Effects of Phase-Locking Deficits on Speech Recognition in Older Adults With Presbycusis

Objective: People with presbycusis (PC) often report difficulties in speech recognition, especially under noisy listening conditions. Investigating the PC-related changes in central representations of envelope signals and temporal fine structure (TFS) signals of speech sounds is critical for understanding the mechanism underlying the PC-related deficit in speech recognition. Frequency-following responses (FFRs) to speech stimulation can be used to examine the subcortical encoding of both envelope and TFS speech signals. This study compared FFRs to speech signals between listeners with PC and those with clinically normal hearing (NH) under either quiet or noise-masking conditions.Methods: FFRs to a 170-ms speech syllable /da/ were recorded under either a quiet or noise-masking (with a signal-to-noise ratio (SNR) of 8 dB) condition in 14 older adults with PC and 13 age-matched adults with NH. The envelope (FFRENV) and TFS (FFRTFS) components of FFRs were analyzed separately by adding and subtracting the alternative polarity responses, respectively. Speech recognition in noise was evaluated in each participant.Results: In the quiet condition, compared with the NH group, the PC group exhibited smaller F0 and H3 amplitudes and decreased stimulus-response (S-R) correlation for FFRENV but not for FFRTFS. Both the H2 and H3 amplitudes and the S-R correlation of FFRENV significantly decreased in the noise condition compared with the quiet condition in the NH group but not in the PC group. Moreover, the degree of hearing loss was correlated with noise-induced changes in FFRTFS morphology. Furthermore, the speech-in-noise (SIN) threshold was negatively correlated with the noise-induced change in H2 (for FFRENV) and the S-R correlation for FFRENV in the quiet condition.Conclusion: Audibility affects the subcortical encoding of both envelope and TFS in PC patients. The impaired ability to adjust the balance between the envelope and TFS in the noise condition may be part of the mechanism underlying PC-related deficits in speech recognition in noise. FFRs can predict SIN perception performance

A Systematic Review of the Coopetition Relationship between Bike-Sharing and Public Transit

The sharing economy, mobile Internet, and smartphones have been widely utilized in recent years to promote the development of bike-sharing services. Bike-sharing serves as a first/last mile travel mode to connect to public transit, which improves trip efficiency, alleviates traffic problems, improves environmental quality, and promotes public health. However, the substitution of public transit by bike-sharing and the decline in public transit ridership have raised concerns among city managers regarding the coopetition between shared mobility services and public transit. To understand the impact of bike-sharing on the decline in public transit and to formulate reasonable synergistic development policies, it is crucial to identify the coopetition relationships between the two. This paper uses a combination of database search and backward snowballing to review existing research. Three research themes were identified: macrolevel studies on bike-sharing and public transit interaction, studies on actual coopetition behaviors based on bike-sharing user surveys, and studies on potential coopetition relationships based on bike-sharing transaction data. The three categories of studies reveal the effect of bike-sharing usage on public transit ridership, the emergency function of bike-sharing in the event of unexpected transit shutdowns, and the substitution and connection relationships between bike-sharing and public transit and the factors influencing them. Finally, this study suggests many directions for future research. This review helps clarify the understanding of the coopetition relationships between bike-sharing and public transit, provides theoretical support to promote the synergistic development of both, and points out ways to deepen the research on the coopetition relationship between the two

Rhamnolipid-Enhanced ZVI-Activated Sodium Persulfate Remediation of Pyrene-Contaminated Soil

