Month: August 2024

Abstract

Parinari curatellifolia is the main species used to produce charcoal in Angola. Its chemical, anatomical, and thermal properties were analyzed. The bark is dark grey, rough, and corky, and the wood is brown to yellow-red. Compared to wood, bark fibers presented lower length, lumen, and wall thickness. There is not much difference between height and cell numbers of rays. Sieve tube elements appear solitary or in small groups (2–3 cells), and vessels were of two diameter classes but diffuse-porous. Bark basic density was lower than wood (505 kg.m^− 3vs. 580 kg.m^− 3). The mean chemical composition from bark vs. wood of P. curatellifolia was ash (3.2% vs. 1.6%), total extractives (12.2% vs. 10.0%), total lignin (42.4% vs. 28.4%), and suberin 5.4%. Families identified by GC-MS from DCM extracts were predominated by fatty acids in wood and triterpenoid contents in bark. Bark and wood had higher antioxidant activity in FRAP and DPPH methods. The bark had a monomeric lignin composition richer in guaiacyl-units (25.9% vs. 22.5%) and lower syringyl-units (5.7% vs. 8.5%). Potassium was the most abundant mineral, while the least was cadmium found in wood and bark. Regarding thermal properties, bark presented higher moisture content (9.0% vs. 8.0%), ash (3.33% vs. 1.61%), total volatiles (27.5% vs. 20.7%), lower fixed carbon (69.1% vs. 77.7%) and higher heating value (20.9 MJ/kg vs. 19.1 MJ/kg). According to these characteristics, both biomasses are interesting for developing more value-added products (e.g., charcoal, bio-chemicals with phytochemistry and pharmacology activities) besides burning under the context of biorefineries.

Abstract

This paper proposes a new complex background segmentation method based on the modified fully convolutional network semantic segmentation for noncontact cable vibration frequency estimation. The estimation of frequency from video data is challenged by the presence of background object motion, which directly impacts the accuracy of the video-based method. To address this issue, image tests were carried out among the existing model (U2-Net) to explore the effect of the efficient channel attention (ECA) and convolutional block attention module (CBAM) on cable segmentation performance. As a result, a relative optimal model was identified. This modified model was then used to remove the complex background, while retaining the vibration signals specific to the cable. Subsequently, phase matrices encoding cable vibration were calculated using a phase-based motion estimation algorithm at various cable locations. The modal response of the cable vibration was estimated using the complexity pursuit (CP) algorithm from the segmented video. Finally, the vibration frequency of the cable was estimated. The proposed method was validated on a small-scale cable model. The results are in good agreement with the values sampled by the accelerometer, with an average relative error of 4.50%. This estimation shows the significant potential of the proposed method in structural health monitoring.

Abstract

Semantic image segmentation is extensively used for automatic concrete crack detection. In previous studies on semantic image segmentation, concrete images were usually labeled as crack and noncrack zones, and recognition models were then trained using artificial neural networks. However, there is not enough edge information in concrete images for the trained model to identify effectively fine concrete cracks (widths < 0.1 mm). Furthermore, complex backgrounds in concrete images can cause false detections. To improve efficiency and reduce false detections, this study develops a three-stage automatic crack-width identification method for fine concrete cracks. First, a full crack skeleton information identification based on image segmentation is proposed. The performance of the mainstream image segmentation architectures, PSP-Net, Seg-Net, U-Net, and Res-Unet, are compared and analyzed, demonstrating that the Res-Unet-based crack skeleton segmentation is the most accurate at fine-crack detection and able to solve the information loss problem that occurs when learning the imbalanced data of fine concrete cracks. Second, a fractal dimension (FD)-based false detection removal process is applied to discriminate true cracks and false detections. The results show that false detections (line-like curves, shadows, and surface stains) can be removed, increasing the matching rate from 0.6476 to 0.8351. Finally, the FD features of the crack skeleton with maximum widths < 0.1 mm, crack widths in the range of 0.1–0.2 mm, and crack widths > 0.2 mm are calculated. Findings illustrate that the values of the FD feature for the three crack-width ranges are suitable for quantitative characterization of identified crack widths.

