Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Characterization of Fungal Colonization on the Provox™ Tracheoesophageal Voice Prosthesis in Post Laryngectomy Patients

Background: Tracheoesophageal voice prostheses (TVPs) have been the gold standard in rehabilitation, after laryngectomy, producing faster and premier voicing towards esophageal speech. Fungal colonization shortens the device’s lifetime and leads to prosthesis dysfunction, leakage, and subsequent respiratory infection. Therefore, in the current study, we aimed to investigate the fungal colonization patterns and to propose prophylactic measures that shall increase the longevity of voice prosthesis. Methods: Failed TVPs were removed - due to leakage and/or aspiration - from 66 post laryngectomy patients and examined. They were referred to Amiralam and Rasoul Hospital, the main centers of Ear, Nose, and Throat in Tehran, Iran from April 2018 to January 2020. Fungal colonization patterns were assessed using DNA sequencing techniques. Furthermore, the susceptibility to fluconazole, amphotericin B, nystatin, and white vinegar was evaluated according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. Results: Resident fungal species from the upper airways colonized all the 66 TVPs (100%). Diabetes (31%) and smoking (98%) were the predominant underlying disease and predisposing factors, respectively. Among the 79 fungal agents isolated from the 66 TVPs, Candida glabrata (n=25, 31.7%) was the most common. A significant reduction in minimum inhibitory concentration (MIC) values were observed for white vinegar when used alone (P<0.05). Conclusion: White vinegar at a very low concentration could decrease the amount of fungal colonization on TVPs without any adverse effects; its wide accessibility and affordability ensure a decrease in the overall health cost.
Economic decisions on the livestock production of highlanders to control zoonoses risk using Bayesian network analysis

Pig rearing continues to be an important source of food and serves for ritual use among highlanders in Northern Thailand. The review of Trichinellosis outbreak reports from the past ten years (2003-2012) suggests that more than 90 percent of the outbreaks have occurred in the highlands with several major foci scattered throughout the borderland provinces. To help us understand the transmission of the disease, the research applied an EcoHealth-One Health approach to develop a trandisciplinary framework considering the interaction of highlanders with the pigs they grow and their environment as a single system. The research identified four subsystems to investigate Trichinellosis risk, including, animal husbandry, food chain, environment,
Variational-Scale Segmentation for Multispectral Remote-Sensing Images Using Spectral Indices

Many studies have focused on performing variational-scale segmentation to represent various geographical objects in high-resolution remote-sensing images. However, it remains a significant challenge to select the most appropriate scales based on the geographical-distribution characteristics of ground objects. In this study, we propose a variational-scale multispectral remote-sensing image segmentation method using spectral indices. Real scenes in remote-sensing images contain different types of land cover with different scales. Therefore, it is difficult to segment images optimally based on the scales of different ground objects. To guarantee image segmentation of ground objects with their own scale information, spectral indices that can be used to enhance some types of land cover, such as green cover and water bodies, were introduced into marker generation for the watershed transformation. First, a vector field model was used to determine the gradient of a multispectral remote-sensing image, and a marker was generated from the gradient. Second, appropriate spectral indices were selected, and the kernel density estimation was used to generate spectral-index marker images based on the analysis of spectral indices. Third, a series of mathematical morphology operations were used to obtain a combined marker image from the gradient and the spectral index markers. Finally, the watershed transformation was used for image segmentation. In a segmentation experiment, an optimal threshold for the spectral-index-marker generation method was identified. Additionally, the influence of the scale parameter was analyzed in a segmentation experiment based on a five-subset dataset. The comparative results for the proposed method, the commonly used watershed segmentation method, and the multiresolution segmentation method demonstrate that the proposed method yielded multispectral remote-sensing images with much better performance than the other methods.
Lower cutoff frequency improvement of planar EBG-patterned PDN using edge termination

