Dimensional Environment Research Articles

Impact of 3D Endovision System on Learning Process of Laparoscopic Transabdominal Preperitoneal Repair of Groin Hernia.

Background: Laparo-endoscopic hernia surgery is recommended by various international bodies. However, its uptake by general surgeon is low. We aim to assess the impact of Three Dimensional (3D) endovision system in learning laparoscopic transabdominal preperitoneal (TAPP) repair of groin hernia and transferability of skills acquired from 3D to the Two Dimensional (2D) environment. Methodology: Senior resident doctor with no previous experience in laparoscopic hernia surgery did 20 consecutive cases of TAPP repair using 3D endovision system followed by another five cases of TAPP repair using 2D endovision system. Total operating time, operating time during different phases of hernia surgery, faculty take over time, path length of needle holder, and scissors were recorded. Cumulative sum (CUSUM) and split group analysis were done to assess the learning process. Trainee's operating time was compared with that of experts' from previously published study of the same group. Data were compared between last block of five cases done using 3D system and cases done using 2D system for skill transferability. Results: CUSUM method provided inflection points of total operating time, hernia dissection and mesh placement at 9th case, and peritoneal suturing at 11th case in learning TAPP hernia. After 10th case, trainee's operating time was within the middle 50 percentage of experts operating time. Total operating time in last block of cases done under 3D vision and that of 2D endovision comparable, although peritoneal closure was significantly longer in 2D vision (P = .074, .2, .145, .001). Conclusion: Reduction on operating time appears after ninth case of TAPP hernia repair using the 3D endovision system. The skills acquired under 3D endovision system are transferable to perform the procedure under 2D endovision system, albeit incompletely. Use of 3D technology may facilitate adaptation of TAPP hernia repair by young surgeons.

Vascularized tumor on a microfluidic chip to study mechanisms promoting tumor neovascularization and vascular targeted therapies.

The cascade of events leading to tumor formation includes induction of a tumor supporting neovasculature, as a primary hallmark of cancer. Developing vasculature is difficult to evaluate in vivo but can be captured using microfluidic chip technology and patient derived cells. Herein, we established an on chip approach to investigate the mechanisms promoting tumor vascularization and vascular targeted therapies via co-culture of cancer spheroids and endothelial cells in a three dimensional environment. Methods: We investigated both, tumor neovascularization and therapy, via co-culture of human derived endothelial cells and adjacently localized metastatic renal cell carcinoma spheroids on a commercially available microfluidic chip system. Metastatic renal cell carcinoma spheroids adjacent to primary vessels model tumor, and induce vessels to sprout neovasculature towards the tumor. We monitored real time changes in vessel formation, probed the interactions of tumor and endothelial cells, and evaluated the role of important effectors in tumor vasculature. In addition to wild type endothelial cells, we evaluated endothelial cells that overexpress Prostate Specific Membrane Antigen (PSMA), that has emerged as a marker of tumor associated neovasculature. We characterized the process of neovascularization on the microfluidic chip stimulated by enhanced culture medium and the investigated metastatic renal cell carcinomas, and assessed endothelial cells responses to vascular targeted therapy with bevacizumab via confocal microscopy imaging. To emphasize the potential clinical relevance of metastatic renal cell carcinomas on chip, we compared therapy with bevacizumab on chip with an in vivo model of the same tumor. Results: Our model permitted real-time, high-resolution observation and assessment of tumor-induced angiogenesis, where endothelial cells sprouted towards the tumor and mimicked a vascular network. Bevacizumab, an antiangiogenic agent, disrupted interactions between vessels and tumors, destroying the vascular network. The on chip approach enabled assessment of endothelial cell biology, vessel's functionality, drug delivery, and molecular expression of PSMA. Conclusion: Observations in the vascularized tumor on chip permitted direct and conclusive quantification of vascular targeted therapies in weeks as opposed to months in a comparable animal model, and bridged the gap between in vitro and in vivo models.

