bluuebunny/crossref_metadata_2025 huggingface dataset:
Morphological and Phylogenetic Studies of Three New Species of Calocybe (Agaricales, Basidiomycota) from China
Authors: Qi Yue , Xu Aiguo , Zhou Ye , Bi Kexin , Qin Weiqiang , Guo Hongbo , Yu Xiaodan
Published: August 2022

Three species, Calocybe lilacea, C. longisterigma, and C. subochraceus, were newly discovered in Inner Mongolia, Hunan, and Liaoning provinces of China. Calocybe lilacea is mainly characterized by its small-sized basidiocarp, brownish-orange pileus, lilac gray to dull violet stipe, and noncellular epicutis. The main characteristics of C. longisterigma are its light brown to brownish-orange pileus, long sterigmata, and noncellular epicutis. The main morphological features of C. subochraceus are its small-sized basidiocarp, pale-orange pileus, adnexed lamellae, tortuous stipe, and noncellular epicutis. These morphological features confirmed that the three species of Calocybe all belonged to Sect. Carneoviolaceae. Phylogenetic analysis based on a combined dataset (ITS–nrLSU–RPB2) determined that the three species belong to the genus Calocybe and form a distinct lineage. The morphological differences between the three new species and other related species of Calocybe are also discussed.
Three New Species of Dicephalospora (Helotiaceae, Helotiales) from Thailand
Authors: Phutthacharoen Kunthida , Chethana K. W. Thilini , Lestari Anis S. , Stadler Marc , Hyde Kevin D.
Published: August 2022

Dicephalospora is a genus of Helotiaceae (Helotiales) that presently comprises 14 species, all of which were collected from Asia. The current study describes three additional species and a collection from Chiang Rai and Chiang Mai Provinces, Thailand. The new fungi were identified based on morphological characteristics coupled with phylogenetic analyses of combined LSU and ITS nrDNA loci. Dicephalospora chiangraiensis is characterized by small asci (90–110 × 5–10 µm) and ascospores of 20–25 × 2–4 µm, featuring a non-mucilaginous cap. Dicephalospora irregularis is characterized by sessile apothecia, non-amyloid asci, branched, filiform paraphyses, and fusoid-clavate to ellipsoid ascospores with a mucilaginous cap, while D. inthanonensis is characterized by unbranched and aseptate paraphyses, a partly globose blue reaction with Melzers reagent at ascal apices, and fusoid ascospores in the range of 24–32 × 3–5 µm with a non-mucilaginous cap. With the present study, the number of species of Dicephalospora known from Thailand has now increased to three. A dichotomous key to the species of the genus is also provided.
The Contribution of Subtidal Seagrass Meadows to the Total Carbon Stocks of Gazi Bay, Kenya
Authors: Omollo Derrick Joannes , Wang’ondu Virginia Wangeci , Githaiga Michael Njoroge , Gorman Daniel , Kairo James Gitundu
Published: August 2022

Seagrass beds occur globally in both intertidal and subtidal zones within shallow marine environments, such as bays and estuaries. These important ecosystems support fisheries production, attenuate strong wave energies, support human livelihoods and sequester large amounts of CO2 that may help mitigate the effects of climate change. At present, there is increased global interest in understanding how these ecosystems could help alleviate the challenges likely to face humanity and the environment into the future. Unlike other blue carbon ecosystems, i.e., mangroves and saltmarshes, seagrasses are less understood, especially regarding their contribution to the carbon dynamics. This is particularly true in regions with less attention and limited resources. Paucity of information is even more relevant for the subtidal meadows that are less accessible. In Kenya, much of the available information on seagrasses comes from Gazi Bay, where the focus has been on the extensive intertidal meadows. As is the case with other regions, there remains a paucity of information on subtidal meadows. This limits our understanding of the overall contribution of seagrasses in carbon capture and storage. This study provides the first assessment of the species composition and variation in carbon storage capacity of subtidal seagrass meadows within Gazi Bay. Nine seagrass species, comprising of Cymodocea rotundata, Cymodocea serrulata, Enhalus acoroides, Halodule uninervis, Halophila ovalis, Halophila stipulacea, Syringodium isoetifolium, Thalassia hemprichii, and Thalassodendron ciliatum, were found. Organic carbon stocks varied between species and pools, with the mean below ground vegetation carbon (bgc) stocks (5.1 ± 0.7 Mg C ha−1) being more than three times greater than above ground carbon (agc) stocks (0.5 ± 0.1 Mg C ha−1). Mean sediment organic carbon stock (sed Corg) of the subtidal seagrass beds was 113 ± 8 Mg C ha−1. Combining this new knowledge with existing data from the intertidal and mangrove fringed areas, we estimate the total seagrass ecosystem organic carbon stocks in the bay to be 196,721 Mg C, with the intertidal seagrasses storing about 119,790 Mg C (61%), followed by the subtidal seagrasses 55,742 Mg C (28%) and seagrasses in the mangrove fringed creeks storing 21,189 Mg C (11%). These findings are important in highlighting the need to protect subtidal seagrass meadows and for building a national and global data base on seagrass contribution to global carbon dynamics.
Synchronous/Metachronous Multiple Primary Malignancies: Review of Associated Risk Factors
Authors: Pan Szu-Ying , Huang Chi-Ping , Chen Wen-Chi
Published: August 2022

