bluuebunny/crossref_metadata_2025 huggingface dataset:
Paleobiogeographical origins of Fasciola hepatica and F. gigantica in light of new DNA sequence characteristics of F. nyanzae from hippopotamus
Authors: Bargues María Dolores , Halajian Ali , Artigas Patricio , Luus-Powell Wilmien J. , Valero M. Adela , Mas-Coma Santiago
Published: September 2022

Fascioliasis is a highly pathogenic disease affecting humans and livestock worldwide. It is caused by the liver flukesFasciola hepaticatransmitted byGalba/Fossarialymnaeid snails in Europe, Asia, Africa, the Americas and Oceania, andF. giganticatransmitted byRadixlymnaeids in Africa and Asia. An evident founder effect appears in genetic studies as the consequence of their spread by human-guided movements of domestic ruminants, equines and Old World camelids in the post-domestication period from the beginning of the Neolithic. Establishing the geographical origins of fasciolid expansion is multidisciplinary crucial for disease assessment. Sequencing of selected nuclear ribosomal and mitochondrial DNA markers ofF. nyanzaeinfecting hippopotamuses (Hippopotamus amphibius) in South Africa and their comparative analyses withF. hepaticaandF. gigantica, and the twoFascioloidesspecies,Fs. jacksonifrom Asian elephants andFs. magnafrom Holarctic cervids, allow to draw a tuned-up evolutionary scenario during the pre-domestication period. Close sequence similarities indicate a direct derivation ofF. hepaticaandF. giganticafromF. nyanzaeby speciation after host capture phenomena. Phylogenetic reconstruction, genetic distances and divergence estimates fully fit fossil knowledge, past interconnecting bridges between continents, present fasciolid infection in the wild fauna, and lymnaeid distribution. The paleobiogeographical analyses suggest an origin forF. giganticaby transfer from primitive hippopotamuses to grazing bovid ancestors of Reduncinae, Bovinae and Alcelaphinae, by keeping the same vectorRadix natalensisin warm lowlands of southeastern Africa in the mid-Miocene, around 13.5 mya. The origin ofF. hepaticashould have occurred after capture from primitive, less amphibiousHexaprotodonhippopotamuses to mid-sized ovicaprines as the wild bezoarCapra aegagrusand the wild mouflonOvis gmelini, and fromR. natalensistoGalba truncatulain cooler areas and mountainous foothills of Asian Near East in the latest Miocene to Early Pliocene, around 6.0 to 4.0 mya and perhaps shortly afterwards.
Mutations in SARS-CoV-2 nucleocapsid in variants of concern impair the sensitivity of SARS-CoV-2 detection by rapid antigen tests
Authors: Hagag Ibrahim T. , Pyrc Krzysztof , Weber Saskia , Balkema-Buschmann Anne , Groschup Martin H. , Keller Markus
Published: September 2022

Rapid antigen tests (RATs) are used as convenient SARS-CoV-2 tests to minimize infection risks in the private and public domain (e.g., access to shops, concerts, sports, and other social events). RATs are: however, less sensitive than quantitative reverse transcription Polymerase chain reaction (RT-qPCR) assays; hence, samples with low viral loads may be misdiagnosed. Reports on the ability of RATs to detect SARS-CoV-2 variants of concern (VOCs) Delta and Omicron are often only qualitative. We, therefore, examined the analytical sensitivities of four different RATs for the detection of both full virus and recombinant proteins of relevant VOCs. Since most RATs are based on the detection of the SARS-CoV-2 nucleocapsid protein (N-protein), we constructed multiple N-protein mutants (mirroring specific amino acid exchanges of VOC N-proteins) using prokaryotic expression plasmids and site-directed PCR mutagenesis. Testing of recombinant proteins by four RATs revealed amino acid substitutions R203K and R203M, are critical for the sensitivity of some RATs. Interestingly, R203M mutation completely abrogated antigen detection even at high protein concentrations in the Delta variant. As a proof-of-concept study, we show that one or two specific amino acid changes in the N-protein can negatively impact the analytical sensitivity of RATs. Hence, antibodies used in such lateral flow assays should be optimized and target preferentially more conserved regions of N-protein.
Genomic Prediction of Wheat Grain Yield Using Machine Learning
Authors: Sirsat Manisha Sanjay , Oblessuc Paula Rodrigues , Ramiro Ricardo S.
Published: September 2022

