Depth Threshold Research Articles

Fluvio‐hydrological characteristics and diverse bedrock geology control the dynamic growth, truncation, and amalgamation of bedrock streambed and marine potholes

AbstractA total of 393 potholes (368 fluvial and 25 marine potholes) were studied at seven different sites in both the fluvial and marine environments. Diverse bedrock properties and large‐scale delivery of tools and grinders regulate the dynamic growth, truncation, and amalgamation of potholes. Therefore, the principal objectives of the study are (i) to examine the relationship between the growth of potholes and substrate lithological with structural characteristics (applying geospatial and Schmidt hammer for rock strength analysis) and (ii) to measure the morphology, and size of tools and grinders, processes of truncation and amalgamation in hydro‐geomorphic environment using various indices and field techniques. The result showed that large potholes are stretched in the direction of lineament axes and roughly parallel to the river flow direction. Here, the steady growth of pothole depth‐diameter is controlled by active bedrock structures, tools, or grinders, and monsoonal high‐velocity bank full discharge. Consequently, the deepening and widening of potholes are relatively slow at Bindu, Deuli, and marine beach Neil Island due to fewer structures and little supply of tools or grinders. In small stretches, (Damodar, Subarnarekha, and Rarhu) canyons and gorge‐like features (bedrock incision) are formed at Rajrappa, Bhakuyadi, and Guridih sites due to cyclic truncation and amalgamation. Truncation and amalgamation processes restrict the vertical depth threshold value of potholes within 3 m, particularly at Rajrappa, Bhakuyadi, and Guridih sites. Scientific study of the pothole's dynamic growth is greatly necessary for the different environmental engineering and river hydraulic projects like excavation, dredging, and dam or barrage construction. Successively, it is essential to compute the cost of rock excavation or dredging, primarily for the mechanical strength of the bedrock river channel and its stability.

Water depth threshold for carbon emissions and its temperature dependence in a typical saline-alkali wetland in Northeast China

Water depth threshold for carbon emissions and its temperature dependence in a typical saline-alkali wetland in Northeast China

Detecting the late Frasnian semichatovae Event on the deep shelf of North Gondwana

The semichatovae Event is a mid-late Frasnian (Late Devonian) episode of a major marine transgression that coincides with the spread of the conodont Palmatolepis semichatovae . The occurrence of this species and the associated event were therefore proposed to define the Middle-Late Frasnian boundary. As this species is not found on the north Gondwana platforms, this event is only documented on the Laurussia marine outer-shelves. As such, it is not known in the Frasnian reference section within the Upper Quarry Coumiac, located in the Montagne Noire (southern France). In this contribution, we have used a multidisciplinary approach that combines sedimentology, conodont assemblages, magnetic susceptibility, and concentrations of certain elements that are indicative of detrital components to precisely date this event in the absence of Palmatolepis semichatovae by means of global scale correlations. We found that a significant part of the environmental signal has been preserved in the strata, and we could locate the semichatovae transgressive event in the cross-section in the lower part of Zone FZ 11. During this period of recurrent environmental perturbations, conodonts responded to sea-level changes only above a certain depth threshold which is reached only with the semichatovae event.

Assessing Watershed Flood Resilience Based on a Grid-Scale System Performance Curve That Considers Double Thresholds

