Object Recognition Research Articles

A multi-subject and multi-session EEG dataset for modelling human visual object recognition

We share a multi-subject and multi-session (MSS) dataset with 122-channel electroencephalographic (EEG) signals collected from 32 human participants. The data was obtained during serial visual presentation experiments in two paradigms. Dataset of first paradigm consists of around 800,000 trials presenting stimulus sequences at 5 Hz. Dataset of second paradigm comprises around 40,000 trials displaying each image for 1 second. Each participant completed between 1 to 5 sessions on different days, and each session lasted for approximately 1.5 hours of EEG recording. The stimulus set used in the experiments included 10,000 images, with 500 images per class, manually selected from PASCAL and ImageNet image databases. The MSS dataset can be useful for various studies, including but not limited to (1) exploring the characteristics of EEG visual response, (2) comparing the differences in EEG response of different visual paradigms, and (3) designing machine learning algorithms for cross-subject and cross-session brain-computer interfaces (BCIs) using EEG data from multiple subjects and sessions.

Technical Aspects of Deploying UAV and Ground Robots for Intelligent Logistics Using YOLO on Embedded Systems

Automation of logistics enhances efficiency, reduces costs, and minimizes human error. Image processing—particularly vision-based AI—enables real-time tracking, object recognition, and intelligent decision-making, thereby improving supply chain resilience. This study addresses the challenge of deploying deep learning-based object detection on resource-constrained embedded platforms, such as NVIDIA Jetson devices on UAVs and ground robots, for real-time logistics applications. Specifically, we provide a comprehensive comparative analysis of YOLOv5 and YOLOv8, evaluating their performance in terms of inference speed, accuracy, and dataset-specific metrics using both the Common Objects in Context (COCO) dataset and a novel, custom logistics dataset tailored for aerial and ground-based logistics scenarios. A key contribution is the development of a user-friendly graphical user interface (GUI) for selective object visualization, enabling dynamic interaction and real-time filtering of detection results—significantly enhancing practical usability. Furthermore, we investigate and compare deployment strategies in both Python 3.9 and C# (ML. NET v3 and .NET Framework 7) environments, highlighting their respective impacts on performance and scalability. This research offers valuable insights and practical guidelines for optimizing real-time object detection deployment on embedded platforms in UAV- and ground robot-based logistics, with a focus on efficient resource utilization and enhanced operational effectiveness.

Efficacy of Stem Cell-derived Extracellular Vesicles in the Treatment of Alzheimer's Disease Model Mice: A Systematic Review and Meta-analysis.

Alzheimer's disease (AD) is a neurodegenerative disease that is still incurable. Therapy with stem cell or extracellular vesicles is a promising strategy for AD treatment. Therefore, we evaluated whether stem cell-derived extracellular vesicles could improve cognitive function and pathological features in AD model mice. PubMed, Web of Science, Embase, and The Cochrane Library were searched for studies reporting stem cell-derived extracellular vesicles treatment of AD mice from the establishment of each database to 1st August 2023. SYRCLE was used to assess the risk of bias. The extracted data were analyzed using RevMan 5.4 and Stata 15 software. 19 studies were included in the analysis. Meta-analysis showed that treatment with stem cell-derived extracellular vesicles significantly improved cognitive performance of AD mice in the Morris water maze test and the novel object recognition test, reduced β-amyloid deposition, alleviated neuroinflammation and decreased levels of the proinflammatory cytokines and glial fibrillary acidic protein (GFAP) in the brain of AD mice. However, stem cell-derived extracellular vesicle did not affect the level of brain phosphorylated tau (p-Tau). stem cell-derived extracellular vesicles may promote the degradation of β-amyloid plaques in the brain, regulate immunity and protect nerves, which result in cognitive improvement in AD mice.

Stool-derived extracellular vesicles increase inflammasome signaling and regulate the gut-brain axis after stroke in Alzheimer's disease transgenic mice.

Stool-derived extracellular vesicles increase inflammasome signaling and regulate the gut-brain axis after stroke in Alzheimer's disease transgenic mice.

"The Effects of Oral Gestational Particulate Matter 10 Exposure: Insights into Neurodevelopmental Milestones, Inhibitory Control, Adult Sociability, and Object Recognition."

