Computer-Vision-Oriented Adaptive Sampling in Compressive Sensing.

Compressive sensing (CS) is recognized for its adeptness at compressing signals, making it a pivotal technology in the context of sensor data acquisition. With the proliferation of image data in Internet of Things (IoT) systems, CS is expected to reduce the transmission cost of signals captured by various sensor devices. However, the quality of CS-reconstructed signals inevitably degrades as the sampling rate decreases, which poses a challenge in terms of the inference accuracy in downstream computer vision (CV) tasks. This limitation imposes an obstacle to the real-world application of existing CS techniques, especially for reducing transmission costs in sensor-rich environments. In response to this challenge, this paper contributes a CV-oriented adaptive CS framework based on saliency detection to the field of sensing technology that enables sensor systems to intelligently prioritize and transmit the most relevant data. Unlike existing CS techniques, the proposal prioritizes the accuracy of reconstructed images for CV purposes, not only for visual quality. The primary objective of this proposal is to enhance the preservation of information critical for CV tasks while optimizing the utilization of sensor data. This work conducts experiments on various realistic scenario datasets collected by real sensor devices. Experimental results demonstrate superior performance compared to existing CS sampling techniques across the STL10, Intel, and Imagenette datasets for classification and KITTI for object detection. Compared with the baseline uniform sampling technique, the average classification accuracy shows a maximum improvement of 26.23%, 11.69%, and 18.25%, respectively, at specific sampling rates. In addition, even at very low sampling rates, the proposal is demonstrated to be robust in terms of classification and detection as compared to state-of-the-art CS techniques. This ensures essential information for CV tasks is retained, improving the efficacy of sensor-based data acquisition systems.

Rapid, Micron-Resolution 3D Printing of Nd:YAG Ceramic with Optical Gain.

Polycrystalline yttrium aluminum garnet (YAG) ceramic doped with neodymium (Nd), referred to as Nd:YAG, is widely used in solid-state lasers. However, conventional powder metallurgy methods suffer from expenses, time consumption, and limitations in customizing structures. This study introduces a novel approach for creating Nd:YAG ceramics with 3D free-form structures from micron (∼70 µm) to centimeter scales. Firstly, sol-gel synthesis is employed to form photocurable colloidal solutions. Subsequently, by utilizing a home-built micro-continuous liquid interface printing process, precursors are printed into 3D poly(acrylic acid) hydrogels containing yttrium, aluminum, and neodymium hydroxides, with a resolution of 5.8 µm pixel-1 at a speed of 10 µm s-1. After the hydrogels undergo thermal dehydration, debinding, and sintering, polycrystalline Nd:YAG ceramics featuring distinguishable grains are successfully produced. By optimizing the concentrations of the sintering aids (tetraethyl orthosilicate) and neodymium trichloride (NdCl3), the resultant samples exhibit satisfactory photoluminescence, emitting light concentrated at 1064 nm when stimulated by a 532 nm laser. Additionally, Nd:YAG ceramics with various 3D geometries (e.g., cone, spiral, and angled pillar) are printed and characterized, which demonstrates the potential for applications, such as laser and amplifier fibers, couplers, and splitters in optical circuits, as well as gain metamaterials or metasurfaces.

Host plant-induced changes in metabolism and osmotic regulation gene expression in Diaphorina citri adults.

The Asian citrus psyllid (ACP), Diaphorina citri Kuwayama (Hemiptera: Liviidae), is a worldwide citrus pest. It transmits the pathogen Candidatus Liberibacter spp. of Huanglongbing (HLB), causing severe economic losses to the citrus industry. Severalgenera of plants in the Rutaceae family are the hosts of D. citri. However, the impact of these hosts on the metabolism and osmotic regulation gene expression of the pest remains unexplored. In this study, the contents of total sugars, sucrose, fructose, and glucose in young shoots, old leaves, and young leaves of 'Shatangju' mandarin and Murraya exotica were analyzed. Metabolomic analysis found that sucrose and trehalose were more abundant in the gut samples of D. citri adults fed on M. exotica when compared to what's in 'Shatangju' mandarin. A total of six aquaporin genes were identified in D. citri through the genome and transcriptome data. Subsequently, the expression patterns of these genes were investigated with respect to their developmental stage and tissue specificity. Additionally, the expression levels of osmotic regulation and trehalose metabolism genes in adults fed on different plants were evaluated. Our results provide useful information on the transfer of sugar between plants and D. citri. Our results preliminary revealed the sugar metabolism regulation mechanism in D. citri adults.

