Multimodal Scheme Research Articles

Alzheimer’s Disease and Melatonin/Testosterone/Estrogens: Neurophysiological and Neuroendocrinological Routing of Longevity

Alzheimer’s disease is the evolutionary, genetic and epigenetic routing of Homo sapiens , with the introduction of the ADNM - 365/22/77 (Alzheimer’s Disease & Nuclear Medicine) rehabilitation program and medical and social neurocommunications and accompaniments (Research Institute of Neuroscience, 2022). Innovative neuromodulation methods in combined neuroendocrine therapy/rehabilitation (drug, non-pharmacological, etc.) predict the protection of brain aging. To restore circadian neuroplasticity of the brain, a multimodal scheme was introduced: circadian glasses, functional nutrition and physical activity. A combined and hybrid cluster has been developed and implemented in the diagnosis, treatment, prevention and rehabilitation of cognitive impairment and cognitive disorders. Bioelectromagnetic characteristics of light exposure to the visual analyzer, is the strongest synchronizing signal for the circadian system and optimal operation of Homo sapiens brain. Optimization of neurobiological and chronomedicine processes is possible with the circadian production of melatonin and ensuring its long-term concentration in the human body. Sex hormones have numerous protective and antioxidant effects in the adult brain, increasing neural function and resistance and promoting neuronal survival. As the body ages, there is a relatively rapid loss of ovarian hormones in women after menopause and a gradual but indeed significant decrease in testosterone in men. Reproductive aging in both men and women has a negative effect on neural function and represents a significant age-related risk factor for neurodegenerative diseases, primarily Alzheimer's disease. A key positive factor in all studies is the age of initiation of menopausal hormone therapy, early initiation of menopausal hormone therapy is protective against Alzheimer's disease. Neuroendocrinological multimodal methods make it possible to significantly increase the duration of an active and high-quality healthy life of a person. The start time of exogenous estrogen therapy was also highly significantly associated with the risk of dementia: if hormone replacement therapy began in the first 5 years after the onset of menopause, the risk of developing Alzheimer’s disease was significantly lower. In addition, estrogens act in the brain, regulating a wide range of behaviors and physiological functions in both sexes.

Transparent Thiol‐ene/Acrylate‐Based MicroECoG Devices Used for Concurrent Recording of Fluorescent Calcium Signals and Electrophysiology in Awake Animals

AbstractShape memory polymers (SMPs) are suitable substrate materials for soft neural interfaces due to their tunable elastic characteristics. The stability and biocompatibility of intracortical SMP probes are demonstrated. In this work, a SMP‐based cortical implant capable of recording high‐density micro‐electrocorticography is utilized in a multimodal neuroimaging scheme. The transparent nature of thiol‐ene/acrylate substrate is exploited, and the feasibility of measuring intracranial electroencephalogram and fluorescent GCaMP6 signals with two‐photon imaging through the device is presented in mice. The potential influence of the optical properties of the microdevice is investigated using fluorescent microbeads, hippocampal brain slices, and awake animals. It is found that neurites and cell soma can be efficiently detected with sufficient resolution to follow changes in the calcium signal. These chronically implanted devices do not suppress the quality of optical signals exceeding 22 weeks after implantation. These results indicate that thiol‐ene/acrylate ECoG is an appropriate tool to combine electrophysiology with two‐photon imaging while leveraging the inherent tissue‐friendly properties of SMPs.

Elongatable Gripper Fingers With Integrated Stretchable Tactile Sensors for Underactuated Grasping and Dexterous Manipulation

The ability to grasp a wider range of objects in size and shape directly relates to the performance of robotic grippers. Adapting to complex geometries of objects requires large degrees of freedom to allow complex configurations. However, complexity in controlling many individual joints leads to introduction of underactuated mechanisms, in which traditional finger designs composed of revolute joints allow only flexion/extension motions. In this article, we propose a length-adjustable linkage mechanism in the underactuated finger controlled by an antagonistic tendon pair. The resulting gripper can elongate the fingers for an increased task space or shorten them for a finer spatial resolution. For tactile sensing, hyperelastic soft sensors are used to stretch with finger elongation. Contact pressures measured by the soft sensors are used in force-feedback control for which either the joint angles or the link lengths are adjusted. Lastly, a multimodal control scheme that combines elongation and flexion modes is demonstrated with tasks of dexterous manipulation.