Genomic Prediction (GP) is a powerful approach for inferring complex phenotypes from genetic markers. GP is critical for improving grain yield, particularly for staple crops such as wheat and rice, which are crucial to feeding the world. While machine learning (ML) models have recently started to be applied in GP, it is often unclear what are the best algorithms and how their results are affected by the feature selection (FS) methods. Here, we compared ML and deep learning (DL) algorithms with classical Bayesian approaches, across a range of different FS methods, for their performance in predicting wheat grain yield (in three datasets). Model performance was generally more affected by the prediction algorithm than the FS method. Among all models, the best performance was obtained for tree-based ML methods (random forests and gradient boosting) and for classical Bayesian methods. However, the latter was prone to fitting problems. This issue was also observed for models developed with features selected by BayesA, the only Bayesian FS method used here. Nonetheless, the three other FS methods led to models with no fitting problem but similar performance. Thus, our results indicate that the choice of prediction algorithm is more important than the choice of FS method for developing highly predictive models. Moreover, we concluded that random forests and gradient boosting algorithms generate highly predictive and robust wheat grain yield GP models.
Experimental and Numerical Studies on Fatigue Characteristics of CFRP Shaft Tube
Authors: Ding Guoping , Yan Xiaoyu , Gao Xiaoling , Xiao Jieliang
Published: September 2022

Carbon Fiber Reinforced Plastic (CFRP) shaft tube structure is widely applied in different fields, including aerospace, automotive, and wind power. Since CFRP shaft tube is often subjected to bending fatigue loads, it is of great significance to research its bending fatigue characteristics. Because of its unique advantages, such as a smaller size, lighter weight, and the outstanding ability to form a sensor network, the Fiber Bragg Grating (FBG) sensor is very applicable for health monitoring research of composite material structures. Taking the CFRP shaft tube under bending load as the research object, based on the theory of composite material mechanics and applying the research idea of combining simulation analysis and experiment, the fatigue life, residual stiffness, and fatigue damage evolution of CFRP tubes under three-point bending fatigue loading were studied. Moreover, the fatigue characteristics of CFRP tubes under different fatigue loading were analyzed. At the same time, the ultrasonic phased array was used to obtain the fatigue damage evolution rule by scanning and analyzing the damage to the CFRP shaft tube after different fatigue loading times. Through the application of the FBG sensors, the whole process of fatigue evolution of the CFRP shaft tube was fully monitored.
MFFAMM: A Small Object Detection with Multi-Scale Feature Fusion and Attention Mechanism Module
Authors: Qu Zhong , Han Tongqiang , Yi Tuming
Published: September 2022

Aiming at the low detection accuracy and poor positioning for small objects of single-stage object detection algorithms, we improve the backbone network of SSD (Single Shot MultiBox Detector) and present an improved SSD model based on multi-scale feature fusion and attention mechanism module in this paper. Firstly, we enhance the feature extraction ability of the shallow network through the feature fusion method that is beneficial to small object recognition. Secondly, the RFB (Receptive Field block) is used to expand the object’s receptive field and extract richer semantic information. After feature fusion, the attention mechanism module is added to enhance the feature information of important objects and suppress irrelevant other information. The experimental results show that our algorithm achieves 80.7% and 51.8% mAP on the PASCAL VOC 2007 classic dataset and MS COCO 2017 dataset, which are 3.2% and 10.6% higher than the original SSD algorithm. Our algorithm greatly improves the accuracy of object detection and meets the requirements of real-time.
Effects of Lead, Copper and Cadmium on Bioaccumulation and Translocation Factors and Biosynthesis of Photosynthetic Pigments in Vicia faba L. (Broad Beans) at Different Stages of Growth
Authors: Saadaoui Wassim , Gamboa-Rosales Hamurabi , Sifuentes-Gallardo Claudia , Durán-Muñoz Héctor , Abrougui Khaoula , Mohammadi Ali , Tarchoun Neji
Published: September 2022

