% SBP, respectively. The adaptation time consisted 7, 14, 21, or 28 d consecutively for each pig followed by 5 d for fecal collection. Feces were collected from d 8 to 13, d 15 to 20, d 22 to 27, and d 29 to 34, respectively. In Exp. 2, six pigs (35.1±1.7 kg) with T-cannulas at the terminal ileum were fed to 3 diets in a replicated 3×3 Latin square design with 3 periods and 2 replicate pigs per diet. Each period consisted 5 d for diet adaptation followed by 2 d for digesta collection. Results The digestible energy (DE) value and the apparent total tract digestibility (ATTD) of gross energy (GE), dry matter (DM), ash, and organic matter in diets linearly decreased (p< 0.05) as the adaptation time increased or as the dietary SBP increased, while the ATTD of neutral detergent fibre and acid detergent fibre in diets linearly increased (p<0.01) as the dietary SBP increased. The DE value and the ATTD of GE and crude protein (CP) in SBP linearly increased (p<0.05) as the adaptation time increased, while the ATTD of CP in SBP linearly decreased (p<0.01) as the inclusion level increased. The standardized ileal digestibility of Lys, Met, Thr, and Trp in SBP was 37.03%, 51.62%, 40.68%, and 46.22%, respectively. Conclusion The results of this study indicated that the ATTD of energy and nutrients were decreased as inclusion rate of SBP increased.
Multiclass Universum SVM

We introduce Universum learning for multiclass problems and propose a novel formulation for multiclass universum SVM (MU-SVM). We also propose an analytic span bound for model selection with almost 2-4x faster computation times than standard resampling techniques. We empirically demonstrate the efficacy of the proposed MUSVM formulation on several real world datasets achieving > 20% improvement in test accuracies compared to multi-class SVM.
A Jointly Learned Context-Aware Place of Interest Embedding for Trip Recommendations

Trip recommendation is an important location-based service that helps relieve users from the time and efforts for trip planning. It aims to recommend a sequence of places of interest (POIs) for a user to visit that maximizes the user's satisfaction. When adding a POI to a recommended trip, it is essential to understand the context of the recommendation, including the POI popularity, other POIs co-occurring in the trip, and the preferences of the user. These contextual factors are learned separately in existing studies, while in reality, they impact jointly on a user's choice of a POI to visit. In this study, we propose a POI embedding model to jointly learn the impact of these contextual factors. We call the learned POI embedding a context-aware POI embedding. To showcase the effectiveness of this embedding, we apply it to generate trip recommendations given a user and a time budget. We propose two trip recommendation algorithms based on our context-aware POI embedding. The first algorithm finds the exact optimal trip by transforming and solving the trip recommendation problem as an integer linear programming problem. To achieve a high computation efficiency, the second algorithm finds a heuristically optimal trip based on adaptive large neighborhood search. We perform extensive experiments on real datasets. The results show that our proposed algorithms consistently outperform state-of-the-art algorithms in trip recommendation quality, with an advantage of up to 43% in F1-score.
Modified Si-Ni-San Decoction Ameliorates Central Fatigue by Improving Mitochondrial Biogenesis in the Rat Hippocampus

The traditional Chinese medicine (TCM) decoction Si-Ni-San (SNS) has been utilised for millennia to improve physiological coordination of the functions of the liver and spleen, which are regarded as the main pathological organs of central fatigue in TCM. This study evaluates the effect of a modified SNS (MSNS) formula on central fatigue in rats and explores molecular changes associated with hippocampal mitochondrial biogenesis. Central fatigue was induced through a 21-day sleep deprivation protocol. We assessed MSNS's effects on behaviour, blood and liver biomarkers, and mitochondrial ultrastructure. We found that MSNS could reverse various signs of central fatigue such as its effects on hippocampal gene and protein expression levels of sirtuin 1 (SIRT1), peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α), and nuclear respiratory factor 1 (NRF1). We also observed evidence of MSNS decreasing central fatigue, such as decreasing creatine kinase activity, decreasing levels of malondialdehyde and blood urea nitrogen, increasing lactate dehydrogenase and superoxide dismutase activities, increasing mitochondrial DNA copy number, and reversing mitochondrial ultrastructure changes. These findings suggest that MSNS can ameliorate central fatigue and that its molecular mechanism involves mitochondrial biogenesis enhancement mediated by hippocampal SIRT1, PGC-1α, and NRF1.
Pathological missorting of endogenous MAPT/Tau in neurons caused by failure of protein degradation systems

