Passionfruit Genomic Database (PGD): a comprehensive resource for passionfruit genomics.

Passionfruit (Passiflora edulis) is a significant fruit crop in the commercial sector, owing to its high nutritional and medicinal value. The advent of high-throughput genomics sequencing technology has led to the publication of a vast amount of passionfruit omics data, encompassing complete genome sequences and transcriptome data under diverse stress conditions. To facilitate the efficient integration, storage, and analysis of these large-scale datasets, and to enable researchers to effectively utilize these omics data, we developed the first passionfruit genome database (PGD). The PGD platform comprises a diverse range of functional modules, including a genome browser, search function, heatmap, gene expression patterns, various tools, sequence alignment, and batch download, thereby providing a user-friendly interface. Additionally, supplementary practical tools have been developed for the PGD, such as gene family analysis tools, gene ontology (GO) terms, a pathway enrichment analysis, and other data analysis and mining tools, which enhance the data's utilization value. By leveraging the database's robust scalability, the intention is to continue to collect and integrate passionfruit omics data in the PGD, providing comprehensive and in-depth support for passionfruit research. The PGD is freely accessible via http://passionfruit.com.cn .

A Real-Time Vehicle Detection System under Various Bad Weather Conditions Based on a Deep Learning Model without Retraining.

Numerous vehicle detection methods have been proposed to obtain trustworthy traffic data for the development of intelligent traffic systems. Most of these methods perform sufficiently well under common scenarios, such as sunny or cloudy days; however, the detection accuracy drastically decreases under various bad weather conditions, such as rainy days or days with glare, which normally happens during sunset. This study proposes a vehicle detection system with a visibility complementation module that improves detection accuracy under various bad weather conditions. Furthermore, the proposed system can be implemented without retraining the deep learning models for object detection under different weather conditions. The complementation of the visibility was obtained through the use of a dark channel prior and a convolutional encoder-decoder deep learning network with dual residual blocks to resolve different effects from different bad weather conditions. We validated our system on multiple surveillance videos by detecting vehicles with the You Only Look Once (YOLOv3) deep learning model and demonstrated that the computational time of our system could reach 30 fps on average; moreover, the accuracy increased not only by nearly 5% under low-contrast scene conditions but also 50% under rainy scene conditions. The results of our demonstrations indicate that our approach is able to detect vehicles under various bad weather conditions without the need to retrain a new model.

Gaze Tracking and Point Estimation Using Low-Cost Head-Mounted Devices.

In this study, a head-mounted device was developed to track the gaze of the eyes and estimate the gaze point on the user's visual plane. To provide a cost-effective vision tracking solution, this head-mounted device is combined with a sized endoscope camera, infrared light, and mobile phone; the devices are also implemented via 3D printing to reduce costs. Based on the proposed image pre-processing techniques, the system can efficiently extract and estimate the pupil ellipse from the camera module. A 3D eye model was also developed to effectively locate eye gaze points from extracted eye images. In the experimental results, average accuracy, precision, and recall rates of the proposed system can achieve an average of over 97%, which can demonstrate the efficiency of the proposed system. This study can be widely used in the Internet of Things, virtual reality, assistive devices, and human-computer interaction applications.

Study of Postural Stability Features by Using Kinect Depth Sensors to Assess Body Joint Coordination Patterns.

