bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanical Assembly Monitoring Method Based on Semi-Supervised Semantic Segmentation
Authors: Wu Suichao , Chen Chengjun , Wang Jinlei
Published: January 2023

Semantic segmentation of assembly images is to recognize the assembled parts and find wrong assembly operations. However, the training of supervised semantic segmentation requires a large amount of labeled data, which is time-consuming and laborious. Moreover, the sizes of mechanical assemblies are not uniform, leading to low segmentation accuracy of small-target objects. This study proposes an adversarial learning network for semi-supervised semantic segmentation of mechanical assembly images (AdvSemiSeg-MA). A fusion method of ASFF multiscale output is proposed, which combines the outputs of different dimensions of ASFF into one output. This fusion method can make full use of the high-level semantic features and low-level fine-grained features, which helps to improve the segmentation accuracy of the model for small targets. Meanwhile, the multibranch structure RFASPP module is proposed, which enlarges the receptive field and ensures the target object is close to the center of the receptive field. The CoordConv module is introduced to allow the convolution to perceive spatial position information, thus enabling the semantic segmentation network to be position-sensitive. In the discriminator network, spectral normalization is introduced. The proposed method obtains state-of-art results on the synthesized assembly depth image dataset and performs well on actual assembly RGB image datasets.
Nisin E, a New Nisin Variant Produced by Streptococcus equinus MDC1
Authors: Christophers Meg , Heng Lauren , Heng Nicholas
Published: January 2023

Members of the genus Streptococcus inhabit a variety of sites in humans and other animals and some species are prolific producers of proteinaceous antibiotics (bacteriocins). As little is known about (i) streptococci inhabiting domestic pets, and (ii) whether novel bacteriocin-producing streptococci can be isolated from domestic pets, the aim of this study is to address these gaps in the research literature. In this study, Streptococcus equinus MDC1, isolated from a healthy dog, was found to exhibit potent antibacterial activity against Micrococcus luteus in a simultaneous antagonism assay, suggesting that strain MDC1 produces a lantibiotic bacteriocin. The inhibitory activity spectrum of S. equinus MDC1, determined using agar-based deferred antagonism assays against >70 indicator strains, was found to be similar to that of nisin U (a lantibiotic produced by Streptococcus uberis). However, the spectra of the two bacteriocins differed by 23 strains, mainly with the MDC1 bacteriocin having no inhibitory activity towards certain streptococci of human origin (e.g., Streptococcus gordonii, Streptococcus anginosus, Streptococcus salivarius). The genome of S. equinus MDC1, which was sequenced completely using single-molecule real-time (SMRT) next-generation DNA sequencing technology, comprises a single 1,936,555-basepair chromosome containing seven copies of the ribosomal RNA operon, 69 tRNA genes and nearly 1900 putative coding sequences. Analysis of the MDC1 genome sequence using the bacteriocin detection algorithms BAGEL4 and antiSMASH revealed the location of a 13,164-basepair 11-gene locus, designated nmd, which encoded a mature nisin E peptide that differed from nisin U by only two amino acids (Ile15→Ala and Leu21→Ile) and an extra C-terminal asparagine residue, and the proteins required for post-translational modification of the bacteriocin, processing, export, and producer immunity. Despite the high homology (90.6% identity, 93.8% similarity) between nisin E and nisin U, there was considerably less homology (47.4–76.3% identity, 68.4–88.8% similarity) between the other proteins encoded by their respective biosynthetic loci. This new natural variant of nisin, called nisin E, represents the first nisin variant to be reported for S. equinus; additionally, its differences with nisin U may provide some insight into the amino acids that influence bacteriocin potency and killing spectrum.
A Neural Network-Based Partial Fingerprint Image Identification Method for Crime Scenes
Authors: Sun Yuting , Tang Yanfeng , Chen Xiaojuan
Published: January 2023

Fingerprints are the most widely used of all biological characteristics in public safety and forensic identification. However, fingerprint images extracted from the crime scene are incomplete. On the one hand, due to the lack of effective area in partial fingerprint images, the extracted features are insufficient. On the other hand, a broken ridge may lead to a large number of false feature points, which affect the accuracy of fingerprint recognition. Existing fingerprint identification methods are not ideal for partial fingerprint identification. To overcome these problems, this paper proposes an attention-based partial fingerprint identification model named APFI. Firstly, the algorithm utilizes the residual network (ResNet) for feature descriptor extraction, which generates a representation of spatial information on fingerprint expression. Secondly, the channel attention module is inserted into the proposed model to obtain more accurate fingerprint feature information from the residual block. Then, to improve the identification accuracy of partial fingerprints, the angular distance between features is used to calculate the similarity of fingerprints. Finally, the proposed model is trained and validated on a home-made partial fingerprint image dataset. Experiments on the home-made fingerprint datasets and the NIST-SD4 datasets show that the partial fingerprint identification method proposed in this paper has higher identification accuracy than other state-of-the-art methods.
Influence of Normal Stiffness and Shear Rate on the Shear Behaviors and Acoustic Emissions Characteristics of Artificial Rock Joints
Authors: Jiang Yujing , Li Xinpeng , Wang Changsheng , Luan Hengjie , Zhang Sunhao , Wang Gang , Wang Pu
Published: January 2023