Enhancing flood resilience has become crucial for watershed flood prevention. However, current methods for quantifying resilience often exhibit coarse spatiotemporal granularity, leading to insufficient precision in watershed resilience assessments and hindering the accurate implementation of resilience enhancement measures. This study proposes a watershed flood resilience assessment method based on a system performance curve that considers thresholds of inundation depth and duration. A nested one- and two-dimensional coupled hydrodynamic model, spanning two spatial scales, was utilized to simulate flood processes in plain river network areas with detailed and complex hydraulic connections. The proposed framework was applied to the Hangjiahu area (Taihu Basin, China). The results indicated that the overall trend of resilience curves across different underlying surfaces initially decreased and then increase, with a significant decline observed within 20–50 h. The resilience of paddy fields and forests was the highest, while that of drylands and grasslands was the lowest, but the former had less recovery ability than the latter. The resilience of urban systems sharply declined within the first 40 h and showed no signs of recovery, with the curve remaining at a low level. In some regions, the flood tolerance depth and duration for all land use types exceeded the upper threshold. The resilience of the western part of the Hangjiahu area was higher than that of other regions, whereas the resilience of the southern region was lower compared to the northern region. The terrain and tolerance thresholds of inundation depth were the main factors affecting watershed flood resilience. The findings of this study provide a basis for a deeper understanding of the spatiotemporal evolution patterns of flood resilience and for precisely guiding the implementation and management of flood resilience enhancement projects in the watershed.

Exploring nanopore direct sequencing performance of forensic STRs, SNPs, InDels, and DNA methylation markers in a single assay

IntroductionThe field of forensic DNA analysis has undergone rapid advancements in recent decades. The integration of massively parallel sequencing (MPS) has notably expanded the forensic toolkit, moving beyond identity matching to predicting phenotypic traits and biogeographical ancestry. This shift is of particular significance in cases where conventional DNA profiling fails to identify a single suspect. Supplementing forensic analyses with estimated biological age may be valuable but involves a complex and time-consuming DNA methylation analysis. This study explores and validates the performance of a comprehensive forensic third-generation sequencing assay utilizing Oxford Nanopore Technologies (ONT) in an adaptive and direct sequencing approach. We incorporated the most widely used forensic markers, i.e., STRs, SNPs, InDels, mitochondrial DNA (mtDNA), and two methylation-based clock classifiers, thereby combining forensic genetic and epigenetic analysis in one single workflow. Methods and resultsIn our investigation, DNA from six anonymous individuals was sequenced using the ONT standard adaptive direct sequencing approach, reaching a mean percentage of on-target reads ranging from 6.6 % to 7.7 % per sample. ONT data was compared to standard MPS data and Illumina EPIC DNA methylation profiles. Basecalling employed recommended ONT software packages. TREAT was used for ONT-based analysis of autosomal and Y-chromosome STRs, achieving 90–92 % correct calls depending on allelic read depth thresholds. InDel analyses for two lower-quality samples proved challenging due to inadequate read depth, while the remaining four samples significantly contributed to the observed percentage markers (60.9 %) and correct calls (97.8 %). SNP analysis achieved a 98 % call rate, with only two mismatches and two missed alleles. ONT-generated DNA methylation data demonstrated Pearson’s correlation coefficients with EPIC data ranging from 0.67 to 0.97 for Horvath’s clock. Additional age-associated markers exhibited Pearson’s correlation coefficients with chronological age between 0.14 (ELOVL2) and 0.96 (FHL2) at read depths of <30 and <20, respectively. Despite excluding mtDNA from our targeted sequencing approach, adaptive proof-reading fragments covered the complete mtDNA with an average read depth of 21–72, showing 100 % concordance with reference data. DiscussionOur exploratory study using ONT adaptive sequencing for conventional forensic and age associated DNA methylation markers showed high sequencing accuracy for a significant number of markers, showcasing ONT as a promising (epi)genetic forensic method. Future studies must address three critical aspects: determining clear quantity and quality measures and detection thresholds for accuracy, optimizing input DNA quantity for forensic casework expectations, and addressing ethical considerations associated with phenotype and ancestry analysis to prevent ethnic biases.

Megabenthic Diversity Patterns on a Seamount in the Philippine Sea: Implications for Conservation Planning on the Kyushu-Palau Ridge.