"The Effects of Oral Gestational Particulate Matter 10 Exposure: Insights into Neurodevelopmental Milestones, Inhibitory Control, Adult Sociability, and Object Recognition."

Hippocampal MCT4 as a key regulator in excessive exercise-induced cognitive impairment: involvement of neuroinflammation.

As human life expectancy increases, maintaining a healthy lifestyle has become crucial. However, excessive exercise (EE) can lead to negative consequences such as muscle damage and exercise addiction. Recently, numerous reports have indicated that EE negatively impacts cognitive performance, although the exact mechanism remains unclear. This study aimed to investigate the specific mechanisms underlying cognitive alterations induced by EE. We conducted the Y-maze, Barnes maze, and Novel Object Recognition Test to assess both short-term and long-term memory, as well as object recognition ability. We then validated our findings using qRT-PCR to elucidate the underlying mechanisms. Additionally, Diclofenac (Dic), an anti-inflammatory drug, was administered to evaluate its effects on cognitive function and the results of the molecular experiments. EE-induced mice exhibited cognitive impairments, along with elevated expression of inflammatory cytokines such as tumor necrosis factor-α, interleukin (IL) -6, and IL-1β, and downregulated monocarboxylate transporters (MCTs) like MCT4. However, animals pre-treated with Dic regained cognitive function, alongside restored levels of IL-6, IL-1β, and MCT4. MCT4 plays may play a crucial role in EE-induced cognitive impairments.

Slight and hidden hearing loss differentially affect short- and long-term memory in young rats.

Mild forms of hearing loss (HL) have been linked to cognitive impairments in children, yet the neurobiological mechanisms underlying this connection remain unclear. Existing research using animal models mostly focuses on more severe levels of HL or investigates only limited aspects of cognition. To gain a broader understanding of how slight/hidden HL affects cognitive behaviors, we induced HL in 4-week-old Wistar rats through noise exposure. Auditory brainstem response measurements confirmed slight and hidden HL, but this auditory impairment did not alter the density of inner hair cells or their synapses with the spiral ganglion (primary auditory) neurons. Both short- and long- term memory formation were tested using the object location, novel object recognition, and social recognition task. Behaviorally, rats with slight/hidden HL performed better than normal hearing (NH) rats during short-term cognition tests. However, long-term memory was impaired in rats with slight/hidden HL when compared to NH controls. Slight/hidden HL also did not consistently affect (social) exploration. In conclusion, this study demonstrates that slight and hidden HL differentially affect short- and long-term cognitive processes in an animal model of early (noise-induced) HL, without affecting (social) exploration. These results suggest a nuanced relationship between slight and hidden HL and both short- and long-term memory formation, underscoring the importance of broader cognitive phenotyping and further investigation into the neurobiological structures linking hearing impairment with cognitive function.

A simultaneous EEG and eye-tracking dataset for remote sensing object detection

We introduce the EEGET-RSOD, a simultaneous electroencephalography (EEG) and eye-tracking dataset for remote sensing object detection. This dataset contains EEG and eye-tracking data when 38 remote sensing experts located specific objects in 1,000 remote sensing images within a limited time frame. This task reflects the typical cognitive processes associated with human visual search and object identification in remote sensing imagery. To our knowledge, EEGET-RSOD is the first publicly available dataset to offer synchronized eye-tracking and EEG data for remote sensing images. This dataset will not only advance the study of human visual cognition in real-world environment, but also bridge the gap between human cognition and artificial intelligence, enhancing the interpretability and reliability of AI models in geospatial applications.

Blocking Hippocampal Voltage-gated Potassium channel Kv1.3 by Dalfampridine abrogates Cognitive Impairment in Experimental Autoimmune Encephalomyelitis Mouse Model.

Blocking Hippocampal Voltage-gated Potassium channel Kv1.3 by Dalfampridine abrogates Cognitive Impairment in Experimental Autoimmune Encephalomyelitis Mouse Model.