The incidence of secondary primary malignancy (SPM) has been reported to range from 1.33% to 5.8%, according to the location of the primary cancer and the follow-up duration. The highest occurrence rate of SPM, of 36.6% within 6 months, has been reported in lung cancer. Genitourinary malignancies were reported to be the third-most-common SPM in several reports. However, the incidence of genitourinary malignancy as the first primary cancer associated with SPM has not been reported. Several risk factors are related to the occurrence of SPM, including viral infection chemotherapy, radiation, genetics, smoking, betel quid chewing, and environmental factors. An early survey for SPM is indicated in first primary malignancy patients with these associated factors. In this study, we summarize several risk factors related to the occurrence of SPMs and preventive tests, which may help in their early detection and, consequently, better survival.
Screening for Myocardial Injury after Mild SARS-CoV-2 Infection with Advanced Transthoracic Echocardiography Modalities
Authors: Rácz Gergely , Takács Hedvig , Kormányos Árpád , Polestyuk Bianka , Borbás János , Gyenes Nándor , Schvartz Noémi , Németh Gergely , Kincses Zsigmond Tamás , Sepp Róbert , Nagy Viktória
Published: August 2022

Although the clinical manifestations of SARS-CoV-2 viral infection affect mainly the respiratory system, cardiac complications are common and are associated with increased morbidity and mortality. While echocardiographic alterations indicating myocardial involvement are widely reported in patients hospitalized for acute COVID-19 infection, much fewer data available in non-hospitalized, mildly symptomatic COVID-19 patients. In our work, we aimed to investigate subclinical cardiac alterations characterized by parameters provided by advanced echocardiographic techniques following mild SARS-CoV-2 viral infection. A total of 86 patients (30 males, age: 39.5 ± 13.0 yrs) were assessed 59 ± 33 days after mild SARS-CoV-2 viral infection (requiring no hospital or <5 days in-hospital treatment) by advanced echocardiographic examination including 2-dimensional (2D) speckle tracking echocardiography and non-invasive myocardial work analysis, and were compared to an age-and sex-matched control group. Altogether, variables from eleven echocardiographic categories representing morphological or functional echocardiographic parameters showed statistical difference between the post-COVID patient group and the control group. The magnitude of change was subtle or mild in the case of these parameters, ranging from 1–11.7% of relative change. Among the parameters, global longitudinal strain [−20.3 (−21.1–−19.0) vs. −19.1 (−20.4–−17.6) %; p = 0.0007], global myocardial work index [1975 (1789–2105) vs. 1829 (1656–2057) Hgmm%; p = 0.007] and right ventricular free wall strain values (−26.6 ± 3.80 vs. −23.8 ± 4.0%; p = 0.0003) showed the most significant differences between the two groups. Subclinical cardiac alterations are present following even mild SARS-CoV-2 viral infection. These more subtle alterations are difficult to detect by routine echocardiography. Extended protocols, involving speckle-tracking echocardiography, non-invasive measurement of cardiac hemodynamics, and possibly myocardial work are necessary for detection and adequate follow-up.
Serum Periostin May Help to Identify Patients with Poor Collaterals in the Hyperacute Phase of Ischemic Stroke
Authors: Spantler Dora , Csecsei Peter , Borocz Katalin , Berki Timea , Zavori Laszlo , Schwarcz Attila , Lenzser Gabor , Molnar Tihamer
Published: August 2022

Background: Periostin is a glycoprotein that mediates cell functions in the extracellular matrix and appears to be a promising biomarker in neurological damage, such as ischemic stroke (IS). We aimed to measure serum periostin levels in the hyperacute phase of ischemic stroke to explore its predictive power in identification of patients with poor collaterals (ASPECT < 6). Methods: We prospectively enrolled 122 patients with acute ischemic stroke within the first 6 h after onset. The early ischemic changes were evaluated by calculating ASPECT score on admission using a native CT scan. An unfavorable outcome was defined as the modified Rankin Scale (mRS) > 2 at 90 days follow-up. Blood samples were collected on admission immediately after CT scan and periostin serum concentrations were determined by ELISA. Results: The admission concentration of serum periostin was significantly higher in patients with unfavorable outcome than in patients with favorable outcome (615 ng/L, IQR: 443–1070 vs. 390 ng/L, 260–563, p < 0.001). In a binary logistic regression model, serum periostin level was a significant predictor for ASPECT < 6 status on admission, within 6 h after stroke onset (OR, 5.911; CI, 0.990–0.999; p = 0.015). Conclusion: Admission periostin levels can help to identify patients who are not suitable for neurointervention, especially if advanced neuroimaging is not available.
A Wind-Tunnel Assessment of Parameters That May Impact Spray Drift during UAV Pesticide Application
Authors: Grant Shanique , Perine Jeff , Abi-Akar Farah , Lane Timothy , Kent Brenna , Mohler Christopher , Scott Chris , Ritter Amy
Published: August 2022

