An architectural framework for automatic detection of autism using deep convolution networks and genetic algorithm

The brainchild in any medical image processing lied in how accurately the diseases are diagnosed. Especially in the case of neural disorders such as autism spectrum disorder (ASD), accurate detection was still a challenge. Several noninvasive neuroimaging techniques provided experts information about the functionality and anatomical structure of the brain. As autism is a neural disorder, magnetic resonance imaging (MRI) of the brain gave a complex structure and functionality. Many machine learning techniques were proposed to improve the classification and detection accuracy of autism in MRI images. Our work focused mainly on developing the architecture of convolution neural networks (CNN) combining the genetic algorithm. Such artificial intelligence (AI) techniques were very much needed for training as they gave better accuracy compared to traditional statistical methods.

Formation of Baked Yarn of Complex Structure, Methods for Determining The Hairiness of The Yarn and Hair Characteristics

This paper examines the differences between the main purpose of the process of falling from individual fibers in a given linear density, density and elasticity and the methods of determining the hairiness of the yarn, the hairiness of the yarn is determined by the number of knots per unit length.

A Review on Manufacturing and Post-Processing Technology of Vascular Stents

Percutaneous coronary intervention (PCI) with stent implantation is one of the most effective treatments for cardiovascular diseases (CVDs). However, there are still many complications after stent implantation. As a medical device with a complex structure and small size, the manufacture and post-processing technology greatly impact the mechanical and medical performances of stents. In this paper, the development history, material, manufacturing method, and post-processing technology of vascular stents are introduced. In particular, this paper focuses on the existing manufacturing technology and post-processing technology of vascular stents and the impact of these technologies on stent performance is described and discussed. Moreover, the future development of vascular stent manufacturing technology will be prospected and proposed.

Nephrology considerations in the management of durable and temporary mechanical circulatory support

Durable and temporary mechanical circulatory support (MCS) use is growing for a range of cardiovascular indications. Kidney dysfunction is common in persons evaluated for or receiving durable or temporary MCS, and portends worse outcomes. This kidney dysfunction can be due to pre-existing kidney chronic kidney disease (CKD), acute kidney injury (AKI) related to acute cardiovascular disease necessitating MCS, AKI due to cardiac procedures, and due to acute and chronic MCS effects and complications. Durable MCS, with implantable continuous flow pumps, is used for long-term support in advanced HF refractory to guideline directed medical and device therapy, either permanently or as a bridge to heart transplantation. Temporary MCS-encompassing in this review intra-aortic balloon pumps (IABPs), axial flow pumps, centrifugal flow pumps, and venoarterial ECMO-is used for diverse situations: high risk percutaneous coronary interventions (PCI), acute decompensated heart failure (HF), cardiogenic shock, and resuscitation following cardiac arrest. The wide adoption of MCS makes it imperative to improve understanding of the effects of MCS on kidney health/function, and of kidney health/function on MCS outcomes. The complex structure and functions of the kidney, and the complex health states of individuals receiving MCS, makes investigations in this area challenging, and current knowledge is limited. Fortunately, the increasing nephrology toolbox of non-invasive kidney health/function assessments may enable development and testing of individualized management strategies and therapeutics in the future. We review technology, epidemiology, pathophysiology, clinical considerations, and future directions in MCS and nephrology.

Supramolecular assembly of protein building blocks: from folding to function

Several phenomena occurring throughout the life of living things start and end with proteins. Various proteins form one complex structure to control detailed reactions. In contrast, one protein forms various structures and implements other biological phenomena depending on the situation. The basic principle that forms these hierarchical structures is protein self-assembly. A single building block is sufficient to create homogeneous structures with complex shapes, such as rings, filaments, or containers. These assemblies are widely used in biology as they enable multivalent binding, ultra-sensitive regulation, and compartmentalization. Moreover, with advances in the computational design of protein folding and protein–protein interfaces, considerable progress has recently been made in the de novo design of protein assemblies. Our review presents a description of the components of supramolecular protein assembly and their application in understanding biological phenomena to therapeutics.

Effective TCP Flow Management Based on Hierarchical Feedback Learning in Complex Data Center Network

Many studies focusing on improving Transmission Control Protocol (TCP) flow control realize a more effective use of bandwidth in data center networks. They are excellent ways to more effectively use the bandwidth between clients and back-end servers. However, these schemes cannot achieve the total optimization of bandwidth use for data center networks as they do not take into account the path design of TCP flows against a hierarchical complex structure of data center networks. To address this issue, this paper proposes a TCP flow management scheme specified a hierarchical complex data center network for effective bandwidth use. The proposed scheme dynamically controls the paths of TCP flows by reinforcement learning based on a hierarchical feedback model, which obtains an optimal TCP flow establishment policy even if both the network topology and link states are more complicated. In evaluation, the proposed scheme achieved more effective bandwidth use and reduced the probability of TCP incast up to 30% than the conventional TCP flow management schemes: Variant Load Balancing (VLB), Equal Cost Multi Path (ECMP), and Intelligent Forwarding Strategy Based on Reinforcement Learning (IFS-RL) in the complex data center network.

