Miracle-dz/UniFAR-FTUs huggingface dataset:
Scavenger community structure along an environmental gradient from boreal forest to alpine tundra in Scandinavia

Abstract Scavengers can have strong impacts on food webs, and awareness of their role in ecosystems has increased during the last decades. In our study, we used baited camera traps to quantify the structure of the winter scavenger community in central Scandinavia across a forest–alpine continuum and assess how climatic conditions affected spatial patterns of species occurrences at baits. Canonical correspondence analysis revealed that the main habitat type (forest or alpine tundra) and snow depth was main determinants of the community structure. According to a joint species distribution model within the HMSC framework, species richness tended to be higher in forest than in alpine tundra habitat, but was only weakly associated with temperature and snow depth. However, we observed stronger and more diverse impacts of these covariates on individual species. Occurrence at baits by habitat generalists (red fox, golden eagle, and common raven) typically increased at low temperatures and high snow depth, probably due to increased energetic demands and lower abundance of natural prey in harsh winter conditions. On the contrary, occurrence at baits by forest specialists (e.g., Eurasian jay) tended to decrease in deep snow, which is possibly a consequence of reduced bait detectability and accessibility. In general, the influence of environmental covariates on species richness and occurrence at baits was lower in alpine tundra than in forests, and habitat generalists dominated the scavenger communities in both forest and alpine tundra. Following forecasted climate change, altered environmental conditions are likely to cause range expansion of boreal species and range contraction of typical alpine species such as the arctic fox. Our results suggest that altered snow conditions will possibly be a main driver of changes in species community structure.
Online multi-sensor calibration based on moving object tracking

Modern autonomous systems often fuse information from many different sensors to enhance their perception capabilities. For successful fusion, sensor calibration is necessary, while performing it online is crucial for long-term reliability. Contrary to currently common online approach of using ego-motion estimation, we propose an online calibration method based on detection and tracking of moving objects. Our motivation comes from the practical perspective that many perception sensors of an autonomous system are part of the pipeline for detection and tracking of moving objects. Thus, by using information already present in the system, our method provides resource inexpensive solution for the long-term reliability of the system. The method consists of a calibration-agnostic track to track association, computationally lightweight decalibration detection, and a graph-based rotation calibration. We tested the proposed method on a real-world dataset involving radar, lidar and camera sensors where it was able to detect decalibration after several seconds, while estimating rotation with error from a 20 s long scenario. GRAPHICAL ABSTRACT
Efficient Salient Object Detection Model with Dilated Convolutional Networks

SUMMARY Introduction of Fully Convolutional Networks (FCNs) has made record progress in salient object detection models. However, in order to retain the input resolutions, deconvolutional networks with unpooling are applied on top of FCNs. This will cause the increase of the computation and network model size in segmentation task. In addition, most deep learning based methods always discard e ﬀ ective saliency prior knowledge completely, which are shown e ﬀ ective. Therefore, an e ﬃ cient salient object detection method based on deep learning is proposed in our work. In this model, dilated convolutions are exploited in the networks to produce the output with high resolution without pooling and adding deconvolutional networks. In this way, the parameters and depth of the network are decreased sharply compared with the traditional FCNs. Furthermore, manifold ranking model is explored for the saliency reﬁnement to keep the spatial consistency and contour preserving. Experimental results verify that performance of our method is superior with other state-of-art meth-ods. Meanwhile, the proposed model occupies the less model size and fastest processing speed, which is more suitable for the wearable processing systems.
How do performance gaps shape managerial strategy? The role of sector-differences in U.S. nursing homes

Abstract Despite the high volume of literature on managerial strategy, few studies have explored how performance gaps shape managerial strategy, particularly across sectors. Emerging studies indicate that different risk preferences, market competition, and financial incentives across sectors play important roles in shaping managerial strategy in response to performance gaps. Using U.S. nursing homes, this study examines how performance gaps shape prospecting and defending strategies, and whether the relationship is contingent on sector. The findings indicate that nursing home managers are more likely to be prospectors when they outperform past performance or other competitors. When considering sector-differences, this finding is consistent in only for-profit nursing homes. Regardless of performance gaps, for-profit nursing homes are also more likely to adopt a defending strategy compared to their nonprofit or public counterparts. The findings suggest that sector-differences should be carefully considered to understand the impact of performance gaps on managerial strategy.
Intra-tumor heterogeneity and clonal exclusivity in renal cell carcinoma