The objective of this study was to investigate the impact of varying wind speeds (1.5, 3.0, and 4.5 m/s), initial payload volumes (2 and 10 L), and nozzle droplet size characteristics (fine, medium, coarse) on drift during spray applications from an unmanned aerial vehicle (UAV) hovering freely in a wind tunnel. Along the length of the wind tunnel, glass slides were used to collect spray droplets at 14 points distributed in upwind, in-swath, and downwind distances. Analysis of the results showed that there are distinguishable shifts of up to 2 m in-swath as wind speed increases. Downwind of the UAV, a regression of the combined variables indicated that tunnel wind speed changed deposition the most overall, followed by nozzle/droplet size. Initial payload volume was less impactful. Overall, faster wind speeds, finer droplet sizes, and a heavier initial payload were associated with more drift on average. Wind directions and speeds were also measured on a finer scale of tunnel locations to record airflow pattern variability especially closer to the UAV. These findings may provide guidance to regulators and applicators to identify operating conditions for UAVs that limit off-target movement during applications.
Dynamic Sliding Mode Control of DC-DC Converter to Extract the Maximum Power of Photovoltaic System Using Dual Sliding Observer
Authors: Karami-Mollaee Ali , Barambones Oscar
Published: August 2022

This paper concerns the maximum power extraction of a photovoltaic generator system (PGS). The PGS consists of single photovoltaic (PV) cells. To improve the efficiency of a PGS, it is necessary to work within its maximum power point (MPP). In a PGS, output power is dependent on solar irradiance and the operating temperature and, therefore, MPP would be varied. To address this problem, a converter should be placed after the PGS and a smooth control signal should be used to adjust its duty cycle. The other challenge of a total system, i.e., PGS and converter, is the uncertainty involved. To overcome this uncertainty, a dynamic sliding mode control (SMC) can be used to regulate the smooth duty cycle. The low-pass integrator before the system can remove the chattering in dynamic SMC. However, due to the integrator, the states of the system increase and, hence, we propose a dual sliding observer (DSO) to estimate this added state. For a reliable comparison with the conventional SMC, the same proposed DSO can be applied in both dynamic and conventional SMC. The provided comparison shows the effectiveness of dynamic SMC in chattering suppression and real implementation with respect to conventional SMC.
Method for Direct Localization of Multiple Impulse Acoustic Sources in Outdoor Environment
Authors: Mišković Milan , Vukmirović Nenad , Golubović Dragan , Erić Miljko
Published: August 2022

A method for the direct outdoor localization of multiple impulse acoustic sources by a distributed microphone array is proposed. This localization problem is of great interest for gunshot, firecracker and explosion detection localization in a civil environment, as well as for gun, mortar, small arms, artillery, sniper detection localization in military battlefield monitoring systems. Such a kind of localization is a complicated technical problem in many aspects. In such a scenario, the permutation of impulse arrivals on distributed microphones occurs, so the application of classical two-step localization methods, such as time-of-arrival (TOA), time-difference-of-arrival (TDOA), angle-of-arrival (AOA), fingerprint methods, etc., is faced with the so-called association problem, which is difficult to solve. The association problem does not exist in the proposed method for direct (one-step) localization, so the proposed method is more suitable for localization in a given acoustic scenario than the mentioned two-step localization methods. Furthermore, in the proposed method, direct localization is performed impulse by impulse. The observation interval used for the localization could not be arbitrarily chosen; it is limited by the duration of impulses. In the mathematical model formulated in the paper, atmospheric factors in acoustic signal propagation (temperature, pressure, etc.) are included. The results of simulations show that by using the proposed method, centimeter localization accuracy can be achieved.
Color Image Encryption Algorithm Based on Dynamic Block Zigzag Transformation and Six-Sided Star Model
Authors: Zhang Xiaoqiang , Liu Mi , Tian Jingxi , Gong Zhengjun
Published: August 2022

As a result of the rise in network technology, information security has become particularly important. Digital images play an important role in network transmission. To improve their security and efficiency, a new color image encryption algorithm is proposed. The proposed algorithm adopts a classical scrambling–diffusion framework. In the scrambling stage, the dynamic block Zigzag transformation is designed by combining the chaotic sequence with the standard Zigzag transformation, which can dynamically select the transformation range and the number of times. It is used to scramble the pixel positions in the R, G, and B components. In the diffusion stage, the six-sided star model is established by combining the chaotic sequence and the six-sided star structure characteristics, which can store the 24 bits of the pixel in a defined order to realize bit-level diffusion operation. Experimental analyses indicate that our algorithm has the characteristics of high key sensitivity, large key space, high efficiency, and resistance to plaintext attacks, statistical attacks, etc.
Predicting the Performance of a 26 GHz Transconductance Modulated Downconversion Mixer as a Function of LO Drive and DC Bias
Authors: Ball Edward A.
Published: August 2022

