Miracle-dz/UniFAR-FTUs huggingface dataset:
A Plant Leaf Disease Image Classification Method Integrating Capsule Network and Residual Network

In response to the challenge that traditional convolutional neural networks face in effectively capturing the posture and spatial relationships of plant disease lesions on leaves, leading to issues of low recognition accuracy and poor robustness, this paper proposes a plant leaf disease image classification method that integrates capsule networks and residual networks. Firstly, by optimizing and refining the traditional residual network (ResNet), the initial convolutional layer of ResNet is enhanced by replacing its kernel with a concatenation of $3\times 3$ small convolutional kernels, aiming to more effectively extract features of plant leaf lesions. Subsequently, a channel attention mechanism is introduced into the residual block to heighten the model’s focus on crucial features. Finally, the improved ResNet is effectively integrated with the capsule network (CapsNet). The initial pooling layer of ResNet is removed to reduce the loss of positional information. The output of the third residual module of ResNet is then connected with CapsNet, fully leveraging the strengths of both networks to enhance the model’s robustness. Train and test the model on the PlantVillage, AI Challenger 2018, and Tomato Leaf Disease datasets and conduct comparative experiments with other typical classification models. The proposed SE-SK-CapResNet model has demonstrated a remarkable ability to accurately recognize diseased leaves, achieving an accuracy rate of 98.58%, 95.08%, and 97.19%, respectively. Furthermore, this model has exhibited superior performance in image rotation transformations and classification compared to traditional network models. These experimental results suggest that the SE-SK-CapResNet model is a promising solution for the detection of diseased leaves in the field of agriculture.
Increased Paracrine Immunomodulatory Potential of Mesenchymal Stromal Cells in Three-Dimensional Culture

Mesenchymal stromal/stem cells (MSCs) have been investigated extensively through the past years, proving to have great clinical therapeutic potential. In vitro cultivation of MSCs in three-dimensional (3D) culture systems, such as scaffolds, hydrogels, or spheroids, have recently gained attention for tissue engineering applications. Studies on MSC spheroids demonstrated that such cultivation increased the paracrine immunomodulatory potential of the MSCs, accompanied by phenotypic alterations. In this review, we gather results from recent experimental studies on the immunomodulatory abilities of MSCs when cultured as spheroids or in biomaterials like scaffolds or hydrogels compared to regular two-dimensional (2D) culture and show that alterations occurring to MSCs in spheroids also occur in MSCs in biomaterials. We provide a brief description of known mechanisms of MSC immunomodulatory capacity and how they are altered in the two 3D culture systems, together with phenotypic cellular changes. Based on the present knowledge, we highlight vital areas in need of further investigation. The impact of 3D environments on immunomodulation has great potential for tissue engineering and cellular therapy, and this is the first review to gather this knowledge with a comparison across different 3D environments.
An algorithm to estimate traditional snowfall measurements from ultrasonic snow depth sensors at U.S. observing sites

The measurement of snowfall is a climatologically important variable measured at U.S. observing sites dating back to the late 1800’s. Snowfall is inherently difficult to measure due to wind redistribution, compaction and melting that can occur prior to a snowfall measurement taking place. With automation of many U.S. observing sites in the 1990’s, snowfall measurements were abandoned due to lack of technology to continue the measurements at many locations. This study aims to test the feasibility of restoring traditional snowfall measurements at automated stations using changes in snow depth from ultrasonic sensors. The ultrasonic sensors were installed in a triplicate configuration along with a Geonor precipitation gage and a wetness sensor for verification. Results show fairly good agreement between manual measurements and automated snowfall estimates. Differences are mainly due to low density snow that is not measured by the ultrasonic sensors and also does not register measureable precipitation in the Geonor gage. Wind driven events also cause problems for the algorithm, but overall these events were mainly less than 2.5 cm (1 inch) as manually measured but not estimated by the algorithm at all. (
Separation and Lifting of TSP inequalities

The problem of separating a class of TSP inequalities consists in devising a method that, given a fractional point x for a relaxation of the TSP, either nds an inequality in the given class of TSP inequalities that is violated by x or determines that there are no such violated inequalities. Both heuristic and exact e cient separation algorithms are sought after so that we can more easily solve TSP instances when using a cutting plane approach such as branch-and-cut. We present e cient methods for exactly separating over very large classes of TSP inequalities. These inequality classes arise from node lifting familiar TSP inequalities.
Down-Regulation of a Host MicroRNA by a Herpesvirus saimiri Noncoding RNA