A designed, fabricated and tested electromagnetic bandgap (EBG) structure is proposed for resolving the problem of the lower cut-off frequency of conventional planar-type EBGs. Bandwidth enhancement is achieved by incorporating edge termination along the edges of the whole EBG-patterned power plane. Measurement results show that the lower cutoff frequency is shifted downwards from 800 to 13 MHz. This structure also improves the upper cutoff frequency of 4.3 GHz for the conventional planar EBG to 5.2 GHz. Using this structure, simultaneous switching noise can be suppressed over the relative bandwidth of 63%, which is higher than the commonly used EBGs. The structure is easily fabricated with the current method of printed circuit board manufacturing processes and commonly used SMD resistors and capacitors.
Optimization of Surface-Enhanced Raman Spectroscopy Detection Conditions for Interaction between Gonyautoxin and Its Aptamer

This study aimed to optimize the detection conditions for surface-enhanced Raman spectroscopy (SERS) of single-stranded DNA (ssDNA) in four different buffers and explore the interaction between gonyautoxin (GTX1/4) and its aptamer, GO18. The influence of the silver colloid solution and MgSO4 concentration (0.01 M) added under four different buffered conditions on DNA SERS detection was studied to determine the optimum detection conditions. We explored the interaction between GTX1/4 and GO18 under the same conditions as those in the systematic evolution of ligands by exponential enrichment technique, using Tris-HCl as the buffer. The characteristic peaks of GO18 and its G-quadruplex were detected in four different buffer solutions. The change in peak intensity at 1656 cm−1 confirmed that the binding site between GTX1/4 and GO18 was in the G-quadruplex plane. The relative intensity of the peak at 1656 cm−1 was selected for the GTX1/4–GO18 complex (I1656/I1099) to plot the ratio of GTX1/4 in the Tris-HCl buffer condition (including 30 μL of silver colloid solution and 2 μL of MgSO4), and a linear relationship was obtained as follows: Y = 0.1867X + 1.2205 (R2 = 0.9239). This study provides a basis for subsequent application of SERS in the detection of ssDNA, as well as the binding of small toxins and aptamers.
Young Adults with Higher Salt Intake Have Inferior Hydration Status: A Cross-Sectional Study

The body’s water and sodium balances are tightly regulated and monitored by the brain. Few studies have explored the relationship between water and salt intake, and whether sodium intake with different levels of fluid intake leads to changes in hydration status remains unknown. The aim of the present study was to determine the patterns of water intake and hydration status among young adults with different levels of daily salt intakes. Participants’ total drinking fluids and water from food were determined by a 7-day 24-h fluid intake questionnaire for 7 days (from Day 1 to Day 7) and duplicate portion method (Day 5, Day 6 and Day 7). Urine of 24 h for 3 days (Day 5, Day 6 and Day 7) was collected and tested for the osmolality, the urine-specific gravity (USG), the concentrations of electrolytes, pH, creatinine, uric acid and the urea. The fasting blood samples for 1 day (Day 6) were collected and measured for the osmolality and the concentrations of electrolytes. The salt intakes of the participants were evaluated from the concentrations of Na of 24 h urine of 3 days (Day 5, Day 6 and Day 7). Participants were divided into four groups according to the quartile of salt intake, including the low salt intake (LS1), LS2, high salt intake (HS1) and HS2 groups. In total, 156 participants (including 80 male and 76 female young adults) completed the study. The salt intakes were 7.6, 10.9, 14.7 and 22.4 g among participants in the four groups (LS1, LS2, HS1 and HS2 groups, respectively), which differed significantly in all groups (F = 252.020; all p < 0.05). Compared to the LS1 and LS2 groups, the HS2 group had 310–381, 250–358 and 382–655 mL more amounts of water from the total water intake (TWI), total drinking fluids and water from food (all p < 0.05), respectively. Participants in the HS2 group had 384–403, 129–228 and 81–114 mL more in the water, water from dishes and staple foods, respectively, than those in the groups of LS1 and LS2 (p < 0.05). The HS2 group excreted 386–793 mL more urine than those in the groups of LS1 and LS2 (p < 0.05). However, regarding urine osmolality, the percentage of participants with optimal hydration status decreased from 41.0% in LS1 and LS2 to 25.6% in the HS2 group (p < 0.05). Participants with higher salt intake had higher TWI, total drinking fluids and water from food. Nevertheless, they had inferior hydration status. A reduction in salt intake should be encouraged among young adults to maintain optimal hydration status.
Acting on Leader’s Emotions: How and When Emotion Recognition Ability Motivates Voice?