Virtual Reality and Artificial Intelligence: A Perfect Combination for Immersive Gaming

The virtual reality and artificial intelligence, it is the immediate future in the field of game changers. It allows complete immersion and interactivity into experiences. Applied together, they create a level of realism, interactivity, and personalization never before possible. AI-powered algorithms allow NPCs to exhibit life-like behaviors, contextually adapting to player actions and dynamic context-aware responses. VR allows the simulation of three- dimensional environments in which a player is present and immersed between the real and virtual worlds. Dynamic, AI-powered environments evolve in real time and react to players' choices, so no play through will ever be the same. It also greatly contributes to procedural content generation, giving developers an ability to create large, unique worlds without effort. AI-driven personalized game play caters to the challenges, rewards, and storylines desired by the player, adding extra depth to each game. In concert with each other, VR and AI redefine the limits of interactive storytelling and entertainment, thus opening new dimensions for the future of the gaming industry. Keywords: Virtual Reality, Artificial Intelligence, Immersive Game, NPC behavior, dynamic environments, procedural content generation, interactive storytelling, personalized game play, and real-time adaptation-innovating in gaming.

Dynamic three dimensional environment for efficient and large scale generation of smooth muscle cells from hiPSCs

BackgroundChronic ischemic limb disease often leads to amputation, which remains a significant clinical problem. Smooth-muscle cells (SMCs) are crucially involved in the development and progression of many cardiovascular diseases, but studies with primary human SMCs have been limited by a lack of availability. Here, we evaluated the efficiency of two novel protocols for differentiating human induced-pluripotent stem cells (hiPSCs) into SMCs and assessed their potency for the treatment of ischemic limb disease.MethodshiPSCs were differentiated into SMCs via a conventional two-dimensional (2D) protocol that was conducted entirely with cell monolayers, or via two protocols that consisted of an initial five-day three-dimensional (3D) spheroid phase followed by a six-day 2D monolayer phase (3D + 2D differentiation). The 3D phases were conducted in shaker flasks on an orbital shaker (the 3D + 2D shaker protocol) or in a PBS bioreactor (the 3D + 2D bioreactor protocol). Differentiation efficiency was evaluated via the expression of SMC markers (smooth-muscle actin [SMA], smooth muscle protein 22 [SM22], and Calponin-1), and the biological activity of the differentiated hiPSC-SMCs was evaluated via in-vitro assessments of migration (scratch assay), contraction in response to the treatment with a prostaglandin H2 analog (U46619), and tube formation on Geltrex, as well as in-vivo measurements of perfusion (fluorescence angiography) and vessel density in the limbs of mice that were treated with hiPSC-SMCs after experimentally induced hind-limb ischemia (HLI).ResultsBoth 3D + 2D protocols yielded > 5.6 × 107 hiPSC-SMCs/differentiation, which was ~ nine-fold more than that produced via 2D differentiation, and flow cytometry analyses confirmed that > 98% of the 3D + 2D-differentiated hiPSC-SMCs expressed SMA, > 81% expressed SM22, and > 89% expressed Calponin-1. hiPSC-SMCs obtained via the 3D + 2D shaker protocol also displayed typical SMC-like migratory, contraction, and tube-formation activity in-vitro and significantly improved measurements of perfusion, vessel density, and SMA-positive arterial density in the ischemic limb of mouse HLI model.ConclusionsOur dynamic 3D + 2D protocols produced an exceptionally high yield of hiPSC-SMCs. Transplantation of these hiPSC-SMCs results in significantly improved recovery of ischemic limb after ischemic injury in mice.

Multimodal immersion in English language learning in higher education: A systematic review

The development of multimodality has led to increased research on its use to improve students' English language competency. However, no recent review has analyzed multimodality in English language learning in higher education. This systematic review examines 34 research articles published from 2013 to 2024. The primary focus of the study is to explore the application of multimodal pedagogies in higher education, the methods and materials used to assist learners in acquiring English language skills, the English language skills acquired through the usage of multimodality, and the main results of using multiple modes. This systematic review employs the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) standards. It adopts a thorough search strategy across electronic databases, which include Web of Science and Scopus. We found (1) the implementation of multimodality contributes to learners' English language proficiency in English for academic purposes (EAP) and English for specific purposes (ESP) education; (2) there is a predominance of digital multimodality and nonverbal communication use in the higher education classroom, for example, gesture, kinesics, spatial position, facial expression, and gaze the use of the 3D (dimensional) environment, virtual reality (VR); (3) there is an advantage of a multimodal approach in improving higher education learners' vocabulary, reading, speaking, and writing skills and a positive connection between the implementation of multimodality and the development of learners' communicative ability. This systematic review highlights existing research gaps and outlines potential avenues for future investigation aimed at conceptualizing and assessing learners’ skills through multimodal approaches.