Understanding the asperity damage behaviors of joints during shearing is critical for evaluating the stability of deep underground engineering structures. In this paper, we prepared plaster joints and used them for direct shear tests under different normal stiffness (0–7 MPa/mm) and various shear rate (0.5–20 mm/min) conditions. The effects of normal stiffness and shear rate on mechanical behavior and AE characteristics were studied. With the increase of normal stiffness, the damaged area of the surface of the joint and the weight of the damaged, rough body basically show a linear increase. With the increase of the shear rate, the peak shear stress and the final shear stress of the joint are non-linearly decreased (the decrease rate at the shear rate of 0.5–5 mm/min is much larger than that at the shear rate of 5–20 mm/min), more local cracks appear on the surface of the joint, and the dilatancy of the joint slightly decreases. More than 60% of the acoustic emission signals in the shearing process of the joint are concentrated in the post-peak phase. With the increase of normal stiffness, the cumulative number of acoustic emission impacts and cumulative energy both increase. With the increase in shear rate, the accumulated acoustic emission impact number decreases, and the accumulated AE energy tends to increase when the shear rate is 0.5–5 mm/min and decreases when the shear rate increases to 5–20 mm/min.
Patient’s Perception and Real Execution of Walking as Physical Exercise: Looking at Self-Efficacy as a Key Variable in Adherence in Patients with Fibromyalgia
Authors: Gutiérrez Lorena , Lavín-Pérez Ana Myriam , Catalá Patricia , Écija Carmen , Collado-Mateo Daniel , Gil-Arias Alexander , Peñacoba Cecilia
Published: January 2023

Adherence to physical exercise is especially low in patients with fibromyalgia, and there is a tendency to overestimate its performance. This study explores the relationship between perceived and actual walking behavior in patients with fibromyalgia, including self-efficacy as a mediating variable. A prospective study with two time points (with one week between them) was carried out on 132 women diagnosed with fibromyalgia. Self-efficacy towards exercise was assessed at the first time point, and perceived intensity of physical activity and “objective” walking amount (accelerometer) in relation to the previous week were assessed at the second point. Physical and emotional symptoms and the consumption of drugs were also evaluated as covariates. The results show that perception of vigorous-intensity exercise was related to walking (accelerometer) (effort greater than 6 METs). This relationship was explained by the mediating effect of self-efficacy and was not interfered with either by the symptoms or by the consumption of drugs. High self-efficacy regarding physical exercise was directly related to walking behavior despite patients’ interpretation of this activity as a vigorous physical exercise. In intervention and rehabilitation programs, it would be interesting to take into account and promote the self-efficacy of patients in relation to physical exercise in order to maintain adherence to walking.
An Inversion Algorithm for the Dynamic Modulus of Concrete Pavement Structures Based on a Convolutional Neural Network
Authors: Chen Gongfa , Chen Xuedi , Yang Linqing , Han Zejun , Bassir David
Published: January 2023

Based on the spectral element method (SEM) and a convolutional neural network (CNN), an inversion algorithm for the dynamic modulus of concrete pavement structures is proposed in this paper. In order to evaluate the service performance of pavement structures more systematically and accurately via the existing testing techniques using a falling weight deflectometer (FWD), it is necessary to obtain accurate dynamic modulus parameters of the structures. In this work, an inversion algorithm for predicting the dynamic modulus is established by using a CNN which is trained with the dynamic response samples of a multi-layered concrete pavement structure obtained through SEM. The gradient descent method is used to adjust the weight parameters in the network layer by layer in reverse. As a result, the accuracy of the CNN can be improved via iterative training. With the proposed algorithm, more accurate results of the dynamic modulus of pavement structures are obtained. The accuracy and numerical stability of the proposed algorithm are verified by several numerical examples. The dynamic modulus and thickness of concrete pavement structure layers can be accurately predicted by the CNN trained with a certain number of training samples based on the displacement curve of the deflection basin from the falling weight deflectometer. The proposed method can provide a reliable testing tool for the FWD technique of pavement structures.
Effect of Infection Hubs in District-Based Network Epidemic Spread Model
Authors: Khorev Vladimir , Kazantsev Viktor , Hramov Alexander
Published: January 2023

A network model of epidemic spread accounting for inhomogeneous population district division is investigated. Motivated by the COVID-19 pandemic, we analyze the effects of infection development in the area, for example, of a city divided into several population districts. The districts are characterized by a certain intensity of contact inside and with inter-district communication that can be generally controlled by the authorities. Specifically, we consider the effect of the central district, which is the hub of infection. We investigate how the interaction strength influences the city’s level of epidemic development. We obtained that the final infected amount in the district rises with an increasing degree of connection with the hub. However, the model situation was not limited by the first outbreak but included the subsequent waves of infection. We obtained that the appearance and disappearance of subsequent waves of infection essentially depended on the intensity of communication with the infected hub. Our results suggest the mechanism where stricter communication policy can negatively affect the subsequent infection waves.
Design Patterns for Mobile Games Based on Structural Similarity
Authors: Rasool Ghulam , Hussain Yasir , Umer Tariq , Rasheed Jawad , Yeo Sook Fern , Sahin Fatih
Published: January 2023