ABSTRACT Missorting of MAPT/Tau represents one of the early signs of neurodegeneration in Alzheimer disease. The triggers for this are still a matter of debate. Here we investigated the sorting mechanisms of endogenous MAPT in mature primary neurons using microfluidic chambers (MFCs) where cell compartments can be observed separately. Blocking protein degradation pathways with proteasomal or autophagy inhibitors dramatically increased the missorting of MAPT in dendrites on the neuritic side, suggesting that degradation of MAPT in dendrites is a major determinant for the physiological axonal distribution of MAPT. Such missorted dendritic MAPT differed in its phosphorylation pattern from axonal MAPT. By contrast, enhancing autophagy or proteasomal pathways strongly reduced MAPT missorting, thereby confirming the role of protein degradation pathways in the polar distribution of MAPT. Dendritic missorting of MAPT by blocking protein degradation resulted in the loss of spines but not in overall cell toxicity. Inhibition of local protein synthesis in dendrites eliminated the missorting of MAPT, indicating that the accumulation of dendritic MAPT is locally generated. In support of this, a substantial fraction of Mapt/Tau mRNA was detected in dendrites. Taken together, our results indicate that the autophagy and proteasomal pathways play important roles in fine-tuning dendritic MAPT levels and thereby prevent synaptic toxicity caused by MAPT accumulation. Abbreviations Ani: anisomycin; Baf: bafilomycin A1; BSA: bovine serum albumin; cAMP: cyclic adenosine monophosphate; CHX: cycloheximide; DMSO: dimethyl sulfoxide; DIV: days in vitro; Epo: epoxomicin; E18: embryonic day 18; FISH: fluorescence in situ hybridization; IgG: immunoglobulin; kDa: kilodalton; Lac: lactacystin; LDH: lactate dehydrogenase; MFC: microfluidic chambers; MAPs: microtubule-associated proteins; MAPT/Tau: microtubule-associated protein tau; PVDF: polyvinylidene difluoride; PBS: phosphate-buffered saline; PRKA: protein kinase AMP-activated; RD150: round device 150; RT: room temperature; SDS: sodium dodecyl sulfate; SEM: standard error of the mean; Wor: wortmannin.
MicroRNAs in cancer drug resistance: Basic evidence and clinical applications

Development of drug resistance has considerably limited the efficacy of cancer treatments, including chemotherapy and targeted therapies. Hence, understanding the molecular mechanisms underpinning the innate or the acquired resistance to these therapies is critical to improve drug efficiency and clinical outcomes. Several studies have implicated microRNAs (miRNA) in this process. MiRNAs repress gene expression by specific binding to complementary sequences in the 3' region of target messenger RNAs (mRNAs), followed by target mRNA degradation or blocked translation. By targeting molecules specific to a particular pathway within tumor cells, the new generation of cancer treatment strategies has shown significant advantages over conventional chemotherapy. However, the long‐term efficacy of targeted therapies often remains poor, because tumor cells develop resistance to such therapeutics. Targeted therapies often involve monoclonal antibodies (mAbs), such as those blocking the ErB/HER tyrosine kinases, epidermal growth factor receptor (cetuximab) and HER2 (trastuzumab), and those inhibiting vascular endothelial growth factor receptor signaling (e.g., bevacizumab). Even though these are among the most used agents in tumor medicine, clinical response to these drugs is reduced due to the emergence of drug resistance as a result of toxic effects in the tumor microenvironment. Research on different types of human cancers has revealed that aberrant expression of miRNAs promotes resistance to the aforementioned drugs. In this study, we review the mechanisms of tumor cell resistance to mAb therapies and the role of miRNAs therein. Emerging treatment strategies combine therapies using innovative miRNA mimics or antagonizers with conventional approaches to maximize outcomes of patients with cancer.
Stable maintenance of the rudivirus SIRV3 in a carrier state in Sulfolobus islandicus despite activation of the CRISPR-Cas immune response by a second virus SMV1