Weyl fermions in a (2+1)-dimensional gravitational wave spacetime

In this study, we work on understanding the behavior of relativistic fermions within the framework of a (2+1)-dimensional gravitational wave environment. Our main objective is to uncover an analytical solution for the massless Dirac equation in this particular scenario. Initially, we derive a set of coupled equations that describe the quantum dynamics of the system under consideration. Subsequently, we embark on finding an analytical solution for the resulting wave equation governing Weyl fermions by utilizing the generators associated with the [Formula: see text] algebra. This approach enables us to determine the relativistic frequency modes of the system. We then delve into examining how the parameters of the gravitational wave spacetime influence the real oscillation modes of Weyl fermions. Our findings highlight the sensitivity of Weyl fermions to the specific gravitational wave spacetime background being considered.

Random Contrastive Interaction for Particle Swarm Optimization in High-Dimensional Environment

In high dimensional environment, the interaction among particles significantly affects their movements in searching the vast solution space and thus plays a vital role in assisting particle swarm optimization (PSO) to attain good performance. To this end, this paper designs a random contrastive interaction (RCI) strategy for PSO, resulting in RCI-PSO, to tackle large-scale optimization problems (LSOPs) effectively and efficiently. Unlike existing interaction mechanisms for low-dimensional problems, RCI randomly chooses several different peers from the current swarm to construct a random interaction topology for each particle. Then, it lets the particle interact with the selected peers based on their current evolutionary information instead of their historical evolutionary information. Within the topology, RCI only propagates the evolutionary information of two contrastive dominators with the largest difference in fitness to direct the evolution of the particle. Therefore, particles with no more than two dominators in their topologies are not updated. Furthermore, a dynamic topology size adjustment scheme is devised to gradually enlarge the interaction topology. In this way, the swarm gradually switches from exploring the immense search space dispersedly to exploiting the found optimal regions intensively as the evolution continues. With these two strategies, RCI-PSO expectedly compromises search diversity and search convergence well at the swarm level and the particle level. At last, extensive experiments executed on two public LSOP suites verify that RCI-PSO performs competitively with or even much better than totally 40 state-of-theart large-scale approaches and preserves a good capability and scalability in tackling complex LSOPs.

Hemispherical Retina Emulated by Plasmonic Optoelectronic Memristors with All-Optical Modulation for Neuromorphic Stereo Vision.

Binocular stereo vision relies on imaging disparity between two hemispherical retinas, which is essential to acquire image information in three dimensional environment. Therefore, retinomorphic electronics with structural and functional similarities to biological eyes are always highly desired to develop stereo vision perception system. In this work, a hemispherical optoelectronic memristor array based on Ag-TiO2 nanoclusters/sodium alginate film is developed to realize binocular stereo vision. All-optical modulation induced by plasmonic thermal effect and optical excitation in Ag-TiO2 nanoclusters is exploited to realize in-pixel image sensing and storage. Wide field of view (FOV) and spatial angle detection are experimentally demonstrated owing to the device arrangement and incident-angle-dependent characteristics in hemispherical geometry. Furthermore, depth perception and motion detection based on binocular disparity have been realized by constructing two retinomorphic memristive arrays. The results demonstrated in this work provide a promising strategy to develop all-optically controlled memristor and promote the future development of binocular vision system with in-sensor architecture.

Mental health in the virtual world: Challenges and opportunities in the metaverse era.

Current rates of mental illness are worrisome. Mental illness mainly affects females and younger age groups. The use of the internet to deliver mental health care has been growing since 2020 and includes the implementation of novel mental health treatments using virtual reality, augmented reality, and artificial intelligence. A new three dimensional digital environment, known as the metaverse, has emerged as the next version of the Internet. Artificial intelligence, augmented reality, and virtual reality will create fully immersive, experiential, and interactive online environments in the metaverse. People will use a unique avatar to do anything they do in their "real" lives, including seeking and receiving mental health care. In this opinion review, we reflect on how the metaverse could reshape how we deliver mental health treatment, its opportunities, and its challenges.

Evaluation of popular path planning algorithms

The navigation of mobile robots is a key element of autonomous systems, which allows robots to move effectively and securely in changing environments with greater autonomy and precision. This study aims to provide researchers with a comprehensive guide for selecting the best path-planning methods for their particular projects. We evaluate some popular algorithms that are regularly used in mobile robot navigation, in order to demonstrate their specifications and determine where they are most effective. For example, one algorithm is used to model the problem as a standard graph, and another algorithm is found to be the most suitable for highly dynamic and highly dimensional environments, due to its robust path-planning capabilities and efficient route construction. We also filter high-performance algorithms in terms of computational complexity, accuracy, and robustness. In conclusion, this study provides valuable information on its individual strengths and weaknesses, helping robotics and engineers make informed decisions when selecting the most appropriate algorithm for their specific applications.