Simultaneous determination of five compounds of fried Radix Paeoniae Alba extract in beagle dogs plasma by Ultra Performance Liquid Chromatography Tandem Mass Spectrometry and its application in a pharmacokinetic study.

In this present study, we developed a reliable and simple ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) assay for the simultaneous quantification of paeoniflorin, albiflorin, oxypaeoniflorin, benzoylpaeoniflorin and isomaltopaeoniflorin in beagle dog plasma. We also analyzed the pharmacokinetics of those components after oral administration of fried Radix Paeoniae Alba (FRPA) in beagle dogs. Plasma samples were processed by protein precipitation with methanol. Chromatographic separation was performed with a Waters HSS-T3 C18 column (100 × 2.1 mm, 1.8 µm, kept at 40°C) using multiple reaction monitoring mode. A gradient elution procedure was used with solvent A (0.02% formic acid-water) and solvent B (0.02% formic acid-acetonitrile) as mobile phases. Method validation was performed as US Food and Drug Administration guidelines, and the results met the acceptance criteria. The method we establish in this experiment was successfully applied to the pharmacokinetic study after oral administration of FRPA extract to beagle dogs.

Characterization and transcriptomic analyses of the toxicity induced by toosendanin in Spodoptera frugipreda.

The fall armyworm, Spodoptera frugiperda, is a destructive agricultural pest that seriously threatens global food security. Insecticide resistance of this pest has gradually formed in recent years due to improper usage, and alternative methods are badly needed. Toosendanin (TSN) is a botanical compound with broad-spectrum insecticidal activities against many pests. However, the effects of TSN on S. frugiperda are still unclear. In this study, the growth inhibition phenomenon, including weight loss and prolonged developmental duration, in the larvae with TSN exposure was clearly observed. Compared to the control group, a total of 450 and 3314 differentially expressed genes (DEGs) were identified by RNA-Seq in the larvae groups treated with 10 and 20 mg/kg TSN, respectively. Furthermore, the DEGs involved in the juvenile hormone and ecdysone signal pathways and downstream processes, including detoxifying enzyme genes, chitin synthesis and metabolism genes, and cuticular protein genes, were found. Our findings suggest that TSN regulates the expression of key genes in juvenile hormone and ecdysone signal pathways and a series of downstream processes to alter the hormone balance and cuticle formation and eventually inhibit larval growth, which laid the foundation for the molecular toxicological mechanism research of TSN on S. frugiperda larvae.

The effects of carvacrol on development and gene expression profiles in Spodoptera frugiperda.

The fall armyworm, Spodoptera frugiperda, is a highly polyphagous agricultural pest that is widely distributed around the world and causes severe crop yield loss. Carvacrol showed adverse effects on many pests, such as larval death and growth inhibition. While the effects of carvacrol on S. frugiperda larvae are not yet known. In this study, the effects of carvacrol on S. frugiperda, including larval growth inhibition and mortality induction, were observed. The detoxification and digestive enzyme activities of larvae with 1.0 and 2.0 g/kg carvacrol treatments were analyzed. Carvacrol boosted the enzyme activities of carboxylesterase (CarE) and glutathione S-transferase (GST) while decreasing the activities of α-amylase (AMS), lipase (LIP), and trypsin. A total of 3422 differentially expressed genes were identified in the larvae treated with 2.0 g/kg carvacrol, of which the DEGs involved in xenobiotic detoxification, food digestion, and insecticidal targets were further examined. These results suggest that carvacrol could regulate growth and development by affecting the process of food digestion, and exert its toxicity on the larvae through interaction with a variety of insecticidal targets. While the altered expressions of detoxification enzymes might be related to the detoxification and metabolism of carvacrol. Our findings offer a theoretical foundation for the use of carvacrol for S. frugiperda control in the field.