Retraction Note to: A multimodal biometric authentication scheme based on feature fusion for improving security in cloud environment

Retraction Note to: A multimodal biometric authentication scheme based on feature fusion for improving security in cloud environment

Analysis and assessment of the conditions for transportation of dangerous goods along the danube as part of a multimodal scheme

Much of the dangerous goods Classes 2 and 3 are transported under the multimodal water and land transport scheme. The report analyzes the transport of dangerous goods Class 2 and 3, taking into account the specifics of transport and storage. Because of the serious risks of transporting large quantities of dangerous goods, they are also transported along the Danube River by vessels to the river ports, from where they are distributed to the gas stations in the country by trucks.

FEATURES OF THE K EY TYPE AND CHARACTER OF FIRE INJURIES OF MILITARY PERSONNEL DURING MODERN ARMED CONFLICTS

Summary. The results of studying the main damaging factors of servicemen, it is necessary to consider a large number of components of a military conflict. The problem is that in some conflicts there is little data on the loss ratio. Ancient wars were not as familiar as modern ones. Data on ancient wars are sometimes exaggerated, or vice versa, in order to prevent a catastrophe in the military and political sense, they are underestimated. The study of the structure of combat trauma remains a very topical topic. In light of the development of medical and military science, it becomes possible to consider the problem as a multimodal scheme.
 The aim of a view of the battle in the field of service every hour of the holding of a conflict.
 Materials and methods for further development. In the peaceful hour of the middle of the civilian population, there are a lot of wounds in the fire, so they have to go for the crime of criminalization of the suspension, as well as in the case of non-merciless vapours on the edge, with the unprotected, unbearable weather in the winter.
 The results of that discussion. The analysis of scientific information during the ATO / OUF showed that in the structure of sanitary losses of a surgical profile, injuries from ear problems to become 56.7% – 62.6% to the most obvious, isolated character.
 Conclusions. Clinical-epidemiological and clinical-anatomical pre-diagnoses reported that injuries due to splinter ears of children become 80.4 %, with cultivars — 13.1 %, with minor-explosive — 2.2 % and with explosive injuries.

Contribution of general aviation to ensuring transport accessibility to the Arctic regions: the challenges and areas of focus

The article defines the dominant position of general aviation to ensure passenger transportation, to render the sanitary aviation and the Ministry of Emergencies services, taking into consideration the natural and climatic conditions of the Russian Federation Eastern Arctic. It analyzes the current state of the transport system of this territory, which is characterized by the railway communication lack, available roads for only seasonal purpose – winter roads, and the key role of water transport in the organization of freight transport based on the complex long-term (more than one year) multimodal delivery schemes, extremely high cost of regional and local air transportation. The purpose of the study is to analyze the state of the general aviation system in the Eastern Arctic of Russia and identify the factors, constraining its development, and to formulate proposals for their elimination. The article examines the state of the operating airport network, route network and operators’ fleet of aircraft – in service which render services to these territories. The limited airport network does not provide aviation accessibility to each settlement of the Arctic zone and causes transport discrimination. The lack of scheduled flights in local communication leads to increased waiting time for transportation and reduces demand. The outdated general aviation fleet with low economic efficiency is outcompeted by the helicopter service. The cost of a helicopter flight hour in the Arctic is 500–650 thousand rubles. The article considers the legal restrictions, that are associated with overstated requirements for companies and aviation enterprises serving the general aviation activities and hinder the development of local air transportation in the Arctic zone. Based on the analysis of foreign experience, the areas of focus to improve the Russian legislation, regulating the general aviation activities, which will allow us to reduce the costs to maintain the airport network, thereby stimulating its expansion for the purpose of increasing the level of transport accessibility to remote settlements of the Arctic zone, are proposed. The proposed measures to improve the air transport system in the Arctic zone are aimed to achieve the formulated targets.

Research on Optimizing Multimodal Transport Path under the Schedule Limitation Based on Genetic Algorithm

Abstract Multimodal transportation is getting more and more attention due to its economical and efficient characteristics. Choosing a reasonable transportation plan can effectively control transportation costs. Considering that there are fixed schedules for railway and waterway transportation in real life, this article will establish a multimodal transportation route optimization model with the goal of minimizing the total transportation cost consisting of transportation cost, transit cost, waiting cost and carbon emission cost. The genetic algorithm based on preservation strategy and immigration strategy is used to solve the model. The effectiveness of the model is proved by the case study, and it can provide decision support for the choice of multimodal transportation scheme.

Multi-Scale Attention 3D Convolutional Network for Multimodal Gesture Recognition.

