Deep Areas Research Articles

Passable area segmentation for open-pit mine road from vehicle perspective

Recognition of passable areas of mine roads based on vehicle perspective is crucial for autonomous vehicles to drive in unmanned open-pit mine scenes. In the past few years, deep learning-based passable area recognition methods have been proven feasible. However, these works have mainly focused on structured urban road environments. Few works designed for mine road region detection due to dataset scarcity. In this article, we propose the mine road scapes segmentation dataset, which is collected from open-pit mine road environments. The dataset is collected from different mine areas, covers different daytime and dusk periods, and annotates the road and non-road areas in detail. Besides, a novel transformer-based road segmentation network is proposed, which is designed for the mine road characteristics of texture and distribution. The segmentation network is composed of an improved transformer feature extraction backbone, which can simultaneously aggregate global context and local detail information, and realize pixel-level recognition. We solve the problem of mine road segmentation benchmark under vehicle perspective. Moreover, by comparing the results of current mainstream methods on the mine road dataset, our method obtains state-of-the-art performance.

A System‐Level Feasibility Study of a Lead‐Free Ultrasonically Powered Light Delivery Implant for Optogenetics

Body implants play a crucial role in clinical applications, encompassing data acquisition, diagnosis, and disease treatment. However, challenges in size, power consumption, and biocompatibility, particularly in brain applications requiring small, battery‐free devices for deep areas, hinder their development. Despite potential advances through simplified, single‐purpose devices, such as recording or stimulation, overcoming the power and biocompatibility issues remains a hurdle. Addressing this, the article introduces an ultrasonically powered light delivery implant (LDI) utilizing lead‐free piezoelectric material (Li0.08K0.46Na0.46) NbO3 to harvest energy from external ultrasonic waves. The prototype includes a piezoelectric cube, a chip fabricated in 180 nm CMOS technology, and a microscale light‐emitting diode (μ‐LED) for optogenetics. Achieving an end‐to‐end efficiency of 0.75%, the LDI holds promise for various optogenetic studies, particularly in animal studies targeting specific brain areas for treating Parkinson's disease. The delivered optical power on the μ‐LED surface, at 14.1 mW mm−2, presents applicability to diverse studies involving specific opsins.

A Novel High‐Resolution In Situ Tool for Studying Carbon Biogeochemical Processes in Aquatic Systems: The Lake Aiguebelette Case Study

AbstractLakes and reservoirs are a significant source of atmospheric methane (CH4), with emissions comparable to the largest global CH4 emitters. Understanding the processes leading to such significant emissions from aquatic systems is therefore of primary importance for producing accurate projections of emissions in a changing climate. In this work, we present the first deployment of a novel membrane inlet laser spectrometer (MILS) for fast simultaneous detection of dissolved CH4, ethane (C2H6) and the stable carbon isotope of methane (δ13CH4). During a 1‐day field campaign, we performed 2D mapping of surface water of Lake Aiguebelette (France). Average dissolved CH4 concentrations and δ13CH4 were 391.9 ± 156.3 nmol L−1 and −67.3 ± 3.4‰ in the littoral area and 169.8 ± 26.6 nmol L−1 and −61.5 ± 3.6‰ in the pelagic area. The dissolved CH4 concentration in the pelagic zone was 50 times larger than the concentration expected at equilibrium with the atmosphere, confirming an oversaturation of dissolved CH4 in surface waters over shallow and deep areas. The results suggest the presence of CH4 sources less enriched in 13C in the littoral zone (presumably the littoral sediments). The CH4 pool became more enriched in 13C with distance from shore, suggesting that oxidation prevailed over epilimnetic CH4 production and it was further confirmed by an isotopic mass balance technique with the high‐resolution data. This new in situ fast response sensor allows one to obtain unique high‐resolution and high‐spatial coverage data sets within a limited amount of survey time. This tool will be useful in the future for studying processes governing CH4 dynamics in aquatic systems.