Characterization of the physiological, histopathological, and gene expression alterations in Spodoptera frugiperda larval midguts affected by toosendanin exposure.

The fall armyworm, Spodoptera frugiperda, is a polyphagous pest worldwide and feeds on many grain and cash crops, which threatens the safety of agriculture and forestry production. Toosendanin (TSN) is a commercial insecticidal active ingredient used to manage various pests in the field and showed adverse effects against S. frugiperda, while the effects of TSN on the larval midguts are not yet known. In this study, the effects of 10 and 20 mg/kg TSN exposures on the larval midguts were analyzed. The structural changes of the larval midgut induced by TSN treatments were also determined by hematoxylin-eosin staining. Besides, TSN treatments also changed the enzyme activities of three digestive enzymes (α-amylase, lipase, and trypsin) and two detoxification enzymes (CarE and GST). A total of 2868 differentially expressed genes (DEGs) were identified by RNA-Seq in the larval midguts with 20 mg/kg TSN treatment, and the DEGs responsible for food digestion and detoxification were further examined. Our findings revealed the preliminary modes of action of TSN on the larval midguts of S. frugiperda, which provide a preliminary rationale for controlling S. frugiperda with TSN in the field.

Skip DETR: end-to-end Skip connection model for small object detection in forestry pest dataset.

Object detection has a wide range of applications in forestry pest control. However, forest pest detection faces the challenges of a lack of datasets and low accuracy of small target detection. DETR is an end-to-end object detection model based on the transformer, which has the advantages of simple structure and easy migration. However, the object query initialization of DETR is random, and random initialization will cause the model convergence to be slow and unstable. At the same time, the correlation between different network layers is not strong, resulting in DETR is not very ideal in small object training, optimization, and performance. In order to alleviate these problems, we propose Skip DETR, which improves the feature fusion between different network layers through skip connection and the introduction of spatial pyramid pooling layers so as to improve the detection results of small objects. We performed experiments on Forestry Pest Datasets, and the experimental results showed significant AP improvements in our method. When the value of IoU is 0.5, our method is 7.7% higher than the baseline and 6.1% higher than the detection result of small objects. Experimental results show that the application of skip connection and spatial pyramid pooling layer in the detection framework can effectively improve the effect of small-sample obiect detection.

Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) now arise in the context of heterogeneous human connectivity and population immunity. Through a large-scale phylodynamic analysis of 115,622 Omicron BA.1 genomes, we identified >6,000 introductions of the antigenically distinct VOC into England and analyzed their local transmission and dispersal history. We find that six of the eight largest English Omicron lineages were already transmitting when Omicron was first reported in southern Africa (22 November 2021). Multiple datasets show that importation of Omicron continued despite subsequent restrictions on travel from southern Africa as a result of export from well-connected secondary locations. Initiation and dispersal of Omicron transmission lineages in England was a two-stage process that can be explained by models of the country's human geography and hierarchical travel network. Our results enable a comparison of the processes that drive the invasion of Omicron and other VOCs across multiple spatial scales.

The comparison of gut gene expression and bacterial community in Diaphorina citri (Hemiptera: Liviidae) adults fed on Murraya exotica and 'Shatangju' mandarin (Citrus reticulate cv. Shatangju).

BACKGROUND: Diaphorina citri Kuwayama is an important citrus pest. It serves as the vector for the transmission of Candidatus Liberibacter asiaticus (CLas), which induced a destructive disease, Huanglongbing, and caused huge economic losses. During the interaction between insects and plants, insects have evolved a series of mechanisms to adapt to various host plants. Murraya exotica and 'Shatangju' mandarin (Citrus reticulate cv. Shatangju) are the Rutaceae species from different genera that have been discovered as suitable hosts for D. citri adults. While the adaptation mechanism of this pest to these two host plants is unclear. RESULTS: In this study, RNA-seq and 16 S rDNA amplification sequencing were performed on the gut of D. citri adults reared on M. exotica and 'Shatangju' mandarin. RNA-seq results showed that a total of 964 differentially expressed genes were found in different gut groups with two host plant treatments. The impacted genes include those that encode ribosomal proteins, cathepsins, and mitochondrial respiratory chain complexes. According to 16 S rDNA sequencing, the compositions of the gut bacterial communities were altered by different treatments. The α and ß diversity analyses confirmed that the host plant changes influenced the gut microbial diversity. The functional classification analysis by Tax4Fun revealed that 27 KEGG pathways, mostly those related to metabolism, including those for nucleotide metabolism, energy metabolism, metabolism of cofactors and vitamins, amino acid metabolism, carbohydrate metabolism, xenbiotics biodegradation and metabolism, lipid metabolism, and biosynthesis of other secondary metabolites, were significantly altered. CONCLUSION: Our preliminary findings shed light on the connection between D. citri and host plants by showing that host plants alter the gene expression profiles and bacterial community composition of D. citri adults.