The oligotrophic tropical western Pacific region is characterized by a high density of seamounts, with the Kyushu-Palau Ridge (KPR) being the longest seamount chain here. Effective spatial management plans for seamount ecosystems necessitate an understanding of distribution patterns and key environmental factors influencing benthic communities. However, knowledge regarding deep-sea biodiversity patterns over intricate topography remains limited. In this study, we investigated a seamount with a water depth of 522 m at the summit located in the southern section of KPR. Survey transects were conducted from 522 m to 4059 m. By analyzing video-recorded data obtained by a human-occupied vehicle (HOV) during dives and environmental variables derived from bathymetry, distinct assemblages were identified through noise clustering. α- and β-diversity patterns within the seamount megabenthic community were analyzed across the depth gradient, along with investigation of their environmental drivers. A total of 10,596 megafauna individuals were documented, categorized into 88 morphospecies and statistically separated into six distinct community clusters using noise clustering analysis. Species abundance and richness were highest within the 700-800 m water depth range, declining notably beyond 2100 m, indicating a critical threshold for habitat classification in this region. The β-diversity of megabenthic communities was high (0.836). Although β-diversity patterns along the depth gradient were mostly dominated by differences in species richness, the contribution of species replacement increased with depth, becoming dominant at depths greater than 3000 m. Depth emerged as the primary driver of spatial variation in community structure, while near-bottom current velocity, topographic parameters (bathymetric position index, slope), and substrate type also influenced the formation of microhabitats. The study highlights the depth gradients, thresholds, and other intricate environmental factors shaping the spatial heterogeneity of these communities. It provides valuable insights for the future development of effective survey and conservation strategies for benthic biodiversity on the KPR.

Utility of an Instantaneous Salt Dilution Method for Measuring Streamflow in Headwater Streams.

Streamflow records are biased toward large streams and rivers, yet small headwater streams are often the focus of ecological research in response to climate change. Conventional flow measurement instruments such as acoustic Doppler velocimeters (ADVs) do not perform well during low-flow conditions in small streams, truncating the development of rating curves during critical baseflow conditions dominated by groundwater inflow. We revisited an instantaneous solute tracer injection method as an alternative to ADVs based on paired measurements to compare their precision, efficiency, and feasibility within headwater streams across a range of flow conditions. We show that the precision of discharge measurements using salt dilution by slug injection and ADV methods were comparable overall, but salt dilution was more precise during the lowest flows and required less time to implement. Often, headwater streams were at or below the depth threshold where ADV measurements could even be attempted and transects were complicated by coarse bed material and cobbles. We discuss the methodological benefits and limitations of salt dilution by slug injection and conclude that the method could facilitate a proliferation of streamflow observation across headwater stream networks that are highly undersampled compared to larger streams.

Evaluating Changes in Adult Cochlear Implant Users' Brain and Behavior Following Auditory Training.

To describe the effects of two types of auditory training on both behavioral and physiological measures of auditory function in cochlear implant (CI) users, and to examine whether a relationship exists between the behavioral and objective outcome measures. This study involved two experiments, both of which used a within-subject design. Outcome measures included behavioral and cortical electrophysiological measures of auditory processing. In Experiment I, 8 CI users participated in a music-based auditory training. The training program included both short training sessions completed in the laboratory as well as a set of 12 training sessions that participants completed at home over the course of a month. As part of the training program, study participants listened to a range of different musical stimuli and were asked to discriminate stimuli that differed in pitch or timbre and to identify melodic changes. Performance was assessed before training and at three intervals during and after training was completed. In Experiment II, 20 CI users participated in a more focused auditory training task: the detection of spectral ripple modulation depth. Training consisted of a single 40-minute session that took place in the laboratory under the supervision of the investigators. Behavioral and physiologic measures of spectral ripple modulation depth detection were obtained immediately pre- and post-training. Data from both experiments were analyzed using mixed linear regressions, paired t tests, correlations, and descriptive statistics. In Experiment I, there was a significant improvement in behavioral measures of pitch discrimination after the study participants completed the laboratory and home-based training sessions. There was no significant effect of training on electrophysiologic measures of the auditory N1-P2 onset response and acoustic change complex (ACC). There were no significant relationships between electrophysiologic measures and behavioral outcomes after the month-long training. In Experiment II, there was no significant effect of training on the ACC, although there was a small but significant improvement in behavioral spectral ripple modulation depth thresholds after the short-term training. This study demonstrates that auditory training improves spectral cue perception in CI users, with significant perceptual gains observed despite cortical electrophysiological responses like the ACC not reliably predicting training benefits across short- and long-term interventions. Future research should further explore individual factors that may lead to greater benefit from auditory training, in addition to optimization of training protocols and outcome measures, as well as demonstrate the generalizability of these findings.