Abstract

In this paper, we incorporate spatial analysis to estimate industry-level productivity in the presence of inter-sectoral linkages. Since each industry plays a role in providing intermediate goods to other sectors, the interdependence of economic activities across industries is inevitable. We exploit the linkage patterns from the input-output relationship to define cross-industry dependencies in economic space. We propose a spatial stochastic frontier model, which extends the stochastic frontier model to a spatially dependent specification. The models are estimated using quasi-maximum likelihood methods. Applying the approach to U.S. industry-level data from 1947 to 2010, we find that sectoral dependencies are the consequences of indirect effects via the supply chain network of industries resulting in larger output elasticities as well as scale effects for the networked production processes. However, productivity growth is estimated comparably across different spatial and non-spatial model specifications.

Abstract

The Red Sea had inimitable geological ancient times and is considered a new ocean basin model. It has many islands of numerous sizes in the southern sector and a widespread group of shoals, such as Farasan (Saudi Arabia) and Dahlak (Eretria), due to its geological setting differences. In this work, a group of applications was used to provide a wider vision of the potential field, as well as to image the thermal and subsurface structures of the study area (Farasan and Dahlak Islands) using available marine potential field datasets (marine gravity and magnetic) and topographic and bathymetric datasets. These datasets were downloaded from the GEOSOFT server (Data sources: http://dap.geosoft.com/). We applied different filters of the marine potential field datasets data (e.g., horizontal gradient filter) to create a subsurface structure image. The horizontal gradient technique was used to locate density edges/boundaries from gravity data. The basement depth was displayed, as it was required during the Curie depth estimation by means of mathematical formulas. The profile ~ 500 km in length was selected to cross the study area and its surroundings so as to perform the joint 2D inversion modeling process. The results showed that the Farasan Islands have a shallower Curie point depth and basement relief than Dahlak Islands, indicating that both island groups were not isolated from each other but molded and formed independently. The results revealed that the islands’ different thermal systems were based on heat flow values calculated for each group.

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Abstract

The main goal of this work is summed up in a univariate chaotic analysis of the runoff series using a topological approach. As such, nineteen series of daily runoff from eight large watersheds in northern Algeria were analyzed. Firstly, preliminary analyses of two traditional dynamic and metric approaches have been tested. In the dynamic approach, three algorithms have shown that the largest Lyapunov exponent for the series is positive, which supports the hypothesis of the existence of chaos. In the metric approach, the Grassberger and Procaccia algorithm clearly shows the saturation of the correlation dimension, which indicates the existence of deterministic dynamics for all studied stations. Secondly, the application of the topological approach in this study constitutes in itself a new contribution to the demonstration of chaos in hydrology by using the recurrence plot (RP) and the recurrence quantification analysis (RQA). As such, the RP structures of the runoff series seem to be more comparable to chaotic systems. In addition, RQA parameters give high values of determinism and laminarity, which supports the hypothesis of the existence of deterministic chaos. The presence of chaos in the runoff series can be identified by the existence of a strong probability of recurrence, indicating a fairly low level of complexity and fairly high predictability. Ultimately, the comparison of these approaches together made it possible to confirm the hypothesis according to which the process generating the runoff series is deterministic and suggests low-dimensional chaotic dynamics.

Abstract

Anthropogenic land use has caused a major crisis to the biodiversity of stream fishes in recent decades, especially with regard to biotic homogenisation. Understanding the response of stream fishes to anthropogenic land use will help to promptly implement effective conservation measures. In this study, we investigated the effects of agriculture on fish diversity in streams in the Wannan Mountains, China. We predicted that agriculture would influence fish diversity by affecting local habitat conditions. The results showed that habitat conditions (e.g. water temperature, water width, water depth) differed significantly between disturbed and reference sites. The disturbed sites had high species richness due to the addition of translocated species outpacing the loss of endemic species. Moreover, fish assemblages showed taxonomic differentiation accompanied by functional homogenisation, which mainly resulted from the addition of translocated species with redundant functional traits. However, the emergence of homogenisation shows a time delay. The biotic differentiation of fish assemblages in agroecosystems is temporary in the Wannan Mountains, and homogenisation may eventually develop as stress intensifies. Thus, it is urgent and necessary to take effective conservation measures to delay or prevent fish assemblages from worsening in agroecosystems before homogenisation develops.