Purpose Employee voice has been considered as an important means to understand the cutting-edge information, gain social status and performance advantage for leaders, employees and the organization, respectively. However, our knowledge about how and when employees’ emotions influence voice remains limited. Design/Methodology/Approach In order to better illustrate the role of emotion on voice, based on emotion as social information theory and similarity attraction theory, we proposed a research model through which emotion recognition ability affects voice via perceived ambidextrous leadership. A sample of 182 comprised of full-time employees and their 43 immediate supervisors was collected through questionnaires in China, and analyzed via hierarchical regression method. Findings We found that subordinate’s emotional recognition ability has a significant positive effect on promotive and prohibitive voice, and that perceived ambidextrous leadership plays a significant mediating role between subordinate’s emotional recognition ability and promotive voice, while no mediating role is found between subordinate’s emotional recognition ability and prohibitive voice. In addition, in contrast to leader-subordinate gender dissimilarity, leader-subordinate gender similarity is more effective in strengthening the impact of emotion recognition ability on perceived ambidextrous leadership, and thus promotes employee voice. Originality/Value This research not only advances our understanding of employee voice, but also provides specific reference for management practices from the perspective of gender.
Efficient coding of natural scenes improves neural system identification

Neural system identification aims at learning the response function of neurons to arbitrary stimuli using experimentally recorded data, but typically does not leverage normative principles such as efficient coding of natural environments. Visual systems, however, have evolved to efficiently process input from the natural environment. Here, we present a normative network regularization for system identification models by incorporating, as a regularizer, the efficient coding hypothesis, which states that neural response properties of sensory representations are strongly shaped by the need to preserve most of the stimulus information with limited resources. Using this approach, we explored if a system identification model can be improved by sharing its convolutional filters with those of an autoencoder which aims to efficiently encode natural stimuli. To this end, we built a hybrid model to predict the responses of retinal neurons to noise stimuli. This approach did not only yield a higher performance than the “stand-alone” system identification model, it also produced more biologically-plausible filters. We found these results to be consistent for retinal responses to different stimuli and across model architectures. Moreover, our normatively regularized model performed particularly well in predicting responses of direction-of-motion sensitive retinal neurons. In summary, our results support the hypothesis that efficiently encoding environmental inputs can improve system identification models of early visual processing.
Teaching and research in plant health in times of COVID-19

The current pandemic caused by the SARS-CoV-2 virus has led to radical changes in the teaching and research of plant health. Confinement forced us to make a rapid transition from the in-person model to virtual environments using different digital platforms such as Google, Microsoft Teams, Blackboard, Moodle. Research activities were planned based on a strict access schedule for students and academics when using research facilities. Theoretical subjects were taught in completely virtual settings, incorporating playful learning tools such as ‘flipped classroom’ and gamification. In theoretical-practical subjects, such as Introduction to Plant Pathology, new teaching schemes were designed. The most successful and innovative model was to take the laboratory to the student’s home. Students used conventional materials to isolate and identify phytopathogenic fungi through the Foldscope, a paper microscope with a resolution of up to two microns, priced less than 200 MXN. Teaching-learning innovation can improve the commonly adopted model of video conferences.
Mineralogy and geochemistry of the Middle Permian Pingdiquan Formation black shales on the eastern margin of the Junggar Basin, north‐west China: Implications for palaeoenvironmental and organic matter accumulation analyses