Software design patterns have a proven impact on the quality of software applications and the development process of an application. The success of design patterns in the software industry has attracted mobile game developers and researchers to apply patterns in the context of mobile games. Researchers have already proposed different frameworks and design patterns, but they are not truly beneficial for game developers. The high-level taxonomies can be adjuvant while proposing useful design patterns. The existing taxonomies for mobile games do not consider different parts of a game that outline top-level structure. In this paper, we propose a new taxonomy that emphasizes the top-level structure for identifying new design patterns for mobile games. We propose five novel generic design patterns that might be applied to the development of mobile games and other software applications. The presented design patterns are, in a true sense, programming patterns that outline top-level generic classes and interfaces, and that could be the basis for the development of new games. We developed four demo games by using these patterns for the realization of taxonomy and design patterns.
Sustainable Microalgal Harvesting Process Applying Opuntia cochenillifera: Process Parameters Optimization
Authors: Rodrigues Jacqueline R. da S. , Santos Ramon da S. , Matos Rayssa A. , Pires José C. M. , Salgado Eva M.
Published: January 2023

Microalgae harvesting by coagulation can use coagulant agents such as alum, synthetic polymers or biocoagulants. Biocoagulants have attracted the attention of researchers because they are natural, biodegradable, and promote high microalgal harvesting efficiencies. This study aims to optimize the harvesting of Chlorella vulgaris based on the dosage of the Opuntia cochenillifera extract and the choice of eluent for biopolymer extraction. The outdoor cultivation of C. vulgaris achieved a specific growth rate of 0.455 d−1 and a maximum biomass concentration of 1.28 gDW L−1. In order to harvest the microalgal biomass, the polymer present in the mucilage of O. cochenillifera was extracted using NaOH and HCl. Coagulation and sedimentation assays were performed with different coagulant dosages: 3.5, 5.9, and 8.2 g L−1. The maximum harvesting efficiencies using the acid and alkaline extract coagulant solutions were 80.8% and 99.5%, respectively, with a dosage of 3.5 g L−1. According to the results, the C. vulgaris biomass can be harvested with the mucilage from O. cochenillifera in acid and alkaline eluents. The application of this biocoagulant constitutes a sustainable solution for microalgal harvesting.
Acknowledgment to the Reviewers of AppliedChem in 2022
Authors:   AppliedChem Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Electric Field Analysis on the Corona Discharge Phenomenon According to the Variable Air Space between the Ionizer and Ground Current Collector
Authors: Jang Kyung-Hoon , Seo Sang-Won , Kim Dong-Jin
Published: January 2023

In this paper, we present the optimized air space of the lightning protection rod (SK-AOR380) with the function of a charge transfer system (CTS). For evaluation of CTS in the laboratory setting, some studies have focused on the modification of the structure and shape of the CTS; the air space is designed (>2 mm) as an empirical design without quantitative data. However, in this paper, we have focused on the air space between the ionizer conductor and current collector to control the inception and occurrence position of corona discharge in air insulation. This is because the performance, such as the initial corona discharge inception of CTS, is determined by the air space. The simulation analysis was performed in a narrow, micro-sized air space as a first step, where the air space was reduced to the extent possible for simulation. To evaluate the performance of SK-AOR380 according to the narrow air space, we considered the numerical analysis method. The fundamental equations consist of Poisson’s equation and the charge continuity equation. Poisson’s equation for electric fields is a fully coupled numerical model based on the charge continuity equations for a positively charged ion, negatively charged ion, and free electron. Fowler–Nordheim electron emission was employed for the boundary condition at the surface of the ionizer conductor. To simulate the corona discharge behavior under standard lightning impulse voltage, we used a source of lightning voltage with 1.2/50 μs based on a double exponential equation; the corona discharge behaviors (electric field distribution, free electron density, positive and negative ion density) were investigated dependent on each time step (0.5, 1 and 1.2 μs) until 3.5 μs. The results revealed that the characteristics graph of free electron density, positive and negative ion density showed similar trends, with lightning impulse voltage increasing with increasing time steps until 1.2 μs and each density resulted in a decreasing trend from 1.2 μs to 3.5 μs. The SK-AOR380 is improved with a decreasing air space in terms of electric field distribution, electron, and ion density. In other words, the 0.0005 mm air space created a non-uniform electric field distribution with a large field enhancement, causing ionization to initiate corona discharge. In addition, in the case of a 0.0005 mm air space, the electric field and electron density are increased by 1.3 and 1.9 times, respectively, than that of 0.001 mm. However, there was no longer a significant difference under 0.0005 mm in the simulation results. To improve the CTS, we suggest the air space between the ionizer conductor and current collector should be less than 2 mm than that of conventional CTS from our research work.
Acknowledgment to the Reviewers of Astronomy in 2022
Authors:   Astronomy Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
X-ray Spectroscopy Based on Micro-Calorimeters at Internal Targets of Storage Rings
Authors: Herdrich Marc Oliver , Hengstler Daniel , Fleischmann Andreas , Enss Christian , Gumberidze Alexandre , Hillenbrand Pierre-Michel , Indelicato Paul , Fritzsche Stephan , Stöhlker Thomas
Published: January 2023