Feasibility Study of Numerical Calculation and Machine Learning Hybrid Approach for Renal Denervation Temperature Prediction

Transcatheter renal denervation (RDN) is a novel treatment to reduce blood pressure in patients with resistant hypertension using an energy-based catheter, mostly radio frequency (RF) current, by eliminating renal sympathetic nerve. However, several inconsistent RDN treatments were reported, mainly due to RF current narrow heating area, and the inability to confirm a successful nerve ablation in a deep area. We proposed microwave energy as an alternative for creating a wider ablation area. However, confirming a successful ablation is still a problem. In this paper, we designed a prediction method for deep renal nerve ablation sites using hybrid numerical calculation-driven machine learning (ML) in combination with a microwave catheter. This work is a first-step investigation to check the hybrid ML prediction capability in a real-world situation. A catheter with a single-slot coaxial antenna at 2.45 GHz with a balloon catheter, combined with a thin thermometer probe on the balloon surface, is proposed. Lumen temperature measured by the probe is used as an ML input to predict the temperature rise at the ablation site. Heating experiments using 6 and 8 mm hole phantom with a 41.3 W excited power, and 8 mm with 36.4 W excited power, were done eight times each to check the feasibility and accuracy of the ML algorithm. In addition, the temperature on the ablation site is measured for reference. Prediction by ML algorithm agrees well with the reference, with a maximum difference of 6 °C and 3 °C in 6 and 8 mm (both power), respectively. Overall, the proposed ML algorithm is capable of predicting the ablation site temperature rise with high accuracy.

The Performance of Anidolic Light Pipe Daylighting System in Office Building (Case Study : Bosowa Tower Makassar)

Producing available daylight in buildings is an important issue for reasons of energy efficiency. To make an office space that is comfortable for employees, the concept of daylighting quality must be considered. This research aims to examine intensity of natural lighting in the workspace of Bosowa Tower Makassar, and apply Anidolic Light Pipe (ALP) daylighting system in reducing the illumination value in the building perimeter area and increasing the illumination value in the deeper area. The research used quantitative methods, collecting information about measurements of the workspace’s existing condition and evaluating ALP performance on a physical model. The building’s south and north sides indicated high illumination values, especially under clear sky condition. On the other hand, the deeper part of the building receives little natural light and is therefore rather dark. According to ALP performance tests with physical scale model simulation in an overcast sky condition, it can be concluded that this daylighting system can reduce the illumination value by 15,01% at a distance of 0,5 m from the window due to its shading external, and was able to increase the illumination value by 394,92% at a distance of 11,5 m from the window.

Critical evaluation of effectiveness of magnetic resonance imaging for targeting of deep brain areas in movement disorders surgery

Critical evaluation of effectiveness of magnetic resonance imaging for targeting of deep brain areas in movement disorders surgery

Poster Session I: Noninvasive neuromodulation of subcortical visual pathways with transcranial focused ultrasound.

Transcranial ultrasound stimulation (TUS) is an emerging tool to noninvasively modulate neural activity in deep brain areas. In preparation for our first in-human TUS studies, we targeted TUS to the lateral geniculate nucleus (visual thalamus) in a large mammal (sheep). Full-field light flash stimuli were presented with or without concomitant TUS in randomly interleaved trials. Similar to what has previously observed by Fry et al (Nature 1959) in cats, EEG visual-evoked potentials (VEPs) were reversibly suppressed by TUS to the LGN. No changes in VEPs were observed in sheep who received sham-TUS to a control site in the basal ganglia, ruling out potential transducer auditory-somatosensory confounds. Magnetic resonance acoustic radiation force imaging (MR-ARFI), a technique to measure the ultrasound focus in situ, showed a focal volume of microscopic displacement at the expected target. Excitingly, MR-ARFI predicted the suppressive effect on VEPs in individual subjects, suggesting that MR-ARFI can be used to confirm TUS targeting and estimate neurophysiological impact. We are now translating this paradigm into human, targeting TUS to the LGN while participants perform a contrast detection task with EEG recording of steady-state VEPs. MR-ARFI will be measured to evaluate targeting and estimate TUS dosage in each participant. This work provides the foundation for a dissection of the roles of different subcortical nuclei in different aspects of human vision.