Dynamic domain analysis for predicting concept drift in engineering AI-enabled software

ABSTRACT Purpose This research addresses the challenge of concept drift in AI-enabled software, particularly within autonomous vehicle systems where concept drift in object recognition (like pedestrian detection) can lead to misclassifications and safety risks. This study introduces a proactive framework to detect early signs of domain-specific concept drift by leveraging domain analysis and natural language processing techniques. This method is designed to help maintain the relevance of domain knowledge and prevent potential failures in AI systems due to evolving concept definitions. Design/methodology/approach The proposed framework integrates natural language processing and image analysis to continuously update and monitor key domain concepts against evolving external data sources, such as social media and news. By identifying terms and features closely associated with core concepts, the system anticipates and flags significant changes. This was tested in the automotive domain on the pedestrian concept, where the framework was evaluated for its capacity to detect shifts in the recognition of pedestrians, particularly during events like Halloween and specific car accidents. Findings The framework demonstrated an ability to detect shifts in the domain concept of pedestrians, as evidenced by contextual changes around major events. While it successfully identified pedestrian-related drift, the system’s accuracy varied when overlapping with larger social events. The results indicate the model’s potential to foresee relevant shifts before they impact autonomous systems, although further refinement is needed to handle high-impact concurrent events. Research limitations This study focused on detecting concept drift in the pedestrian domain within autonomous vehicles, with results varying across domains. To assess generalizability, we tested the framework for airplane-related incidents and demonstrated adaptability. However, unpredictable events and data biases from social media and news may obscure domain-specific drifts. Further evaluation across diverse applications is needed to enhance robustness in evolving AI environments. Practical implications The proactive detection of concept drift has significant implications for AI-driven domains, especially in safety-critical applications like autonomous driving. By identifying early signs of drift, this framework provides actionable insights for AI system updates, potentially reducing misclassification risks and enhancing public safety. Moreover, it enables timely interventions, reducing costly and laborintensive retraining requirements by focusing only on the relevant aspects of evolving concepts. This method offers a streamlined approach for maintaining AI system performance in environments where domain knowledge rapidly changes. Originality/value This study contributes a novel domain-agnostic framework that combines natural language processing with image analysis to predict concept drift early. This unique approach, which is focused on real-time data sources, offers an effective and scalable solution for addressing the evolving nature of domain-specific concepts in AI applications.

Cystic Fibrosis-related neurodegenerative disease associated with tauopathy and cognitive decline in aged CF mice.

Cystic Fibrosis-related neurodegenerative disease associated with tauopathy and cognitive decline in aged CF mice.

Acute hypobaric hypoxia attenuates the anti-fatigue effects of pitolisant by downregulating the expression of organic cation transporter 1 and P-glycoprotein

ObjectiveThis study investigates the effects of acute hypobaric hypoxia (HH) on the anti-fatigue properties of pitolisant and explores the underlying mechanisms. The aim is to provide a theoretical basis for expanding its clinical indications and optimizing its use in individuals exposed to HH conditions.MethodsThe anti-fatigue effects of pitolisant were evaluated using the water maze, novel object recognition, and rotating rod tests. Drug concentrations and dopamine levels were analyzed using High-Performance Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (HPLC-MS/MS). Additionally, gene and protein expression levels of P-glycoprotein (P-gp) and organic cation transporter 1 (OCT1) were assessed to explore the mechanisms by which HH affects pitolisant’s pharmacodynamics.ResultsA 40 mg/kg dose of pitolisant significantly improved learning, memory, cognitive, and motor functions in sleep-deprived mice under HH conditions (P < 0.05). Pharmacokinetic analysis revealed a reduction in pitolisant concentration in the brain under HH conditions. Furthermore, OCT1 protein expression decreased after 1 h and 1 day of HH exposure (P < 0.05), while P-gp expression decreased after 1 h (P < 0.05).ConclusionHH possibly reduced pitolisant’s brain concentration and efficacy by altering the expression of OCT1 and P-gp transporters. A 40 mg/kg dose was necessary for an effective anti-fatigue response. Pitolisant shows potential for supporting circadian rhythm regulation in shift workers and individuals suffering from jet lag. When used under HH conditions, adjusting the dose and frequency may be necessary due to altered pharmacokinetics.

Hippocampal Neural Stem Cell Exosomes Promote Brain Resilience against the Impact of Tau Oligomers.