Analogue Quantum Simulation with Fixed-Frequency Transmon Qubits

We experimentally assess the suitability of transmon qubits with fixed frequencies and fixed interactions for the realization of analogue quantum simulations of spin systems. We test a set of necessary criteria for this goal on a commercial quantum processor using full quantum process tomography and more efficient Hamiltonian tomography. Significant single qubit errors at low amplitudes are identified as a limiting factor preventing the realization of analogue simulations on currently available devices. We additionally find spurious dynamics in the absence of drive pulses, which we identify with coherent coupling between the qubit and a low dimensional environment. With moderate improvements, analogue simulation of a rich family of time-dependent many-body spin Hamiltonians may be possible.

OBJECT DETECTION AND LOCALISATION FOR BIM ENRICHMENT

Abstract. The use of Building Information Models (BIM) during the entire life cycle of a building or facility requires an up-to-date and detailed digital representation. Nowadays the BIM focus mostly lies on the design and construction phase of the building and is rarely used for the rest of the life cycle. For further use the BIM must be updated after construction and enriched with appliance objects such as safety equipment, heating elements to enhance its usability. In this work a new approach is presented to detect and locate appliance objects in a three dimensional environment using object detection in images created by indoor mobile mapping devices. By detecting and locating these appliance objects in the three dimensional world they can be included in the BIM model. This approach enables the detection and localization needed for the placement of placeholders or detailed geometric models of those appliances in the BIM model or other digital representations. Resulting in an increased level of detail and usability of the digital representation of the building or facility during its further life cycle. Overall, this work demonstrates and examines the accuracy of the detection and localization of appliance objects.

Study of optical properties of DM–DM planar interface by incorporating non-linearity and NID space

Study of the optical characteristics of materials, objects and geometries has wider role and applications in science and engineering. Reflection and transmission coefficients are used to study the optical properties of planar geometries. Primary aim of the presented work is to study the reflection and transmission of second harmonic generation in non-integer dimensional environment. Nonlinear medium in our considered geometry is of second harmonic generation type hence we only studied the second order reflection and transmission characteristics. Solution of the nonlinear wave equation is obtained by using slowly varying amplitude approximation and method of separation of variables in NID space is used to study how the presence of NID medium alter the electromagnetic waves. As a special case of the original geometry we also studied the changes in the behavior of the coefficients when an epsilon negative and a mu negative NID mediums are used as a reflected half space. In all the cases impact of the non-linearity and the noninteger dimensions on the unknown coefficients are studied separately. It is studied that higher amplitude of the reflection coefficient can be achieved by using a dielectric magnetic NID medium compared to epsilon negative NID medium. On the other hand it is also noted that for epsilon near zero medium, amplitude of the reflection coefficient reaches zero for specific values of the nonlinear permeability and incident angle whereas, for mu negative NID medium amplitude of both the coefficients increases (decreases) by increasing the values of ϵic(ϵrc). It is also noted that dimensions of the NID mediums can be used as a controlling factor for the amplitude of the coefficients by keeping the same shape. For the verification of the analytical results nonlinear power law is used.

Abstract 12750: Three Dimensional Environment for Efficient and Large Scale Generation of Smooth Muscle Cells From HiPSCs