Impact of the Deep and Comprehensive Free Trade Zone on the Economic Development of the Republic of Moldova

The Republic of Moldova, being a state with a small economy, has considerably diversified its sales markets, focusing primarily on the European Union market, which currently absorbs more than half of its exports. The present study tries to highlight the benefits of the Association Agreement and the Deep and Comprehensive Free Trade Area (DCFTA) implementation, which contributes to increasing the competitiveness of domestic companies on European markets and the liberalization of trade in goods and services. In conclusion, some measures are highlighted that are necessary to be implemented by the Republic of Moldova, in order to ensure the economy reorientation towards export by diversifying both the geographical structure and products in particular, improving commercial policy regulations, product quality, attracting investments foreign direct, the elimination of corruption.

GAS GEOCHEMICAL ANOMALIES IN THE BOTTOM SEDIMENTS OF THE TATAR TROUGH (SEA OF JAPAN)

The paper presents the results of gas geochemical and lithogeochemical studies of bottom sediments in the Tatar Strait trough (Sea of Japan) based on cruise data from the R/V “Akademik M.A. Lavrentyev” (LV-81 and LV-85). Anomalies of hydrocarbon gases (HCG) and chemical elements in surface bottom sediments were determined. It has been established that sediments with anomalous methane contents are significantly enriched in Mn, Sc, V, Co, Ni, Cu, As, Se, Mo, Cd, Sb, Te, Tl, U, the concentration coefficients (Kk) of which are 1.3–5.9 times higher than their similar values at other stations. The data obtained allow us to assume the presence of gas sources of hydrocarbon migration, the continental slope and deep water area of the Tatar trough is promising for setting up detailed work on the assessment of oil and gas potential and gas hydrate content.

ФЕНОМЕНОЛОГІЯ МІСТИЦИЗМУ ГЕРДИ ВАЛЬТЕР І БОГОСЛОВСЬКА АНТРОПОЛОГІЯ ЕДИТ ШТАЙН: ІСТОРИКО-ФІЛОСОФСЬКИЙ ПІДХІД

This article examines two prominent aspects of contemporary philosophical and religious discourse: the phenomenology of mysticism in the work of Gerda Walther and theological anthropology presented in the writings of Edith Stein. Phenomenology of mysticism is one of the most interesting topics in modern philosophy and religious studies. This deep research area examines and analyzes spiritual experience and mysticism through the lens of a philosophical approach called phenomenology. Two outstanding women and friends, Gerda Walther and Edith Stein, made a significant contribution to the development of this field. Deep reflections on the nature of mysticism, faith and theological anthropology are found in their research works. Phenomenology of mysticism allows us to better understand the nature of spiritual experience and inner experiences, and also to show the phenomena of mysticism through the phenomenological method. The works of G. Walther highlight the key aspects of this approach. On the other hand, E. Stein offers theological anthropology, which examines faith and religious experience in the context of human existence and through the relationship with God. Her works provide a strong conceptual basis for understanding faith and its role in the modern world. Therefore, the article is an attempt to consider their thoughts and contribution to the development of the phenomenology of mysticism and theological anthropology and their contribution to philosophy and religious studies.

The impact of new western land and sea corridor development on port deep hinterland transport service and route selection

New transportation corridor development aims to provide more convenient transportation conditions for port deep hinterland areas and to enhance the two-way opening of land and sea through the utilization of various transport modes, such as railroad, highway, and water transportation. In this paper, the microcontainer transport service and route selection problem is introduced within a new transportation corridor context, and a decision-making tool is provided for shippers to develop door-to-door service plans. A multiobjective 0–1 planning model is constructed with the objective of minimizing the total transportation cost, transportation time, and carbon emissions. The loading and unloading time windows of railroad and waterway transportation, as well as the time window of consignee receipt, are considered in model construction to obtain the nondominated Pareto optimal front. The validity of both the model and algorithm is demonstrated in this paper by using the Chongqing-Hamburg and Chengdu-Hamburg routes, following the development of the New Western Land and Sea Corridor (NWLSC), as examples. The example results show that the NWLSC is appealing for time-sensitive cargoes, and its economic benefits can be enhanced if relevant policies such as railroad freight reductions are supported. The findings in this paper can provide decision support for western provinces in the implementation of targeted policies to regulate and optimize the regional transportation structure, which can further promote the opening up of western Chinese provinces as well as the integrated and coordinated development of coastal and inland regions, providing practical value for reducing carbon emissions.