A stable posture requires the coordination of multiple joints of the body. This coordination of the multiple joints of the human body to maintain a stable posture is a subject of research. The number of degrees of freedom (DOFs) of the human motor system is considerably larger than the DOFs required for posture balance. The manner of managing this redundancy by the central nervous system remains unclear. To understand this phenomenon, in this study, three local inter-joint coordination pattern (IJCP) features were introduced to characterize the strength, changing velocity, and complexity of the inter-joint couplings by computing the correlation coefficients between joint velocity signal pairs. In addition, for quantifying the complexity of IJCPs from a global perspective, another set of IJCP features was introduced by performing principal component analysis on all joint velocity signals. A Microsoft Kinect depth sensor was used to acquire the motion of 15 joints of the body. The efficacy of the proposed features was tested using the captured motions of two age groups (18-24 and 65-73 years) when standing still. With regard to the redundant DOFs of the joints of the body, the experimental results suggested that an inter-joint coordination strategy intermediate to that of the two extreme coordination modes of total joint dependence and independence is used by the body. In addition, comparative statistical results of the proposed features proved that aging increases the coupling strength, decreases the changing velocity, and reduces the complexity of the IJCPs. These results also suggested that with aging, the balance strategy tends to be more joint dependent. Because of the simplicity of the proposed features and the affordability of the easy-to-use Kinect depth sensor, such an assembly can be used to collect large amounts of data to explore the potential of the proposed features in assessing the performance of the human balance control system.

Learning-Directed Dynamic Voltage and Frequency Scaling Scheme with Adjustable Performance for Single-Core and Multi-Core Embedded and Mobile Systems.

Dynamic voltage and frequency scaling (DVFS) is a well-known method for saving energy consumption. Several DVFS studies have applied learning-based methods to implement the DVFS prediction model instead of complicated mathematical models. This paper proposes a lightweight learning-directed DVFS method that involves using counter propagation networks to sense and classify the task behavior and predict the best voltage/frequency setting for the system. An intelligent adjustment mechanism for performance is also provided to users under various performance requirements. The comparative experimental results of the proposed algorithms and other competitive techniques are evaluated on the NVIDIA JETSON Tegra K1 multicore platform and Intel PXA270 embedded platforms. The results demonstrate that the learning-directed DVFS method can accurately predict the suitable central processing unit (CPU) frequency, given the runtime statistical information of a running program, and achieve an energy savings rate up to 42%. Through this method, users can easily achieve effective energy consumption and performance by specifying the factors of performance loss.

Characterisation of siRNAs derived from new isolates of bamboo mosaic virus and their associated satellites in infected ma bamboo (Dendrocalamus latiflorus).

We characterised the virus-derived small interfering RNAs (vsiRNA) of bamboo mosaic virus (Ba-vsiRNAs) and its associated satellite RNA (satRNA)-derived siRNAs (satsiRNAs) in a bamboo plant (Dendrocalamus latiflorus) by deep sequencing. Ba-vsiRNAs and satsiRNAs of 21-22 nt in length, with both (+) and (-) polarity, predominated. The 5'-terminal base of Ba-vsiRNA was biased towards A, whereas a bias towards C/U was observed in sense satsiRNAs, and towards A in antisense satsiRNAs. A large set of bamboo genes were identified as potential targets of Ba-vsiRNAs and satsiRNAs, revealing RNA silencing-based virus-host interactions in plants. Moreover, we isolated and characterised new isolates of bamboo mosaic virus (BaMV; 6,350 nt) and BaMV-associated satRNA (satBaMV; 834 nt), designated BaMV-MAZSL1 and satBaMV-MAZSL1, respectively.

Ionic Liquids Impact the Bioenergy Feedstock-Degrading Microbiome and Transcription of Enzymes Relevant to Polysaccharide Hydrolysis.