The dependency of RF performance on the local oscillator (LO) drive amplitude and DC bias is an important topic for RF mixers, especially as carrier frequency increases and generation of RF power thus becomes more complex. The prediction of mixer performance, without initial reliance on full circuit simulations, can provide important insights. In this work, mathematical models without the prior use of circuit simulation are developed, leading to a strategy to predict the conversion gain (Gc), DC current, 1 dB input compression point (IP1dB) and third order input intercept point (IIP3) for a SiGe bipolar transistor transconductance mixer. The models show the possibility to trade-off LO RF power and DC bias to achieve a desired performance. The concepts allow a prediction of the necessary DC bias required to support a chosen LO level and desired conversion transconductance or linearity. The mathematical model results, circuit simulation results, and measured hardware results from a 26 GHz prototype of a single-ended mixer are presented and compared, showing good agreement. In a lab-measured example, LO power reduction from +10 dBm to +3 dBm resulted in only a 1 dB reduction in conversion gain, by modifying the DC bias as predicted. The peak conversion gain predicted by the models is within 2.0 dB of circuit simulation and 2.5 dB of measured PCB results. The RMS error for predicted DC current, compared to circuit simulation, is 1.9 mA or better.
Development of Metamaterial Inspired Non-Uniform Circular Array Superstate Antenna Using Characteristic Mode Analysis
Authors: Bhavani Kothakonda Durga , Madhav Boddapati Taraka Phani , Das Sudipta , Hussain Niamat , Ali Syed Samser , Babu Kommanaboyina Vasu
Published: August 2022

In this work, using characteristic mode analysis, a multi-layered nonuniform metasurface structured antenna has been optimized. The driven patch of square structure and the parasitic patch elements of circular radiating cross-slotted meta-structure are used in the proposed model. The modal significance characteristic angles and surface currents are analyzed based on characteristic mode to optimize the nonuniform structures. The antenna is resonating between 5.5–6.1 GHz, covering WLAN applications with an average gain of 7.9 dBi and efficiency greater than 90%. Transient mode, terminal mode, and eigenmode-based analyses are performed on the proposed design, and comparative analysis has been presented in this work. The prototype model fabrication and real-time measurement analysis with simulation results matching are presented for application validation.
Global Correlation Enhanced Hand Action Recognition Based on NST-GCN
Authors: Yang Shiqiang , Li Qi , He Duo , Wang Jinhua , Li Dexin
Published: August 2022

Hand action recognition is an important part of intelligent monitoring, human–computer interaction, robotics and other fields. Compared with other methods, the hand action recognition method using skeleton information can ignore the error effects caused by complex background and movement speed changes, and the computational cost is relatively small. The spatial-temporal graph convolution networks (ST-GCN) model has excellent performance in the field of skeleton-based action recognition. In order to solve the problem of the root joint and the further joint not being closely connected, resulting in a poor hand-action-recognition effect, this paper firstly uses the dilated convolution to replace the standard convolution in the temporal dimension. This is in order to process the time series features of the hand action video, which increases the receptive field in the temporal dimension and enhances the connection between features. Then, by adding non-physical connections, the connection between the joints of the fingertip and the root of the finger is established, and a new partition strategy is adopted to strengthen the hand correlation of each joint point information. This helps to improve the network’s ability to extract the spatial-temporal features of the hand. The improved model is tested on public datasets and real scenarios. The experimental results show that compared with the original model, the 14-category top-1 and 28-category top-1 evaluation indicators of the dataset have been improved by 4.82% and 6.96%. In the real scene, the recognition effect of the categories with large changes in hand movements is better, and the recognition results of the categories with similar trends of hand movements are poor, so there is still room for improvement.
Detection of COVID-19 from Deep Breathing Sounds Using Sound Spectrum with Image Augmentation and Deep Learning Techniques
Authors: Abayomi-Alli Olusola O. , Damaševičius Robertas , Abbasi Aaqif Afzaal , Maskeliūnas Rytis
Published: August 2022

The COVID-19 pandemic is one of the most disruptive outbreaks of the 21st century considering its impacts on our freedoms and social lifestyle. Several methods have been used to monitor and diagnose this virus, which includes the use of RT-PCR test and chest CT/CXR scans. Recent studies have employed various crowdsourced sound data types such as coughing, breathing, sneezing, etc., for the detection of COVID-19. However, the application of artificial intelligence methods and machine learning algorithms on these sound datasets still suffer some limitations such as the poor performance of the test results due to increase of misclassified data, limited datasets resulting in the overfitting of deep learning methods, the high computational cost of some augmentation models, and varying quality feature-extracted images resulting in poor reliability. We propose a simple yet effective deep learning model, called DeepShufNet, for COVID-19 detection. A data augmentation method based on the color transformation and noise addition was used for generating synthetic image datasets from sound data. The efficiencies of the synthetic dataset were evaluated using two feature extraction approaches, namely Mel spectrogram and GFCC. The performance of the proposed DeepShufNet model was evaluated using a deep breathing COSWARA dataset, which shows improved performance with a lower misclassification rate of the minority class. The proposed model achieved an accuracy, precision, recall, specificity, and f-score of 90.1%, 77.1%, 62.7%, 95.98%, and 69.1%, respectively, for positive COVID-19 detection using the Mel COCOA-2 augmented training datasets. The proposed model showed an improved performance compared to some of the state-of-the-art-methods.
Contouring Control of a Five-Axis Machine Tool with Equivalent Errors
Authors: Chen Shyh-Leh , Khong Mun-Hooi , Hsieh Sheng-Min
Published: August 2022