Herpes Virus MiRNA Modulation Viruses use a number of strategies to manipulate the cells of their host to ensure a successful infection. Herpesvirus saimiri (HVS) generates highly conserved small noncoding RNAs HSUR 1 and HSUR 2, which modulate expression of a number of proteins in infected primate T cells. Cazalla et al. (p. 1563; see the Perspective by Pasquinelli) observed complementarity between HSUR sequences and the seed regions of three different miRNAs—miR-142-3p, miR-27, and miR-16—and found that these HSURs could bind to the miRNAs. Furthermore, the level of mature miR-27 was modulated by binding to HSUR 1, which targeted the miRNA for degradation. A viral noncoding RNA regulates the level of a complementary host-cell microRNA. T cells transformed by Herpesvirus saimiri express seven viral U-rich noncoding RNAs of unknown function called HSURs. We noted that conserved sequences in HSURs 1 and 2 constitute potential binding sites for three host-cell microRNAs (miRNAs). Coimmunoprecipitation experiments confirmed that HSURs 1 and 2 interact with the predicted miRNAs in virally transformed T cells. The abundance of one of these miRNAs, miR-27, is dramatically lowered in transformed cells, with consequent effects on the expression of miR-27 target genes. Transient knockdown and ectopic expression of HSUR 1 demonstrate that it directs degradation of mature miR-27 in a sequence-specific and binding-dependent manner. This viral strategy illustrates use of a ncRNA to manipulate host-cell gene expression via the miRNA pathway.
TBK1 Kinase Addiction in Lung Cancer Cells Is Mediated via Autophagy of Tax1bp1/Ndp52 and Non-Canonical NF-κB Signalling

K-Ras dependent non-small cell lung cancer (NSCLC) cells are ‘addicted’ to basal autophagy that reprograms cellular metabolism in a lysosomal-sensitive manner. Here we demonstrate that the xenophagy-associated kinase TBK1 drives basal autophagy, consistent with its known requirement in K-Ras-dependent NSCLC proliferation. Furthermore, basal autophagy in this context is characterised by sequestration of the xenophagy cargo receptor Ndp52 and its paralogue Tax1bp1, which we demonstrate here to be a bona fide cargo receptor. Autophagy of these cargo receptors promotes non-canonical NF-κB signalling. We propose that this TBK1-dependent mechanism for NF-κB signalling contributes to autophagy addiction in K-Ras driven NSCLC.
Model based activity recognition in smart home environments

In the area of smart homes context aware systems play a key role towards adaptive smart environments. Our research currently focuses on the combination of positioning information with model-based approaches to recognize residents activity patterns (e.g. "breakfast routine"), in order to adjust the environment accordingly (e.g. light, sound and temperature). We employ a semantically enriched IFC building model for spatial analysis tasks and an ontology based component to reason about typical activity patterns in order to derive reliable situation estimations. Living Place Hamburg, a fully functional smart home, allows for evaluation of our results under real life conditions. Keywords—smart home, context awareness, low level context reasoning, spatial analysis, ontology based context reasoning
Facial Reconstruction Using Volumetric Data

In this paper we demonstrate computer aided techniques in the area of the reconstruction of facial features from skeletal remains. We outline the desired features of a system for skull identification, and demonstrate our progress in the area which builds upon our previous work on distance fields for volumetric data. In addition to the application we demonstrate an accurate 3D closing operator in practise on large data sets, cross correlation for automatic feature detection, and the current output from the technique which uses a 2D warp of the 3D distance field.
Implications of climatic and non-climatic variables on food security in developing economies: a conceptual review

Numerous of studies estimate the influence of climatic factors on food-grain crops as a proxy for integrated food security in different regions of India, conclude that climate change has a significant and negative impact on food security in India [13]. Few studies used agricultural productivity of food-grain and commercial crops to assess the climatic change impact on agricultural productivity using district-wise and state-wise panel data in India [2,4-7]. These studies also predicted that climate change would bring serious threat for food security especially for developing countries [1-3,8]. Since, food security is not a function of foodgrain crops only and some other socio-economic and government policy factors also may affect the food security. Therefore, study based on food-grain crops may be unable to identify the actual situation of food security. Earlier studies did not empirically measure the influence of climatic factors on overall food security. Overall food security covers all the components of food security that is consider as food security index (FSI) [5,9-11]. FSI is an integrated index that includes a wide range of factors which are significantly associated with food security [5,9-11]. Furthermore, there is debate ongoing among the researchers in different field of studies (e.g., economics, sociology, health and biological sciences), national policy makers, development thinkers, international development organization and global policy maker that what must be proper solution to estimate the influence of climatic indicators, socio-economic variables, government policy factors and geographical factors on overall food security at individual level to households level, and country level to global level [9-12]. But anyone could not develop a concrete and rational scientific method to solve aforementioned problem. The question, therefore, to estimate the influence of climatic parameters and geographical location on FSI is still a greater challenge for existing researchers. For above-mentioned perspectives, few studies argued that scientific research communities need to develop an appropriate econometric model which would be useful to investigate the complex association of climatic factors with FSI. To account aforesaid drawback of earlier studies, the present study attempts to answer the following research questions:
Combination of methylated-DNA precipitation and methylation-sensitive restriction enzymes (COMPARE-MS) for the rapid, sensitive and quantitative detection of DNA methylation