The Middle Permian black shales from the eastern Junggar Basin of northern Xinjiang, north‐west China are one of the richest and thickest lacustrine hydrocarbon source rocks in China. The palaeoenvironmental settings and controlling factors of organic matter accumulation along the margins of the Middle Permian lacustrine basin remain unclear, although the same works have been undertaken in the centre of the Middle Permian lacustrine basins. Here, we performed a combination of mineralogical and geochemical analyses on the black shales of the Middle Permian Pingdiquan Formation from the eastern margin areas of the Junggar Basin. The results show that the Pingdiquan Formation black shales in the study areas are organic‐rich, with total organic carbon (TOC) contents of 0.74–17.61 wt% (avg. 5.81 wt%). Salinity proxies including Sr/Ba and Rb/K ratios, combined with traces of gypsum and halite in a few samples, suggest brackish to saline water conditions. Palaeoclimate proxies indicate a warm‐humid environment during the deposition of the Pingdiquan Formation black shales. The redox proxies V/(V + Ni), V/Cr and U/Th ratios, and Eu and Ce anomalies together indicate dysoxic‐anoxic conditions of lake water. Strong positive correlations between palaeoproductivity proxies (P/Al, Ni/Al, Cu/Al, and Zn/Al) and TOC contents imply that palaeoproductivity may have played an essential role in organic matter accumulation during the deposition of the black shales. In contrast, negative correlations between terrestrial detrital input proxies (Al and Ti) and TOC contents indicate that terrestrial detrital input may have acted as a diluent to organic matter accumulation. Additionally, although the correlation between redox proxies [V/(V + Ni) and U/Th] and TOC contents is not straightforward, dysoxic‐anoxic conditions of lake water are an essential prerequisite for organic matter accumulation in the Pingdiquan Formation black shales.
Estimating Distributions of Parameters in Nonlinear State Space Models with Replica Exchange Particle Marginal Metropolis–Hastings Method

Extracting latent nonlinear dynamics from observed time-series data is important for understanding a dynamic system against the background of the observed data. A state space model is a probabilistic graphical model for time-series data, which describes the probabilistic dependence between latent variables at subsequent times and between latent variables and observations. Since, in many situations, the values of the parameters in the state space model are unknown, estimating the parameters from observations is an important task. The particle marginal Metropolis–Hastings (PMMH) method is a method for estimating the marginal posterior distribution of parameters obtained by marginalization over the distribution of latent variables in the state space model. Although, in principle, we can estimate the marginal posterior distribution of parameters by iterating this method infinitely, the estimated result depends on the initial values for a finite number of times in practice. In this paper, we propose a replica exchange particle marginal Metropolis–Hastings (REPMMH) method as a method to improve this problem by combining the PMMH method with the replica exchange method. By using the proposed method, we simultaneously realize a global search at a high temperature and a local fine search at a low temperature. We evaluate the proposed method using simulated data obtained from the Izhikevich neuron model and Lévy-driven stochastic volatility model, and we show that the proposed REPMMH method improves the problem of the initial value dependence in the PMMH method, and realizes efficient sampling of parameters in the state space models compared with existing methods.
Topology Aware Channel Assignment in Single-radio Stub Wireless Mesh Networks