SNX27 suppresses SARS-CoV-2 infection by inhibiting viral lysosome/late endosome entry

After binding to its cell surface receptor angiotensin converting enzyme 2 (ACE2), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the host cell through directly fusing with plasma membrane (cell surface pathway) or undergoing endocytosis traveling to lysosome/late endosome for membrane fusion (endocytic pathway). However, the endocytic entry regulation by host cell remains elusive. Recent studies show ACE2 possesses a type I PDZ binding motif (PBM) through which it could interact with a PDZ domain-containing protein such as sorting nexin 27 (SNX27). In this study, we determined the ACE2-PBM/SNX27-PDZ complex structure, and, through a series of functional analyses, we found SNX27 plays an important role in regulating the homeostasis of ACE2 receptor. More importantly, we demonstrated SNX27, together with retromer complex (the core component of the endosomal protein sorting machinery), prevents ACE2/virus complex from entering lysosome/late endosome, resulting in decreased viral entry in cells where the endocytic pathway dominates. The ACE2/virus retrieval mediated by SNX27–retromer could be considered as a countermeasure against invasion of ACE2 receptor-using SARS coronaviruses.

8 Å structure of the outer rings of the Xenopus laevis nuclear pore complex obtained by cryo-EM and AI

The nuclear pore complex (NPC), one of the largest protein complexes in eukaryotes, serves as a physical gate to regulate nucleocytoplasmic transport. Here, we determined the 8 Å resolution cryo-electron microscopic (cryo-EM) structure of the outer rings containing nuclear ring (NR) and cytoplasmic ring (CR) from the Xenopus laevis NPC, with local resolutions reaching 4.9 Å. With the aid of AlphaFold2, we managed to build a pseudoatomic model of the outer rings, including the Y complexes and flanking components. In this most comprehensive and accurate model of outer rings to date, the almost complete Y complex structure exhibits much tighter interaction in the hub region. In addition to two copies of Y complexes, each asymmetric subunit in CR contains five copies of Nup358, two copies of the Nup214 complex, two copies of Nup205 and one copy of newly identified Nup93, while that in NR contains one copy of Nup205, one copy of ELYS and one copy of Nup93. These in-depth structural features represent a great advance in understanding the assembly of NPCs.

Characterization of Thickness Loss in a Storage Tank Plate with Piezoelectric Wafer Active Sensors

In terms of the structural health inspection of storage tanks by ultrasonic guided wave technology, many scholars are currently focusing on the tanks’ floor and walls, while little research has been conducted on storage tank roofs. However, the roof of a storage tank is prone to corrosion because of its complex structure and unique working environment. For this purpose, this paper proposes a reflection/transmission signal amplitude ratio (RTAR) coefficient method for corrosion depth assessment. We studied the relationship between the RTAR coefficient, the corrosion depth, and the guided wave frequency to establish a depth assessment model. More importantly, unlike the traditional reflection coefficient method, the characteristics of guided wave signals, including the propagation and attenuation, are introduced in this model for accurate assessment. To eliminate the interference of residual vibration and improve the detection accuracy of defects, we built a corrosion detection system by using piezoelectric sensors and carried out field tests to verify the performance of the proposed method. We demonstrate that corrosion defects with a minimum depth of 0.2 mm can be quantitatively evaluated.

Landscape Characteristics Affecting Small Mammal Occurrence in Heterogeneous Olive Grove Agro-Ecosystems

Understanding how small mammals (SM) are associated with environmental characteristics in olive groves is important to identify potential threats to agriculture and assess the overall conservation value and functioning of agro-ecosystems. Here, we provide first insights on this topic applied to traditional olive groves in northeast (NE) Portugal by assessing the landscape attributes that determine SM occurrence, focusing on one species of conservation concern (Microtus cabrerae Thomas 1906) and one species often perceived as a potential pest of olives (Microtus lusitanicus Gerbe 1879). Based on SM genetic non-invasive sampling in 51 olive groves and surrounding habitats, we identified seven rodent species and one insectivore. Occupancy modelling indicated that SM were generally less detected within olive groves than in surrounding habitats. The vulnerable M. cabrerae reached a mean occupancy (95% CI) of 0.77 (0.61–0.87), while M. lusitanicus stood at 0.37 (0.24–0.52). M. cabrerae was more likely to occur in land mosaics with high density of agricultural field edges, while M. lusitanicus was more associated with high density of pastureland patches. Overall, our study suggests that the complex structure and spatial heterogeneity of traditionally managed olive grove agro-ecosystems may favor the occurrence of species-rich SM communities, possibly including well-established populations of species of conservation importance, while keeping potential pest species at relatively low occupancy rates.