A promising therapeutic intervention for preventing the onset and progression of Alzheimer's disease is to protect and improve synaptic resilience, a well-established early vulnerability associated with the toxic effects of oligomers of amyloid β (AβO) and Tau (TauO). We have previously reported that exosomes from hippocampal neural stem cells (NSCs) protect synapses against AβO. Here, we demonstrate how exosomes can also shield against TauO toxicity in adult mice synapses, potentially benefiting primary and secondary tauopathies. Exosomes from hippocampal NSCs (NSCexo) or mature neurons (MNexo) were delivered intracerebroventricularly to adult wild-type male mice (C57Bl6/J). After 24 h, TauO were administered to suppress long-term potentiation (LTP) and memory, measured by electrophysiology and contextual memory deficits measured using novel object recognition test. We also assessed TauO binding to synapses using isolated synaptosomes and cultured hippocampal neurons. Furthermore, mimics of select miRNAs present in NSCexo were delivered intracerebroventricularly to mice prior to assessment of TauO-induced suppression of hippocampal LTP. Our results showed that NSC-, not MN-, derived exosomes, prevented TauO-induced memory impairment, LTP suppression, and reduced Tau accumulation and TauO internalization in synaptosomes. These findings suggest that NSC-derived exosomes can protect against synaptic dysfunction and memory deficits induced by both AβO and TauO, offering a novel therapeutic strategy for multiple neurodegenerative states.

Lesion of the ventral or dorsal hippocampus in the rat delays puberty, follicular growth and secretion of sex steroid hormones

IntroductionThe hypothalamus-pituitary-gonad axis is controlled by gonadotropins and by a direct neural pathway to the gonads. New evidence suggests the existence of neural connection from the hippocampus to the hypothalamus that can regulate its function. It could be a new control on the well-regulated hormonal and neural connection to the gonads and hence in reproduction. The objective of this study was to analyze the effects of independent lesion of the dorsal or ventral hippocampus in the female rat on the onset of puberty, follicular growth and serum concentration of sex steroid and gonadotropins.MethodsPrepubertal female rats of the CII-ZV strain, 21 days old, were used. Ventral (VH-L) or dorsal (DH-L) hippocampus lesions by the administration of ibotenic acid were performed using stereotaxic surgery. Controls were sham-operated (VH-Sham and DH- Sham), a fifth group was used as absolute control. At 30 days of age all groups underwent novel object recognition tests (NORT).ResultsData from memory using NORT showed a decrease both in short- and long-term memory in the animals in the VH- L and DH-L groups compared to their respective sham-operated controls and the absolute control group. Similarly, injured rats presented delayed vaginal opening and in first vaginal estrus, a decrease in the number of healthy ovarian follicles and an increase in follicular atresia. The ventral or dorsal hippocampus lesions also caused a significant decrease in the secretion of estradiol and progesterone, an increased plasma testosterone. Only DH-L group showed a significant decrease in serum FSH concentrations compared to their respective control groups.DiscussionThese results show for the first time that the hippocampus participates in a stimulatory manner, that could overcome the gonadotropic control by acting by a neural connection to the gonads giving a novel integrative mechanism between learning processes with neuroendocrine mechanism regulating the ovary function.

Integrated Financial Ecosystems: AI-Driven Innovations in Taxation, Insurance, Mortgage Analytics, and Community Investment Through Cloud, Big Data, and Advanced Data Engineering

Finance has a broad impact on individuals and economies. This is especially true during critical times such as the current pandemic, when unpredictability and policy changes affect an individual’s earnings, savings, investments, and more. Meanwhile, there is a variety of opaque and challenging to understand new financial offers by FinTech companies. Regulatory and technological aspects both call for innovation in this finance. To bring transparency, standard human-understandable explanations and verifications are proposed for consumer finance. Laying the groundwork for citizen sense-making tools that could be part of e.g. FinTech regulation compliance. Task is positioned at the nexus of Financial Machine Learning, Visual Analytics, and Artificial Intelligence (AI) fairness. A new finance-centered story-guided system design pattern illustrated with prototypes. A continuum of visual explanations across a spectrum of reviewing the model’s understanding- and proposing simple Event Glossary on consumer finance—relevant machine-learning explainability (XAI). The goal is to narrate a machine-learned model’s decisions in a human-understandable way, ideally in natural language. This anticipation of potentially askable questions was introduced in the context of ImageNet object recognition, but can be translated to a variety of different tasks, including consumer loans risk for personal finances or reviewing loans applications for a bank. In the personal finance task, for instance, this explanation might answer questions such as “Why did my mortgage rate increase?,” “Why can I afford less of a loan?,” or “Why am I shown this offer?” At the intersection of Visual Analytics and AI fairness, the focus is on explaining text- and entity-based models rather than the previously considered deep image- or speech-recognition ones. Further, the focus on text and event data interpretation, common in financial regulation.