Ionic liquid (IL) pretreatment is a promising approach for the conversion of lignocellulose to biofuels. The toxicity of residual IL, however, negatively impacts the performance of industrial enzymes and microorganisms in hydrolysis and fermentation. In this study, a thermophilic microbial community was cultured on switchgrass amended with various levels of the ionic liquid 1-ethyl-3-methylimidazolium acetate. Changes in the microbial community composition and transcription of genes relevant to IL tolerance and lignocellulose hydrolysis were quantified. Increasing the level of IL to 0.1% (wt) led to increased levels of relative abundance and transcription in organisms of the phylum Firmicutes. Interestingly, IL concentrations of up to 1% (wt) also resulted in greater xylanase transcription and enzyme activity as well as increased transcription of endoglucanase, beta-glucosidase, and IL tolerance genes compared to communities without IL. IL levels above 1% (wt) resulted in decreased enzyme activity and transcription of genes involved in lignocellulose hydrolysis. The results indicate that moderate levels of IL select for thermophilic microorganisms that not only tolerate IL but also effectively hydrolyze lignocellulose from switchgrass. Discovery of IL-tolerant organisms and enzymes is critical for the development of biological processes that convert IL-pretreated biomass to biofuels and chemicals. Employing metatranscriptomic analysis of enrichment cultures can facilitate the discovery of microorganisms and enzymes that may be active in the presence of toxic compounds such as ionic liquids. IMPORTANCE Pretreatment using ionic liquids (IL) is a promising approach for the conversion of lignocellulose to biofuels. Because IL can be inhibitory to enzymes and microorganisms involved in downstream hydrolysis and fermentation steps, discovery of IL-tolerant organisms and enzymes is critical for advancing this technology. Employing metatranscriptomics in the analysis of IL-enriched cultures facilitated tracking of dynamic changes in a complex microbial community at the level of gene transcription and doing so with genome resolution. Specific organisms were discovered that could simultaneously tolerate a moderate IL concentration and transcribe a diverse array of cellulolytic enzymes. Gene sequences of cellulolytic enzymes and efflux pumps from those same organisms were also identified, providing important resources for future research on engineering IL-tolerant organisms and enzymes.

DNA methylome of the 20-gigabase Norway spruce genome.

DNA methylation plays important roles in many biological processes, such as silencing of transposable elements, imprinting, and regulating gene expression. Many studies of DNA methylation have shown its essential roles in angiosperms (flowering plants). However, few studies have examined the roles and patterns of DNA methylation in gymnosperms. Here, we present genome-wide high coverage single-base resolution methylation maps of Norway spruce (Picea abies) from both needles and somatic embryogenesis culture cells via whole genome bisulfite sequencing. On average, DNA methylation levels of CG and CHG of Norway spruce were higher than most other plants studied. CHH methylation was found at a relatively low level; however, at least one copy of most of the RNA-directed DNA methylation pathway genes was found in Norway spruce, and CHH methylation was correlated with levels of siRNAs. In comparison with needles, somatic embryogenesis culture cells that are used for clonally propagating spruce trees showed lower levels of CG and CHG methylation but higher level of CHH methylation, suggesting that like in other species, these culture cells show abnormal methylation patterns.

Ionic liquid-tolerant microorganisms and microbial communities for lignocellulose conversion to bioproducts.

Chemical and physical pretreatment of biomass is a critical step in the conversion of lignocellulose to biofuels and bioproducts. Ionic liquid (IL) pretreatment has attracted significant attention due to the unique ability of certain ILs to solubilize some or all components of the plant cell wall. However, these ILs inhibit not only the enzyme activities but also the growth and productivity of microorganisms used in downstream hydrolysis and fermentation processes. While pretreated biomass can be washed to remove residual IL and reduce inhibition, extensive washing is costly and not feasible in large-scale processes. IL-tolerant microorganisms and microbial communities have been discovered from environmental samples and studies begun to elucidate mechanisms of IL tolerance. The discovery of IL tolerance in environmental microbial communities and individual microbes has lead to the proposal of molecular mechanisms of resistance. In this article, we review recent progress on discovering IL-tolerant microorganisms, identifying metabolic pathways and mechanisms of tolerance, and engineering microorganisms for IL tolerance. Research in these areas will yield new approaches to overcome inhibition in lignocellulosic biomass bioconversion processes and increase opportunities for the use of ILs in biomass pretreatment.

Molecular characterization and detection of a recombinant isolate of bamboo mosaic virus from China.

The complete genome sequences of three isolates of bamboo mosaic virus (BaMV) from mainland China were determined and compared to those of BaMV isolates from Taiwan. Sequence analysis showed that isolate BaMV-JXYBZ1 from Fuzhou shares 98 % nucleotide sequence identity with BaMV-YTHSL14 from nucleotides 2586 to 6306, and more than 94 % nucleotide sequence identity with BaMV-MUZHUBZ2 in other regions. Recombination and phylogenetic analyses indicate that BaMV-JXYBZ1 is a recombinant with one recombination breakpoint. To our knowledge, this is the first report of a BaMV recombinant worldwide.