Trace elements in the environmental media contribute to toxicities of different types. Their presence in the arable pedosphere is a human-health risk factor. This study focused on Vicia faba represented by two Tunisian varieties of bean (Mamdouh) and faba bean (Badii). The objective was to analyze the effects of lead, copper and cadmium on their growth, chlorophyll-content and carotenoids-content, as well as the bioaccumulation and translocation factor, at different stages of growth. For each metal, the concentrations the plants were subjected to were 6, 0.3 and 0.03 mg/L of the metal in the compound for lead nitrate, copper nitrate and cadmium acetate, respectively. The analysis was carried out using an atomic absorption spectrophotometer (ICP-MS), encompassing all the parts of the plant. The authors detected a perceptible decrease in the fresh weight of roots and shoots, as well as a drop in the chlorophyll and carotenoid, for all the three heavy metals. Cadmium turned out to be the most toxic of the three metals and copper (which is incidentally an essential micronutrient for plant growth) the least. As far as the bioaccumulation factor was concerned, bean and faba bean exhibited different behaviours, both with regard to the growth stages and the heavy metal absorbed. During the vegetative growth stage, both were accumulators of all the three heavy metals (a translocation factor less than unity). However, in the flowering stage, faba bean was a hyper-accumulator of copper (TF > 1); while the bean plants accumulated a lot of lead in the pods-stage (TF > 1). It is worthwhile to pose new research questions and try to answer them in this study, if legumes are accumulator or hyper accumulator plants in which stage and in where organ accumulate more HMs.
Temperature Field and Stability Analysis of the Frozen Wall Based on the Actual Position of Freezing Holes
Authors: Long Wei , Rong Chuanxin , Shi Hao , Huang Shiqing , Wang Zhi , Duan Yin , Ma Haochen
Published: September 2022

Taking the Qingdong Mine as the research object, combined with field measurement data, numerical simulation and theoretical analysis are used to examine the temperature field and stability of the frozen wall in the mine, respectively. The results show that during the active freezing period, under the same freezing time, the average temperature of the effective frozen wall of the fine sand layer is 0.2–1.0 and 0.5–2.5 °C lower than that of the sandy clay layer and clay layer, respectively. The effective frozen wall thickness of the fine sand layer is 0.04–0.17 and 0.17–0.33 m larger than that of the sandy clay layer and clay layer, respectively. The soil cooling between the two circles of freezing holes is the fastest. Due to the deflection of the freezing holes, the interface temperature field is asymmetrical. For deep clay with a depth of 200–250 m, it is most economical and reasonable for the brine temperature in the active freezing period to be −25 and −30 °C. At the designed brine temperature for cooling, during the excavation of the control layer of the topsoil layer (−216 m sandy clay), the side-wall temperature, average temperature, and thickness of the frozen wall meet the design requirements. The ultimate bearing capacity of the frozen wall is 3.20 MPa. When the well is empty for 30 h after excavation, the maximum radial displacement is 26.85 mm, so the frozen wall strength and stability are in a safe state. Overall, the findings of this study can serve as a useful reference for similar freezing projects.
SRRI Methodology to Quantify the Seismic Resilience of Road Infrastructures
Authors: Forcellini Davide
Published: September 2022

The assessment of the seismic risk connected with the functionality of infrastructure has become an important issue in civil engineering, and consists of estimating costs due to earthquakes. In this regard, bridges are the most vulnerable systems among the various components of road infrastructure and the assessment of their resilience has recently been proposed. However, the development of methodologies that can assess the resilience of the full road infrastructure still constitutes a gap in the literature. This paper aims to fill this gap by proposing a novel methodology to include direct and indirect losses using a probability-based approach. A case study was carried out to investigate a road network consisting of two interdependent infrastructures.
Influence of High-Power Ultrasound on Yield of Proteins and Specialized Plant Metabolites from Sugar Beet Leaves (Beta vulgaris subsp. vulgaris var. altissima)
Authors: Dukić Josipa , Hunić Matea , Nutrizio Marinela , Režek Jambrak Anet
Published: September 2022