A Tunable Terahertz Absorber Based on Double-Layer Patterned Graphene Metamaterials.

Graphene is widely used in tunable photonic devices due to its numerous exotic and exceptional properties that are not found in conventional materials, such as high electron mobility, ultra-thin width, ease of integration and good tunability. In this paper, we propose a terahertz metamaterial absorber that is based on patterned graphene, which consists of stacked graphene disk layers, open ring graphene pattern layers and metal bottom layers, all separated by insulating dielectric layers. Simulation results showed that the designed absorber achieved almost perfect broadband absorption at 0.53-1.50 THz and exhibited polarization-insensitive and angle-insensitive characteristics. In addition, the absorption characteristics of the absorber can be adjusted by changing the Fermi energy of graphene and the geometrical parameters of the structure. The above results indicate that the designed absorber can be applied to photodetectors, photosensors and optoelectronic devices.

Polymerization-Induced Proteinosome Formation Initiated by Artificial Cells.

Cellular communication is essential for living cells to coordinate the individual cellular responses and make collective behaviors. In the past decade, the communications between artificial cells have aroused great interest due to the potential applications of the structures in bioscience and biotechnology. To mimic the cellular communication, artificial cell assisted synthesis of proteinosomes was studied in this research. Multienzyme proteinosomes with glucose oxidase (GOx) and horseradish peroxidase (HRP) decorated on the membranes were synthesized by the thermally triggered self-assembly approach. Free radicals produced in a cascade reaction taking place on the surfaces of the multienzyme proteinosomes initiated reversible addition-fragmentation chain transfer (RAFT) polymerization of NIPAM at a temperature above LCST of PNIPAM in the presence of bovine serum albumin (BSA) or alcohol dehydrogenase (ADH)/acetaldehyde dehydrogenase (ALDH), and daughter proteinosomes with BSA or ADH/ALDH on the surfaces were fabricated. The structures of the GOx/HRP initiator proteinosomes, and the synthesized daughter proteinosomes were characterized with transmission electron microscopy, atomic force microscopy, fluorescence microscopy, dynamic light scattering, and micro-DSC. Enzyme activity assays demonstrate the high bioactivities of the enzymes on the surfaces of the initiator and the synthesized daughter proteinosomes.

Privacy-preserving Speech-based Depression Diagnosis via Federated Learning.

Mental health disorders, such as depression, affect a large and growing number of populations worldwide, and they may cause severe emotional, behavioral and physical health problems if left untreated. As depression affects a patient's speech characteristics, recent studies have proposed to leverage deep-learning-powered speech analysis models for depression diagnosis, which often require centralized learning on the collected voice data. However, this centralized training requiring data to be stored at a server raises the risks of severe voice data breaches, and people may not be willing to share their speech data with third parties due to privacy concerns. To address these issues, in this paper, we demonstrate for the first time that speech-based depression diagnosis models can be trained in a privacy-preserving way using federated learning, which enables collaborative model training while keeping the private speech data decentralized on clients' devices. To ensure the model's robustness under attacks, we also integrate different FL defenses into the system, such as norm bounding, differential privacy, and secure aggregation mechanisms. Extensive experiments under various FL settings on the DAIC-WOZ dataset show that our FL model can achieve high performance without sacrificing much utility compared with centralized-learning approaches while ensuring users' speech data privacy. Clinical Relevance- The experiments were conducted on publicly available clinical datasets. No humans or animals were involved.