With metallic-magnetic calorimeters (MMCs), promising detectors for high-precision X-ray spectrometry in atomic and fundamental physics experiments are available. In this work, we present a pilot experiment based on a maXs-30 type MMC-spectrometer for recording X-rays emitted in collisions of lithium-like uranium ions with a molecular nitrogen gas jet in the internal target of the ESR storage ring of the GSI. Sample spectra have been measured, and a multitude of X-ray transitions have been unambiguously identified. As a first test and for comparison with data recorded at an EBIT, the 2s Lamb shift in lithium-like uranium was estimated.
Facial Palsy Secondary to Cholesteatoma: A Case-Series of 14 Patients
Authors: Psillas George , Constantinidis Jiannis
Published: January 2023

Background: To evaluate patients with middle ear cholesteatoma presenting with facial palsy (FP). Material-Methods: A total of 14 subjects (10 males and 4 females), with a mean age of 42.5 years, were included in our study. The majority of patients presented with incomplete FP (House–Brackmann HB II-IV, 11 cases) and the remaining 3 patients had complete facial paralysis (HB V-VI). A canal wall down mastoidectomy was performed in all the patients, followed by partial facial nerve decompression. Results: At the one-year follow-up, eleven (78.5%) patients demonstrated satisfactory recovery to HB I-II. Facial function recovered to HB grade I-II in 9 (100%) patients who were surgically treated within one month, and in 2 (40%) patients who underwent surgery after one month. The tympanic segment of facial nerve was the most common site of involvement (8 patients). The multiple regression analysis showed that a higher preoperative HB grade combined with a gradual than sudden onset of FP more likely resulted in worse postoperative HB grade. Conclusion: Early surgical removal of cholesteatoma associated with FP is more likely to result in good facial nerve recovery (78.5% of cases), when it is performed within one month from the onset of FP. According to the literature, the tympanic segment of the facial nerve was more frequently damaged (77.7%), followed by the mastoid segment (22.9%), labyrinthine segment (11.1%), and geniculate ganglion (11.1%). Labyrinthine fistula, mainly of the lateral semicircular canal, can be expected in cases of facial nerve dehiscence. The canal wall down mastoidectomy combined with partial decompression surgery was the most preferred surgical treatment for the FP secondary to cholesteatoma.
Centrally Extended Jordan (∗)-Derivations Centralizing Symmetric or Skew Elements
Authors: Alali Amal S. , Alnoghashi Hafedh M. , Rehman Nadeem ur
Published: January 2023

Let A be a non-commutative prime ring with involution ∗, of characteristic ≠2(and3), with Z as the center of A and Π a mapping Π:A→A such that [Π(x),x]∈Z for all (skew) symmetric elements x∈A. If Π is a non-zero CE-Jordan derivation of A, then A satisfies s4, the standard polynomial of degree 4. If Π is a non-zero CE-Jordan ∗-derivation of A, then A satisfies s4 or Π(y)=λ(y−y*) for all y∈A, and some λ∈C, the extended centroid of A. Furthermore, we give an example to demonstrate the importance of the restrictions put on the assumptions of our results.
On Perfectness of Systems of Weights Satisfying Pearson’s Equation with Nonstandard Parameters
Authors: Aptekarev Alexander , Dyachenko Alexander , Lysov Vladimir
Published: January 2023

Measures generating classical orthogonal polynomials are determined by Pearson’s equation, whose parameters usually provide the positivity of the measures. The case of general complex parameters (nonstandard) is also of interest; the non-Hermitian orthogonality with respect to (now complex-valued) measures is considered on curves in C. Some applications lead to multiple orthogonality with respect to a number of such measures. For a system of r orthogonality measures, the perfectness is an important property: in particular, it implies the uniqueness for the whole family of corresponding multiple orthogonal polynomials and the (r+2)-term recurrence relations. In this paper, we introduce a unified approach which allows to prove the perfectness of the systems of complex measures satisfying Pearson’s equation with nonstandard parameters. We also study the polynomials satisfying multiple orthogonality relations with respect to a system of discrete measures. The well-studied families of multiple Charlier, Krawtchouk, Meixner and Hahn polynomials correspond to the systems of measures defined by the difference Pearson’s equation with standard real parameters. Using the same approach, we verify the perfectness of such systems for general parameters. For some values of the parameters, discrete measures should be replaced with the continuous measures with non-real supports.
Bypassing the Kochen–Specker Theorem: An Explicit Non-Contextual Statistical Model for the Qutrit
Authors: Oaknin David H.
Published: January 2023

We describe an explicitly non-contextual statistical model of hidden variables for the qutrit, which fully reproduces the predictions of quantum mechanics, and thus, bypasses the constraints imposed by the Kochen–Specker theorem and its subsequent reformulations. We notice that these renowned theorems crucially rely on the implicitly assumed existence of an absolute frame of reference with respect to which physically indistinguishable tests related by spurious gauge transformations can supposedly be assigned well-defined distinct identities. We observe that the existence of such an absolute frame of reference is not required by fundamental physical principles, and hence, assuming it is an unnecessarily restrictive demand.
A Multi-Stage Early Stress Detection Model with Time Delay Subject to a Person’s Stress
Authors: Pham Hoang
Published: January 2023