Tumorigenesis is an evolutionary process in which different clones evolve over time. Interactions between clones can affect tumor evolution and hence disease progression and treatment outcome. We analyzed 178 tumor samples in 89 clear cell renal cell carcinoma patients and found high intra-tumor heterogeneity with 62% of mutations detected in only one of two biopsies per patient. We developed a novel statistical test to identify gene pairs that are altered in co-occurring clones of the same tumor, including the pairs TP53 and MUC16, as well as BAP1 and TP53. The mutations in these gene pairs are clonally exclusive meaning that they occurred in different branches of the tumor phylogeny, suggesting a synergistic effect between the two clones carrying these mutations. Our analysis sheds new light on tumor development and implies that clonal interactions are common within tumors, which may eventually open up novel treatment strategies to improve cancer treatment.
Fully integrated multi-scale modelling of damage and time-dependency in thermoplastic-based woven composites

In this work, a multi-scale model established from the concept of periodic homogenization is utilized to predict the cyclic and time-dependent response of thermoplastic-based woven composites. The macroscopic behaviour of the composite is determined from finite element simulations of the representative unit cell of the periodic microstructure, where the local non-linear constitutive laws of the components are directly integrated, namely, the matrix and the yarns. The thermoplastic matrix is described by a phenomenological multi-mechanisms constitutive model accounting for viscoelasticity, viscoplasticity and ductile damage. For the yarns, a hybrid micromechanical–phenomenological constitutive model accounting for anisotropic damage and anelasticity induced by the presence of a diffuse micro-crack network is utilized. The capabilities of the overall multi-scale model are validated by comparing the numerical predictions with experimental data. Further illustrative examples are also provided, where the composite undergoes time-dependent deformations under uni-axial and non-proportional multi-axial loading paths. The multi-scale model is also employed to analyze the influence of the local deformation processes on the macroscopic response of the composite.
Hormonal profile and characteristics of polychistic ovarium syndrome among Madurese tribe, Indonesia

Polycystic ovarium syndrome (PCOS), the most common endocrine disorders in women of reproductive age, characterized by menstrual disorders (amenorrhea/oligomenorrhea), hirsutism, the appearance of acne, alopecia and the results of biochemical tests that show increased androgens (testosterone). Increased serum luteinizing hormone (LH) and follicle stimulating hormone (FSH) serve as diagnostic tests for PCOS over the years, but from several research results obtained inconsistent results that need further research. The purpose of this study is to analyze the hormonal profile and characteristics of polycystic ovary syndrome (PCOS) in Madura. Case-control study conducted in March-August 2019 in the Madura tribe. There were 32 subjects with PCOS and 32 healthy women participated in this study. Hormonal examination was using a serum and followed by enzyme-linked immune sorbent assay (ELISA kit). Levels Follicle-stimulating hormone (FSH) average was 8.74 and SHBGs were 10.02 lower in PCOS patients and LH levels were higher in PCOS patients; ratio LH/FSH was 0.76. The results of the Madurese study showed that levels of FSH, LH, weight significantly related to PCOS sex hormone binding globulin (SHBG), however body mass index (BMI) levels were not related to PCOS.
The effectiveness of behavioural interventions on increasing revenue from local fee

PurposeThe objective was to increase earnings of the city of Prievidza from waste disposal fee by proactive communication – reminder (a letter) and leaflets with targeted framing. The quasi-experiment aims to find out which type of leaflet framing (an injunctive social norm or public good) causes the most effective change in the debtors' behaviour.Design/methodology/approachThe article presents the results of a behavioural quasi-experiment, carried out on a local government level. The effectiveness of the intervention was tested in a quasi-experiment with the sample size 712, which is 35% of all waste disposal fee debtors in Prievidza.FindingsThe intervention that has proven to be the most effective was a reminder together with an injunctive social norm leaflet. It resulted in a 1.7 times higher probability for the debt to be paid. The results also indicate that a reminder is significantly more effective if targeted at debtors who only owe one payment–this group was three times more likely to pay their debt after being exposed to the intervention.Practical implicationsPublic policy recommendation is to primarily target the group of debtors who owe one payment.Originality/valueAnother testing and replication of this experiment design is highly important. Nonetheless, the first testing (field quasi-experiment) shows the potential of using the notification as well as social norm framing. It also appears that self-governments should use notifications to primarily address debtors without a long history of non-payment.
Variational Autoencoder Based Unsupervised Domain Adaptation For Semantic Segmentation

Unsupervised domain adaptation, which transfers supervised knowledge from a labeled domain to an unlabeled domain, remains a tough problem in the field of computer vision, especially for semantic segmentation. Some methods inspired by adversarial learning and semi-supervised learning have been developed for unsupervised domain adaptation in semantic segmentation and achieved outstanding performances. In this paper, we propose a novel method for this task. Like adversarial learning-based methods using a discriminator to align the feature distributions from different domains, we employ a variational autoencoder to get to the same destination but in a non-adversarial manner. Since the two approaches are compatible, we also integrate an adversarial loss into our method. By further introducing pseudo labels, our method can achieve state-of-the-art performances on two benchmark adaptation scenarios, GTA5-toCITYSCAPES and SYNTHIA-to-CITYSCAPES.
A Generative Time Series Clustering Framework Based on an Ensemble Mixture of HMMs