Introduction: Smooth muscle cells (SMCs) play an important role in maintaining vascular homeostasis and the development of diseases. We assess feasibility and efficacy of differentiation human induced pluripotent stem cells (hiPSCs) to SMCs in a 3-dimension (3D). Methods: hiPSCs were cultured in shaker flasks or PBS-0.1 Vessels for 48 h. Differentiation initiated (as day 0) by culturing hiPSC spheroids in RPMI+B27 without insulin (B27-) and CHIR99021 (CHIR) for 24 h. Day 1, medium was replaced with RPMI+B27-, platelet derived growth factor β (PDGF-β), and transforming growth factor β1 (TGFβ1) for 48 h, refreshed medium on day 3 for 48 h. Day 5, differentiating hiPSC-spheroids were dissociated to single cells and cultured as monolayer in RPMI +4% FBS, PDGF-β, and TGFβ1 for 72 h. Refreshed medium day 8 for 72 h. Differentiation efficiency was determined by flow cytometry and fluorescence immunostaining. The biological function of 3D differentiated SMCs was assessed in vitro and in a mouse model of ischemic limb disease in vivo . Results: Both 3D differentiation methods efficiently differentiated hiPSCs into SMCs. Flow cytometry showed that 99.4% cells expressed smooth muscle actin (SMA), 97.9% expressed myosin heavy chain 11 (MYH11), 95.1% expressed SM22, 97.5% expressed calponin, and 97.7% expressed calveolin-3 using shaker flasks. They were 99.6% for SMA, 97.9% for MYH11, 97% for SM22, 89.6% for calponin, and 87.2% for calveolin-3, respectively, using PBS-0.1 Vessels. Mean SMC cell number obtained was 4.56 x 10 7 for shaker flasks and 5.69 x 10 7 for PBS-0.1 Vessels, respectively, which were significantly higher than hiPSCs differentiated in monolayer (5.7x10 6 ). Fluorescence immunostaining confirmed that SMCs differentiated from both methods expressed SMA, MYH11, SM22, Calponin, and calveolin-3. Differentiated SMCs migrated in scratch assay, contracted in response to U-46619, an analog of the endoperoxide prostaglandin, and formed tubular structure on Matrigel in vitro. Fluorescence angiogram imaging showed that SMC transplantation effectively induced perfusion in mouse ischemic limbs. Conclusions: Both 3D differentiation methods, using shaker flasks or PBS-0.1 vessels, efficiently differentiated hiPSCs into large scales of functional SMCs.

Characterizing High Rate GNSS Velocity Noise for Synthesizing a GNSS Strong Motion Learning Catalog

Data-driven approaches to identify geophysical signals have proven beneficial in high dimensional environments where model-driven methods fall short. GNSS offers a source of unsaturated ground motion observations that are the data currency of ground motion forecasting and rapid seismic hazard assessment and alerting. However, these GNSS-sourced signals are superposed onto hardware-, location- and time-dependent noise signatures influenced by the Earth’s atmosphere, low-cost or spaceborne oscillators, and complex radio frequency environments. Eschewing heuristic or physics based models for a data-driven approach in this context is a step forward in autonomous signal discrimination. However, the performance of a data-driven approach depends upon substantial representative samples with accurate classifications, and more complex algorithm architectures for deeper scientific insights compound this need. The existing catalogs of high-rate (≥1Hz) GNSS ground motions are relatively limited. In this work, we model and evaluate the probabilistic noise of GNSS velocity measurements over a hemispheric network. We generate stochastic noise time series to augment transferred low-noise strong motion signals from within 70 kilometers of strong events (≥ MW 5.0) from an existing inertial catalog. We leverage known signal and noise information to assess feature extraction strategies and quantify augmentation benefits. We find a classifier model trained on this expanded pseudo-synthetic catalog improves generalization compared to a model trained solely on a real-GNSS velocity catalog, and offers a framework for future enhanced data driven approaches.

Product quality prediction method in small sample data environment

The low degree of enterprise digitization and the existence of personalized customization and small batch production manufacturing modes lead to the characteristics of small samples and high dimensions of data collected by manufacturing enterprises. The product quality prediction method based on big data is prone to overfitting in the small sample and high dimensional data environment, and the model generalization performance is poor. In order to solve the above problems, this paper conducts research in two aspects of data augmentation and model optimization respectively. At the data augmentation level, a data generation model RVAE-CGAN is proposed, RVAE constrains the value space of GAN and eliminates the influence of outliers in the original data on the quality of generated samples. Using DBSCAN to cluster raw data to generate conditional vectors for guiding sample generation, and finally obtain high-quality generated samples. At the model optimization level, a product quality prediction model PPO-SVR is proposed. The PPO method is used to optimize the hyperparameters of the SVR model and improve the prediction effect of the model. RVAE-CGAN and PPO-SVR models are combined, and RVAE-CGAN is used to expand the number of samples to train PPO-SVR. The experimental results show that the product quality prediction model constructed based on RVAE-CGAN and PPO-SVR outperforms the BP neural network prediction model trained on mixed data. Therefore, the combination of data augmentation and model optimization proposed in this paper can significantly improve the prediction effect of the product quality prediction model in the small sample data environment.