Stress is the body’s response to something that requires action or attention. In general, anything that poses a real challenge or threat to a person’s well-being can cause stress. Stress can slow down a person’s well-being activities. Often, you might not know whether you are stressed, if you are under too much stress, or when it is time to seek help. This paper presents a mathematical model with time delay subject to a person’s stress for early stress detection to assess whether a person is stress-free, has stress but is undetected, or has stress in any specific state such as minor, moderate, or severe stress. Being more alert to the effects of stress and reducing the uncertainty of undetected stress, or better, preventing it, may help people, especially teens, manage it more effectively and cope better, even a person happens to be stressed. The model can be extended to study the effects of multiple stress factors in light of the prolonged COVID-19 pandemic on people’s mental stress.
Acknowledgment to the Reviewers of Batteries in 2022
Authors:   Batteries Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Aqueous Zinc–Chalcogen Batteries: Emerging Conversion-Type Energy Storage Systems
Authors: Zhang Long , Liu Yongchang
Published: January 2023

Aqueous zinc (Zn) metal batteries are considered competitive candidates for next-generation energy storage, attributed to the abundance, low redox potential, and high theoretical capacity of Zn. However, conventional cathode materials are mainly based on ion-insertion electrochemistry, which can only deliver limited capacity. The conversion-type aqueous zinc–chalcogen batteries (AZCBs) have received widespread attention because they combine the advantages of chalcogen cathodes (S, Se, and Te) and Zn anodes to significantly enhance their capacity. Research on AZCBs has increased continuously; however, it is still in its infancy because the selection and regulation of cathode material systems are not comprehensive and systematic, and the investigation of the mechanisms is not thorough. Herein, we present a detailed overview explaining the recent progress of AZCBs, providing comprehensive guidelines for further research. First, research based on S cathodes, which is the most studied system among AZCBs, is summarized. Second, research based on Se and Te cathodes is described. Research on these different systems is mainly focused on electrolyte modification and cathode optimization. In each section, various strategies are introduced, and the working mechanisms are also discussed. Finally, the challenges and prospects for the development of AZCBs are presented.
Fast Identification of Micro-Health Parameters for Retired Batteries Based on a Simplified P2D Model by Using Padé Approximation
Authors: Xu Jianing , Sun Chuanyu , Ni Yulong , Lyu Chao , Wu Chao , Zhang He , Yang Qingjun , Feng Fei
Published: January 2023

Better performance consistency of regrouped batteries retired from electric vehicles can guarantee the residual value maximized, which greatly improves the second-use application economy of retired batteries. This paper develops a fast identification approach for micro-health parameters characterizing negative electrode material and electrolyte in LiFePO4 batteries on the basis of a simplified pseudo two-dimensional model by using Padé approximation is developed. First, as the basis for accurately identifying micro-health parameters, the liquid-phase and solid-phase diffusion processes of pseudo two-dimensional model are simplified based on Padé approximation, especially according to enhanced boundary conditions of liquid-phase diffusion. Second, the reduced pseudo two-dimensional model with the lumped parameter is proposed, the target parameters characterizing negative electrode material (εn, Ds,n) and electrolyte (De, Ce) are grouped with other unknown but fixed parameters, which ensures that no matter whether the target parameters can be achieved, the corresponding varying traces is able to be effectively and independently monitored by lumped parameters. Third, the fast identification method for target micro-health parameters is developed based on the sensitivity of target parameters to constant-current charging voltage, which shortens the parameter identification time in comparison to that obtained by other approaches. Finally, the identification accuracy of the lumped micro-health parameters is verified under 1 C constant-current charging condition.
Acknowledgment to the Reviewers of Beverages in 2022
Authors:   Beverages Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
The Role of Emergent Processing Technologies in Beer Production
Authors: Carvalho Gonçalo , Leite Ana Catarina , Leal Rita , Pereira Ricardo
Published: January 2023

The brewing industry is regarded as a fiercely competitive and insatiable sector of activity, driven by the significant technological improvements observed in recent years and the most recent consumer trends pointing to a sharp demand for sensory enhanced beers. Some emergent and sustainable technologies regarding food processing such as pulsed electric fields (PEF), ultrasound (US), thermosonication (TS), high-pressure processing (HPP), and ohmic heating (OH) have shown the potential to contribute to the development of currently employed brewing methodologies by both enhancing the quality of beer and contributing to processing efficiency with a promise of being more environmentally friendly. Some of these technologies have not yet found their way into the industrial brewing process but already show potential to be embedded in continuous thermal and non-thermal unit operations such as pasteurization, boiling and sterilization, resulting in beer with improved organoleptic properties. This review article aims to explore the potential of different advanced processing technologies for industrial application in several key stages of brewing, with particular emphasis on continuous beer production.
State of the Art and Future of Stem Cell Therapy in Ischemic Stroke: Why Don’t We Focus on Their Administration?
Authors: Valeri Andrea , Mazzon Emanuela
Published: January 2023