The complete chloroplast genome sequence of Anoectochilus roxburghii.

The complete chloroplast sequence of the Anoectochilus roxburghii, a popular traditional Chinese medicine for the treatment of cancer, was determined in this study. The chloroplast genome (cpDNA)^ was 152,802 bp in length, containing a pair of inverted repeats of 52,728 bp separated by a large single-copy region and a small single-copy region of 82,641 bp and 17,433 bp, respectively. The chloroplast genome encodes 116 predicted functional genes, including 81 protein-coding genes, four ribosomal RNA genes, and 31 transfer RNA genes, 25 of which are duplicated in the inverted repeat regions. The cpDNA is GC-rich (36.9%).

Preservation of microbial communities enriched on lignocellulose under thermophilic and high-solid conditions.

BACKGROUND: Microbial communities enriched from diverse environments have shown considerable promise for the targeted discovery of microorganisms and enzymes for bioconversion of lignocellulose to liquid fuels. While preservation of microbial communities is important for commercialization and research, few studies have examined storage conditions ideal for preservation. The goal of this study was to evaluate the impact of preservation method on composition of microbial communities enriched on switchgrass before and after storage. The enrichments were completed in a high-solid and aerobic environment at 55 °C. Community composition was examined for each enrichment to determine when a stable community was achieved. Preservation methods included cryopreservation with the cryoprotective agents DMSO and glycerol, and cryopreservation without cryoprotective agents. Revived communities were examined for their ability to decompose switchgrass under high-solid and thermophilic conditions. RESULTS: High-throughput 16S rRNA gene sequencing of DNA extracted from enrichment samples showed that the majority of the shift in composition of the switchgrass-degrading community occurred during the initial three 2-week enrichments. Shifts in community structure upon storage occurred in all cryopreserved samples. Storage in liquid nitrogen in the absence of cryoprotectant resulted in variable preservation of dominant microorganisms in enriched samples. Cryopreservation with either DMSO or glycerol provided consistent and equivalent preservation of dominant organisms. CONCLUSIONS: A stable switchgrass-degrading microbial community was achieved after three 2-week enrichments. Dominant microorganisms were preserved equally well with DMSO and glycerol. DMSO-preserved communities required more incubation time upon revival to achieve pre-storage activity levels during high-solid thermophilic cultivation on switchgrass. Despite shifts in the community with storage, the samples were active upon revival under thermophilic and high-solid conditions. The results suggest that the presence of microorganisms may be more important than their relative abundance in retaining an active microbial community.

An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

Ensilage and bioconversion of grape pomace into fuel ethanol.

Two types of grape pomace were ensiled with eight strains of lactic acid bacteria (LAB). Both fresh grape pomace (FrGP) and fermented grape pomace (FeGP) were preserved through alcoholic fermentation but not malolactic conversion. Water leaching prior to storage was used to reduce water-soluble carbohydrates and ethanol from FrGP and FeGP, respectively, to increase malolactic conversion. Leached FeGP had spoilage after 28 days of ensilage, whereas FrGP was preserved. Dilute acid pretreatment was examined for increasing the conversion of pomace to ethanol via Escherichia coli KO11 fermentation. Dilute acid pretreatment doubled the ethanol yield from FeGP, but it did not improve the ethanol yield from FrGP. The ethanol yields from raw pomace were nearly double the yields from the ensiled pomace. For this reason, the recovery of ethanol produced during winemaking from FeGP and ethanol produced during storage of FrGP is critical for the economical conversion of grape pomace to biofuel.

Improving the efficiency of enzyme utilization for sugar beet pulp hydrolysis.