Ultrasound with water as a green solvent is an effective strategy for reducing losses and increasing the utilization of by-products. The extraction of proteins and specialized plant metabolites from sugar beet leaves (Beta vulgaris subsp. vulgaris var. altissima) promotes sustainability in the agro-food chain. Guided by sustainability, samples treated with ultrasound showed lower energy consumption and lower CO2 emissions. Furthermore, the spectrophotometric determination revealed higher protein and phenol yields in ultrasonically treated samples compared to thermally treated ones. The highest yield of total proteins, 147.91 ± 4.58 mg (gd.m.)−1, was observed during ultrasound treatment (amplitude 100%, treatment time 9 min). Under the same extraction conditions, the same trend was observed in the yield of total phenols 17.89 ± 0.38 mg (gd.m.)−1. High-power ultrasound, compared to the thermal extraction method, has increased the yield of proteins and specialized plant metabolites with significantly lower energy consumption and CO2 emissions. The obtained results are in accordance with the foundations of sustainable development. From an economic and environmental point of view, ultrasound with the use of green solvents would be an excellent replacement for conventional extraction methods.
Microdosimetry Study of Proton Quality Factor Using Analytic Model Calculations
Authors: Papadopoulos Alexis , Kyriakou Ioanna , Matsuya Yusuke , Incerti Sébastien , Daglis Ioannis A. , Emfietzoglou Dimitris
Published: September 2022

The quality factor (Q) is formally linked to the stochastic (e.g., carcinogenic) risk of diverse ionizing radiations at low doses and/or low dose rates. Q can be a function of the non-stochastic physical quantity Linear Energy Transfer (LET) or the microdosimetric parameter lineal energy (y). These two physical quantities can be calculated either by Monte Carlo (MC) track-structure simulations or by analytic models. In this work, various generalized analytical models were utilized and combined to determine the proton lineal energy spectra in liquid water spheres of various sizes (i.e., 10–3000 nm diameter) over the proton energy range of 1–250 MeV. The calculated spectra were subsequently used within the Theory of Dual Radiation Action (TDRA) and the ICRU Report 40 microdosimetric methodologies to determine the variation of Q¯ with proton energy. The results revealed that the LET-based Q values underestimated the microdosimetric-based Q¯ values for protons with energy below ~100 MeV. At energies relevant to the Bragg peak region (<20–30 MeV), the differences were larger than 20–50%, while reaching 200–500% at ~5 MeV. It was further shown that the microdosimetric-based Q¯ values for protons below ~100 MeV were sensitive to the sphere size. Finally, condensed-phase effects had a very small (<5%) influence on the calculated microdosimetric-based Q¯ over the proton energy range considered here.
Statistical Analysis of the Crosswalk Lighting Design Correctness
Authors: Sȩdziwy Adam , Kotulski Leszek
Published: September 2022

The main goal of roadway lighting design is ensuring compliance with mandatory lighting standards and thus increasing safety for all road users. On the other hand, a design process being only a part of a road investment has to be completed in possibly a short time, due to business needs. The commonly used method for reconciling both requirements is using predefined lighting projects (templates) which are matched with similar, real-life lighting situations. This approach works well for a typical roadway lighting design but not necessarily for crosswalk illumination due to different specifics of underlying calculations (they focus on the contrast of a pedestrian against its background rather than roadway illumination). As one deals with pedestrian safety here, we decided to perform extensive tests to find out whether a standard compliant lighting project prepared for a given crosswalk can be safely applied (in terms of preserving standard compliance) to another similar crosswalk. To accomplish that, we investigated nearly 900 million situations obtained as modifications of the reference template. Results proved that even a 5% change of layout sizes (crosswalk width, lamp spacing, pole height etc.) makes 40% of obtained projects violate illumination requirements. The conclusion of this result is that the template-based design approach broadly used for roadway lighting cannot be applied for pedestrian crossings as it may cause serious safety issues.
Structural Dynamic Model Updating with Automatic Mode Identification Using Particle Swarm Optimization
Authors: Li Kaiyang , Fang Jie , Sun Bing , Li Yi , Cai Guobiao
Published: September 2022