Stroke is one of the leading causes of death and disability worldwide, so there is an urgent need to find a therapy for the tragic outcomes of this cerebrovascular disease. Stem cells appeared to be a good solution for many conditions, so different experiments were made to establish stem cells as a feasible therapy for stroke. The aim of this review is to analyze the state of the art of stem cell therapy for stroke and if the route of administration could represent a valid adjusting point for ameliorating the therapy’s outcome. To obtain this, we searched the scientific literature of the last 10 years for relevant in vitro and in vivo evidence regarding stem cells’ potential in stroke therapy. In vitro evidence points to hypoxia, among the preconditioning strategies, as the most used and probably efficient method to enhance cells qualities, while in vivo results raise the question if it is the type of cells or how they are administrated which can make the difference in terms of efficiency. Unfortunately, despite the number of clinical trials, only a few were successfully concluded, demonstrating how urgent the necessity is to translate pre-clinical results into clinics. Since any type of stem cell seems suitable for therapy, the chosen route of administration corresponds to different engraftment rates, distribution and efficiency in terms of the beneficial effects of stem cells. Intravenous administration was widely used for delivering stem cells into the human body, but recently intranasal administration has given promising results in vivo. It allows stem cells to efficiently reach the brain that was precluded to intravenous administration, so it is worth further investigation.
Phylogeny and Morphology of Novel Species and New Collections Related to Sarcoscyphaceae (Pezizales, Ascomycota) from Southwestern China and Thailand
Authors: Zeng Ming , Gentekaki Eleni , Hyde Kevin D. , Zhao Qi , Matočec Neven , Kušan Ivana
Published: January 2023

Sarcoscyphaceae (Pezizales) is distinguished by small to large, vividly-coloured sessile to stipitate apothecia, plurinucleate and pigmented paraphyses, operculate asci with thick walls, and plurinucleate, uniguttulate to multiguttulate ascospores with smooth walls or ornamentations. We collected more than 40 Sarcoscyphaceae specimens from dead twigs or wood. Based on morphology and phylogeny, these species belong to Cookeina, Nanoscypha, Phillipsia, Pithya, and Sarcoscypha. Among these, we introduce three new species–Nanoscypha aequispora, Pithya villosa, and Sarcoscypha longitudinalis. Phylogenetic analyses based on ITS, LSU, SSU, rpb2, and tef-1α gene regions indicate the relationships of these species within Sarcoscyphaceae. Meanwhile, we propose Ph. gelatinosa as a synonym of Ph. domingensis. One new record of C. sinensis is reported from Thailand.
Fecundity, Length at First Sexual Maturity and Gonadal Development of Lepidorhombus boscii in the Eastern Adriatic Sea
Authors: Ugrin Nika , Paladin Antonela , Krstulović Šifner Svjetlana
Published: January 2023

This study presents data on the seasonal changes in population structure, maturation, fecundity and reproduction of the Lepidorhombus boscii from the central-eastern Adriatic Sea. This species is a commercially valuable fish in the Adriatic Sea; still, knowledge about its reproductive biology is very scarce. The analyses are based on the data collected between July 2020 and June 2021 by bottom trawls. In total, 963 individuals were collected out of which 508 were females (47.24%) and 455 were males (52.75%). Throughout the year, oocytes in the previtellogenic and vitellogenic stages were present in the ovaries, and the development of the ovaries followed the values of the gonadosomatic index. L. boscii has asynchronous ovarian development and a prolonged spawning season in the Adriatic Sea with the main spawning season between November and March. The oocyte diameter ranged from 34.01 to 562.72 μm (178.49 ± 129.83 μm). This study presents the first information on the reproductive cycle of L. boscii in the eastern Adriatic Sea and contributes to the understanding of the biology of this species necessary for its sustainable management.
Accumulation of Fat Not Responsible for Femoral Head Necrosis, Revealed by Single-Cell RNA Sequencing: A Preliminary Study
Authors: Wang Yingjie , Li Dandan , Chen Haijia , Li Zhuolin , Feng Bin , Weng Xisheng
Published: January 2023

The etiology of osteonecrosis of the femoral head (ONFH) is not yet fully understood. However, ONFH is a common disease with high morbidity, and approximately one-third of cases are caused by glucocorticoids. We performed single-cell RNA sequencing of bone marrow to explore the effect of glucocorticoid on ONFH. Bone marrow samples of the proximal femur were extracted from four participants during total hip arthroplasty, including two participants diagnosed with ONFH for systemic lupus erythematosus (SLE) treated with glucocorticoids (the case group) and two participants with femoral neck fracture (the control group). Unbiased transcriptome-wide single-cell RNA sequencing analysis and computational analyses were performed. Seventeen molecularly defined cell types were identified in the studied samples, including significantly dysregulated neutrophils and B cells in the case group. Additionally, fatty acid synthesis and aerobic oxidation were repressed, while fatty acid beta-oxidation was enhanced. Our results also preliminarily clarified the roles of the inflammatory response, substance metabolism, vascular injury, angiogenesis, cell proliferation, apoptosis, and dysregulated coagulation and fibrinolysis in glucocorticoid-induced ONFH. Notably, we list the pathways that were markedly altered in glucocorticoid-induced ONFH with SLE compared with femoral head fracture, as well as their common genes, which are potential early therapeutic targets. Our results provide new insights into the mechanism of glucocorticoid-induced ONFH and present potential clues for effective and functional manipulation of human glucocorticoid-induced ONFH, which could improve patient outcomes.
Towards Decoding Hepatotoxicity of Approved Drugs through Navigation of Multiverse and Consensus Chemical Spaces
Authors: López-López Edgar , Medina-Franco José L.
Published: January 2023