In this study, the contouring control problem of a five-axis machine tool was examined. Due to the rotation axes, there are two coordinate systems involved in the five-axis machine tool, namely the workpiece coordinate system and machine coordinate system. The five-axis machine tool is required to follow a given desired path with tool orientation specified in the workpiece coordinate system. However, the system dynamics of the machine tool is described in the machine coordinates. Kinematic transformations exist between the two coordinate systems. One challenge of the problem is to design a controller in the machine coordinate system that will meet the requirements in the workpiece coordinate system. Another challenge is to minimize both the position contour error and tool orientation error. The method of equivalent errors is adopted to design the contouring controller. The desired path and tool orientation in the workpiece coordinate system are transformed into a five-dimensional hyper-curve in the machine coordinate system. A contouring controller was designed to follow the five-dimensional hyper-curve using the method of equivalent errors. Both numerical and experimental results validate the effectiveness of the proposed contouring control method.
Recent Advances in Green Hydrogen Technology
Authors: Calise Francesco
Published: August 2022

During the 20th century, the global energy system was mainly based on the use of fossil fuels, such as oil, natural gas, and coal [...]
Peculiarities of Calculating the Thermal Conductivity of Moist Autoclaved Aerated Concrete
Authors: Backiel-Brzozowska Beata , Nikitsin Vadzim I. , Alsabry Abdrahman , Nikitsin Serafim K. , Rutkowska Wioleta
Published: August 2022

The pore space of autoclaved aerated concretes (ACCs), regardless of their apparent density, is represented by large pores formed as a result of gas formation and fine capillary pores. With the free absorption of liquid moisture, only the capillary pores are filled. Large pores contain vapor-air mixture. Considering such a bimodal pore size distribution, it is proposed to determine the thermal conductivity of moist ACC in two stages. First, an inhomogeneous ternary system that consists of a solid skeleton with a fine porous structure containing gas and liquid moisture should be considered. Then a binary system is taken into account, the first component of which is the mentioned ternary system, and the other component of which consists of isolated gas inclusions in large pores. To determine the thermal conductivity of the ternary system, the dependences constructed using the theory of generalized conductivity were used. The thermal conductivity of the binary system was calculated using well-known formulas. It was found that the results of thermal conductivity calculations based on the proposed two-step method deviate from the experimental data in the range from −7.29 to +5.75%, with an average deviation of −0.71%. With the one-step calculation method (assuming a unimodal pore distribution), the spread of analogous data ranges from −30.72 to −21.98%, with an average deviation of −26%.
The Use of Singular Spectrum Analysis and K-Means Clustering-Based Bootstrap to Improve Multistep Ahead Load Forecasting
Authors: Sulandari Winita , Yudhanto Yudho , Rodrigues Paulo Canas
Published: August 2022

In general, studies on short-term hourly electricity load modeling and forecasting do not investigate in detail the sources of uncertainty in forecasting. This study aims to evaluate the impact and benefits of applying bootstrap aggregation in overcoming the uncertainty in time series forecasting, thereby increasing the accuracy of multistep ahead point forecasts. We implemented the existing and proposed clustering-based bootstrapping methods to generate new electricity load time series. In the proposed method, we use singular spectrum analysis to decompose the series between signal and noise to reduce the variance of the bootstrapped series. The noise is then bootstrapped by K-means clustering-based generation of Gaussian normal distribution (KM.N) before adding it back to the signal, resulting in the bootstrapped series. We apply the benchmark models for electricity load forecasting, SARIMA, NNAR, TBATS, and DSHW, to model all new bootstrapped series and determine the multistep ahead point forecasts. The forecast values obtained from the original series are compared with the mean and median across all forecasts calculated from the bootstrapped series using the Malaysian, Polish, and Indonesian hourly load series for 12, 24, and 36 steps ahead. We conclude that, in this case, the proposed bootstrapping method improves the accuracy of multistep-ahead forecast values, especially when considering the SARIMA and NNAR models.
An Accurate Power Flow Method for Microgrids with Conventional Droop Control
Authors: Lu Fang , Liu Hongda
Published: August 2022

With conventional droop control, the droop relationship between the voltage and reactive power is not purely linear because of the filter reactance. This paper focuses on the theoretical analysis to account for this characteristic and presents a precise power flow method for conventional droop control. The proposed method is universal, which can handle not only conventional droop control, but also other control strategies, such as robust droop control, constant power control, and constant voltage–frequency control. It can also handle frequency-dependent active and reactive power loads and is adapted for islanded and grid-connected systems. The proposed method extends the applicability of conventional power flow methods to microgrids so that the framework of the method is generic; any conventional power flow algorithm can be adapted to this framework. Compared with the time-domain simulation method, the proposed method is accurate, simple, and easy to implement for industrial applications.
High-Efficiency and High-Performance Power Electronics for Power Grids and Electrical Drives
Authors: Luna Massimiliano
Published: August 2022

Since the invention of the light bulb by T [...]
Facile Synthesis of N, S-Doped Carbon Quantum Dots from Food Waste as Fluorescent Probe for Sensitive Detection of Thiamphenicol and Its Analogues in Real Food Samples along with an Application in Bioimaging
Authors: Chen Shujuan , Ouyang Wanlin , Zhu Yiting , He Li , Zou Likou , Ao Xiaolin , Liu Shuliang , Yang Yong , Li Jianlong
Published: August 2022