Research on the surface modification and microstructure evolution during gear profile grinding based on cellular automaton

The matrix structure of high-strength gears mainly comprises martensite with high stacking fault energy. The dominant mechanism of microstructure evolution in the surface layer during profile grinding is continuous dynamic recrystallization. However, the understanding of continuous dynamic recrystallization structure evolution during gear profile grinding remains limited. In this study, a predictive model based on cellular automaton for martensite structure evolution during gear profile grinding is proposed. Coupled with the finite element method, the microstructure evolution prediction of high-strength steel gears in profile grinding is conducted. The proposed model demonstrates good consistency with experimental data in calculating the proportion of low angle grain boundaries during grinding process. By combining experimental and theoretical prediction results, the mechanism of the influence of grinding depth on grain refinement in surface layer during gear profile grinding is elucidated. The dislocation density increases with the increase of grinding depth, leading to the generation and transformation of more subgrains. By analyzing the grain size and the proportion of subgrain boundaries, an optimal grinding depth threshold under dry grinding conditions is determined. This study provides valuable insights into the continuous dynamic recrystallization structure evolution during gear profile grinding process.

Field performance validation of the Louisiana balanced asphalt mix design framework

The balanced mix design (BMD) approach was implemented by agencies to complement the volumetric mix design method. The BMD approach addresses typical pavement distresses using mechanical tests. This study aimed to validate the Hamburg Wheel Track (HWT) rut depth and Semi Circular Bend (SCB) critical strain-energy release rate (Jc) thresholds specified in the Louisiana BMD framework. Seven field projects, including 13 pavement sections with 8–18 service years, were evaluated. Field distress data showed that the maximum HWT rut depth and minimum SCB Jc thresholds are effective parameters for assessing rutting and cracking performance, respectively.

Satellite-Based Background Aerosol Optical Depth Determination via Global Statistical Analysis of Multiple Lognormal Distribution

Determining background aerosol optical depth threshold value (BAOD) is critical to aerosol type identification and air pollution control. This study presents a statistical method to select the best BAOD threshold value using the VIIRS DB AOD products at 1 × 1 degree resolution from 2012 to 2019 as a major testbed. A series of multiple lognormal distributions with 1 to 5 peaks are firstly applied to fit the AOD histogram at each grid point, and the distribution with the highest correlation coefficient (R) gives preliminary estimations of BAOD, which is defined as either the intersection point of the first two normal distribution curves when having multiple peaks, or the midpoint between the peak AOD and the first AOD with non-zero probability when the mono peak is the best fit. Then, the lowest 1st to 100th percentile AOD distributions are compared with the preliminary BAOD distribution on a global scale. The final BAOD is obtained from the best cutoff percentile AOD distributions with the lowest bias compared with preliminary BAOD. Results show that the lowest 30th percentile AOD is the best estimation of BAOD for different AOD datasets and different seasons. Analysis of aerosol chemical information from MERRA-2 further supports this selection. Based on the BAOD, we updated the VIIRS aerosol type classification scheme, and the results show that the updated scheme is able to achieve reliable detection of aerosol type change in low aerosol loading conditions.

