Search

Introduction: This study focuses on the central mountain region of the Peruvian Andes, particularly its western slopes, high-altitude areas, and inter-Andean valleys situated above 3000 m.a.s.l. Despite its ecological importance, the region remains understudied, resulting in significant information gaps. Objective: To identify flora species along an altitudinal gradient in the Cajatambo district. Methods: Sampling was carried out at five distinct altitudinal levels using a combination of sampling techniques. Taxonomic identification was performed, and statistical analyses including ANOVA, the Mantel test, and NMDS were applied. Results: 424 plant species were identified, revealing the dominance of Asteraceae. The approach used allowed for the identification of floristic and structural patterns in various habitats, ranging from arid montane scrub to puna grassland. Surprisingly, Asteraceae richness had a significant impact on species diversity, while altitude did not. Additionally, floristic similarity between nearby altitudinal levels was not related to geographical distance. The analysis of ecosystems has shown that certain families are adaptable. Additionally, floristic diversity has been affected by human activity near the district capital. The distribution of medicinal species has been limited due to selective extraction. Conclusions: The shrubland and thorny scrub was the most diverse ecosystem and had the widest distribution across the altitudinal gradient.

One of the most important factors when assessing the resilience of critical infrastructure is its vulnerability to extreme events. This study focuses on developing correlation maps that define the vulnerability to fire risk of critical infrastructure and its zone of influence. Using an index approach, a vulnerability assessment is challenging due to the fact that observing and measuring certain vulnerability aspects is not too easy. Furthermore, analyzing the unique vulnerabilities of individual elements becomes intricate, given their interdependencies and correlations. Leveraging GIS mapping techniques, we investigate the impacts of infrastructure disruption on neighboring elements and the urban fabric. The methodology enables multiple levels of assessment, facilitating the identification of vulnerable elements and optimizing decision-making processes before and after extreme events. Our findings highlight the significance of prioritizing emergency planning, enhancing accessibility, implementing preventive measures, and adopting a proactive emergency response approach. In conclusion, these measures contribute to mitigating vulnerability and safeguarding critical infrastructure and surrounding communities from extreme events.

Although some studies have been conducted to compute fragility surfaces of buildings using vector-valued seismic intensity measures (IMs), in all the cases, the first component of the vector usually is the spectral acceleration at first mode of vibration of the structure Sa(T1). In this study, fragility surfaces of three reinforced concrete buildings (RCB) subjected to narrow-band ground motions obtained from soft soil of Mexico City are computed considering vector-valued IMs based not only on Sa(T1), but also the velocity V(T1), pseudo-velocity Sv(T1), and normalized input energy by the mass EI/m(T1) as the first component. As second component of the vector-valued IMs, the Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), effective duration (tD), earthquake damage potential (ID) and four Np spectral shape-based parameters obtained through spectral acceleration (NpSa), velocity (NpV), pseudo-velocity (NpSv), and input energy (NpEI) have been analyzed. In order to obtain fragility surfaces, Multinomial Logistic Regression (MLR) was applied. It is observed that those vector-valued IMs based on the spectral shape proxies were more efficient to predict the probability of failure of RCB. For this reason, it is important to consider spectral shape vector-valued IMs in order to reduce uncertainty in the structural response of buildings under earthquakes. Thus, the use of two parameters instead of a single intensity measure improves the efficiency. Moreover, the fragility surfaces can be used for the seismic risk evaluation of buildings.

Transition zones, specifically embankment structures on railway tracks, are recurrently damaged by high-speed rail traffic, thus producing abrupt variations in the track vertical stiffness. The main objective of this work is to study the implementation of Construction and Demolition (C&D) wastes, specifically Bi-Block (BB) concrete sleepers, to minimize the issues related to the differences in stiffness along the area of the technical landfills, using unconventional environmental solutions. The use of BB wastes can reduce the environmental impacts caused by the construction sector. The studied solutions produce similar stiffness levels to traditional solutions. The Multicriteria Decision Support Methodology for the Relative Sustainability Assessment of Building Technologies (MARS-SC) allows concluding that the studied solutions are more sustainable than the traditional ones.

We present a combined experimental and theoretical investigation on Ca+ ions in helium droplets, HeNCa+. The clusters have been formed in the laboratory by means of electron-impact ionization of Ca-doped helium nanodroplets. Energies and structures of such complexes have been computed using various approaches such as path integral Monte Carlo, diffusion Monte Carlo and basin-hopping methods. The potential energy functions employed in these calculations consist of analytical expressions following an improved Lennard-Jones formula whose parameters are fine-tuned by exploiting ab initio estimations. Ion yields of HeNCa+ -obtained via high-resolution mass spectrometry- generally decrease with N with a more pronounced drop between N=17 and N=25, the computed quantum HeNCa+ evaporation energies resembling this behavior. The analysis of the energies and structures reveals that covering Ca+ with 17 He atoms leads to a cluster with one of the smallest energies per atom. As new atoms are added, they continue to fill the first shell at the expense of reducing its stability, until N=25, which corresponds to the maximum number of atoms in that shell. Behavior of the evaporation energies and radial densities suggests liquid-like cluster structures.