Herein, N, S co-doped carbon quantum dots (N, S-CDs) with high absolute quantitative yield (Abs-QY) of 50.2% were produced by hydrothermal treatment of food residue crayfish shells. A new detection method of thiamphenicol (TAP) and its analogues was established by discovering the obvious fluorescence response between TAP and N, S-CDs, which achieved a wide linear range of 20–300 μg·L−1 with a detection limit (LOD) of 11.12 μg·L−1. This novel probe exhibited strong sensitivity and shows rapid response in complex food matrices (overall detection time is less than 45 min) mainly induced by static quenching. Spiked food sample recovery ranged from 97.3 to 99.34%. Further, the cell experiments of N, S-CDs were conducted, and the cell viability remained 91.76% under high concentration of N, S-CDs due to the environmentally friendly materials. The low cytotoxicity and good cytocompatibility make these N, S-CDs compatible for cell bioimaging and intracellular detection of TAP.
Plant-Derived Antimicrobial Peptides: Novel Preservatives for the Food Industry
Authors: Baindara Piyush , Mandal Santi M.
Published: August 2022

Food spoilage is a widespread issue brought on by the undesired growth of microbes in food products. Thousands of tons of usable food or food products are wasted every day due to rotting in different parts of the world. Several food preservation techniques are employed to prevent food from rotting, including the use of natural or manufactured chemicals or substances; however, the issue persists. One strategy for halting food deterioration is the use of plant-derived antimicrobial peptides (AMPs), which have been investigated for possible bioactivities against a range of human, plant, and food pathogens. The food industry may be able to benefit from the development of synthetic AMPs, produced from plants that have higher bioactivity, better stability, and decreased cytotoxicity as a means of food preservation. In order to exploit plant-derived AMPs in various food preservation techniques, in this review, we also outline the difficulties in developing AMPs for use as commercial food preservatives. Nevertheless, as technology advances, it will soon be possible to fully explore the promise of plant-derived AMPs as food preservatives.
Comparison of Wet Fractionation Methods for Processing Broccoli Agricultural Wastes and Evaluation of the Nutri-Chemical Values of Obtained Products
Authors: Domokos-Szabolcsy Éva , Elhawat Nevien , Domingos Geraldo , Kovács Zoltán , Koroknai Judit , Bodó Enikő , Fári Miklós , Alshaal Tarek , Bákonyi Nóra
Published: August 2022

The main objective of this study was to increase the economic value of broccoli green agro-waste using three wet fractionation methods in the shadow of green biorefinery and the circular economy. Product candidates were obtained directly by using a mechanical press, and indirectly by using microwave coagulation or via lactic acid fermentation of green juice. The leaf protein concentrates (LPC) fractions displayed significantly higher dry matter content and crude protein content (34–39 m/m% on average) than the green juice fraction (27.4 m/m% on average), without considerable changes in the amino acids composition ratio. UHPLC-ESI-ORBITRAP-MS/MS analysis showed that kaemferol and quercetin are the most abundant flavonols, forming complexes with glycosides and hydroxycinnamic acids in green juice. Lacto-ermentation induced a considerable increase in the quantity of quercetin (48.75 μg·g−1 dry weight) and kaempferol aglycons (895.26 μg·g−1 dry weight) of LPC. In contrast, chlorogenic acid isomers and sulforaphane disappeared from LPC after lactic acid fermentation, while microwave treatment did not cause significant differences. These results confirm that both microwave treatment and lacto-fermentation coagulate and concentrate most of the soluble proteins. Also, these two processes affect the amount of valuable phytochemicals differently, so it should be considered when setting the goals.
On Sharp Estimate of Third Hankel Determinant for a Subclass of Starlike Functions
Authors: Shi Lei , Arif Muhammad , Ullah Khalil , Alreshidi Naseer , Shutaywi Meshal
Published: August 2022

In our present investigation, a subclass of starlike function Sn−1,L* connected with a domain bounded by an epicycloid with n−1 cusps was considered. The main work is to investigate some coefficient inequalities, and second and third Hankel determinants for functions belonging to this class. In particular, we calculate the sharp bounds of the third Hankel determinant for f∈S4L* with zf′(z)f(z) bounded by a four-leaf shaped domain under the unit disk D.
Fast Compact Difference Scheme for Solving the Two-Dimensional Time-Fractional Cattaneo Equation
Authors: Nong Lijuan , Yi Qian , Cao Jianxiong , Chen An
Published: August 2022

The time-fractional Cattaneo equation is an equation where the fractional order α∈(1,2) has the capacity to model the anomalous dynamics of physical diffusion processes. In this paper, we consider an efficient scheme for solving such an equation in two space dimensions. First, we obtain the space’s semi-discrete numerical scheme by using the compact difference operator in the spatial direction. Then, the semi-discrete scheme is converted to a low-order system by means of order reduction, and the fully discrete compact difference scheme is presented by applying the L2-1σ formula. To improve the computational efficiency, we adopt the fast discrete Sine transform and sum-of-exponentials techniques for the compact difference operator and L2-1σ difference operator, respectively, and derive the improved scheme with fast computations in both time and space. That aside, we also consider the graded meshes in the time direction to efficiently handle the weak singularity of the solution at the initial time. The stability and convergence of the numerical scheme under the uniform meshes are rigorously proven, and it is shown that the scheme has second-order and fourth-order accuracy in time and in space, respectively. Finally, numerical examples with high-dimensional problems are demonstrated to verify the accuracy and computational efficiency of the derived scheme.
Artificial Intelligence Applied to Pancreatic Imaging: A Narrative Review
Authors: Laino Maria Elena , Ammirabile Angela , Lofino Ludovica , Mannelli Lorenzo , Fiz Francesco , Francone Marco , Chiti Arturo , Saba Luca , Orlandi Matteo Agostino , Savevski Victor
Published: August 2022