Gesture recognition is an important direction in computer vision research. Information from the hands is crucial in this task. However, current methods consistently achieve attention on hand regions based on estimated keypoints, which will significantly increase both time and complexity, and may lose position information of the hand due to wrong keypoint estimations. Moreover, for dynamic gesture recognition, it is not enough to consider only the attention in the spatial dimension. This paper proposes a multi-scale attention 3D convolutional network for gesture recognition, with a fusion of multimodal data. The proposed network achieves attention mechanisms both locally and globally. The local attention leverages the hand information extracted by the hand detector to focus on the hand region, and reduces the interference of gesture-irrelevant factors. Global attention is achieved in both the human-posture context and the channel context through a dual spatiotemporal attention module. Furthermore, to make full use of the differences between different modalities of data, we designed a multimodal fusion scheme to fuse the features of RGB and depth data. The proposed method is evaluated using the Chalearn LAP Isolated Gesture Dataset and the Briareo Dataset. Experiments on these two datasets prove the effectiveness of our network and show it outperforms many state-of-the-art methods.

Multimodal image registration for power equipment using clifford algebraic geometric invariance

Imaging inspection and video monitoring are important means for power equipment condition monitoring and diagnosis. However, single model image cannot supply sufficient information for power equipment condition monitoring, such as infrared images and visible images. The image registration can bridge this gap. This paper develops an image registration method fused by infrared and visible images, which constructs the principal direction of corner points using neighborhood contour point geometric invariance under Clifford algebraic space. Simultaneously, we also design a law for fitting optimal spatial information in the main direction of corner points, where the Clifford rotation operator is utilized to realize the spatial transformation of the image to be registered. The experiment reveals that the average registration error is less than 3 pixels by this developed method, reaching sub-pixel registration, subsequently obtaining satisfactory fusion effect of power equipment. This algorithm enriches the multimodal image registration scheme and meets the requirements of monitoring power equipment.

Multimodal Biometric Template Protection Based on a Cancelable SoftmaxOut Fusion Network

Authentication systems that employ biometrics are commonplace, as they offer a convenient means of authenticating an individual’s identity. However, these systems give rise to concerns about security and privacy due to insecure template management. As a remedy, biometric template protection (BTP) has been developed. Cancelable biometrics is a non-invertible form of BTP in which the templates are changeable. This paper proposes a deep-learning-based end-to-end multimodal cancelable biometrics scheme called cancelable SoftmaxOut fusion network (CSMoFN). By end-to-end, we mean a model that receives raw biometric data as input and produces a protected template as output. CSMoFN combines two biometric traits, the face and the periocular region, and is composed of three modules: a feature extraction and fusion module, a permutation SoftmaxOut transformation module, and a multiplication-diagonal compression module. The first module carries out feature extraction and fusion, while the second and third are responsible for the hashing of fused features and compression. In addition, our network is equipped with dual template-changeability mechanisms with user-specific seeded permutation and binary random projection. CSMoFN is trained by minimizing the ArcFace loss and the pairwise angular loss. We evaluate the network, using six face–periocular multimodal datasets, in terms of its verification performance, unlinkability, revocability, and non-invertibility.

The Trajectory of Cerebrospinal Fluid Growth-Associated Protein 43 in the Alzheimer's Disease Continuum: A Longitudinal Study.

Synaptic degeneration has been suggested as an early pathological event that strongly correlates with severity of dementia in Alzheimer's disease (AD). However, changes in longitudinal cerebrospinal fluid (CSF) growth-associated protein 43 (GAP-43) as a synaptic biomarker in the AD continuum remain unclear. To assess the trajectory of CSF GAP-43 with AD progression and its association with other AD hallmarks. CSF GAP-43 was analyzed in 788 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including 246 cognitively normal (CN) individuals, 415 individuals with mild cognitive impairment (MCI), and 127 with AD dementia based on cognitive assessments. The associations between a multimodal classification scheme with amyloid-β (Aβ), tau, and neurodegeneration, and changes in CSF GAP-43 over time were also analyzed. CSF GAP-43 levels were increased at baseline in MCI and dementia patients, and increased significantly over time in the preclinical (Aβ-positive CN), prodromal (Aβ-positive MCI), and dementia (Aβ-positive dementia) stages of AD. Higher levels of CSF GAP-43 were also associated with higher CSF phosphorylated tau (p-tau) and total tau (t-tau), cerebral amyloid deposition and hypometabolism on positron emission tomography, the hippocampus and middle temporal atrophy, and cognitive performance deterioration at baseline and follow-up. Furthermore, CSF GAP-43 may assist in effectively predicting the probability of dementia onset at 2- or 4-year follow-up. CSF GAP-43 can be used as a potential biomarker associated with synaptic degeneration in subjects with AD; it may also be useful for tracking the disease progression and for monitoring the effects of clinical trials.