Hypermethylation of CpG island (CGI) sequences is a nearly universal somatic genome alteration in cancer. Rapid and sensitive detection of DNA hypermethylation would aid in cancer diagnosis and risk stratification. We present a novel technique, called COMPARE-MS, that can rapidly and quantitatively detect CGI hypermethylation with high sensitivity and specificity in hundreds of samples simultaneously. To quantitate CGI hypermethylation, COMPARE-MS uses real-time PCR of DNA that was first digested by methylation-sensitive restriction enzymes and then precipitated by methyl-binding domain polypeptides immobilized on a magnetic solid matrix. We show that COMPARE-MS could detect five genome equivalents of methylated CGIs in a 1000- to 10 000-fold excess of unmethylated DNA. COMPARE-MS was used to rapidly quantitate hypermethylation at multiple CGIs in >155 prostate tissues, including benign and malignant prostate specimens, and prostate cell lines. This analysis showed that GSTP1, MDR1 and PTGS2 CGI hypermethylation as determined by COMPARE-MS could differentiate between malignant and benign prostate with sensitivities >95% and specificities approaching 100%. This novel technology could significantly improve our ability to detect CGI hypermethylation.
Quantitative Estimation of RNA Transcripts Suggests Persistence of Pax-6 Expression in the Postembryonic Chick Retina

Pax-6 is expressed during early embryonic development of the eye. Very little is known about its expression in the functionally mature retina. We have detected Pax-6 transcripts in the ganglion cell- and amacrine cell layers at days 3, 10, 17 and 31 posthatching and in 2- to 3-month-old chick retina by in situ hybridization. These observations were confirmed by a quantitative analysis. Competitive RT-PCR with a homologous internal control revealed a significant reduction (p < 0.001) in the number of Pax-6 transcripts in day 17 retina [(0.39 ± 0.13) × 1010/mg tissue] compared to day 3 retina [(1.65 ± 0.48) × 1010/mg tissue]. Although significantly lower than at day 3, the day 31 retina [(0.7 ± 0.16) × 1010/mg tissue] and retina from 2- to 3-month-old chicks [(0.9 ± 0.28) × 1010/mg tissue] contained an increased number of Pax-6 transcripts in comparison to day 17. On the basis of the amount of RNA, the number of Pax-6 transcripts in the day 3 retina [(0.45 ± 0.14) × 1010/μg RNA] relative to day 17 retina [(0.4 ± 0.08) × 1010/μg RNA] did not change significantly (p = 0.29). However, at day 31 and at 2–3 months of age an increased number of Pax-6 transcripts [(0.65 ± 0.14) × 1010/μg RNA and (0.65 ± 0.2) × 1010/μg RNA, respectively)] were found. In view of the known association of Pax-6 expression with proliferation and emergence of different cell types, these data suggest that cell types in ganglion and inner nuclear cell layers may retain proliferative potential for an extended period in the young adult retina.
Two Multiplex Assays That Simultaneously Identify 22 Possible Mutation Sites in the KRAS, BRAF, NRAS and PIK3CA Genes

Recently a number of randomized trials have shown that patients with advanced colorectal cancer do not benefit from therapies targeting the epidermal growth factor receptor when their tumors harbor mutations in the KRAS, BRAF and PIK3CA genes. We developed two multiplex assays that simultaneously screen 22 nucleotides in the KRAS, NRAS, BRAF and PIK3CA genes for mutations. The assays were validated on 294 tumor DNA samples from patients with advanced colorectal cancer. In these samples 119 KRAS codon 12 and 13 mutations had been identified by sequence analysis, 126 tumors were wild-type for KRAS and the analysis failed in 49 of the 294 samples due to poor DNA quality. The two mutation assays detected 130 KRAS mutations, among which were 3 codon 61 mutations, and in addition 32 PIK3CA, 13 BRAF and 6 NRAS mutations. In 19 tumors a KRAS mutation was found together with a mutation in the PIK3CA gene. One tumor was mutant for both PIK3CA and BRAF. In summary, the mutations assays identified 161 tumors with a mutation, 120 were wild-type and the analysis failed in 13. The material cost of the 2 mutation assays was calculated to be 8-fold lower than the cost of sequencing required to obtain the same data. In addition, the mutation assays are less labor intensive. We conclude that the performance of the two multiplex mutation assays was superior to direct sequencing. In addition, these assays are cheaper and easier to interpret. The assays may also be of use for selection of patients with other tumor types.
Sediment provenance, sediment-dispersal systems, and major arc-magmatic events recorded in the Mexican foreland basin, North-Central and Northeastern Mexico

