Miracle-dz/UniFAR-FTUs huggingface dataset:
Photoelectrochemical Properties of InxGa1–xN/GaN Multiquantum Well Structures in Depletion Layers

Photoelectrochemical conversion from light to chemical energy is one of the most promising candidates for renewable energy generation. The most crucial of the many serious problems to be solved for this conversion is the slow carrier transfer at the semiconductor–electrolyte interface. We propose one of solutions using quantum wells, and in the work reported here we evaluated the electrochemical and photoelectrochemical properties of InxGa1–xN/GaN multi quantum well (MQW) structures in the depletion layer. The structures were grown by conventional metal–organic vapor phase epitaxy on (0001) sapphire substrates. Their electrochemical and photoelectrochemical properties differ from those of the bulk materials.
An Efficient and Accurate Iris Recognition Algorithm Based on a Novel Condensed 2-ch Deep Convolutional Neural Network

Recently, deep learning approaches, especially convolutional neural networks (CNNs), have attracted extensive attention in iris recognition. Though CNN-based approaches realize automatic feature extraction and achieve outstanding performance, they usually require more training samples and higher computational complexity than the classic methods. This work focuses on training a novel condensed 2-channel (2-ch) CNN with few training samples for efficient and accurate iris identification and verification. A multi-branch CNN with three well-designed online augmentation schemes and radial attention layers is first proposed as a high-performance basic iris classifier. Then, both branch pruning and channel pruning are achieved by analyzing the weight distribution of the model. Finally, fast finetuning is optionally applied, which can significantly improve the performance of the pruned CNN while alleviating the computational burden. In addition, we further investigate the encoding ability of 2-ch CNN and propose an efficient iris recognition scheme suitable for large database application scenarios. Moreover, the gradient-based analysis results indicate that the proposed algorithm is robust to various image contaminations. We comprehensively evaluated our algorithm on three publicly available iris databases for which the results proved satisfactory for real-time iris recognition.
Association of the Yips and Musculoskeletal Problems in Highly Skilled Golfers: A Large Scale Epidemiological Study in Japan

The yips are a set of conditions associated with intermittent motor disturbances that affect precision movement, especially in sports. Specifically, skilled golfers suffer from the yips, although its clinical characteristics and pathophysiology have not been well-studied. We surveyed skilled golfers to characterize their yips-related symptoms, to explore potential confounding factors associated with the yips. Golfers’ demographic information, golfing-career-related history, musculoskeletal status and manifestations of the yips are surveyed. Among the 1576 questionnaires distributed, 1457 (92%) responses were received, of which 39% of golfers had experienced the yips. The median age and golfing careers were 48 and 28 years, respectively. Golfers who had experienced the yips were older and had longer golfing careers and more frequent musculoskeletal problems than those without experience of the yips. The multivariate logistic regression analysis revealed that a longer golfing career and musculoskeletal problems were independent factors associated with yips experience. More severe musculoskeletal problems were associated with higher odds of experiencing the yips. A positive association between the yips and musculoskeletal problems was also observed. The yips have similar characteristics to task-specific movement disorders, with a detrimental effect caused by excessive repetition of a routine task. These findings support the notion that the yips are a type of task-specific dystonia.
New Nanomaterials with Intrinsic Antioxidant Activity by Surface Functionalization of Niosomes with Natural Phenolic Acids