ABSTRACT Carrier state viral infection constitutes an equilibrium state in which a limited fraction of a cellular population is infected while the remaining cells are transiently resistant to infection. This type of infection has been characterized for several bacteriophages but not, to date, for archaeal viruses. Here we demonstrate that the rudivirus SIRV3 can produce a host-dependent carrier state infection in the model crenarchaeon Sulfolobus. SIRV3 only infected a fraction of a Sulfolobus islandicus REY15A culture over several days during which host growth was unimpaired and no chromosomal DNA degradation was observed. CRISPR spacer acquisition from SIRV3 DNA was induced by coinfecting with the monocaudavirus SMV1 and it was coincident with increased transcript levels from subtype I-A adaptation and interference cas genes. However, this response did not significantly affect the carrier state infection of SIRV3 and both viruses were maintained in the culture over 12 days during which SIRV3 anti-CRISPR genes were shown to be expressed. Transcriptome and proteome analyses demonstrated that most SIRV3 genes were expressed at varying levels over time whereas SMV1 gene expression was generally low. The study yields insights into the basis for the stable infection of SIRV3 and the resistance to the different host CRISPR-Cas interference mechanisms. It also provides a rationale for the commonly observed coinfection of archaeal cells by different viruses in natural environments.
Single molecule analysis of lamin dynamics

The nuclear envelope (NE) is an essential cellular structure that contributes to nuclear stability, organization, and function. Mutations in NE-associated proteins result in a myriad of pathologies with widely diverse clinical manifestations, ages of onsets, and affected tissues. Notably, several hundred disease-causing mutations have been mapped to the LMNA gene, which encodes the intermediate filament proteins lamin A and C, two of the major architectural components of the nuclear envelope. However, how NE dysfunction leads to the highly variable pathologies observed in patient cells and tissues remains poorly understood. One model suggests alterations in the dynamic properties of the nuclear lamina and its associated proteins contribute to disease phenotype. Here, we describe the application of single molecule tracking (SMT) methodology to characterize the behavior of nuclear envelope transmembrane proteins (NETs) and nuclear lamins in their native cellular environment at the single molecule level. As proof-of-concept, we demonstrate by SMT that Halo-tagged lamin B1, Samp1, lamin A, and lamin A Δ50 have distinct binding and kinetic properties, and we identify several disease-relevant mutants which exhibit altered binding dynamics. SMT is also able to separately probe the dynamics of the peripheral and the nucleoplasmic populations of lamin A mutants. We suggest that SMT is a robust and sensitive method to investigate how pathogenic mutations or cellular processes affect protein dynamics at the NE.
Deep Brain Stimulation and L-DOPA Therapy: Concepts of Action and Clinical Applications in Parkinson's Disease