The diagnosis, evaluation, and treatment planning of pancreatic pathologies usually require the combined use of different imaging modalities, mainly, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Artificial intelligence (AI) has the potential to transform the clinical practice of medical imaging and has been applied to various radiological techniques for different purposes, such as segmentation, lesion detection, characterization, risk stratification, or prediction of response to treatments. The aim of the present narrative review is to assess the available literature on the role of AI applied to pancreatic imaging. Up to now, the use of computer-aided diagnosis (CAD) and radiomics in pancreatic imaging has proven to be useful for both non-oncological and oncological purposes and represents a promising tool for personalized approaches to patients. Although great developments have occurred in recent years, it is important to address the obstacles that still need to be overcome before these technologies can be implemented into our clinical routine, mainly considering the heterogeneity among studies.
The Impact of the Introduction of the Breast Unit Model in a Northwestern Italian Region
Authors: Paleari Laura , Tassinari Federico , Astengo Matteo , Amicizia Daniela , Paganino Chiara , Paoli Gabriella , Pronzato Paolo , Ansaldi Filippo
Published: August 2022

Breast cancer is the most common tumor in middle-aged and older women. In 2003, the European Parliament recommended to Member States that all women with breast cancer should be treated by a multidisciplinary team and that a network of certified breast centers be organized (the centers have been called Breast Units (BUs)). With the present study, we aim to explore the impact of the introduction of the BU organizational model in the Liguria region, Italy, through different outcome indicators. An explorative retrospective analysis was conducted through the period from 2013 to 2019 to assess the impact of the introduction of the BU model in our region. We identified two periods: before (2014–2015) and after (2017–2018) the introduction of this organizational model to assess its value impact through the definition of six measurable outcome indicators. Length of hospitalization, repeated specialist outpatient diagnostic procedures and the rate of subjects who started radiotherapy treatment within 60 days improved after the introduction of BUs. The passive health migration rate only improved significantly for one local health unit (LHU), while reintervention and diagnosis–surgery time did not show any enhancement after the introduction of the BU model. The BU model seems to provide an increase in several aspects of the healthcare offered to breast cancer patients in Liguria, specifically in those areas where a shared guideline could assist healthcare workers. Future research, such as pilot studies, are needed to assess the impact of the introduction of the BU model in our reality.
Combining Sea Level Rise Inundation Impacts, Tidal Flooding and Extreme Wind Events along the Abu Dhabi Coastline
Authors: Chow Aaron C. H. , Sun Jiayun
Published: August 2022

This paper describes the development of a two-dimensional, basin-scale tidal model with waves and wave run-up to determine the inundation impacts on the Abu Dhabi coastline due to the combined effect of sea level rise, tidal flooding, storm surge and waves. The model combines a hydrodynamics model (DELFT3D), a spectral wave model (SWAN) and wave run-up. A high horizontal resolution (down to about 30 m) is employed in the vicinity of Abu Dhabi—a city built on a system of mangrove islands along the Arabian Gulf coast—to enable prediction of impact at the scale of the local infrastructure, such as individual highway links. The model confirms that, with a rise in sea level of 0.5 m, the islands along the outer coast of Abu Dhabi will experience inundation due to tidal flooding, wind, and high Shamal-induced waves. The incorporation of the wind and waves results in a prediction of more than double the area found underwater within the study area (from 82 to 188 km2). The inner water channel regions of Abu Dhabi, while mostly unaffected by wind-driven wave events, are still vulnerable to tidal flooding. Finally, the paper demonstrates the use of the model to predict whether protection of one segment of the city’s coastline will adversely affect the inundation potential of nearby unprotected segments.
Demographic Control Measure Implications of Tuberculosis Infection for Migrant Workers across Taiwan Regions
Authors: Chen Szu-Chieh , Wang Tzu-Yun , Tsai Hsin-Chieh , Chen Chi-Yun , Lu Tien-Hsuan , Lin Yi-Jun , You Shu-Han , Yang Ying-Fei , Liao Chung-Min
Published: August 2022

A sharp increase in migrant workers has raised concerns for TB epidemics, yet optimal TB control strategies remain unclear in Taiwan regions. This study assessed intervention efforts on reducing tuberculosis (TB) infection among migrant workers. We performed large-scale data analyses and used them to develop a control-based migrant worker-associated susceptible–latently infected–infectious–recovered (SLTR) model. We used the SLTR model to assess potential intervention strategies such as social distancing, early screening, and directly observed treatment, short-course (DOTS) for TB transmission among migrant workers and locals in three major hotspot cities from 2018 to 2023. We showed that social distancing was the best single strategy, while the best dual measure was social distancing coupled with early screening. However, the effectiveness of the triple strategy was marginally (1–3%) better than that of the dual measure. Our study provides a mechanistic framework to facilitate understanding of TB transmission dynamics between locals and migrant workers and to recommend better prevention strategies in anticipation of achieving WHO’s milestones by the next decade. Our work has implications for migrant worker-associated TB infection prevention on a global scale and provides a knowledge base for exploring how outcomes can be best implemented by alternative control measure approaches.
Effects of Continuous Positive Airway Pressure Therapy on Nocturnal Blood Pressure Fluctuation Patterns in Patients with Obstructive Sleep Apnea
Authors: Kumagai Hajime , Sawatari Hiroyuki , Hoshino Tetsuro , Konishi Noriyuki , Kiyohara Yuka , Kawaguchi Kengo , Murase Yoko , Urabe Ayako , Arita Aki , Shiomi Toshiaki
Published: August 2022