Nanoantioxidants have emerged as smart devices able to provide improved stability and biocompatibility and sustained and targeted release of conventional antioxidants. In the current research, a new family of nanoantioxidants has been developed by covalently grafting gallic (GA), caffeic (CF) and ferulic (FR) acid on the surfaces of Tween 80 niosomes. First, empty and curcumin (CUR)-loaded vesicles were prepared using a thin-layer evaporation technique and then functionalized with phenolic acids using carbodiimide chemistry. Nanoantioxidants obtained were characterized in terms of size, polydispersity index, zeta potential, and loading efficiency. Their antioxidant activity was studied by ABTS and DPPH assays. Surface functionalization of empty and CUR-loaded vesicles provided stable vesicles with intrinsic antioxidant properties. In vitro antioxidant assays highlighted that vesicles functionalized with FR or GA exhibited better antioxidant activity compared to CF-grafted niosomes. Furthermore, vesicles loaded with CUR and functionalized with GA and CF showed an enhanced scavenging ability of ABTS and DPPH radicals, compared to the single antioxidant-loaded formulations, highlighting an important synergic effect of CUR when used in combination with GA ad CF.
Efficient Visible-Light Photocatalysis of TiO2-δ Nanobelts Utilizing Self-Induced Defects and Carbon Doping

Efficient visible-light photocatalysis was realized by exploring self-induced defect states, including the abundant surface states of TiO2-δ nanobelts synthesized through metal–organic chemical vapor deposition (MOCVD). The TiO2-δ nanobelts exhibited two strong defect-induced absorption peaks at 2.91 and 1.92 eV, overlapping with the conduction band states so that photoexcited carriers can contribute effectively for the photocatalysis reaction. To further enhance visible-light photocatalytic activity, carbon atoms, the by-product of the MOCVD reaction, were self-doped at the judiciously determined growth conditions. The resulting visible-light photocatalysis suggests that the large surface area and consequent high concentration of the surface states of the TiO2-δ nanobelts can be effectively utilized in a wide range of photocatalysis applications.
Sperm DNA fragmentation and male age: results of in vitro fertilization treatments

Objective This study aimed to assess the effects of sperm DNA fragmentation in parents belonging to different age groups. The couples included in the study comprised normozoospermic men and infertile women undergoing conventional IVF. Methods The results obtained from 163 conventional IVF cycles were analyzed retrospectively. The couples enrolled in the study included women aged between 30 and 37 years. Sperm DNA fragmentation was studied using the TUNEL assay. The patients were split into four groups based on male age and sperm DNA fragmentation, as follows: Group 1: ≤39 years and TUNEL assay ≤20%; Group 2: ≤39 years and TUNEL assay >20%; Group 3: ≥40 years and TUNEL assay ≤20%; and Group 4: ≥40 years and TUNEL assay >20%. Results No significant differences were found in semen parameters or fertilization rates between groups. Groups with <20% sperm DNA fragmentation showed significant differences in other parameters, including higher blastocyst formation rate (Group 1: 63% and Group 3: 60% vs. Group 2: 43% and Group 4: 41%, p<0.05) and higher expanded blastocyst formation rate (Group 1: 42% and Group 3: 40% vs. Group 2: 21% and Group 4: 18%, p<0.05). Miscarriage rate was significantly higher in Group 4 (42% and 46% vs. 5%, 25% and 5% in Groups 1, 2 and 3, respectively, p<0.05). Conclusions Our results showed lower blastocyst formation rates from IVF when males had high levels of sperm DNA fragmentation. Higher miscarriage rates were also observed in couples with males aged 40+ years. These results reinforce the need to inform couples with male partners aged 40+ years about the potential risks inherent to fertility treatment.
Assessment of Histological Features in Squamous Cell Carcinoma Involving Head and Neck Skin and Mucosa