The integrated landscape of eRNA in gastric cancer reveals distinct immune subtypes with prognostic and therapeutic relevance.

The comprehensive regulation effect of eRNA on tumor immune cell infiltration and the outcome remains obscure. We comprehensively identify the eRNA-mediated immune infiltration patterns of gastric cancer (GC) samples. We creatively proposed a random forest machine-learning (ML) algorithm to map eRNA to mRNA expression patterns. The eRNA score was constructed using principal component analysis algorithms and validated in an independent cohort. Three subtypes with distinct eRNA expression patterns were determined in GC. There were significant differences between the three subtypes in the overall survival rate, immune cell infiltration characteristics, and immunotherapy response indicators. The patients in the high eRNA score group have a higher overall survival rate and might benefit from immunotherapy. This work revealed that eRNA regulation might be a new prognostic index and might offer a potential biomarker in the response of immunotherapy. Evaluating the eRNA regulation manner of GC will contribute to guiding more effective immunotherapy strategies.

Fair and Privacy-Preserving Alzheimer's Disease Diagnosis Based on Spontaneous Speech Analysis via Federated Learning.

As the most common neurodegenerative disease among older adults, Alzheimer's disease (AD) would lead to loss of memory, impaired language and judgment, gait disorders, and other cognitive deficits severe enough to interfere with daily activities and significantly diminish quality of life. Recent research has shown promising results in automatic AD diagnosis via speech, leveraging the advances of deep learning in the audio domain. However, most existing studies rely on a centralized learning framework which requires subjects' voice data to be gathered to a central server, raising severe privacy concerns. To resolve this, in this paper, we propose the first federated-learning-based approach for achieving automatic AD diagnosis via spontaneous speech analysis while ensuring the subjects' data privacy. Extensive experiments under various federated learning settings on the ADReSS challenge dataset show that the proposed model can achieve high accuracy for AD detection while achieving privacy preservation. To ensure fairness of the model performance across clients in federated settings, we further deploy fair aggregation mechanisms, particularly q-FEDAvg and q-FEDSgd, which greatly reduces the algorithmic biases due to the data heterogeneity among the clients. Clinical Relevance -The experiments were conducted on publicly available clinical datasets. No humans or animals were involved.

Integrated miRNA and transcriptome profiling to explore the molecular mechanism of Spodoptera frugiperda larval midgut in response to azadirachtin exposure.

As a destructive agricultural pest, Spodoptera frugiperda has spread worldwide in the past few years. Azadirachtin, an environmentally friendly and most promising compound, showed adverse effects, including mortality and growth inhibition, against S. frugiperda. While the effects of azadirachtin on the midgut of this pest remain to be determined. In this study, structural damage was observed in the larval midguts of S. frugiperda with azadirachtin exposure. RNA-seq on the larval midguts with different azadirachtin treatments was performed. Compared to the control group, a total of 3344 and 4759 differentially expressed genes (DEGs) were identified in the midguts with 0.1 and 0.5 µg/g azadirachtin exposure, respectively. Among them, the DEGs encoding detoxification enzymes/proteins, immune-related proteins, digestion and absorption-related proteins, and transcript factors were further analyzed. High-throughput sequencing was also used for the identification of differentially expressed microRNAs in different treatments. A total of 153 conserved miRNAs and 147 novel miRNAs were identified, of which 11 and 29 miRNAs were affected by 0.1 and 0.5 µg/g azadirachtin treatments, respectively. The integrated analysis found that 13 and 178 miRNA versus mRNA pairs were acquired in the samples with 0.1 and 0.5 µg/g azadirachtin treatments, respectively. The results of high-throughput sequencing were confirmed by real-time quantitative polymerase chain reaction (RT-qPCR). These results provide useful information for revealing the molecular mechanism of S. frugiperda larval midgut in response to azadirachtin.

Continuous Three-Dimensional Printing of Architected Piezoelectric Sensors in Minutes.