Drug-induced liver injury (DILI) is the principal reason for failure in developing drug candidates. It is the most common reason to withdraw from the market after a drug has been approved for clinical use. In this context, data from animal models, liver function tests, and chemical properties could complement each other to understand DILI events better and prevent them. Since the chemical space concept improves decision-making drug design related to the prediction of structure–property relationships, side effects, and polypharmacology drug activity (uniquely mentioning the most recent advances), it is an attractive approach to combining different phenomena influencing DILI events (e.g., individual “chemical spaces”) and exploring all events simultaneously in an integrated analysis of the DILI-relevant chemical space. However, currently, no systematic methods allow the fusion of a collection of different chemical spaces to collect different types of data on a unique chemical space representation, namely “consensus chemical space.” This study is the first report that implements data fusion to consider different criteria simultaneously to facilitate the analysis of DILI-related events. In particular, the study highlights the importance of analyzing together in vitro and chemical data (e.g., topology, bond order, atom types, presence of rings, ring sizes, and aromaticity of compounds encoded on RDKit fingerprints). These properties could be aimed at improving the understanding of DILI events.
Modus operandi of ClC-K2 Cl− Channel in the Collecting Duct Intercalated Cells
Authors: Stavniichuk Anna , Pyrshev Kyrylo , Tomilin Viktor N. , Kordysh Mariya , Zaika Oleg , Pochynyuk Oleh
Published: January 2023

The renal collecting duct is known to play a critical role in many physiological processes, including systemic water–electrolyte homeostasis, acid–base balance, and the salt sensitivity of blood pressure. ClC-K2 (ClC-Kb in humans) is a Cl−-permeable channel expressed on the basolateral membrane of several segments of the renal tubule, including the collecting duct intercalated cells. ClC-Kb mutations are causative for Bartters’ syndrome type 3 manifested as hypotension, urinary salt wasting, and metabolic alkalosis. However, little is known about the significance of the channel in the collecting duct with respect to the normal physiology and pathology of Bartters’ syndrome. In this review, we summarize the available experimental evidence about the signaling determinants of ClC-K2 function and the regulation by systemic and local factors as well as critically discuss the recent advances in understanding the collecting-duct-specific roles of ClC-K2 in adaptations to changes in dietary Cl− intake and maintaining systemic acid–base homeostasis.
Is Glial Dysfunction the Key Pathogenesis of LRRK2-Linked Parkinson’s Disease?
Authors: Iseki Tatou , Imai Yuzuru , Hattori Nobutaka
Published: January 2023

Leucine rich-repeat kinase 2 (LRRK2) is the most well-known etiologic gene for familial Parkinson’s disease (PD). Its gene product is a large kinase with multiple functional domains that phosphorylates a subset of Rab small GTPases. However, studies of autopsy cases with LRRK2 mutations indicate a varied pathology, and the molecular functions of LRRK2 and its relationship to PD pathogenesis are largely unknown. Recently, non-autonomous neurodegeneration associated with glial cell dysfunction has attracted attention as a possible mechanism of dopaminergic neurodegeneration. Molecular studies of LRRK2 in astrocytes and microglia have also suggested that LRRK2 is involved in the regulation of lysosomal and other organelle dynamics and inflammation. In this review, we describe the proposed functions of LRRK2 in glial cells and discuss its involvement in the pathomechanisms of PD.
Type 2 Diabetes and Alzheimer’s Disease: The Emerging Role of Cellular Lipotoxicity
Authors: Marrano Nicola , Biondi Giuseppina , Borrelli Anna , Rella Martina , Zambetta Tommaso , Di Gioia Ludovico , Caporusso Mariangela , Logroscino Giancarlo , Perrini Sebastio , Giorgino Francesco , Natalicchio Annalisa
Published: January 2023

Type 2 diabetes (T2D) and Alzheimer’s diseases (AD) represent major health issues that have reached alarming levels in the last decades. Although growing evidence demonstrates that AD is a significant comorbidity of T2D, and there is a ~1.4–2-fold increase in the risk of developing AD among T2D patients, the involvement of possible common triggers in the pathogenesis of these two diseases remains largely unknown. Of note, recent mechanistic insights suggest that lipotoxicity could represent the missing ring in the pathogenetic mechanisms linking T2D to AD. Indeed, obesity, which represents the main cause of lipotoxicity, has been recognized as a major risk factor for both pathological conditions. Lipotoxicity can lead to inflammation, insulin resistance, oxidative stress, ceramide and amyloid accumulation, endoplasmic reticulum stress, ferroptosis, and autophagy, which are shared biological events in the pathogenesis of T2D and AD. In the current review, we try to provide a critical and comprehensive view of the common molecular pathways activated by lipotoxicity in T2D and AD, attempting to summarize how these mechanisms can drive future research and open the way to new therapeutic perspectives.
Single-Cell Profiling Comparisons of Tumor Microenvironment between Primary Advanced Lung Adenocarcinomas and Brain Metastases and Machine Learning Algorithms in Predicting Immunotherapeutic Responses
Authors: Wu Yijun , Kang Kai , Han Chang , Wang Li , Wang Zhile , Zhao Ailin
Published: January 2023