Time series have met high interest in various fields for measuring the evolution of a quantity over time. Several machine learning techniques are proposed to extract knowledge from this type of data and make them more meaningful. Clustering is one such prominent technique, for detecting homogeneous subgroups from a data set when there is no prior knowledge about classes. It has been called upon various fields to discover hidden models that arise from the data. In this paper, we propose a new framework called Generative time series Clustering with Bagging (GCBag). It combines the power of several techniques designed for time series. Most existing works use DTW to provide a starting point for HMMs to estimate their parameters. As a result, the estimation becomes dependent on this single provided initialization, which can be biased. The originality of GCBag lies in the use of bagging during the clustering where it significantly raises the stability of models. Consequently, we have succeeded in improving the quality of clustering while preserving the descriptive aspect. Several experiments are conducted to demonstrate the effectiveness of GCBag over the existing models for time series clustering, on both synthetic and real time series data.
Presence of Bradyrhizobium sp. under Continental Conditions in Central Europe

Soil samples from different locations with varied soybean cultivation histories were taken from arable fields in 2018 in East Germany and Poland (Lower Silesia) to evaluate the specific microsymbionts of the soybean, Bradyrhizobium japonicum, one to seven years after inoculation. Soybeans were grown in the selected farms between 2011 and 2017. The aim of the experiment was to investigate whether there is a difference in rhizobia contents in soils in which soybeans have been recultivated after one to seven years break, and whether this could lead to differences in soybean plant growth. The obtained soil samples were directly transferred into containers, then sterilized soybean seeds were sown into pots in the greenhouse. After 94 days of growth, the plants were harvested and various parameters such as the nodular mass, number of nodules, and dry matter in the individual plant parts were determined. In addition, the relative abundances of Bradyrhizobium sp. in soil samples were identified by sequencing. No major decline in Bradyrhizobium sp. concentration could be observed due to a longer interruption of soybean cultivation. Soil properties such as pH, P, and Mg contents did not show a significant influence on the nodule mass or number, but seem to have an influence on the relative abundance of Bradyrhizobium sp. The investigations have shown that Bradyrhizobium japonicum persists in arable soils even under Central European site conditions and enters into an effective symbiosis with soybeans for up to seven years.
Nanobiotechnological basis of an oxygen carrier with enhanced carbonic anhydrase for CO2 transport and enhanced catalase and superoxide dismutase for antioxidant function

This is a mini review on the biotechnological aspects of the most extensively developed hemoglobin-based oxygen carriers The emphasis is on the most recent Polyhemoglobin-catalase-superoxide dismutase-carbonic anhydrase (PolyHb-CAT-SOD-CA), which is a nanobiotechnological complex that is being investigated and scaled up with the potential for clinical use as nanobiotherapeutics. Hemoglobin, a tetramer, is an excellent oxygen carrier. However, in the body it is converted into toxic dimers. Diacid or glutaraldehyde can crosslink hemoglobin into polyhemoglobin (PolyHb) and prevent its breakdown into toxic dimers. This has been developed and tested in clinical trials. A bovine polyhemoglobin has been approved for routine clinical use for surgical procedures in South Africa and Russia. Clinical trials with human PolyHb in hemorrhagic shock were effective but with a very slight increase in non-fatal myocardial ischemia. This could be due to a number of reasons. For those conditions with ischemia-reperfusion, one would need an oxygen carrier with antioxidant properties. One approach to remedy this is with prepared polyhemoglobin-catalase-superoxide dismutase (PolyHb-CAT-SOD). Another reason is an increase in intracellular pCO2. We therefore added an enhanced level of carbonic anhydrase to prepare a PolyHb-CAT-SOD-CA. The result is an oxygen carrier with enhanced Carbonic Anhydrase for CO2 transport and enhanced Catalase and Superoxide Dismutase for antioxidant functions. Detailed efficacy and safety studies have led to the industrial scale up towards clinical trial. In the meantime, oxygen carriers are being investigated around the world for use in ex vivo biotechnological fluid for organ preservation for transplantation, with one already approved in France.
Serum enzyme activities in blood and milk in the different stage of lactation in holstein dairy cows