This retrospective study was designed to evaluate the effects of continuous positive airway pressure (CPAP) therapy, a well-established treatment for obstructive sleep apnea (OSA), on nocturnal blood pressure fluctuations (NBPFs) during rapid eye movement (REM) and non-REM sleep, and to evaluate the NBPF patterns in patients with OSA. We included 34 patients with moderate-to-severe OSA who underwent polysomnography using pulse transit time before and at 3–6 months after CPAP therapy. Nocturnal BP and NBPF frequency in REM and non-REM sleep were investigated, as well as NBPF pattern changes after receiving CPAP therapy. CPAP therapy resulted in significant reductions in the apnea–hypopnea index (AHI), arousal index, nocturnal systolic and diastolic BP, and NBPF frequency in REM and non-REM sleep (all p < 0.01). A higher AHI before CPAP resulted in lower nocturnal systolic BP (r = 0.40, p = 0.019) and NBPFs (r = 0.51, p = 0.002) after CPAP. However, 58.8% of patients showed no change in NBPF patterns with CPAP therapy. CPAP therapy significantly improved almost all sleep-related parameters, nocturnal BP, and NBPF frequency in REM and non-REM sleep periods, but NBPF patterns showed various changes post-CPAP therapy. These results suggest that factors other than OSA influence changes in NBPF patterns.
Does Body Position Influence Bioelectrical Impedance? An Observational Pilot Study
Authors: Więch Paweł , Wołoszyn Filip , Trojnar Patrycja , Skórka Mateusz , Bazaliński Dariusz
Published: August 2022

As the availability of various bioelectric impedance analysis (BIA) tools is increasing, the patient’s position during the test may be of significant importance for the comparability of the results. An observational pilot study was undertaken between March and May 2021 at the Center for Innovative Research in Medical and Natural Sciences at the University of Rzeszow, Rzeszów, Poland. All participants (n = 49: M: 21.05 y ± 1.12 vs. F: 21.34 y ± 2.06) were subjected to measurements of selected nutritional status indicators and body components in three positions: lying, sitting and standing. The body composition indicators were obtained using a bioelectrical impedance device, AKERN BIA 101 Anniversary Sport Edition Analyzer (Akern SRL, Pontassieve, Florence, Italy). The results were analyzed using dedicated software (BodygramPlus 1.2.2.12 from AKERN 2016, Florence, Italy). Our observations indicate that there is a significant difference between lying and standing as well as sitting and standing with respect to anthropometric and nutritional indicators (resistance, reactance, phase angle, standardized phase angle, body cell mass index and fat-free mass index) and body composition components, with particular reference to intracellular and extracellular water. The described differences are significant for both sexes. This study showed that this significantly influenced the scores of components directly related to resistance, reactance and hydrated cell mass, while not affecting the percentages or absolute values of fat and fat-free mass.
Evolution Characteristics and Formation Mechanism of Production-Living-Ecological Space in China: Perspective of Main Function Zones
Authors: Xu Ning , Chen Wanxu , Pan Sipei , Liang Jiale , Bian Jiaojiao
Published: August 2022

The main function zone (MFZ) is the major strategy of China’s economic development and ecological environment protection. Clarifying the logical relationship between “MFZ strategy” and “territorial spatial layout” is vital to construct regional economic layout and territorial spatial supporting system of high-quality development. However, few studies have revealed the evolution process and formation mechanism of the production-living-ecological space (PLES) structure of China’s MFZ over a long period of time. To bridge the gap, based on the land use dataset in China from 1980 to 2020, this study analyzed the evolution patterns of PLES in China’s MFZs using multiple methods and measured the formation mechanism of PLES in different types of MFZs with the GeoDetector model. Results showed that the spatial structure of China’s national territory has evolved drastically in the past 40 years, showing significant horizontal regional differentiation and vertical gradient differentiation. Ecological space has been continuously decreasing, while production space and living space have been continuously increasing, and the evolution of PLES varied significantly in different MFZs. During the study period, the gravity center of PLES in China all moved westward. The spatial distribution pattern of production space and living space was from northeast to southwest, and the ecological space was from east to west. The evolution of China’s territorial spatial structure was subject to the combined effects of natural and socio-economic factors, exhibiting significant differences in different MFZs. Land use intensity had the most prominent influence on the formation of PLES, followed by elevation. The influences of different factors on PLES structure were strengthened mainly through two types of nonlinear enhancement and dual-factor enhancement. This study can provide scientific support for the optimal management and high-quality development of territorial space in China.