Assessment and Characterization of Woji Creek Riverbed in Port Harcourt, Rivers State, Nigeria, Utilizing Side Scan Sonar Technology

Woji Creek plays a crucial role in vessel navigation, supports diverse flora and fauna habitats, and sustains local livelihoods. However, human activities and natural events have led to changes in its riverbed over time. Given its significance for coastal stability and geomorphology, there is a pressing need to classify, evaluate, and ensure its environmental sustainability. The primary objective of this study is to employ side scan sonar technology to classify and assess the riverbed of Woji Creek in Port Harcourt, Nigeria. The study aims to classify the riverbed, analyze water depth variations, evaluate navigational suitability, and determine turbidity levels within the creek. To achieve these objectives, the methodology involved acquiring Side-Scan Sonar (SSS) and Sub-bottom profile data. These datasets underwent backscatter processing to create geocoded backscatter images. Feature points were extracted and matched from these images to derive riverbed classification, depth categories, water volume distribution, and river turbidity analysis. The riverbed classification revealed the presence of three primary sediment types: Clayey Silty Sand, Silty Clay, and Silty Sand, each with distinct implications for navigation. Shallow, Moderate, Deep, and Very Deep areas were identified within Woji Creek, each influencing navigational conditions. Additionally, the water volume distribution analysis provided essential insights into depth limitations and route planning.
 Moreover, the assessment of river turbidity identified low, moderate, and high turbidity zones, reflecting water clarity and suspended particle levels. These findings serve as invaluable decision support tools for navigation planning and management in Woji Creek, offering comprehensive insights into the riverbed, depth suitability, volume distribution, and water quality. Leveraging this data can enhance strategic decision-making processes and contribute to the sustainable management of this vital waterway.

Identification of modern meteoric water, glacial meteoric water, and fossil seawater in a deep borehole at the coastal area of Horonobe, north Japan, using groundwater dating and paleoclimatic proxy methods

Groundwater flow in deep areas of coastal regions has attracted significant attention for geological radioactive waste disposal or geological CO2 storage. To investigate groundwater flow in coastal areas, groundwater dating methods with the potential to assess slow groundwater flow were used at depths of up to 1200 m at Hamasato, Horonobe, northern Japan. Multiple groundwater dating methods were applied using pore water in drilling core and pumping groundwater. This study shows that modern meteoric water, glacial meteoric water, and fossil seawater are distributed in sand and silt layers at 300–360 and 90–300 m in depth and in silt and mud layers below 800 m in depth, respectively. Modern meteoric water infiltrated after and glacial meteoric water infiltrated during the latest glacial period were identified using δD and δ18O values, estimated recharge temperature from noble gas concentrations, and 14C concentrations. The estimated recharge temperatures of modern and glacial meteoric waters were 8.1 ± 2.0 and 2.1 ± 2.0 °C, respectively, whereas the δD and δ18O values were −68 ± 3‰ and −10.3 ± 0.2‰, −81 ± 2‰ and −11.4 ± 0.3‰, respectively. The 14C age of modern meteoric water was 10–16 ka. However, the 14C age of glacial meteoric water could not be estimated because it was highly diluted by 14C-free CO2 from methanogenesis and marine carbonate dissolution. Fossil seawater was identified using δD, δ18O, 36Cl, and 4He. δD and δ18O values underwent water-rock interaction and approached inland fossil seawater with increasing depth. 36Cl/Cl values did not reach secular equilibrium in situ in the Yuchi Formation due to its relatively short geological age and consolidation-induced porosity changes. However, the Yuchi Formation seawater is considered extremely old because its 36Cl/Cl ratio is higher than that of modern seawater as a result of 36Cl production, which also explains the observed 36Cl/Cl increases with depth toward the secular equilibrium ratio (36Cl/Clse). 4He concentrations were in the order of 10−6 ccSTP/gw, corresponding to an in situ accumulation age of 1–2 Ma, neglecting the external flux. The contribution of external flux could be negligible for the short geological age and rapid sedimentation rates. 4He ages were equivalent to the geological age of the Yuchi Formation. Core investigations can interpolate groundwater investigations because cores, particularly those from low-hydraulic conductivity layers, can be collected continuously. In addition, stable and radioactive isotopes and noble gases can help identify modern meteoric water, glacial meteoric water, and fossil seawater, assisting in understanding the groundwater flow velocity.