Stub Wireless Mesh Networks (WMN) are multi-hop networks composed by wireless routers and connected to an infra-structured network through a set of gateway nodes. Stub WMN have multiple applications such as extending Internet coverage, providing last mile smart grid networks, or deploying wireless infrastructure for surveillance purposes. These applications of WMN have different requirements regarding throughput, delay and equipment costs. If the cost of the equipment is a relevant requirement, the number of wireless interface cards may have to be limited to assist the reduction of the cost, however, the capacity of the network must be addressed. Radio interference causes a reduction of the WMN capacity and of its performance but the usage of multiple channels may help mitigating this problem. This work addresses the problem of channel assignment in stubWMN using the CSMA/CA access method and formed by multiple gateways, and by nodes having a single radio interface available to form the WMN. The problem consists in centrally deciding in which channel each WMN node shall operate so that the WMN becomes connected and the network performance is optimal. We argue that the problem can be solved by using solely the network topology information, instead of using also traffic information as done by state of the art works. In order to prove this claim a large set of experiments were conducted involving the simulation of thousands of network topologies. The main contribution of this thesis is a centralized joint routing and channel assignment algorithm for single-radio WMN (TILIA) used to improve the performance of single-radio WMN using multiple channels. We improve the performance of multi-channel WMN by controlling solely the channel in which each node operates. This performance gain is obtained by enhancing the gateway neighborhood, in particular by increasing its size and avoiding hidden nodes on links around the gateway, while keeping the load balanced between channels. TILIA uses a breadth-first tree growing technique but, instead of growing a single tree, TILIA grows a forest of trees each of which rooted at a different gateway and operating on a different radio channel.
Optimization Design of Surface Wave Electromagnetic Acoustic Transducers Based on Simulation Analysis and Orthogonal Test Method

The energy conversion of electromagnetic acoustic transducers (EMATs) is typically lower, which seriously restricts the application of EMATs in the field of non-destructive testing and evaluation. In this work, parameters of surface wave EMATs, including structural parameters and electrical parameters, are investigated using the orthogonal test method to improve the transducer’s energy conversion efficiency. Based on the established finite element 2-D model of EMATs, the amplitude of the displacement components at the observation point of a plate is the optimization objective to be maximized with five parameters pertaining to the magnets, meander-line coils, and excitation signal as design variables. Results show that the signal amplitude of EMATs is 3.48 times on in-plane and 3.49 times on out-of-plane, respectively, compared with the original model. Furthermore, a new material (amorphous nanocrystalline material of type 1K107) is applied to optimize the magnetic circuit of EMATs and enhance the eddy current in an aluminum plate to increase the signal amplitude. Finally, the signal amplitudes obtained from the three types of models, that is, the original one, the optimization one after an orthogonal test, and the optimization one with the addition of magnetic concentrators, are analyzed and compared, indicating that the signal amplitude, compared with the original one, is 6.02 times on in-plane and 6.20 times on out-of-plane, respectively.
Solar-Powered Multi-Network Greenhouse: Automated Mushroom Monitoring and Management System Using Microcontrollers and IoT-Based Applications

This study utilized the Solar Powered Multi-Network Greenhouse through microcontrollers and IoT-based application to design an automated mushroom monitoring and management system. As mushrooms are more to suffer from increased temperature especially in tropical countries like the Philippines, this study develops an automated system where composition is controlled by a microcontroller and monitored by Arduino IDE. The greenhouse monitoring device used different highly-capable sensors, which provides accurate parameters used for monitoring systems and better control management for cultivation. The different possible solutions to control parameters and maintain stability value suitable for mushroom cultivation were addressed. Thus, the prototype went through series of trials and tests to ensure functionality and accuracy of the device. Likewise, performance testing was conducted for temperature, relative humidity, and light to control and monitor the needs of the mushroom. The results revealed that the device is accurate, functional and capable. The study suggests that the greenhouse could be improved by installing a CCTV for constant monitoring of the interior and exterior of the greenhouse. The greenhouse could also be considered to be situated in a more private place as well as improve some of the application features.
Complex intuitionistic fuzzy soft SWARA - COPRAS approach: An application of ERP software selection

In this manuscript, we propose an integrated framework based on COmplex PRoportional ASsessment and Step-wise Weight Assessment Ratio Analysis approach within the complex intuitionistic fuzzy soft (CIFS) context. This context is an ideal technique with complex fuzzy foundation that means to denote multi-dimensional data in a concise. In this framework, criteria weights are evaluated by the SWARA technique, and the ranking of alternatives is determined by the COPRAS method using CIFSs. Further, to illustrate the applicability of the presented technique, an empirical case study of ERP software selection problem is taken. A comparative study and sensitivity analysis is presented to verify the strength of the presented methodology.