Billions of IoT devices lacking proper security mechanisms have been manufactured and deployed for the last years, and more will come with the development of Beyond 5G technologies. Their ...vulnerability to malware has motivated the need for efficient techniques to detect infected IoT devices inside networks. With data privacy and integrity becoming a major concern in recent years, increasing with the arrival of 5G and Beyond networks, new technologies such as federated learning and blockchain emerged. They allow training machine learning models with decentralized data while preserving its privacy by design. This work investigates the possibilities enabled by federated learning concerning IoT malware detection and studies security issues inherent to this new learning paradigm. In this context, a framework that uses federated learning to detect malware affecting IoT devices is presented. N-BaIoT, a dataset modeling network traffic of several real IoT devices while affected by malware, has been used to evaluate the proposed framework. Both supervised and unsupervised federated models (multi-layer perceptron and autoencoder) able to detect malware affecting seen and unseen IoT devices of N-BaIoT have been trained and evaluated. Furthermore, their performance has been compared to two traditional approaches. The first one lets each participant locally train a model using only its own data, while the second consists of making the participants share their data with a central entity in charge of training a global model. This comparison has shown that the use of more diverse and large data, as done in the federated and centralized methods, has a considerable positive impact on the model performance. Besides, the federated models, while preserving the participant’s privacy, show similar results as the centralized ones. As an additional contribution and to measure the robustness of the federated approach, an adversarial setup with several malicious participants poisoning the federated model has been considered. The baseline model aggregation averaging step used in most federated learning algorithms appears highly vulnerable to different attacks, even with a single adversary. The performance of other model aggregation functions acting as countermeasures is thus evaluated under the same attack scenarios. These functions provide a significant improvement against malicious participants, but more efforts are still needed to make federated approaches robust.
The Cauchy slicings for globally hyperbolic spacetimes and their relation with the causal boundary are surveyed and revisited, starting at the seminal conformal boundary constructions by R. Penrose. ...Our study covers: (1) adaptive possibilities and techniques for their Cauchy slicings, (2) global hyperbolicity of sliced spacetimes, (3) critical review on the conformal and causal boundaries for a globally hyperbolic spacetime, and (4) procedures to compute the causal boundary of a Cauchy temporal splitting by using isocausal comparison with a static product. New simple counterexamples on
R
2
illustrate a variety of possibilities related to these splittings, such as the logical independence (for normalized sliced spacetimes) between the completeness of the slices and global hyperbolicity, the necessity of uniform bounds on the slicings in order to ensure global hyperbolicity, or the insufficience of these bounds for the computation of the causal boundary. A refinement of one of these examples shows that the space of all the (normalized, conformal classes of) globally hyperbolic metrics on a smooth product manifold
R
×
S
is not convex, even though it is path connected by means of piecewise convex combinations.
In the standard cold dark matter (CDM) theory for understanding the formation of structure in the Universe, there exists a tight connection between the properties of dark matter (DM) haloes, and ...their formation epochs. Such relation can be expressed in terms of a single key parameter, namely the halo concentration. In this work, we examine the median concentration–mass relation, c(M), at present time, over more than 20 orders of magnitude in halo mass, i.e. from tiny Earth-mass microhaloes up to galaxy clusters. The c(M) model proposed by Prada et al. (2012), which links the halo concentration with the rms amplitude of matter linear fluctuations, describes remarkably well all the available N-body simulation data down to ∼10−6
h
−1 M⊙ microhaloes. A clear fattening of the halo concentration–mass relation towards smaller masses is observed, that excludes the commonly adopted power-law c(M) models, and stands as a natural prediction for the CDM paradigm. We provide a parametrization for the c(M) relation that works accurately for all halo masses. This feature in the c(M) relation at low masses has decisive consequences e.g. for γ-ray DM searches, as it implies more modest boosts of the DM annihilation flux due to substructure, i.e. ∼35 for galaxy clusters and ∼15 for galaxies like our own, as compared to those huge values adopted in the literature that rely on such power-law c(M) extrapolations. We provide a parametrization of the boosts that can be safely used for dwarfs to galaxy cluster-size haloes.