Sugar beet pulp (SBP) is a carbohydrate-rich residue of table sugar processing. It shows promise as a feedstock for fermentable sugar and biofuel production via enzymatic hydrolysis and microbial fermentation. This research focused on the enzymatic hydrolysis of SBP and examined the effects of solid loading (2-10 %, dry basis), enzyme preparation, and enzyme recycle on the production of fermentable sugars. The enzyme partitioning to the solid and liquid phases during SBP enzymatic hydrolysis and loss during recycling were investigated using SDS-PAGE and Zymogram analysis. Without considering product inhibition, the cellulase added initially to the SBP hydrolysis lost only 6 % filter paper activity and negligible carboxymethyl cellulose activity upon multiple cycles of SBP hydrolysis. It was found that enzyme dosage can be reduced by 50 % while maintaining similar, and in some cases higher fermentable sugar yield. The removal of hydrolysis products will further improve enzymatic hydrolysis of SBP for biofuel production.

Influence of moisture content on microbial activity and silage quality during ensilage of food processing residues.

Seasonally produced biomass such as sugar beet pulp (SBP) and tomato pomace (TP) needs to be stored properly to meet the demand of sustainable biofuel production industries. Ensilage was used to preserve the feedstock. The effect of moisture content (MC) on the performance of ensilage and the relationship between microorganism activities and MC were investigated. For SBP, MC levels investigated were 80, 55, 30, and 10% on a wet basis. For TP, MC levels investigated were 60, 45, 30, and 10%. Organic acids, ethanol, ammonia, pH and water soluble carbohydrates (WSC) were measured to evaluate the silage quality. Ensilage improved as the MC decreased from 80 to 55% for SBP and from 60 to 45% for TP. When the MC decreased to 30%, a little microbial activity was detected for both feedstocks. Storage at 10% MC prevented all the microbial activity. The naturally occurring microorganisms in TP were found to preserve TP during silage and were isolated and determined by polymerase chain reaction (PCR). The results suggest that partial drying followed by ensilage may be a good approach for stabilization of food processing residues for biofuels production.

Effects of ensilage on storage and enzymatic degradability of sugar beet pulp.

Ensiling was investigated for the long-term storage of Sugar Beet Pulp (SBP). Eight strains of lactic acid bacteria (LAB) and a non-inoculated control were screened based on their ability to rapidly reduce pH, produce a large amount of lactic acid and inhibit undesirable fermentations. Lactobacillus brevis B-1836 (LAB #120), Lactobacillus fermentum NRRL B-4524 (LAB #137) and a non-inoculated control were selected for further research to determine the effects of LAB inoculation level and packing density on SBP silage quality and sugar yield upon enzymatic hydrolysis. Both SBP preservation and prevention of cellulose and hemicellulose loss were better when SBP was treated with LAB #137 compared to LAB #120 and the non-inoculated control. Additionally, the ensiling process was found to significantly improve the enzymatic digestibility of SBP by as much as 35%. The results suggest that ensiling may be a promising technology for SBP stabilization and pretreatment for bioconversion to products.

Solid-liquid extraction of alkali metals and organic compounds by leaching of food industry residues.

Leaching was studied for its application in extracting inorganic and organic constituents from fresh fermented grape pomace, air-dried fermented grape pomace and air-dried sugar beet pulp. Samples of each feedstock were leached in water at ambient temperature for 30 or 120 min at dry solid-to-liquid ratios of 1/20 and 1/50 kg/L. Leaching removed 82% of sodium, 86% of potassium, and 76% of chlorine from sugar beet pulp, and reduced total ash concentration in air-dry fermented grape pomace from 8.2% to 2.9% of dry matter, 8.2% to 4.4% in fresh fermented grape pomace, and 12.5% to 5.4% in sugar beet pulp. Glycerol (7-11 mg/dry g), ethanol (131-158 mg/dry g), and acetic acid (24-31 mg/dry g) were also extracted from fermented grape pomace. These results indicate that leaching is a beneficial pretreatment step for improving the quality of food processing residues for thermochemical and biochemical conversion.