L-DOPA is still the most effective pharmacological therapy for the treatment of motor symptoms in Parkinson's disease (PD) almost four decades after it was first used. Deep brain stimulation (DBS) is a safe and highly effective treatment option in patients with PD. Even though a clear understanding of the mechanisms of both treatment methods is yet to be obtained, the combination of both treatments is the most effective standard evidenced-based therapy to date. Recent studies have demonstrated that DBS is a therapy option even in the early course of the disease, when first complications arise despite a rigorous adjustment of the pharmacological treatment. The unique feature of this therapeutic approach is the ability to preferentially modulate specific brain networks through the choice of stimulation site. The clinical effects have been unequivocally confirmed in recent studies; however, the impact of DBS and the supplementary effect of L-DOPA on the neuronal network are not yet fully understood. In this review, we present emerging data on the presumable mechanisms of DBS in patients with PD and discuss the pathophysiological similarities and differences in the effects of DBS in comparison to dopaminergic medication. Targeted, selective modulation of brain networks by DBS and pharmacodynamic effects of L-DOPA therapy on the central nervous system are presented. Moreover, we outline the perioperative algorithms for PD patients before and directly after the implantation of DBS electrodes and strategies for the reduction of side effects and optimization of motor and non-motor symptoms.
Decentralized Control of a Hexapod Robot Using a Wireless Time Synchronized Network

Robots and control systems rely upon precise timing of sensors and actuators in order to operate intelligently. We present a functioning hexapod robot that walks with a dual tripod gait; each tripod is actuated using its own local controller running on a separate wireless node. We compare and report the results of operating the robot using two different decentralized control schemes. With the first scheme, each controller relies on its own local clock to generate control signals for the tripod it controls. With the second scheme, each controller relies on a variable that is local to itself but that is necessarily the same across controllers as a by-product of their host nodes being part of a time synchronized IEEE802.15. 4e network. The gait synchronization error (time difference between what both controllers believe is the start of the gait period) grows linearly when the controllers use their local clocks, but remains bounded to within 112 microseconds when the controllers use their nodes' time synchronized local variable.
Facial Action Unit Detection Using Attention and Relation Learning

Attention mechanism has recently attracted increasing attentions in the field of facial action unit (AU) detection. By finding the region of interest of each AU with the attention mechanism, AU-related local features can be captured. Most of the existing attention based AU detection works use prior knowledge to predefine fixed attentions or refine the predefined attentions within a small range, which limits their capacity to model various AUs. In this paper, we propose an end-to-end deep learning based attention and relation learning framework for AU detection with only AU labels, which has not been explored before. In particular, multi-scale features shared by each AU are learned first, and then both channel-wise and spatial attentions are adaptively learned to select and extract AU-related local features. Moreover, pixel-level relations for AUs are further captured to refine spatial attentions so as to extract more relevant local features. Without changing the network architecture, our framework can be easily extended for AU intensity estimation. Extensive experiments show that our framework (i) soundly outperforms the state-of-the-art methods for both AU detection and AU intensity estimation on the challenging BP4D, DISFA, FERA 2015, and BP4D+ benchmarks, (ii) can adaptively capture the correlated regions of each AU, and (iii) also works well under severe occlusions and large poses.
Capturing genetic variation in crop wild relatives: An evolutionary approach

Crop wild relatives (CWRs) offer novel genetic resources for crop improvement. To assist in the urgent need to collect and conserve CWR germplasm, we advance here the concept of an “evolutionary” approach. Central to this approach is the predictive use of spatial proxies of evolutionary processes (natural selection, gene flow and genetic drift) to locate and capture genetic variation. As a means to help validate this concept, we screened wild‐collected genotypes of woodland strawberry (Fragaria vesca) in a common garden. A quantitative genetic approach was then used to test the ability of two such proxies—mesoclimatic variation (a proxy of natural selection) and landscape isolation and geographic distance between populations (proxies of gene flow potential)—to predict spatial genetic variation in three quantitative traits (plant size, early season flower number and flower frost tolerance). Our results indicated a significant but variable effect of mesoclimatic conditions in structuring genetic variation in the wild, in addition to other undetermined regional scale processes. As a proxy of gene flow potential, landscape isolation was also a likely determinant of observed patterns—as opposed to, and regardless of, geographic distance between populations. We conclude that harnessing proxies of adaptive and nonadaptive evolutionary processes could provide a robust and valuable means to identify genetic variation in CWRs. We thus advocate wider use and development of this approach amongst researchers, breeders and practitioners, to expedite the capture and in situ conservation of genetic resources provided by crop wild relatives.