Background: squamous cell carcinoma (SCC) is the second most common type of malignancy worldwide. Skin and mucosa of the head and neck areas are the most frequently affected. An aggressive behavior in SCC is not easily detected, and despite all efforts, mortality in these types of cancer did not show major improvements during recent decades. In this study, we aim to determine the role of histological features available through standard pathology assessment in SCC and their relation with tumor behavior and patients’ survival. Method: in a group of one hundred patients diagnosed with SCC involving the head and neck areas, we assessed the presence of four histological features (tumor/stroma ratio, immune infiltration at the front of invasion, tumor-budding activity, and tumor necrosis), their correlations with tumor type (mucosal or cutaneous), tumor clinicopathological characteristics, and their prognostic potential. Results: the comparison between histological features in cutaneous versus mucosal SCC reveals no significant differences for any of the four parameters assessed. We found significant correlations between tumor/stroma ratio and lymphatic metastasis (p = 0.0275), perineural invasion (p = 0.0006), and clinical staging (p = 0.0116). Immune infiltration at the front of invasion revealed similar correlations with lymph node involvement (p = 0.002), perineural invasion (p = 0.0138), and clinical staging (p = 0.0043). Tumor budding and tumor necrosis correlated with the size of the tumor (p = 0.0077 and p = 0.0004) and the clinical staging (p = 0.0039 and p = 0.0143). In addition, tumor budding was significantly correlated with perineural invasion (p = 0.0454). In mucosal SCC, patients with improved outcome revealed high values for the tumor/stroma ratio (p = 0.0159) and immune infiltration at the front of invasion (p = 0.0274). However, the multivariate analysis did not confirm their independent prognostic roles. Conclusions: extended histological assessments that include features such as tumor/stroma ratio, immune infiltration at the front of invasion, tumor budding, and tumor necrosis can be an easy, accessible method to collect additional information on tumor aggressiveness in skin and mucosa SCC affecting the head and neck areas.
kESVR: An Ensemble Model for Drug Response Prediction in Precision Medicine Using Cancer Cell Lines Gene Expression

Background: Cancer cell lines are frequently used in research as in-vitro tumor models. Genomic data and large-scale drug screening have accelerated the right drug selection for cancer patients. Accuracy in drug response prediction is crucial for success. Due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data to predict drug response in precision medicine. Method: A novelty k-means Ensemble Support Vector Regression (kESVR) is developed to predict each drug response values for single patient based on cell-line gene expression data. The kESVR is a blend of supervised and unsupervised learning methods and is entirely data driven. It utilizes embedded clustering (Principal Component Analysis and k-means clustering) and local regression (Support Vector Regression) to predict drug response and obtain the global pattern while overcoming missing data and outliers’ noise. Results: We compared the efficiency and accuracy of kESVR to 4 standard machine learning regression models: (1) simple linear regression, (2) support vector regression (3) random forest (quantile regression forest) and (4) back propagation neural network. Our results, which based on drug response across 610 cancer cells from Cancer Cell Line Encyclopedia (CCLE) and Cancer Therapeutics Response Portal (CTRP v2), proved to have the highest accuracy (smallest mean squared error (MSE) measure). We next compared kESVR with existing 17 drug response prediction models based a varied range of methods such as regression, Bayesian inference, matrix factorization and deep learning. After ranking the 18 models based on their accuracy of prediction, kESVR ranks first (best performing) in majority (74%) of the time. As for the remaining (26%) cases, kESVR still ranked in the top five performing models. Conclusion: In this paper we introduce a novel model (kESVR) for drug response prediction using high dimensional cell-line gene expression data. This model outperforms current existing prediction models in terms of prediction accuracy and speed and overcomes overfitting. This can be used in future to develop a robust drug response prediction system for cancer patients using the cancer cell-lines guidance and multi-omics data.
Sleep Valuation Is Associated with Components of Sleep Health and Daytime Functioning in a College Sample: A Survey Study

Sleep valuation, the worth individuals place on sleep, is an understudied construct in the field of sleep medicine. This study introduced a Sleep Valuation Item Bank and explored how sleep valuation is related to sleep health and daytime functioning within a sample of college students. The participants in this study were 247 (85% white, 83% female) undergraduate students who completed an online survey that included questions from a Sleep Valuation Item Bank and questions about sleep and daytime functioning. Correlation and regression analyses were conducted to determine associations between sleep valuation, aspects of sleep health and daytime functioning. Mediation analyses were conducted to determine whether the sleep health variables explained the associations between sleep valuation and daytime functioning. In correlation analyses, sleep valuation was negatively associated with sleepiness and sleep quality. It was also associated with daytime functioning, including general mental and physical health, depression, and anxiety. In the regression analyses, daytime impairments including poorer physical and mental health, anxiety, and depression were associated with higher sleep valuation. Poorer sleep health, including greater sleepiness and lower sleep quality, explained these associations and were associated with higher sleep valuation. Thus, while daytime impairments, such as anxiety and depression, are related to sleep valuation, this relationship may be due in part to the sleep disturbance that often co-occurs with these impairments.
Sleep Health Promotion Interventions and Their Effectiveness: An Umbrella Review