Additive manufacturing (AM), also known as three-dimensional (3D) printing, is thriving as an effective and robust method in fabricating architected piezoelectric structures, yet most of the commonly adopted printing techniques often face the inherent speed-accuracy trade-off, limiting their speed in manufacturing sophisticated parts containing micro-/nanoscale features. Herein, stabilized, photo-curable resins comprising chemically functionalized piezoelectric nanoparticles (PiezoNPs) were formulated, from which microscale architected 3D piezoelectric structures were printed continuously via micro continuous liquid interface production (µCLIP) at speeds of up to ~60 µm s-1, which are more than 10 times faster than the previously reported stereolithography-based works. The 3D-printed functionalized barium titanate (f-BTO) composites reveal a bulk piezoelectric charge constant d 33 of 27.70 pC N-1 with the 30 wt% f-BTO. Moreover, rationally designed lattice structures that manifested enhanced, tailorable piezoelectric sensing performance as well as mechanical flexibility were tested and explored in diverse flexible and wearable self-powered sensing applications, e.g., motion recognition and respiratory monitoring.

A Dataset for Forestry Pest Identification.

The identification of forest pests is of great significance to the prevention and control of the forest pests' scale. However, existing datasets mainly focus on common objects, which limits the application of deep learning techniques in specific fields (such as agriculture). In this paper, we collected images of forestry pests and constructed a dataset for forestry pest identification, called Forestry Pest Dataset. The Forestry Pest Dataset contains 31 categories of pests and their different forms. We conduct several mainstream object detection experiments on this dataset. The experimental results show that the dataset achieves good performance on various models. We hope that our Forestry Pest Dataset will help researchers in the field of pest control and pest detection in the future.

Effect of estradiol as a continuous variable on breast cancer survival by menopausal status: a cohort study in China.

High levels of circulating estradiol (E2) are associated with increased risk of breast cancer, whereas its relationship with breast cancer prognosis is still unclear. We evaluated the effect of E2 concentration on survival endpoints among 8766 breast cancer cases diagnosed between 2005 and 2017 from the Tianjin Breast Cancer Cases Cohort. Levels of serum E2 were measured in pre-menopausal and post-menopausal women. Multivariable-adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI) between quartile of E2 levels and overall survival (OS) and progression-free survival (PFS) of breast cancer. The penalized spline was then used to test for non-linear relationships between E2 (continuous variable) and survival endpoints. 612 deaths and 982 progressions occurred over follow-up through 2017. Compared to women in the quartile 3, the highest quartile of E2 was associated with reduced risk of both PFS in pre-menopausal women (HR 1.79, 95% CI 1.17-2.75, P = 0.008) and OS in post-menopausal women (HR 1.35, 95% CI 1.04-1.74, P = 0.023). OS and PFS in pre-menopausal women exhibited a nonlinear relation ("L-shaped" and "U-shaped", respectively) with E2 levels. However, there was a linear relationship in post-menopausal women. Moreover, patients with estrogen receptor-negative (ER-negative) breast cancer showed a "U-shaped" relationship with OS and PFS in pre-menopausal women. Pre-menopausal breast cancer patients have a plateau stage of prognosis at the intermediate concentrations of E2, whereas post-menopausal patients have no apparent threshold, and ER status may have an impact on this relationship.

Genome-wide association and functional interrogation identified a variant at 3p26.1 modulating ovarian cancer survival among Chinese women.

Ovarian cancer survival varies considerably among patients, to which germline variation may also contribute in addition to mutational signatures. To identify genetic markers modulating ovarian cancer outcome, we performed a genome-wide association study in 2130 Chinese ovarian cancer patients and found a hitherto unrecognized locus at 3p26.1 to be associated with the overall survival (Pcombined = 8.90 × 10-10). Subsequent statistical fine-mapping, functional annotation, and eQTL mapping prioritized a likely casual SNP rs9311399 in the non-coding regulatory region. Mechanistically, rs9311399 altered its enhancer activity through an allele-specific transcription factor binding and a long-range interaction with the promoter of a lncRNA BHLHE40-AS1. Deletion of the rs9311399-associated enhancer resulted in expression changes in several oncogenic signaling pathway genes and a decrease in tumor growth. Thus, we have identified a novel genetic locus that is associated with ovarian cancer survival possibly through a long-range gene regulation of oncogenic pathways.