Bottom fishing beyond trawling. Spatio-temporal trends of mobile and static bottom fisheries on benthic habitats

The effective implementation of the Marine Strategy Framework Directive (MSFD) and formulation of spatial management policies rely heavily on a good understanding of the extent, distribution and intensity of human pressures and their overlap with benthic habitats. However, little research has quantified the pressure and impact on the seabed of bottom contact gears other than trawling. This study analyzes the spatio-temporal trends of fishing pressure of bottom-contact gear, including mobile and static gears, and asseses its relative importance within each benthic habitat. To achieve this, a set of pressure indicators was calculated using vessel monitoring system information from the Bay of Biscay for 2009–2020. Nested General Linear Models were conducted to assess the temporal fluctuation of fishing activities. While trawlers exhibited wider and higher levels of fishing intensity over sedimentary habitats, set gillnet and set longliners were distributed among more sensitive habitats, such as biogenic reef habitats. Additionally, there was a significant decrease in fishing effort in recent years along Offshore circalittoral habitats, particularly with respect bottom trawling, in contrast to increasing fishing intensity in deeper areas. These results emphasize that from a conservation perspective and MSFD implementation, there is a need to quantitatively analyze the fishing footprint of all fishing gears, including static gears in the regional assessments, and the necessity to progress in adapting impact indicators to these fishing activities. The findings are discussed based on the potential impacts of policies such as the MSFD and can assist managers in developing spatial protection measures.

Subclinical macular vessel density alterations in patients with juvenile systemic lupus erythematosus.

The aim is to evaluate subclinical alterations of macular microvasculature in patients with juvenile systemic lupus erythematosus (JSLE). This is a cross-sectional study of 29 eyes of 29 patients diagnosed with JSLE and 29 eyes of 29 healthy controls. The vessel density (VD) of the superficial capillary plexus (SCP), intermediate capillary plexus (ICP), deep capillary plexus (DCP), choriocapillaris (CC), and area of foveal avascular zone (FAZ) was measured using optical coherence tomography angiography (OCTA). A multiple linear regression analysis was performed to evaluate the effects of disease duration and activity on OCTA parameters. The VD of total (p = .007) and the superior (p = .014) and inferior (p = .004) quadrants in SCP was significantly lower in children with JSLE. The VD of total and all quadrants in ICP decreased (p = .015, p = .0045, p = .015, p = .033), except that of the temporal quadrant (p = .366). The total (p = .011) and superior quadrant (p<.01) DCP-VD showed a significant decrease in children with JSLE. The decrease in VD in the total (p = .003) and nasal quadrant (p = .017) of CC was also remarkable. No significant difference in the FAZ area was found between the two groups (p = .774). Multiple linear regression analyses adjusted for age, spherical equivalent, and intraocular pressure were conducted. No contributing factor to OCTA parameters was found. We demonstrated decreased VD in all layers of the retina and CC in patients with JSLE without ocular involvement. Early screening and close follow-up were recommended.

Coupling deformation mechanism of geological stratification and metro tunnel structure in deep quaternary sedimentary area

Coupling deformation mechanism of geological stratification and metro tunnel structure in deep quaternary sedimentary area

Research on top-level planning for sustainable high-quality development of China’s largest scale deep coal mining area

Coal is the dominant energy source in China, as it has an advantageous position in terms of resource distribution. Against the backdrop of China’s high-quality economic development and the global energy crisis, after nearly a decade of preparation, the Xinjie Taigemiao Mine Area (XTMA) has entered the substantial planning and design stage. Based on the resource development conditions and the background of the times of XTMA, the paper provides an in-depth analysis of the connotation and characteristics of XTMA’s high-quality development. Subsequently, the overall development concept of “1358” for XTMA is proposed, which includes one strategic objective, three new models, five attribute goals, and eight assessment indicators. Based on this, a top-level planning and design for the implementation of high-quality development in XTMA is carried out comprehensively from aspects such as spatial layout, intelligent safety, integrated zero-carbon, ecological green, technological innovation, cluster management, and harmonious happiness. Finally, we look forward to the long-term blueprint for high-quality development of the XTMA and put forward urgent recommendations for current construction. The research on the high-quality development plan of XTMA will promote the development of China’s coal industry and is of great significance.