The objective of this work was to assess the use of biomass fly ash (BFA) as cement replacement material or as an alkalinity source in high volume fly ash mortar and concrete. Mortar formulations were prepared with different types of cement replacement: fly ash from thermal power plants, BFA, a blend of two pozzolans, and small amounts of BFA or/and hydrated lime (HL). Mortar formulations were tested both in the fresh and hardened state. The replacement of cement by the two fly ashes led to a decrease in the mechanical strength. The best strength values were obtained when higher HL content was introduced in mortars, however, mortars with the lower BFA content presented the best results for the majority of the tests. In general, BFA has a similar effect on cementitious mortars to coal fly ash, having good performance as cement replacement.

We report accurate quantum calculations of the sieving of Helium atoms by two-dimensional (2D) graphtriyne layers with a new interaction potential. Thermal rate constants and permeances in an ample temperature range are computed and compared for both Helium isotopes. With a pore larger than graphdiyne, the most common member of the γ-graphyne family, it could be expected that the appearance of quantum effects were more limited. We find, however, a strong quantum behavior that can be attributed to the presence of selective adsorption resonances, with a pronounced effect in the low temperature regime. This effect leads to the appearance of some selectivity at very low temperatures and the possibility for the heavier isotope to cross the membrane more efficiently than the lighter, contrarily to what happened with graphdiyne membranes, where the sieving at low energy is predominantly ruled by quantum tunneling. The use of more approximate methods could be not advisable in these situations and prototypical transition state theory treatments might lead to large errors.

This work is a phytosociological approach to the montane rainforests of Peru with the aim of advancing on the diversity of plant communities, which we had already begun in previous research. From 364 phytosociological plots and 3389 species of the South American tropics, we have developed a cluster, using the Sørensen index, to know the similarities between the forests and their parallelism with bioclimatic conditions. After studying the existence of characteristic groups of the Peruvian forests, we have established different communities and phytosociological units for Peru. As a result, we have described seven associations, within three new alliances, which are gathered in the new order Saurauio peruvianae-Condaminetalia corymbosae of the new class Morello pubescentis-Myrsinetea coriaceae. In addition, two associations have been described within the class Pruno rigidae-Oreopanacetea floribundae (mesotropical laurel-like forests), and three for the class Alnetea acuminatae (alder forests and palm groves). The humid forests of Peru are closer to those of Ecuador and to those of the set formed by the three Colombian mountain ranges than to those of Bolivia and Argentina, due to the common flora these share with areas of Paraguay and even of the Parana River region.

This study analyses the distribution of the total metal(loid)s content accumulated in the sediments of the Grande River, the most important river course that runs through the old mining district of La Carolina (Jaén, Spain), whose waters are collected in an urban supply reservoir. In total, 102 sediments samples were taken along the river, 51 in the live-bed channel and another 51 in the floodplain. The samples analysed have high metal(loid)s content, sometimes much higher than the reference levels established by European and regional legislation for soils, especially Pb, As and Ba, with average values of 5452 mg/kg, 116 mg/kg and 2622 mg/kg, respectively. The statistical analysis of the values obtained allows the distribution of the contents of the different elements along the river to be characterized and the associations and dispersion patterns in the sediments of the metal(loid)s coming from the environmental liabilities of the numerous dumpsites and tailings dams generated by mining activity to be defined. In both cases, the high metal(loid)s content identified as well as the resulting values of various environmental indices (the enrichment factor, contamination factor, geoaccumulation index, potential ecological risk index and pollution load index), confirmed that the sediment samples were moderately to highly contaminated over extensive areas of the basin studied, with the greatest intensity and extent in the floodplain sediments.

The internal geometries of progradational units on the coastal plain in southeastern Spain (Carchuna Beach, Granada) since the maximum Holocene marine transgression (ca. 7000 cal BP) have been analysed using ground-penetrating radar (GPR). Radargram analysis shows the presence of sedimentary structures consistent with the progradation of coastal plains, interpreted as laminations associated with the foreset and topset. Laterally, five middle scale progradational units (H2, H3, H4, H5 and H6) are identified. Each of these units can be grouped into two major units. The general trend towards progradation is interrupted at the boundary of the units. Minor scale units (prograding wedges), deposited at topographically lower areas, are detected in GPR profiles. The radargrams also show channel erosional surfaces and sigmoidal landward dipping reflections interpreted as washover channel deposits, with the erosion and transference of sediments between the beach and the back-ridge domain. Furthermore, the saturation of coastline sediments with saltwater rapidly attenuates the GPR signal. Thus, the GPR is also a good tool to detect saltwater intrusions in shallow aquifers.