Dynamic model-updating methods are a useful tool for obtaining high-precision finite element (FE) models. However, when using such methods to update a model, there will be problems with incompleteness and mode switching. To overcome these problems, this paper proposes a structural dynamic model-updating with an automatic mode-identification method. In this method, a mode-identification index is established based on image-similarity recognition to identify the consistency between FE and experimental mode shapes, and particle swarm optimization is introduced to update the model. In addition, to reduce the computational time, Latin hypercube sampling is employed to perform probability statistics of the switching range of the concerned mode orders, and the orders of mode identification are reduced according to the statistics results. In this paper, the proposed method was validated by model-updating of a square plate. The natural frequencies and mode shapes of the plate were obtained by experimental modal analysis and used as the updating objectives of the FE model. In addition, the boundary condition of the plate was simplified by a series of springs, which were used as updating parameters along with material properties and dimensions. Finally, the FE model of the plate was updated by the present method, and the results indicate that the objective function error of the updated FE model was successfully reduced from 14.31% to 1.05%, which proves that the proposed model-updating method is effective and feasible.
Internet of Things Aware Secure Dew Computing Architecture for Distributed Hotspot Network: A Conceptual Study
Authors: Ray Partha Pratim , Skala Karolj
Published: September 2022

Building a widely distributed hotspot network is a very tedious task due to its complexity. Providing security, fully distributed network services, and a cost-conscious impact are the major challenges behind this goal. To overcome these issues, we have presented a novel distributed hotspot network architecture with five layers that can provide large-scale hotspot coverage as an assimilated result. Our contributions to this new architecture highlight important aspects. First, scalability can be increased by including many Internet of Things (IoT) devices with sensors and Wi-Fi and/or LoraWAN connectivity modules. Second, hotspot owners can rent out their hotspots to create a distributed hotspot network in which the hotspots can act as an ordinary data gateway, a full-fledged hotspot miner, and a light-weight hotspot miner to earn crypto tokens as rewards for certain activities. Third, the advantages of Wi-Fi and LoraWAN can be seamlessly leveraged to achieve optimal coverage, higher network security, and suitable data transmission rate for transferring sensor data from IoT devices to remote application servers and users. Fourth, blockchain is used to enhance the decentralized behavior of the architecture that is presented here by providing immutability and independence from a centralized regulator and making the network architecture more reliable and transparent. The main feature of our paper is the use of the dew-computing paradigm along with hotspots to improve availability, Internet backhaul-agnostic network coverage, and synchronous update capability, and dew-aware leasing to strengthen and improve coverage. We also discuss the key challenges and future roadmap that require further investment and deployment.
Reconstruction of Motion Images from Single Two-Dimensional Motion-Blurred Computed Tomographic Image of Aortic Valves Using In Silico Deep Learning: Proof of Concept
Authors: Long Yawu , Sakuma Ichiro , Tomii Naoki
Published: September 2022

The visualization of motion is important in the diagnosis and treatment of aortic valve disease. It is difficult to perform using computed tomography (CT) because of motion blur. Existing research focuses on suppressing or removing motion blur. The purpose of this study is to prove the feasibility of inferring motion images using motion information from a motion-blurred CT image. An in silico learning method is proposed, to infer 60 motion images from a two-dimensional (2D) motion-blurred CT image, to verify the concept. A dataset of motion-blurred CT images and motion images was generated using motion and CT simulators to train a deep neural network. The trained model was evaluated using two image similarity evaluation metrics, a structural similarity index measure (0.97 ± 0.01), and a peak signal-to-noise ratio (36.0 ± 1.3 dB), as well as three motion feature evaluation metrics, maximum opening distance error between endpoints (0.7 ± 0.6 mm), maximum-swept area velocity error between adjacent images (393.3 ± 423.3 mm2/s), and opening time error (5.5 ± 5.5 ms). According to the results, the trained model can successfully infer 60 motion images from a motion-blurred CT image. This study demonstrates the feasibility of inferring motion images from a motion-blurred CT image under simulated conditions.
Special Issue “Gas Bearings: Modelling, Design and Applications”
Authors: Colombo Federico , Lentini Luigi , Raparelli Terenziano , Trivella Andrea
Published: September 2022