Sleep is receiving increasing attention in public health. The aim of this umbrella review is to determine what non-pharmacological sleep health interventions have been evaluated among healthy populations, by examining target groups, settings, and effectiveness in improving sleep quality and duration. Comprehensive searches were conducted in five electronic databases (January 1975–February 2019), yielding 6505 records. Thirty-five articles were selected meeting the following eligibility criteria: (1) systematic reviews or meta-analyses of (2) sleep health interventions in (3) primarily healthy populations. Two reviewers independently screened for inclusion, extracted the data, and assessed the review quality. This umbrella review was registered with PROSPERO (CRD42019126291). Eleven intervention types were defined, and their effectiveness discussed. Substantial evidence demonstrated the effectiveness of later school start times, behavior change methods, and mind–body exercise. Other intervention types, including sleep education or relaxation techniques, demonstrated some promising impacts on sleep, but with less consistent evidence. Results were limited by high heterogeneity between studies, mixed results, and variable review quality. Nevertheless, this umbrella review is a first step towards understanding the current state of sleep health promotion and gives an overview of interventions across the lifespan.
Abiotic and Biotic Influences on the Movement of Reintroduced Chinese Giant Salamanders (Andrias davidianus) in Two Montane Rivers

Simple Summary The movement of critically endangered Chinese giant salamander (Andrias davidianus) remains poorly understood due to the rareness of wild individuals. We examined the impacts of individual traits and environmental conditions on daily movement patterns of reintroduced giant salamanders. We found that movement tendency of the older salamander cohort was positively affected by the moon phase, but the moon phase did not impact the younger cohort of animals. For daily distance moved, we found temperature had a strong positive effect on both cohorts, whereas precipitation had moderate but opposite effects on the two cohorts. Body mass and body condition did not have any significant impacts on either age classes’ movement tendency or distance. This study helps to fill in knowledge gaps on the movement ecology of reintroduced Chinese giant salamanders, which will benefit the design of future reintroduction efforts for this critically endangered species. Abstract Understanding animal movement is a key question in ecology and biodiversity conservation, which is particularly important for the success of reintroduction projects. The movement of critically endangered Chinese giant salamander (Andrias davidianus) remains poorly understood due to the rareness of wild individuals of this species. We lack movement details about the full annual cycle after reintroduction, especially the abiotic and biotic influences that affect its movement. We utilized pilot reintroduction projects as opportunities to fill in some knowledge gaps on their movement ecology. We released 31 juvenile captive-reared Chinese giant salamanders of two age groups in two rivers in the Qinling Mountains of central China and monitored their daily movements for 16 months using surgically implanted radio transmitters. We examined the impacts of individual traits (body mass, body condition) and environmental conditions (temperature, precipitation, and moon phase) on their daily movement patterns. Data were analyzed using a mixed-effects logistic regression model to understand the drivers of their movement tendency (i.e., whether they move or not) and a linear mixed-effects model was used to understand the drivers of their movement distance. We found that movement tendency of the older salamander cohort was positively affected by the moon phase, increasing near the Full Moon, whereas the younger cohort of animals were not impacted by the moon phase. For daily distance moved, we found temperature had a strong positive effect on both cohorts, whereas precipitation had moderate but opposite effects on the two cohorts Body mass and body condition did not have any significant impacts on either age classes’ movement tendency or distance. This study provides insight into the abiotic factors that impact the temporal and spatial movement ecology of reintroduced giant salamander, which will in turn help with designing best practices for future releases and conservation of this iconic montane aquatic predator.
Inhibitory Effect of pH-Responsive Nanogel Encapsulating Ginsenoside CK against Lung Cancer