Teaching CORnet human fMRI representations for enhanced model-brain alignment

Deep convolutional neural networks (DCNNs) have demonstrated excellent performance in object recognition and have been found to share some similarities with brain visual processing. However, the substantial gap between DCNNs and human visual perception still exists. Functional magnetic resonance imaging (fMRI) as a widely used technique in cognitive neuroscience can record neural activation in the human visual cortex during the process of visual perception. Can we teach DCNNs human fMRI signals to achieve a more brain-like model? To answer this question, this study proposed ReAlnet-fMRI, a model based on the SOTA vision model CORnet but optimized using human fMRI data through a multi-layer encoding-based alignment framework. This framework has been shown to effectively enable the model to learn human brain representations. The fMRI-optimized ReAlnet-fMRI exhibited higher similarity to the human brain than both CORnet and the control model in within- and across-subject as well as within- and across-modality model-brain (fMRI and EEG) alignment evaluations. Additionally, we conducted an in-depth analysis to investigate how the internal representations of ReAlnet-fMRI differ from CORnet in encoding various object dimensions. These findings provide the possibility of enhancing the brain-likeness of visual models by integrating human neural data, helping to bridge the gap between computer vision and visual neuroscience.

Healthy aging delays and dedifferentiates high-level visual representations.

Healthy aging delays and dedifferentiates high-level visual representations.

Role for the liver X receptor agonist 22-ketositosterol in preventing disease progression in an Alzheimer's disease mouse model.

Liver X receptors (LXRs) are promising therapeutic targets for alleviating Alzheimer's disease (AD) symptoms. We assessed the impact of the semi-synthetic LXR agonist 22-ketositosterol on disease progression in an AD mouse model. From 5.5 months of age, APPswePS1ΔE9 (AD) mice and wild-type (WT) littermates received a regular or 22-ketositosterol-supplemented diet (0.017% w/w). Cognition was assessed with object location and recognition tasks and a spontaneous alternation Y-maze test. Amyloid β was quantified using immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA), microglia (Iba1, CD68) and astrocyte (GFAP) markers using IHC. Sterols were determined in food, serum, liver and cerebellum. 22-Ketositosterol activated both liver X receptors-α and -β and promoted cholesterol efflux in cell cultures. Diet supplementation with 22-ketositosterol prevented a decline in the performance of APPswePS1ΔE9 mice in the object location task but not in the other two tasks. Without affecting amyloid β deposition, 22-ketositosterol decreased microglia (Iba1, CD68) and astrocyte (GFAP) markers in the cortex and hippocampus of APPswePS1ΔE9, suggesting potential anti-inflammatory effects. No lipid accumulation was detected in the liver or serum upon 22-ketositosterol supplementation. Diet supplementation with 22-ketositosterol prevented the decline in spatial memory of APPswePS1ΔE9 mice. Our data suggest therapeutic benefits of 22-ketositosterol possibly by enhancing cholesterol efflux and mitigating inflammatory responses, without inducing hepatosteatosis or hypertriglyceridemia.

Research a Smart Assistive Device for Visually Impaired Using IOT

Visually impaired individuals face significant challenges in navigating their surroundings safely and independently. Traditional mobility aids such as canes provide limited assistance and lack real-time hazard detection. This paper presents a Smart Assistive Device for the Visually Impaired using IoT, designed to enhance mobility, safety, and emergency response. The system integrates two ultrasonic sensors—one for depth detection and another for obstacle avoidance—providing immediate feedback through a vibrating motor. A rain sensor detects moisture levels, warning users of wet surfaces. The device also includes a GPS module for real-time location tracking and a GSM module to send emergency SMS alerts. A panic button allows users to instantly send their location to predefined contacts in distress situations. The system is built around an Arduino Nano, ensuring efficient processing and communication. This assistive technology enhances the independence of visually impaired individuals by offering real-time alerts and automated emergency assistance. Future improvements may include AI-based object recognition, voice assistance, and machine learning algorithms for adaptive navigation. This innovation contributes to improving accessibility, safety, and overall quality of life for visually impaired users. KEYWORDS- Smart Assistive Device, Visually Impaired, IoT, Ultrasonic Sensors, GPS, GSM, Panic Button, Rain Sensor, Vibrating Feedback.