Small and Medium Enterprises in Mexico and the Craft Beer Sector in Baja California: Dynamic Capabilities, Culture, and Innovation

This article studies how Small and Medium Enterprises (SMEs) operating in emerging economies implement adaptative strategies to respond to constant changes in demand and global uncertainties, such as those stemming from the current SARS-COV2 pandemic. In this study the knowledge management capabilities used by SMEs in the craft beer sector in a region of northern Mexico are the focus of analysis. The objective is to present the competitive capabilities that craft beer sector has demonstrated in Baja California region and how small companies compete with the national industrial brewery and survive. Sources are data from a sample of companies and interviews with brewery owners, with which the analysis approaches, also, the Baja California business environment. The article highlights the routes of creativity, innovation, and symbolic capital of the companies in the region, and uses ideas from dynamic capabilities and knowledge management theoretical frameworks, to understand the craft brewery milieu. The conclusions in this article include the confirmation about the usefulness of these analytical frameworks based in the capabilities approach and the territorial knowledge. Also, the description of the existence of a complex Baja Californian milieu, where a multimodal scheme of craft beer characterized by different places of distribution and types of beer container, food-districts, at Mexicali, Tijuana, and Ensenada and a second generation of entrepreneur groups leading local business, is identified.

Framework for user behavioural biometric identification using a multimodal scheme with keystroke trajectory feature and recurrent neural network on a mobile platform

Diverse applications are used on mobile devices. Because of the increasing dependence on information systems, immense amounts of personal and sensitive data are stored on mobile devices. Thus, security or privacy breaches are a major challenge. To protect mobile systems and the private information on these systems from being accessed by adversaries, a framework for mobile user identification through the use of a multimodal behavioural biometrics scheme with a keystroke trajectory feature is presented herein. Conventionally, mobile devices have been protected by mechanisms such as PINs or passwords. However, these approaches have numerous disadvantages. Therefore, approaches that employ keystroke biometrics for secure and reliable mobile device identification have been proposed. Because unimodal behavioural biometrics identification mechanisms have limited accuracy and effectiveness, a multimodal scheme that includes different behavioural biometric traits, such as keystroke and swipe biometric traits, is examined. However, the information provided by the spatial and temporal features of keystroke biometrics is not comprehensive. Therefore, a trajectory model is derived to describe the behavioural biometric uniqueness of a user. In the user identification phase, a multistream recurrent neural network (RNN) is adopted. The results reveal that the proposed trajectory model performs well, and the multimodal scheme using an RNN with a late fusion method provides accurate identification results. The proposed system achieved an accuracy of 95.29%, F1 score of 94.64%, and equal error rate of 1.78%. Thus, the proposed mobile identification system is capable of resisting attacks that standard mechanisms may be vulnerable to and represents a valuable contribution to cyber security.

From Immunosuppression to Immunomodulation - Turning Cold Tumours into Hot.

Cancer cells employ various mechanisms to evade and suppress anti-cancer immune responses generating a “cold” immunosuppressive tumour microenvironment. Oncolytic viruses are a promising tool to convert tumour immunosuppression to immunomodulation and improve the efficacy of cancer treatment. Emerging preclinical and clinical findings confirm that oncolytic viruses act in a multimodal scheme, triggering lyses, immunogenic cell death and finally inducing anti-cancer immune responses. In this paper, we tested the local administration of a novel oncolytic adenovirus AdV-D24-ICOSL-CD40L expressing co-stimulatory molecules ICOSL and CD40L to induce the production of tumour infiltrating lymphocytes to the site of injection. Subsequently, in immunocompetent mouse models, we studied possible correlation between tumour infiltrates and anti-cancer efficacy. Described results showed that the delivery of oncolytic viruses encoding immunomodulatory transgenes in combination with anti-PD1 resulted in synergistic inhibition of both melanoma and mesothelioma tumours. Importantly anti-cancer effect positively correlated with cytotoxic CD8+ tumour-infiltrating lymphocytes exerting a central role in the tumour volume control thus generating beneficial outcomes that will undoubtedly provide new insights into possible future treatment strategies to combat cancer. Altogether our findings highlight the importance of oncolytic vectors able to modulate anti-cancer immune responses that can correlate with efficacy in solid malignancies.