Biochar production and use are part of the modern agenda to recycle wastes, and to retain nutrients, pollutants, and heavy metals in the soil and to offset some greenhouse gas emissions. Biochars ...from wood (eucalyptus sawdust, pine bark), sugarcane bagasse, and substances rich in nutrients (coffee husk, chicken manure) produced at 350, 450 and 750°C were characterized to identify agronomic and environmental benefits, which may enhance soil quality. Biochars derived from wood and sugarcane have greater potential for improving C storage in tropical soils due to a higher aromatic character, high C concentration, low H/C ratio, and FTIR spectra features as compared to nutrient-rich biochars. The high ash content associated with alkaline chemical species such as KHCO3 and CaCO3, verified by XRD analysis, made chicken manure and coffee husk biochars potential liming agents for remediating acidic soils. High Ca and K contents in chicken manure and coffee husk biomass can significantly replace conventional sources of K (mostly imported in Brazil) and Ca, suggesting a high agronomic value for these biochars. High-ash biochars, such as chicken manure and coffee husk, produced at low-temperatures (350 and 450°C) exhibited high CEC values, which can be considered as a potential applicable material to increase nutrient retention in soil. Therefore, the agronomic value of the biochars in this study is predominantly regulated by the nutrient richness of the biomass, but an increase in pyrolysis temperature to 750°C can strongly decrease the adsorptive capacities of chicken manure and coffee husk biochars. A diagram of the agronomic potential and environmental benefits is presented, along with some guidelines to relate biochar properties with potential agronomic and environmental uses. Based on biochar properties, research needs are identified and directions for future trials are delineated.
A systematic study of (smooth, strong) cone structures
C
and Lorentz–Finsler metrics
L
is carried out. As a link between both notions, cone triples
(
Ω
,
T
,
F
)
, where
Ω
(resp.
T
) is a 1-form ...(resp. vector field) with
Ω
(
T
)
≡
1
and
F
, a Finsler metric on
ker
(
Ω
)
, are introduced. Explicit descriptions of all the Finsler spacetimes are given, paying special attention to stationary and static ones, as well as to issues related to differentiability. In particular, cone structures
C
are bijectively associated with classes of anisotropically conformal metrics
L
, and the notion of
cone geodesic
is introduced consistently with both structures. As a non-relativistic application, the
time-dependent
Zermelo navigation problem is posed rigorously, and its general solution is provided.
► Annual sediment yield ranged from 4.3
t
km
2
y
−1 to 110
t
km
2
y
−1. ► Particulate organic carbon ranged from 0.1
t
km
2
y
−1 to 2.8
t
km
2
y
−1. ► Highest annual sediment yield represented 25 ...times the minimum annual yield. ► Highest annual particulate carbon yield represented 25 times the minimum one. ► Contributing erosive zones varied spatially from 0.1 to 6
t
ha
−1.
The Soil and Water Assessment Tool (SWAT, 2005) was used to simulate discharge and sediment transport at daily time steps within the intensively farmed Save catchment in south-west France (1110
km
2). The SWAT model was applied to evaluate catchment hydrology and sediment and associated particulate organic carbon yield using historical flow and meteorological data for a 10-years (January 1999–March 2009). Daily data on sediment (27
months, January 2007–March 2009) and particular organic carbon (15
months, January 2008–March 2009) were used to calibrate the model. Data on management practices (crop rotation, planting date, fertiliser quantity and irrigation) were included in the model during the simulation period of 10
years.
Simulated daily discharge, sediment and particulate carbon values matched the observed values satisfactorily. The model predicted that mean annual catchment precipitation for the total study period (726
mm) was partitioned into evapotranspiration (78.3%), percolation/groundwater recharge (14.1%) and abstraction losses (0.5%), yielding 7.1% surface runoff. Simulated mean total water yield for the whole simulation period amounted to 138
mm, comparable to the observed value of 136
mm. Simulated annual sediment yield ranged from 4.3
t
km
−2
y
−1 to 110
t
km
−2
y
−1 (annual mean of 48
t
km
−2
y
−1). Annual yield of particulate organic carbon ranged from 0.1
t
km
−2
y
−1 to 2.8
t
km
−2
y
−1 (annual mean of 1.2
t
km
−2
y
−1). Thus, the highest annual sediment and particulate carbon yield represented 25 times the minimum annual yield. However, the highest annual water yield represented five times the minimum (222
mm and 51
mm, respectively). An empirical correlation between annual water yield and annual sediment and organic carbon yield was developed for this agricultural catchment. Potential source areas of erosion were also identified with the model. The range of the annual contributing erosive zones varied spatially from 0.1 to 6
t
ha
−1 according to the slope and agricultural practices at the catchment scale.