Remote Ischemic Postconditioning Improve Cerebral Ischemia-Reperfusion InjuryInduced Cognitive Dysfunction through Suppressing Mitochondrial Apoptosis in Hippocampus via TK/BK/B2R-Mediated PI3K/AKT.

Remote ischemic postconditioning (RIPostC) is known to improve motor function recovery in animal models, but its efficacy in alleviating cognitive impairment caused by ischemic stroke remains unclear. This study aims to investigate the beneficial role of RIPostC in recovering cognitive impairment induced by cerebral ischemia-reperfusion injury (CIRI). Building upon our previous research findings, we proved that the TK/BK/B2R pathway is crucial for understanding the crosstalk between cognitive impairment and RIPostC. Additionally, in vitro experiments were conducted using the oxygen glucose deprivation/re-oxygenation (OGD/r) HT-22 cell model, which revealed that the mechanism by which RIPostC suppressed mitochondrial apoptosis was mainly through the activation of the B2R/PI3K/AKT signaling pathway, thereby protecting neurons in the ischemic hippocampus from ischemic damage. To investigate the effect of RIPostC on cognitive function recovery following ischemic stroke, we established a rat model using left middle cerebral artery occlusion reperfusion (MCAO/r). 48h after MCAO/r, rats were subjected to 3 circles of RIPostC therapy daily for 12 consecutive days. HOE140 was used to antagonize the bradykinin 2 receptor (B2R). Cognitive function was assessed using a modified neurological severity score, the Morris water maze, and the novel object recognition test. Local infarct volume in the hippocampus was measured through MRI scanning. The apoptosis rate of hippocampal neurons was quantified using TUNEL staining. Protein expression levels of kallikrein (TK) and mitochondrial apoptosis-related proteins, Cyt c, Bcl-2, Bax, cleaved caspase-3, and cleaved caspase-9, were detected in ischemic hippocampal tissue using Western blot (WB). The expression of bradykinin (BK) in serum and the ischemic penumbra was measured using an enzyme-linked immunosorbent (ELISA) assay. In the cell experiments, the HT-22 cell line and OGD/r model were used to simulate in vitro hippocampal ischemia. WB was performed to detect the expression of apoptosis-related proteins and PI3K/AKT pathway proteins. The apoptosis rate of HT-22 cells was detected using Annexin-V/PI flow cytometry and a cell viability kit. JC-1 staining and reactive oxygen species staining were used to evaluate mitochondrial condition. The PI3K/AKT pathway was inhibited using LY294002. RIPostC significantly upregulated the concentrations of TK and BK in the ischemic hippocampus. Behavioral function tests demonstrated that daily RIPostC therapy for 12days significantly promoted cognitive function recovery in MCAO/r rats. Through MRI analysis, we found that RIPostC therapy effectively reduced the infarct volume in the hippocampus. Additionally, TUNEL staining and WB results of apoptosis-related proteins showed that RIPostC therapy significantly reduced apoptosis of hippocampal neurons. However, the therapeutic effect of RIPostC was reversed by the B2R antagonist HOE14, indicating that the TK/BK/B2R pathway mediated the neuroprotective effect of RIPostC. Cell experiments further confirmed that BK/B2R significantly attenuated mitochondrial apoptosis induced by ischemia-hypoxia injury in HT-22 cells. In vivo and in vitro results from WB demonstrated that the BK/B2R pathway activated the PI3K/AKT signaling pathway. Finally, the PI3K inhibitor LY294002 reversed the anti-apoptotic effect induced by BK/B2R. RIPostC therapy effectively inhibited mitochondrial apoptosis of hippocampal neurons and significantly alleviated cognitive dysfunction associated with CIRI by regulating the TK/BK/B2R-medated PI3K/AKT pathway. In conclusion, RIPostC represents a promising therapeutic strategy for combating cognitive dysfunction by inhibiting cell apoptosis in hippocampus. Moreover, our results suggest that RIPostC may have a broader protective effect against apoptosis in other ischemia-reperfusion-related diseases.