The Influence of B4C Film Density on Damage Threshold Based on Monte Carlo Method for X-ray Mirror.

The uniformity and consistency of X-ray mirror film materials prepared by experimental methods are difficult to guarantee completely. These factors directly affect the service life of free electron laser devices in addition to its own optical properties. Therefore, the quality of the film material, especially the density, has a critical effect on its application. Boron carbide film and monocrystalline silicon substrate were suitable examples to explore their influence of density on the damage threshold based on Monte Carlo and heat-conduction methods. Through simulation results, it was found that the change in film density could affect the energy deposition depth and damage threshold. When the film density was 2.48 g/cm3, it had relatively high damage threshold in all energy ranges. And then the specific incident parameter for practical application was investigated. It was found that the damage mechanism of the B4C/Si was the melting of the interface. And the damage threshold was also higher with the film density of 2.48 g/cm3. Therefore, it was recommended to maintain the density at this value as far as possible when preparing the film, and to ensure the uniformity and consistency of the film material.

Rapid sea level rise causes loss of seagrass meadows

As global declines in seagrass populations continue to cause great concern, long-term assessment of seagrass meadows show promise in furnishing valuable clues into fundamental causes of seagrass loss and drivers of environmental change. Here we report two long-term records of seagrass presence in western Gulf of Mexico coastal waters (Laguna Madre) that provided insight into their rapid decline in a relatively pristine ecosystem. Coincident with unprecedented increases in water depth starting in 2014 (14–25 mm y−1), monthly measurements at a deep edge fixed station revealed that two ubiquitous seagrass species (Halodule wrightii and Syringodium filiforme) vanished altogether in just five years; a subsequent basin-wide assessment revealed that seagrasses disappeared at 23% of 144 sentinel stations. Models that incorporate differing sea level rise scenarios and water depth thresholds reveal potential global losses of seagrass habitat (14,000 km2), with expansion into newly created shallow habitats constrained by altered natural shorelines.

Amplitude Modulation Perception and Cortical Evoked Potentials in Children With Listening Difficulties and Their Typically Developing Peers.

Amplitude modulations (AMs) are important for speech intelligibility, and deficits in speech intelligibility are a leading source of impairment in childhood listening difficulties (LiD). The present study aimed to explore the relationships between AM perception and speech-in-noise (SiN) comprehension in children and to determine whether deficits in AM processing contribute to childhood LiD. Evoked responses were used to parse the neural origins of AM processing. Forty-one children with LiD and 44 typically developing children, ages 8-16 years, participated in the study. Behavioral AM depth thresholds were measured at 4 and 40 Hz. SiN tasks included the Listening in Spatialized Noise-Sentences Test (LiSN-S) and a coordinate response measure (CRM)-based task. Evoked responses were obtained during an AM change detection task using alternations between 4 and 40 Hz, including the N1 of the acoustic change complex, auditory steady-state response (ASSR), P300, and a late positive response (late potential [LP]). Maturational effects were explored via age correlations. Age correlated with 4-Hz AM thresholds, CRM separated talker scores, and N1 amplitude. Age-normed LiSN-S scores obtained without spatial or talker cues correlated with age-corrected 4-Hz AM thresholds and area under the LP curve. CRM separated talker scores correlated with AM thresholds and area under the LP curve. Most behavioral measures of AM perception correlated with the signal-to-noise ratio and phase coherence of the 40-Hz ASSR. AM change response time also correlated with area under the LP curve. Children with LiD exhibited deficits with respect to 4-Hz thresholds, AM change accuracy, and area under the LP curve. The observed relationships between AM perception and SiN performance extend the evidence that modulation perception is important for understanding SiN in childhood. In line with this finding, children with LiD demonstrated poorer performance on some measures of AM perception, but their evoked responses implicated a primarily cognitive deficit. https://doi.org/10.23641/asha.25009103.