Organization of projections from the entorhinal cortex to the hippocampal formation of the Egyptian fruit bat Rousettus aegyptiacus.

The hippocampal formation and entorhinal cortex are crucially involved in learning and memory as well as in spatial navigation. The conservation of these structures across the entire mammalian lineage demonstrates their importance. Information on a diverse set of spatially tuned neurons has become available, but we only have a rudimentary understanding of how anatomical network structure affects functional tuning. Bats are the only order of mammals that have evolved true flight, and with this specialization comes the need to navigate and behave in a three dimensional (3D) environment. Spatial tuning of cells in the entorhinal-hippocampal network of bats has been studied for some time, but whether the reported tuning in 3D is associated with changes in the entorhinal-hippocampal network is not known. Here we investigated the entorhinal-hippocampal projections in the Egyptian fruit bat (Rousettus aegyptiacus), by injecting chemical anterograde tracers in the entorhinal cortex. Detailed analyses of the terminations of these projections in the hippocampus showed that both the medial and lateral entorhinal cortex sent projections to the molecular layer of all subfields of the hippocampal formation. Our analyses showed that the terminal distributions of entorhinal fibers in the hippocampal formation of Egyptian fruit bats-including the proximo-distal and longitudinal topography and the layer-specificity-are similar to what has been described in other mammalian species such as rodents and primates. The major difference in entorhinal-hippocampal projections that was described to date between rodents and primates is in the terminal distribution of the DG projection. We found that bats have entorhinal-DG projections that seem more like those in primates than in rodents. It is likely that the latter projection in bats is specialized to the behavioral needs of this species, including 3D flight and long-distance navigation.

3D Path Optimisation of Unmanned Aerial Vehicles Using Q Learning-Controlled GWO-AOA

Unmanned Aerial Vehicles (UAVs) or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance, due to their ability to perform repetitive and tedious tasks in hazardous environments. Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional (3D) flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature. However, not a single optimization algorithms can solve all kind of optimization problem effectively. Therefore, there is dire need to integrate metaheuristic for general acceptability. To address this issue, in this paper, a novel reinforcement learning controlled Grey Wolf Optimisation-Archimedes Optimisation Algorithm (QGA) has been exhaustively introduced and exhaustively validated firstly on 22 benchmark functions and then, utilized to obtain the optimum flyable path without collision for UAVs in three dimensional environment. The performance of the developed QGA has been compared against the various metaheuristics. The simulation experimental results reveal that the QGA algorithm acquire a feasible and effective flyable path more efficiently in complicated environment.

Reciprocal Safety Velocity Cones for Decentralized Collision Avoidance in Multi-Agent Systems

In this paper, we solve the inter-agent collision avoidance problem in an arbitrary n-dimensional Euclidean space using reciprocal safety velocity cones (RSVCs). We propose a decentralized feedback control strategy that guarantees simultaneously asymptotic stabilization to a reference and collision avoidance. Our algorithm is purely decentralized in the sense that each agent uses only local information about its neighbouring agents. Moreover, the proposed solution can be implemented using only inter-agent bearing measurements. Therefore, the algorithm is a sensor-based control strategy which is practically implementable using a wide range of sensors such as vision systems and range scanners. Simulation results in a two dimensional environment cluttered with agents shows that the number of possible deadlocks is marginal and decrease with the decrease in the clutteredness of the workspace.

A Hierarchical Bayesian Model for Inferring and Decision Making in Multi-Dimensional Volatile Binary Environments

The ability to track the changes of the surrounding environment is critical for humans and animals to adapt their behaviors. In high-dimensional environments, the interactions between each dimension need to be estimated for better perception and decision making, for example in volatile or social cognition tasks. We develop a hierarchical Bayesian model for inferring and decision making in multi-dimensional volatile environments. The hierarchical Bayesian model is composed of a hierarchical perceptual model and a response model. Using the variational Bayes method, we derived closed-form update rules. These update rules also constitute a complete predictive coding scheme. To validate the effectiveness of the model in multi-dimensional volatile environments, we defined a probabilistic gambling task modified from a two-armed bandit. Simulation results demonstrated that an agent endowed with the proposed hierarchical Bayesian model is able to infer and to update its internal belief on the tendency and volatility of the sensory inputs. Based on the internal belief of the sensory inputs, the agent yielded near-optimal behavior following its response model. Our results pointed this model a viable framework to explain the temporal dynamics of human decision behavior in complex and high dimensional environments.