We review the current understanding of the Diffuse Gamma-Ray Background (DGRB). The DGRB is what remains of the total measured gamma-ray emission after the subtraction of the resolved sources and of ...the diffuse Galactic foregrounds. It is interpreted as the cumulative emission of sources that are not bright enough to be detected individually. Yet, its exact composition remains unveiled. Well-established astrophysical source populations (e.g. blazars, misaligned AGNs, star-forming galaxies and millisecond pulsars) all represent guaranteed contributors to the DGRB. More exotic scenarios, such as Dark Matter annihilation or decay, may contribute as well. In this review, we describe how these components have been modeled in the literature and how the DGRB can be used to provide valuable information on each of them. We summarize the observational information currently available on the DGRB, paying particular attention to the most recent measurement of its intensity energy spectrum by the Fermi LAT Collaboration. We also discuss the novel analyses of the auto-correlation angular power spectrum of the DGRB and of its cross-correlation with tracers of the large-scale structure of the Universe. New data sets already (or soon) available are expected to provide further insight on the nature of this emission. By summarizing where we stand on the current knowledge of the DGRB, this review is intended both as a useful reference for those interested in the topic and as a means to trigger new ideas for further research.
Colombia's agriculture, forestry and other land use sector accounts for nearly half of its total greenhouse gas (GHG) emissions. The importance of smallholder deforestation is comparatively high in ...relation to its regional counterparts, and livestock agriculture represents the largest driver of primary forest depletion. Silvopastoral systems (SPSs) are presented as agroecological solutions that synergistically enhance livestock productivity, improve local farmers' livelihoods and hold the potential to reduce pressure on forest conversion. The department of Caquetá represents Colombia's most important deforestation hotspot. Targeting smallholder livestock farms through survey data, in this work we investigate the GHG mitigation potential of implementing SPSs for smallholder farms in this region. Specifically, we assess whether the carbon sequestration taking place in the soil and biomass of SPSs is sufficient to offset the per-hectare increase in livestock GHG emissions resulting from higher stocking rates. To address these questions we use data on livestock population characteristics and historic land cover changes reported from a survey covering 158 farms and model the carbon sequestration occurring in three different scenarios of progressively-increased SPS complexity using the CO2 fix model. We find that, even with moderate tree planting densities, the implementation of SPSs can reduce GHG emissions by 2.6 Mg CO2e ha−1 yr−1 in relation to current practices, while increasing agriculture productivity and contributing to the restoration of severely degraded landscapes.
This systematic review and meta-analysis aimed to examine the effects of out-of-school physical activity (PA) interventions, based on Self-Determination Theory (SDT), on basic psychological needs ...(BPN), motivation toward PA, and PA levels in youths.
Systematic review and meta-analyses.
We searched for intervention studies examining the effects of PA interventions based on SDT implemented outside the school published in English and Spanish in six electronic databases up to January 2022.
Outcomes of interest were BPN, motivation, and PA levels. In total, nine studies were included in this review. Seven individual meta-analyses were conducted for each variable, revealing nonsignificant clustered effects for the outcomes autonomy satisfaction (g = 0.12, 95% CI -0.31, 0.55), competence satisfaction (g = 0.02, 95% CI -0.28, 0.32), relatedness satisfaction (g = 0.13, 95% CI -0.43, 0.68), autonomous motivation (g = 0.15, 95% CI -0.38, 0.67), controlled motivation (g = 0.12, 95% CI -0.32, 0.55), amotivation (g = -0.36, 95% CI -0.88, 0.16), and PA behavior (g = 0.02, 95% CI -0.08, 0.12).
Meta-analyses suggest that out-of-school PA interventions based on SDT are not effective in increasing levels of needs satisfaction, types of motivation, and PA levels.
The aim of this study was to evaluate the use of biochar (produced by slow pyrolysis of
Eucalyptus grandis biomass) as bulking agent for the composting of poultry manure. Three composting mixtures ...were prepared by the turned-pile system by mixing poultry manure with different organic wastes used as bulking agent (biochar, coffee husk and sawdust) in a proportion of 1:1 (fresh weight). Despite the inert nature of biochar, the composting mixture prepared with biochar underwent an organic matter degradation of 70% of the initial content. The organic matter of the poultry manure–biochar mixture was characterised by a high polymerisation degree of the humic-like substances, with a relative high proportion of humic acids in relation to fulvic acids. At the end of the composting process, the humic acid fraction represented more than 90% of the alkali extractable fraction, reflecting the intense humification of this material. Enrichment of poultry manure with biochar reduced the losses of nitrogen in the mature composts, although the use of sawdust would be more efficient in preserving the organic matter and nitrogen in the mature compost.
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