Ginsenoside CK is one of the intestinal bacterial metabolites of ginsenoside prototype saponins, such as ginsenoside Rb1, Rb2, Rc, and Rd. Poor water solubility and low bioavailability have limited its application. The nanogel carriers could specifically deliver hydrophobic drugs to cancer cells. Therefore, in this study, a nanogel was constructed by the formation of Schiff base bonds between hydrazide-modified carboxymethyl cellulose (CMC-NH2) and aldehyde-modified β-cyclodextrin (β-CD-CHO). A water-in-oil reverse microemulsion method was utilized to encapsulate ginsenoside CK via the hydrophobic cavity of β-CD. β-CD-CHO with a unique hydrophobic cavity carried out efficient encapsulation of CK, and the drug loading and encapsulation efficiency were 16.4% and 70.9%, respectively. The drug release of CK-loaded nanogels (CK-Ngs) in vitro was investigated in different pH environments, and the results showed that the cumulative release rate at pH 5.8 was 85.5% after 140 h. The methylthiazolyldiphenyl-tetrazolium bromide (MTT) toxicity analysis indicated that the survival rates of A549 cells in CK-Ngs at 96 h was 2.98% compared to that of CK (11.34%). In vivo animal experiments exhibited that the inhibitory rates of CK-Ngs against tumor volume was 73.8%, which was higher than that of CK (66.1%). Collectively, the pH-responsive nanogel prepared herein could be considered as a potential nanocarrier for CK to improve its antitumor effects against lung cancer.
Remote Monitoring of Heart Failure in Patients with Implantable Cardioverter-Defibrillators: Current Status and Future Needs

The management of heart failure remains challenging despite evidence-based medical and pharmacological advances, especially in the ambulatory setting. There is an urgent need to develop strategies to reduce hospitalizations and readmission rates due to heart failure. Frequent monitoring of high-risk patients is imperative, and with the development of wireless and remote technology, frequent monitoring is now possible via remote monitoring. Nowadays, remote management of patients with cardiac implantable electronic devices is being increasingly adopted and integrated into clinical practice. Several clinical trials studied the impact of remote monitoring on clinical outcomes in patients with implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization defibrillators (CRT-Ds). This point of view will focus on the remote monitoring of ICDs and CRT-Ds in patients with heart failure and discusses whether remote monitoring can be used as a potential instrument for the early identification of patients at risk of worsening heart failure.
Analysis of Non-Stationarity for 5.9 GHz Channel in Multiple Vehicle-to-Vehicle Scenarios

The vehicle-to-vehicle (V2V) radio channel is non-stationary due to the rapid movement of vehicles. However, the stationarity of the V2V channels is an important indicator of the V2V channel characteristics. Therefore, we analyzed the non-stationarity of V2V radio channels using the local region of stationarity (LRS). We selected seven scenarios, including three directions of travel, i.e., in the same, vertical, and opposite directions, and different speeds and environments in a similar driving direction. The power delay profile (PDP) and LRS were estimated from the measured channel impulse responses. The results show that the most important influences on the stationary times are the direction and the speed of the vehicles. The average stationary times for driving in the same direction range from 0.3207 to 1.9419 s, the average stationary times for driving in the vertical direction are 0.0359–0.1348 s, and those for driving in the opposite direction are 0.0041–0.0103 s. These results are meaningful for the analysis of the statistical characteristics of the V2V channel, such as the delay spread and Doppler spread. Small-scale fading based on the stationary times affects the quality of signals transmitted in the V2V channel, including the information transmission rate and the information error code rate.