The corrosion of reinforcement caused by chloride ingress significantly reduces the length of the service life of reinforced concrete bridges. Therefore, the condition of bridges is periodically inspected by specially trained engineers regarding the possible occurrence of reinforcement corrosion. Their main goal is to ensure that the structure can resist mechanical and environmental loads and offer a satisfactory level of safety and serviceability. In the course of assessment, measuring the chloride content, through which corrosion could be anticipated and prevented, presents a possible alternative to visual inspections and corrosion tests that can only indicate already existing corrosion. It is hard to determine the cost-effectiveness and actual value of chloride content measurements in a simple and straightforward way. Thus, the main aim of the paper was to study the value of newly gained information, which is obtained when a chloride content in reinforced concrete bridges is measured. This value was here analyzed through the pre-posterior analysis of the cost of measurement and repair, taking into account different types of exposure and material properties for a general case. The research focus was set on the initiation phase in which there are no visible damages. A relative comparison of costs is presented, where the cost of possible reactive/proactive repair was compared with the maximum cost of measurement, while the measurement is still cost effective. The analysis showed a high influence of the initial probability of depassivation on the maximum cost of the cost-effective measurement, as well as a nonreciprocal relation of the minimum cost of cost-effective reactive repair with the measurement accuracy.

This paper presents results on the research currently being carried out with the objective of developing new electrochemistry-based processes to produce renewable synthetic fuels from liquefied biomass. In the current research line, the gas mixtures obtained from the typical electrolysis are not separated into their components but rather are introduced into a reactor together with liquefied biomass, at atmospheric pressure and different temperatures, under acidified zeolite Y catalyst, to obtain synthesis gas. This gaseous mixture has several applications, like the production of synthetic 2nd generation biofuel (e. g., biomethane, biomethanol, bio-dimethyl ether, formic acid, etc.). The behaviour of operational parameters such as biomass content, temperature and the use of different amounts of acidified zeolite HY catalyst were investigated. In the performed tests, it was found that, in addition to the synthesis gas (hydrogen, oxygen, carbon monoxide and carbon dioxide), methane was also obtained. Therefore, this research is quite promising, and the most favourable results were obtained by carrying out the biomass test at 300 °C, together with 4% of acidified zeolite Y catalyst, which gives a methane volumetric concentration equal to 35%.

This paper investigates the reliability of free and open-source algorithms used in the geographical object-based image classification (GEOBIA) of very high resolution (VHR) imagery surveyed by unmanned aerial vehicles (UAVs). UAV surveys were carried out in a cork oak woodland located in central Portugal at two different periods of the year (spring and summer). Segmentation and classification algorithms were implemented in the Orfeo ToolBox (OTB) configured in the QGIS environment for the GEOBIA process. Image segmentation was carried out using the Large-Scale Mean-Shift (LSMS) algorithm, while classification was performed by the means of two supervised classifiers, random forest (RF) and support vector machines (SVM), both of which are based on a machine learning approach. The original, informative content of the surveyed imagery, consisting of three radiometric bands (red, green, and NIR), was combined to obtain the normalized difference vegetation index (NDVI) and the digital surface model (DSM). The adopted methodology resulted in a classification with higher accuracy that is suitable for a structurally complex Mediterranean forest ecosystem such as cork oak woodlands, which are characterized by the presence of shrubs and herbs in the understory as well as tree shadows. To improve segmentation, which significantly affects the subsequent classification phase, several tests were performed using different values of the range radius and minimum region size parameters. Moreover, the consistent selection of training polygons proved to be critical to improving the results of both the RF and SVM classifiers. For both spring and summer imagery, the validation of the obtained results shows a very high accuracy level for both the SVM and RF classifiers, with kappa coefficient values ranging from 0.928 to 0.973 for RF and from 0.847 to 0.935 for SVM. Furthermore, the land cover class with the highest accuracy for both classifiers and for both flights was cork oak, which occupies the largest part of the study area. This study shows the reliability of fixed-wing UAV imagery for forest monitoring. The study also evidences the importance of planning UAV flights at solar noon to significantly reduce the shadows of trees in the obtained imagery, which is critical for classifying open forest ecosystems such as cork oak woodlands.

10,16-dihydroxyhexadecanoic acid obtained from agroresidual tomato waste, was oxidized to produce 7-oxohexadecanedioic acid in good yield (>70%) and purified without oxidation side products in one step. Polycondensation with 1,8-octanediol, yielded the polyester (poly(ω-carboxyl PA-co-OD)) with Mw = 2155.15 and Mn = 1637.27. The best enzymatic reaction conditions to get the polyester were using lipase CAL-B (%-by-wt relative to monomer) in toluene as a solvent for 1 h at 60 °C. The poly(ω-carboxyl PA-co-OD) was characterized by 1H- and 13C-NMR, mass spectrometry (MALDI-TOF) and the polyester film formed with a Langmuir-Blodgett Trough was analyzed by means of spectroscopic ellipsometry and atomic force microscopy.