ABSTRACT The Late Cretaceous-Paleogene Mexican foreland basin (MFB), defined herein, represents the southern continuation of the late Mesozoic Cordilleran foreland basin. Sandstone petrography, new detrital-zircon (DZ) U-Pb geochronology, and paleocurrent data indicate that much of the sedimentary fill of the basin was derived from an active Late Cretaceous-Paleogene magmatic arc, termed here the Mexican Cordilleran arc, on the western continental margin of Mexico. The oldest known strata of the proximal foreland basin in the Mesa Central consist of Cenomanian-Turonian turbidites. Sampled sandstones are compositional volcanic litharenites with abundant neovolcanic grains and a dominant, approximately syndepositional DZ age group ranging ~98–92 Ma that records a major magmatic event in the Mexican Cordilleran arc. Santonian-Campanian strata in the distal MFB consist of carbonate pelagites with abundant interbedded tuffs and tuffaceous sandstones. Represented by the Caracol and San Felipe formations deposited in the forebulge and back-bulge depozones, respectively, these strata form an arcuate outcrop belt ~700 km in length. DZ ages ranging ~85–74 Ma in the arc-derived tuffaceous strata record a second prominent magmatic event. Two principal transport mechanisms delivered volcanogenic sediment to the MFB from multiple, simultaneously active arc sources during Late Cretaceous time: (1) Cenomanian-Turonian east-directed transverse fluvial systems transported volcanic-lithic sand rich in young zircon grains; and (2) airborne ash clouds transported Santonian-Campanian zircon grains to the distal foreland basin in prevailing Late Cretaceous northwesterly winds. Axial transport of sediment derived from active arc sources, Proterozoic basement and derivative sedimentary rocks in northwestern Mexico, in addition to transverse transport from the thrust orogen itself, represents a younger sediment-routing system, modified by advance of the foreland fold-thrust belt, to the Maastrichtian-Paleogene foreland of northeastern Mexico.
Symbol Error Rate Expression for Decode-and-Forward Relaying Using Generalized Selection Combining over Rayleigh Fading Channels

SUMMARY Cooperative transmission is an efficient approach to improve the performance of wireless communications over fading channels without the need for physical co-located antenna arrays. In this paper, we propose a novel cooperative protocol with selective decode-and-forward relays and generalized selection combining (GSC) technique at destination. The advantage of this scheme is that it not only allows us to optimize the structure of destination but also to fully exploit the diversity offered by the channels with an appropriate number of chosen strongest paths. For an arbitrary number of relays, an exact and closed-form expression of the Symbol Error Rate (SER) is derived for M-ary PSK in independent but not identically distributed Rayleigh fading channels. Various simulations are performed and their results exactly match the results of analyses.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

Abstract The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
The transporter associated with antigen processing: a key player in adaptive immunity

Abstract The adaptive immune system co-evolved with sophisticated pathways of antigen processing for efficient clearance of viral infections and malignant transformation. Antigenic peptides are primarily generated by proteasomal degradation and translocated into the lumen of the endoplasmic reticulum (ER) by the transporter associated with antigen processing (TAP). In the ER, peptides are loaded onto major histocompatibility complex I (MHC I) molecules orchestrated by a multisubunit peptide-loading complex (PLC). Peptide-MHC I complexes are targeted to the cell surface for antigen presentation to cytotoxic T cells, which eventually leads to the elimination of virally infected or malignantly transformed cells. Here, we review MHC I mediated antigen processing with a primary focus on the function and structural organization of the heterodimeric ATP-binding cassette (ABC) transporter TAP1/2. We discuss recent data on the molecular transport mechanism of the antigen translocation complex with respect to structural and biochemical information of other ABC exporters. We further summarize how TAP provides a scaffold for the assembly of the macromolecular PLC, thereby coupling peptide translocation with MHC I loading. TAP inhibition by distinct viral evasins highlights the important role of TAP in adaptive immunity.
Transmission Electron Microscopy for the Characterization of Cellulose Nanocrystals

Cellulose nanocrystals (CNCs) are high aspect ratio nanomaterials readily obtained from cellulose microfibrils via strong acid hydrolysis. They feature unique properties stemming from their surface chemistry, their crystallinity, and their three-dimensional structure. CNCs have been exploited in a number of applica‐ tions such as optically active coatings, nanocomposite materials, or aerogels. CNC size and shape determination is an important challenge and transmission electron microscopy (TEM) is one of the most powerful tools to achieve this goal. Because of the specifics of TEM imaging, CNCs require special attention. They have a low density, are highly susceptible to electron beam damage, and easily aggregate. Specific techniques for both imaging and sampling have been developed over the past decades. In this review, we describe the CNCs, their properties, their applications, and the need for a precise characterization of their morphology and size distribution. We also describe in detail the techniques used to record quality images of CNCs. Finally, we survey the literature to provide readers with specific examples of TEM images of CNCs.