Multi-Modal Fusion Based on Depth Adaptive Mechanism for 3D Object Detection

Lidars and cameras are critical sensors for 3D object detection in autonomous driving. Despite the increasing popularity of sensor fusion in this field, accurate and robust fusion methods are still under exploration due to non-homogenous representations. In this paper, we find that the complementary roles of point clouds and images vary with depth. An important reason is that the point cloud appearance changes significantly with increasing distance from the Lidar, while the image's edge, color, and texture information are not sensitive to depth. To address this, we propose a fusion module based on the Depth Attention Mechanism (DAM), which mainly consists of two operations: gated feature generation and point cloud division. The former adaptively learns the importance of bimodal features without additional annotations, while the latter divides point clouds to achieve differential fusion of multi-modal features at different depths. This fusion module can enhance the representation ability of original features for different point sets and provide more comprehensive features by using the dual splicing strategy of concatenation and index connection. Additionally, considering point density as a feature and its negative correlation with depth, we build an Adaptive Threshold Generation Network (ATGN) to generate the depth threshold by extracting density information, which can divide point clouds more reasonably. Experiments on the KITTI dataset demonstrate the effectiveness and competitiveness of our proposed models.

Removing Friction and Bark Improves Drill Resistance Data for Selection on Wood Density in Pinus taeda Plantations

Abstract Wood density is used for genetic selection because of its association with wood quality. Traditional assessments of wood density, such as volumetric measurement and X-ray densitometry, are labor intensive and time consuming. Drill resistance (measured with a Resistograph) is faster and gives an indirect assessment of wood density. The Resistograph generates thousands of data points for each tree that must be summarized. The data include bark and air as the drill enters and exits the bole, as well as friction that builds on the drill shaft. This study evaluated data processing methods for drill resistance to improve correlation with wood density, with a focus on practical implementation by breeding programs. We compared methods that thoroughly removed bark, air, and friction, as well as simple methods based on expected bark thickness and depth to the pith. The most thorough method produced the highest phenotypic correlation with density (rp = 0.81). All methods that excluded data after the drill exits the tree had very strong genetic correlations (rg &gt; 0.92), although avoiding bark gave a noticeable increase in genetic correlation. Unprocessed drill resistance had unacceptably low phenotypic correlations (rp = 0.38) and the lowest genetic correlation observed, although it was still very high (rg = 0.91). For tree breeding programs, we recommend developing reasonable bark and pith depth thresholds and using simple rules to avoid bark and friction.

Recognition and position estimation method for stacked untextured parts

To address the challenge of recognizing and estimating the position of untextured stacked parts, which are common in industrial environments, this study proposes an integrated approach that incorporates the YOLOv7 target detection algorithm and point cloud alignment techniques. First, the YOLOv7 algorithm is utilized to quickly identify and locate the 2D position of the part, followed by a mapping technique to transform the 2D region of interest (ROI) into the corresponding 3D point cloud region. In the point cloud processing stage, depth threshold segmentation and Euclidean clustering segmentation methods are used to separate the target part from the background and other interfering objects. The pose estimation stage uses the SAC-IA algorithm for coarse alignment, followed by an improved ICP algorithm that introduces an adaptive weighting mechanism and a global optimization strategy for fine alignment to obtain the final 6D pose of the part. The improved strategy significantly optimizes the point-pair selection and alignment process and enhances the robustness and accuracy of the algorithm. Through experimental validation on publicly available part piece datasets, the results show that the part identification and pose estimation method proposed in this study can realize fast and accurate identification and pose estimation of different shapes, non-textured, and scattered stacked parts, where the position error can reach up to 1mm and the angular error within 1°, which meets the requirements of practical applications.