Research on Obstacle Detection and Avoidance of Autonomous Underwater Vehicle Based on Forward-Looking Sonar.

Due to the complexity of the ocean environment, an autonomous underwater vehicle (AUV) is disturbed by obstacles when performing tasks. Therefore, the research on underwater obstacle detection and avoidance is particularly important. Based on the images collected by a forward-looking sonar on an AUV, this article proposes an obstacle detection and avoidance algorithm. First, a deep learning-based obstacle candidate area detection algorithm is developed. This algorithm uses the You Only Look Once (YOLO) v3 network to determine obstacle candidate areas in a sonar image. Then, in the determined obstacle candidate areas, the obstacle detection algorithm based on the improved threshold segmentation algorithm is used to detect obstacles accurately. Finally, using the obstacle detection results obtained from the sonar images, an obstacle avoidance algorithm based on deep reinforcement learning (DRL) is developed to plan a reasonable obstacle avoidance path of an AUV. Experimental results show that the proposed algorithms improve obstacle detection accuracy and processing speed of sonar images. At the same time, the proposed algorithms ensure AUV navigation safety in a complex obstacle environment.

Image Retrieval Performance Tuning Using Optimization Algorithms

NThe relentlessness of modern life's pace has pushed many people to look for ways to save time so they may continue living the way they choose. The management of traffic presents a considerable obstacle due to the fact that a large proportion of persons have difficulties associated with transportation. As a result, fixing traffic problems becomes an absolute need. Machine learning stands out as a useful resource in this setting, providing deeper understanding and better analytical tools for sifting through complicated statistical data. The feasibility of travel for both large and light vehicles may be quickly assessed by experts, allowing for more timely and well-informed decisions. These evaluations serve as the basis for developing separate roadways, laws and sets of rules for various classes of vehicles. This study examines six characteristics of vehicular traffic and travel situations over 38,114 occurrences. Our goal is to improve traffic management through prediction and optimization using six different optimizers from the deep learning area. Based on observed patterns of truck traffic over a certain time period, these methods help determine optimal distribution paths for sent commodities. Six different deep learning optimizer models are compared and contrasted in this study. The objective is to use these examples to determine which optimizer is best. It's not easy to pick the best optimizer for use in deep learning. To this goal, we conducted an in-depth analysis of six industry-leading optimizers to identify the best tool for predicting traffic accidents. We ran extensive tests using a dataset that had 30,492 training examples (80%) and 7,622 testing instances (20%). Different seed values, ranging from 20 to 100, were used in each iteration of the experiment. We tested and compared the following optimizers: the Adaptive Gradient (AG) Algorithm, the Adaptive Learning Rate (ALR) Method, the Root Mean Squared (RMS) Propagation, the Adaptive Moment (AM) Estimation, the Nesterov-accelerated Adaptive Moment (NAM) Estimation, and the Stochastic Gradient (SG) Descent, taking into account processing times, prediction accuracy, and error analysis. The results of the experiment showed that the NAM Estimation Optimizer was much superior. Time spent processing data was cut down, and errors were kept to a minimum (0.03%). Prediction accuracy was also exceptionally high at 99.85%. This result reaffirms NAM Estimation's promise as a leading method for improving traffic management and making accurate trip predictions.

Circular Economy in Mountain Value Chains: The Case of Three PDO Cheeses

The circular economy (CE) has shown promise for achieving several of the UN’s Sustainable Development Goals, replacing the linear system and reducing negative impacts on the environment. This research aims to assess the effective adoption of CE principles in three cheeses with geographical indication (GI) through an analysis of the practices identified in their respective value chains. Qualitative interviews show the persistence of historical practices that preserve the heritage behind the product, maintain autonomy in relation to external inputs and save energy or make intelligent use of by-products. Radical adoption of CE principles requires innovation to reduce the use of new inputs and greenhouse gas emissions. GI food products are generally not constrained by standards beyond those set by law, but their specifications can be modified, while respecting practices consistent with the link to the terroir. However, the remoteness of small businesses in deep rural areas, far from research centers, is slowing down the transfer of knowledge and the adoption of the latest technologies, particularly in mountainous areas. More participatory research and innovative initiatives are needed to ensure the transition to a circular economy for traditional mountain products, which are strongly linked to local culinary traditions and cultural identity.