: The objective of this study was to determine correlation between serum blood and milk enzyme activities of aspartate-aminotransferase (AST), alanine- aminotransferase (ALT), alkaline-phosphatase (ALP in the 36 dairy Holstein cows divided into three groups according to production period. Group 1 consisted cows in the start of lactation (n = 12); Group 2 -consisted of early lactation cows (n=12) and Group 3 included mid lactation cows (n=15). Statistically significant higher (P<0.01) activity of AST in blood serum was established in early lactation groups of cows as compared to mid lactation group of cows. ALT activity showed a lower (P<0.01) serum activities in early lactation groups of cows than in the mid lactation cows. Higher values ALP in blood and milk are determined in early lactation groups of cows as compared to mid laltation cows, but without statistical significance (P>0.05). Research results showed possibility of mild degree of hepatic lesions, probably due to fat infiltration in early lactation cows. No significant difference (P>0.05) was observed in milk serum value for AST, ALT and ALP between the three groups of cows. No significant correlations among AST, ALT and ALP activities in blood and milk serum were determined (P>0.05) and shows that activity of these enzyme in the milk are not used as markers for early diagnosis of subclinical metabolic disease.
Adolescents' sleep/wake patterns and school schedules: towards flexibility

In the literature, two main trends may be identified in the countermeasures associated to adolescents’ sleep restriction: sleep education and changes in the school start times (SSTs). However, school educational programmes have been able to increase knowledge about sleep, which did not necessarily result in behavioural changes. Later SSTs have been proposed as a strategy to reduce the adolescents’ sleep restriction, but there is no consensus about the change. Longitudinal studies in adolescent populations are urgently needed in order to determine the efficacy of interventions aiming at a change in SSTs. Academic, behavioural, health and well-being variables could be monitored for an extensive period before and after implementing the new school schedule options, thereby enabling a within-subject experimental design. It is no longer acceptable to impose the “one-size-fits-all” approach on the SSTs.
Physical properties of impregnated sengon wood by monoethylen glycol and nano silica from betung bamboo sticks

Sengon wood (Falcataria moluccana) is a fast-growing species that has low dimensional stability and density. The purposes of this study were to analyze the effect of impregnation treatment by using MEG (monoethylen glycol) and nano silica from betung bamboo sticks on the dimensional stability and density of sengon wood and to identify the characteristics of impregnated sengon wood. The treatments were consisted of untreated (water treated), 50% MEG (MEG), 0.5% nano silica in 50% MEG (MEGsilica 0.5%), 0.75% nano silica in 50% MEG (MEGsilica 0.75%) and 1% nano silica in 50% MEG (MEGsilica 1%). Weight percent gain, anti-swelling efficiency, water uptake, bulking effect, and density were affected by the treatments. It was due to the coverage of MEG and nano silica on cell walls and vessels of sengon wood (SEM analysis). Also, the presence of nano silica in wood treated (SEM-EDX analysis). The cristalinity of sengon wood decreases because MEG is amourphous. FT-IR showed there was no MEG bonds with sengon wood cell wall components or between nano silica and sengon wood. The optimum treatment for sengon wood was MEGsilika 1%.
The shape of the predator biomass distribution affects biological pest control services in agricultural landscapes

1. Understanding how community composition of service-providing organisms affects ecosystem functioning is a key challenge in ecology. Although it has been proposed that taxonomic diversity and functional traits mediate this relationship, how several facets of community structure affect the delivery of key ecosystem services remains to be explored. 2. In this study, we investigated how abundance, taxonomic richness as well as the shape of biomass distribution in predator communities affect biological pest con - trol services in vineyard landscapes. Our analyses were based on a dataset com - bining samples of arthropod predators, measures of predation rates of grape pests and characterization of environmental covariables for 42 fields located in South-Western France. 3. We found that beside the abundance or the taxonomic richness of predators, the shape of biomass distribution (mean, variance, skewness and kurtosis of the dis - tribution) influences the level of biological control. Predator communities largely dominated by low biomass species provided the bulk of biological control services. Lower levels of predation resulted
Resilience of a forest fragment exposed to long-term isolation in Singapore

Background: Fragmentation can fundamentally alter the structure of tropical forests. However, the impacts of fragmentation may vary significantly among regions and lead to different outcomes. Aims: We examined the structure, composition and dynamics of a forest fragment in Singapore to investigate reasons for the apparent resilience of this forest to long-term isolation. Methods: We conducted 5 censuses of 12,688 trees ≥1-cm dbh in a 2-ha plot on the edge of the fragment between 1993 and 2012. Results: Stem density and basal area were not significantly different between 1993 and 2012 and were typical of other south-east Asian forests. However, there were short-term decreases in both variables after droughts in 1997 and 2009, both followed by recovery. Total mortality rate over the 19 years was 3.3% year−1, considerably higher than other tropical forests in Asia, but it was balanced by high recruitment. The 10 most abundant species were primary forest species, pioneer species comprised <5% of all stems, and none of the 338 species in the plot was exotic. However, species abundances changed more than expected by chance for 86 species, and the rank order of the commonest species changed significantly. Species abundance changes were not related to known species traits. Conclusions: Despite the long period of isolation, we found a surprising level of resilience of the Bukit Timah forest. While the forest may be more sensitive to the effects of climatic fluctuations at decadal time scales, there were very few signs of forest degradation in this diverse fragment of tropical forest.