COMPREHENSIVE POTHOLE DETECTION SYSTEM FOR ROAD MAINTENANCE AND SAFETY USING IMAGE PROCESSING AND STEREO VISION

This paper introduces a systematic approach to pothole detection, emphasizing its significance in road maintenance and safety. The proposed system is comprised of meticulously designed modules that collectively contribute to achieving accurate and effective results. Commencing with data collection through cameras capturing road areas of interest, the images undergo manual cropping and resizing for standardization. The core principle of the system revolves around image enhancement, involving grayscale conversion, application of blurring techniques, and adjustments to brightness and contrast. Automatic thresholding extracts essential information encoded within pixels, paving the way for precise edge detection refined through morphological operations. The focus then shifts to pothole detection, incorporating a stereo camera setup to calculate depth and disparity of road surfaces. Critical steps, including image rectification, correspondence matching, and disparity calculations, contribute to the accurate identification and delineation of potholes using depth thresholds. Subsequent modules employ K-Means clustering to segregate regions of interest from the image background, and post-processing steps, including filtering, masking, and refinement, fine-tune the images. Utilizing the HSV color space for grayscale image refinement and the connected component method to isolate white pixel objects further enhance the system's capability. The final step involves the addition of bounding boxes around identified potholes, streamlining their identification process. This comprehensive methodology ensures effective image processing, precise pothole detection, and contributes significantly to road safety and maintenance efforts.

The Impact of Groundwater Burial Depth on the Vegetation of the Dariyabui Oasis in the Central Desert

Vegetation and groundwater are important components of the ecological environment of oases in desert hinterlands and their relationship is crucial to ecosystem stability. In this study, Sentinel-2 data for 2016–2022 and measured groundwater burial depths were analysed for the Dariyabui Oasis in the hinterland of the Taklamakan Desert. The spatial and temporal changes in vegetation and groundwater burial depth from 2019 to 2022 were analysed based on the image–element dichotomous model of the normalised difference vegetation index, utilising the inverse distance weight interpolation method, cubic curve regression, image–element difference, slope trend analysis, and the Markov transfer matrix for determining the temporal and spatial response law between the two. Finally, the threshold value of groundwater burial depth for different vegetation cover types was clarified. The fractional vegetation cover of the Dariyabui Oasis showed a slight increase from 2016 to 2022. Vegetation in the northwest and southeast of the oasis increased, whereas vegetation decreased in the mid-north and northeast regions; 5.14% of the total area experienced increased coverage, whereas 3.35% experienced decreased coverage. The depth of groundwater in the oasis showed a pattern of gradual increase from the entrance to the end of the oasis, that is, south to north. The depth of groundwater in the oasis from 2019 to 2022 was stable, with a 4-year average depth of 4.1069 m and a maximum fluctuation of 0.4560 m. The interannual changes in the groundwater level showed an increasing trend in January–April, while groundwater levels showed a decreasing trend in May–July and August–October and remained constant in June–July and October–December. Oasis vegetation cover showed a negative correlation with groundwater depth, with a depth interval for the highest low-cover vegetation distribution of 3–6 m, and an ultimate depth threshold of 7 m. The depth interval with the highest medium-cover vegetation distribution was 3–4 m, that with the highest high-cover distribution was 2–4 m, and the ultimate depth threshold was 6 m. The depth of the oasis ranged from 3 to 6 m and the ultimate depth threshold was 7 m.

The African Continental Free Trade Area and Financial Development for Female Labour Force Participation in Africa

The study assesses how financial development dynamics can moderate the incidence of African trade integration on female labour force participation. The focus is on 47 African countries for the period 1995 to 2019 and the empirical evidence is based on Fixed Effects regressions. The findings show that financial development moderates African trade integration to engender an overall positive effect on female labour force participation. Moreover, financial depth proxied by liquid liabilities should reach a threshold of approximately 14.304 (% of GDP) in order to completely dampen an initial negative incidence of intra-African trade integration on female labor force participation. It follows that financial development becomes a necessary and sufficient condition to moderate intra-African trade integration in order to positively affect female labor force participation only when the established threshold of financial depth is attained. Other policy implications are discussed.