In soil, polycyclic aromatic hydrocarbons (PAHs) are tightly bound to organic components, but surfactants can effectively transform them from a solid to a liquid phase. In this study, the biosurfactant rhamnolipid (RL) was selected as the eluent; shaking elution in a thermostatic oscillator improved the elution rate of pyrene, and the effects of RL concentration, temperature, and elution time on the elution effect were compared. After four repeated washings, the maximum elution rate was 75.6% at a rhamnolipid concentration of 20 g/L and a temperature of 45 °C. We found that 38 μm Zero-Valent Iron (ZVI) had a higher primary reaction rate (0.042 h−1), with a degradation rate of 94.5% when 3 g/L ZVI was added to 21 mM Na2S2O8 at 60 °C. Finally, electron paramagnetic resonance (EPR) detected DMPO-OH and DMPO-SO4 signals, which played a major role in the degradation of pyrene. Overall, these results show that the combination of rhamnolipid elution and persulfate oxidation system effectively remediated pyrene-contaminated soil and provides some implications for the combined remediation with biosurfactants and chemical oxidation

Pulmonary nodule detection on lung parenchyma images using hyber-deep algorithm

The incidence of lung cancer has seen a significant increase in recent times, leading to a rise in fatalities. The detection of pulmonary nodules from CT images has emerged as an effective method to aid in the diagnosis of lung cancer. Ensuring information security holds utmost significance in the detection of nodules, with particular attention given to safeguarding patient privacy within the context of the Internet of Things (IoT). In this regard, migration learning emerges as a potent technique for preserving the confidentiality of patient data. Firstly, we applied several data-preprocessing steps such as lung segmentation based on K-Means, denoising methods, and lung parenchyma extraction through a dedicated medical IoT network. We used the Microsoft Common Object in Context (MS-COCO) dataset to pre-train the detection framework and fine-tuned it with the Lung Nodule Analysis 16 (LUNA16) dataset to adapt to nodule detection tasks. To evaluate the effectiveness of our proposed pipeline, we conducted extensive experiments that included subjective evaluation of detection results and quantitative data analysis. The results of these experiments demonstrated the efficacy of our approach in accurately detecting pulmonary nodules. Our study provides a promising framework for trustworthy pulmonary nodule detection on lung parenchyma images using a secured hyper-deep algorithm, which has the potential to improve lung cancer diagnosis and reduce fatalities associated with it

Distinct Microbial Community of Phyllosphere Associated with Five Tropical Plants on Yongxing Island, South China Sea

The surfaces of a leaf are unique and wide habitats for a microbial community. These microorganisms play a key role in plant growth and adaptation to adverse conditions, such as producing growth factors to promote plant growth and inhibiting pathogens to protect host plants. The composition of microbial communities very greatly amongst different plant species, yet there is little data on the composition of the microbiome of the host plants on the coral island in the South China Sea. In this study, we investigated the abundances and members of a major microbial community (fungi, bacteria, and diazotrophs) on the leaves of five dominant plant species (Ipomoea pes-caprae, Wedelia chinensis, Scaevola sericea, Cocos nucifera, and Sesuvium portulacastrum) on the island using real-time quantitative polymerase chain reaction (PCR) and high-throughput amplicon sequencing. Quantitative PCR results showed that fungi and bacteria were ubiquitous and variable among different host plants. Scaevola sericea showed the lowest absolute abundance and highest diversity of fungi and bacteria, while Cocos nucifera had the lowest abundance and the highest diversity of diazotrophs compare to the other four plants. There was a small proportion of shared microorganisms among the five different plants, while unique fungi, bacteria and diazotrophs were significantly enriched for different host plant species in this study (p < 0.05). Some of the most abundant organisms found in the communities of these different host plants are involved in important biogeochemical cycles that can benefit their host, including carbon and nitrogen cycles

Respiratory motion prediction and prospective correction for free‐breathing arterial spin‐labeled perfusion MRI of the kidneys