Brain metastasis (BM) occurs commonly in patients with lung adenocarcinomas. Limited evidence indicates safety and efficacy of immunotherapy for this metastatic tumor, though immune checkpoint blockade has become the front-line treatment for primary advanced non-small cell lung cancer. We aim to comprehensively compare tumor microenvironments (TME) between primary tumors (PT) and BM at single-cell resolution. Single-cell RNA transcriptomics from tumor samples of PT (N = 23) and BM (N = 16) and bulk sequencing data were analyzed to explore potential differences in immunotherapeutic efficacy between PT and BM of lung adenocarcinomas. Multiple machine learning algorithms were used to develop and validate models that predict responses to immunotherapy using the external cohorts. We found obviously less infiltration of immune cells in BM than PT, characterized specifically by deletion of anti-cancer CD8+ Trm cells and more dysfunctional CD8+ Tem cells in BM tumors. Meanwhile, macrophages and dendritic cells within BM demonstrated more pro-tumoral and anti-inflammatory effects, represented by distinct distribution and function of SPP1+ and C1Qs+ tumor-associated microphages, and inhibited antigen presentation capacity and HLA-I gene expression, respectively. Besides, we also found the lack of inflammatory-like CAFs and enrichment of pericytes within BM tumors, which may be critical factors in shaping inhibitory TME. Cell communication analysis further revealed mechanisms of the immunosuppressive effects associated with the activation of some unfavorable pathways, such as TGFβ signaling, highlighting the important roles of stromal cells in the anti-inflammatory microenvironment, especially specific pericytes. Furthermore, pericyte-related genes were identified to optimally predict immunotherapeutic responses by machine learning models with great predictive performance. Overall, various factors contribute to the immunosuppressive TME within BM tumors, represented by the lack of critical anti-cancer immune cells. Meanwhile, pericytes may help shape the TME and targeting the associated mechanisms may enhance immunotherapy efficacy for BM tumors in patients with lung adenocarcinomas.
Acknowledgment to the Reviewers of Biomass in 2022
Authors:   Biomass Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Clinical and Personal Predictors of Helmet-CPAP Use and Failure in Patients Firstly Admitted to Regular Medical Wards with COVID-19-Related Acute Respiratory Distress Syndrome (hCPAP-f Study)
Authors: Cei Francesco , Chiarugi Ludia , Brancati Simona , Dolenti Silvia , Montini Maria Silvia , Rosselli Matteo , Filippelli Mario , Ciacci Chiara , Sellerio Irene , Gucci Marco Maria , Vannini Giulia , Lavecchia Rinaldo , Staglianò Loredana , Stefano Daniele di , Gurrera Tiziana , Romagnoli Mario , Francolini Valentina , Dainelli Francesca , Panigada Grazia , Landini Giancarlo , Mazzoccoli Gianluigi , Tarquini Roberto
Published: January 2023

Acute Respiratory Distress Syndrome (ARDS) caused by COVID-19 is substantially different from ARDS caused by other diseases and its treatment is dissimilar and challenging. As many studies showed conflicting results regarding the use of Non-invasive ventilation in COVID-19-associated ARDS, no unquestionable indications by operational guidelines were reported. The aim of this study was to estimate the use and success rate of Helmet (h) Continuous Positive Airway Pressure (CPAP) in COVID-19-associated ARDS in medical regular wards patients and describe the predictive risk factors for its use and failure. In our monocentric retrospective observational study, we included patients admitted for COVID-19 in medical regular wards. hCPAP was delivered when supplemental conventional or high-flow nasal oxygen failed to achieve respiratory targets. The primary outcomes were hCPAP use and failure rate (including the need to use Bilevel (BL) PAP or oro-tracheal intubation (OTI) and death during ventilation). The secondary outcome was the rate of in-hospital death and OTI. We computed a score derived from the factors independently associated with hCPAP failure. Out of 701 patients admitted with COVID-19 symptoms, 295 were diagnosed with ARDS caused by COVID-19 and treated with hCPAP. Factors associated with the need for hCPAP use were the PaO2/FiO2 ratio < 270, IL-6 serum levels over 46 pg/mL, AST > 33 U/L, and LDH > 570 U/L; age > 78 years and neuropsychiatric conditions were associated with lower use of hCPAP. Failure of hCPAP occurred in 125 patients and was associated with male sex, polypharmacotherapy (at least three medications), platelet count < 180 × 109/L, and PaO2/FiO2 ratio < 240. The computed hCPAP-f Score, ranging from 0 to 11.5 points, had an AUC of 0.74 in predicting hCPAP failure (significantly superior to Call Score), and 0.73 for the secondary outcome (non-inferior to IL-6 serum levels). In conclusion, hCPAP was widely used in patients with COVID-19 symptoms admitted to medical regular wards and developing ARDS, with a low OTI rate. A score computed combining male sex, multi-pharmacotherapy, low platelet count, and low PaO2/FiO2 was able to predict hCPAP failure in hospitalized patients with ARDS caused by COVID-19.