ТРАНСПОРТНА ЛОГІСТИКА ЯК ФАКТОР ЗАБЕЗПЕЧЕННЯ ЗОВНІШНЬОЕКОНОМІЧНОЇ ДІЯЛЬНОСТІ ВІТЧИЗНЯНИХ ПІДПРИЄМСТВ

Due to the active development of international cooperation, the issues of optimizing the process of planning and organizing the international delivery of goods and resources to the final consumer, in other words, the need for efficient transport logistics is growing. The purpose of the study is to determine the problems and prospects of transport logistics using in the foreign economic activity of domestic enterprises. Transport is one of the most important sectors of the Ukrainian economy. The share of transport services is quite significant in the structure of foreign trade of services in Ukraine. Exports of transport services in 2020 amount to 4.88 billion dollars, which is 43.7% of total exports of services. Imports – is 1.01 billion dollars (19.5%). Modern conditions of the freight market are characterized by increased competition, reduced profits, increased and emerging new requirements for the quality of services provided. Market conditions are becoming increasingly difficult for logistics and freight forwarding companies. The dynamics of cargo turnover and cargo transportation by types of transport in Ukraine has been studied and the tendency to decrease the volume of cargo turnover in recent years has been revealed. Features of transport and logistics services are considered. It is noted that the transport and logistics support of foreign economic activity should be aimed at: assessing the system of transport and logistics services for compliance with customer requirements, the structure of transport demand, based on market trends; determination of specialized transport and logistics needs, status and dynamics of demand for logistics services; study of the system of organizational and economic interaction of participants of specialized transport and logistics services of cargo transportation of enterprises. Perspective ways of improving domestic transport logistics in the field of foreign economic activity are identified, including: ensuring safe operation of transport; improving the mechanism of sanctions for violating safety rules in transport; improving energy efficiency of vehicles; optimization of multimodal logistics schemes operation; efficient use of logistics infrastructure through improved transportation management, warehousing and information systems.

Secure Multimodal Authentication Scheme for Wireless Sensor Networks

In the current era, it is necessary to device authorization and authentication techniques to secure resources in information technology. There are several methods to substantiate authorization and authentication. User authentication is essential for authenticating user access control in WSNs. Biometric recognition error, lack of anonymity and vulnerability to attacks, user verification problem, revocation problem and disclosure of session key by the gateway node are some of the security flaws encountered. In this study, a Multimodal Authentication Scheme for Wireless Sensor Networks (WSN-MAS) is proposed to authenticate legitimate users. The main objective is the fusion of fingerprint and iris biometric features at feature level to enable additional accuracy to verify and match user identity with stored templates. In this paper, multimodal biometric features are used for authentication to improve performance, reduce system error rates to achieve better security in WSN.

Focal fMRI signal enhancement with implantable inductively coupled detectors

Despite extensive efforts to increase the signal-to-noise ratio (SNR) of fMRI images for brain-wide mapping, technical advances of focal brain signal enhancement are lacking, in particular, for animal brain imaging. Emerging studies have combined fMRI with fiber optic-based optogenetics to decipher circuit-specific neuromodulation from meso to macroscales. High-resolution fMRI is needed to integrate hemodynamic responses into cross-scale functional dynamics, but the SNR remains a limiting factor given the complex implantation setup of animal brains. Here, we developed a multimodal fMRI imaging platform with an implanted inductive coil detector. This detector boosts the tSNR of MRI images, showing a 2–3-fold sensitivity gain over conventional coil configuration. In contrast to the cryoprobe or array coils with limited spaces for implanted brain interface, this setup offers a unique advantage to study brain circuit connectivity with optogenetic stimulation and can be further extended to other multimodal fMRI mapping schemes.

Biometric authentication using a deep learning approach based on different level fusion of finger knuckle print and fingernail

This paper presents a deep learning method for human authentication based on hand dorsal characteristics. The proposed method uses the fingernail (FN) and the finger knuckle print (FKP) extracted from the ring, middle and index fingers. The proposed method was evaluated using a dataset of 1090 hand dorsal images (10 each from 109 persons) which are processed by the hand skin detection, the denoising method, and the procedure adopted for extraction of both finger knuckle and fingernail. A multimodal biometric scheme is used to improve the authentication performance of the proposed system and make it more resistant to spoofing attacks. A Deep learning-based approach using a convolutional neural network (CNN) with AlexNet as a pre-trained model is employed. Different features, extracted from hand images, were combined at different levels using normalization and fusion methods proposed by the authors. Experimental results demonstrate efficiency, robustness, and reliability of the proposed biometric system compared to existing alternatives. Consequently, it can be developed in many real-world applications.

A robust multimodal biometric scheme for human recognition and authentication

A robust multimodal biometric scheme for human recognition and authentication