PurposeRespiratory motion prediction using an artificial neural network (ANN) was integrated with pseudocontinuous arterial spin labeling (pCASL) MRI to allow free-breathing perfusion measurements in the kidney. In this study, we evaluated the performance of the ANN to accurately predict the location of the kidneys during image acquisition.MethodsA pencil-beam navigator was integrated with a pCASL sequence to measure lung/diaphragm motion during ANN training and the pCASL transit delay. The ANN algorithm ran concurrently in the background to predict organ location during the 0.7-s 15-slice acquisition based on the navigator data. The predictions were supplied to the pulse sequence to prospectively adjust the axial slice acquisition to match the predicted organ location. Additional navigators were acquired immediately after the multislice acquisition to assess the performance and accuracy of the ANN. The technique was tested in eight healthy volunteers.ResultsThe root-mean-square error (RMSE) and mean absolute error (MAE) for the eight volunteers were 1.91 ± 0.17 mm and 1.43 ± 0.17 mm, respectively, for the ANN. The RMSE increased with transit delay. The MAE typically increased from the first to last prediction in the image acquisition. The overshoot was 23.58% ± 3.05% using the target prediction accuracy of ± 1 mm.ConclusionRespiratory motion prediction with prospective motion correction was successfully demonstrated for free-breathing perfusion MRI of the kidney. The method serves as an alternative to multiple breathholds and requires minimal effort from the patient

Horizontal gene transfer of Fhb7 from fungus underlies Fusarium head blight resistance in wheat

Fusarium head blight (FHB), a fungal disease caused by Fusarium species that produce food toxins, currently devastates wheat production worldwide, yet few resistance resources have been discovered in wheat germplasm. Here, we cloned the FHB resistance gene Fhb7 by assembling the genome of Thinopyrum elongatum, a species used in wheat distant hybridization breeding. Fhb7 encodes a glutathione S-transferase (GST) and confers broad resistance to Fusarium species by detoxifying trichothecenes through de-epoxidation. Fhb7 GST homologs are absent in plants, and our evidence supports that Th. elongatum has gained Fhb7 through horizontal gene transfer (HGT) from an endophytic Epichloë species. Fhb7 introgressions in wheat confers resistance to both FHB and crown rot in diverse wheat backgrounds without yield penalty, providing a solution for Fusarium resistance breeding

Elimination of the yellow pigment gene PSY-E2 tightly linked to the Fusarium head blight resistance gene Fhb7 from Thinopyrum ponticum

Fhb7 is a major gene that was transferred from Thinopyrum ponticum to chromosome 7D of wheat (Triticum aestivum) and confers resistance to both Fusarium head blight (FHB) and Fusarium crown rot (FCR). However, Fhb7 is tightly linked to the PSY-E2 gene, which causes yellow flour, limiting its application in breeding. To break this linkage, marker K-PSY was developed for tagging PSY-E2 and used with Fhb7 markers to identify recombination between the two genes. Screening 21,000 BC1F2 backcross progeny (Chinese Spring ph1bph1b*2/SDAU 2028) revealed two Fhb7+ wheat-Tp7el2L lines, Shannong 2–16 and Shannong 16–1, that carry a desired truncated Fhb7+ translocation segment without PSY-E2. The two lines show levels of resistance to FHB and FCR similar to those of the original translocation line SDAU 2028, but have white flour. To facilitate Fhb7 use in wheat breeding, STS markers were developed and used to isolate Fhb7 on a truncated Tp7el2 translocation segment. Near-isogenic lines carrying the Fhb7+ segment were generated in the backgrounds of three commercial cultivars, and Fhb7+ lines showed increased FHB and FCR resistance without yield penalty. The breakage of the tight linkage between Fhb7 and PSY-E2 via homoeologous recombination provides genetic resources for improvement of wheat resistance to FHB and FCR and permit the large-scale deployment of Fhb7 in breeding using marker-assisted selection

Horizontal gene transfer of Fhb7 from fungus underlies Fusarium head blight resistance in wheat

Fusarium head blight (FHB) is a fungal disease that devastates global wheat production, with losses of billions of dollars annually. Unlike foliar diseases, FHB occurs directly on wheat spikes (inflorescences). The infection lowers grain yield and also causes the grain to be contaminated by mycotoxins produced by the Fusarium pathogen, thus imposing health threats to humans and livestock. Although plant breeders have improved wheat resistance to FHB, the lack of wheat strains with stable FHB resistance has limited progress