Gas bearings are widely employed in high-precision devices and in high-speed applications, such as in micro turbomachinery and micro machining tools [...]
Deep Learning Model for Selecting Suitable Requirements Elicitation Techniques
Authors: Dafaalla Hatim , Abaker Mohammed , Abdelmaboud Abdelzahir , Alghobiri Mohammed , Abdelmotlab Ahmed , Ahmad Nazir , Eldaw Hala , Hasabelrsoul Aiman
Published: September 2022

Requirement elicitation represents one of the most vital phases in information system (IS) and software development projects. Selecting suitable elicitation techniques is critical for eliciting the correct specification in various projects. Recent studies have revealed that improper novice practices in this phase have increased the failure rate in both IS and software development projects. Previous research has primarily relied on creating procedural systems based on contextual studies of elicitation properties. In contrast, this paper introduces a deep learning model for selecting suitable requirement elicitation. An experiment was conducted wherein a collected dataset of 1684 technique selection attributes were investigate with respect to 14 elicitation techniques. The study adopted seven criteria to evaluate predictive model performance using confusion matrix accuracy, precision, recall, F1 Score, and area under the ROC curve (AUC) and loss curve. The model scored prediction accuracy of 82%, precision score of 0.83, recall score of 0.83, F1 score of 0.82, cross-validation score of 0.82 (± 0.10), One-vs-One ROC AUC score of 0.74, and One-vs-Rest ROC AUC score of 0.75 for each label. Our results indicate the model’s high prediction ability. The model provides a robust decision-making process for delivering correct elicitation techniques and lowering the risk of project failure. The implications of this study can be used to promote the automatization of the elicitation technique selection process, thereby enhancing current required elicitation industry practices.
Adipolin and IL-6 Serum Levels in Chronic Obstructive Pulmonary Disease
Authors: Aslani Mohammad , Amani Mojtaba , Moghadas Faranak , Ghobadi Hassan
Published: September 2022

Objective(s): One of the adipokines that have insulin-sensitizing properties is adipolin, whose reduced levels have been reported in obesity, oxidative stress, and inflammation. The present study investigated serum interleukin-6 (IL-6) and adipolin levels in chronic obstructive pulmonary disease (COPD) patients. Method: A control case study included 60 COPD patients and 30 healthy subjects in the research and measured adipolin and IL-6 serum levels. In addition, serum adipolin levels in COPD patients were assessed according to the GOLD grade. The relationship between serum adipolin levels and study variables were also analyzed. Results: The results showed reduced adipolin levels in COPD patients compared with healthy individuals (p < 0.001). Furthermore, increased levels of IL-6 were evident in the COPD group compared to the control group (p < 0.001). Adipolin serum levels were positively correlated with PFTs and negatively correlated with IL-6 levels. Conclusion: Decreased adipolin levels enhanced disease severity in COPD patients. It seems that the existence of a significant relationship between adipolin and IL-6 may indicate the role of adipolin in the pathophysiology of COPD.
Decreasing Solid Aerosols from Small Heat Sources Using the Optimized Electrostatic Precipitator
Authors: Holubčík Michal , Kantová Nikola Čajová , Trnka Juraj , Jandačka Jozef
Published: September 2022

Air quality and air pollution are important issues, and thus it is necessary to look at possibilities for how to decrease emissions in the atmosphere affordably and effectively. This article focuses on solid aerosols, specifically particulate matter, and the design of a low-cost solution for their decrease in the atmosphere. The mass concentration of particulate matter with the proposed optimized electrostatic precipitator was measured and compared with measurement without its implementation. Based on the results, it can be concluded that the designed ESP type could catch approximately 71% of solid particles. However, the real ability to capture particulate matter could be expected to be approximately 50–60% due to possible clogging, irregular cleaning and maintenance under normal conditions. Further, the article deals with the application of the village model with this type of electrostatic precipitator in households. Based on this model, the production of particulate matter would be reduced from 12.24 t/year to 6.12 t/year considering 50% separation efficiency and to 5.25 t/year considering 60% separation efficiency by the application to all heat sources for burning solid fuels for all emission classes. However, the reduction in particulate matter would be lower in real conditions.
Ground-Based Measurements of Cloud Properties at the Bucharest–Măgurele Cloudnet Station: First Results
Authors: Pîrloagă Răzvan , Ene Dragoş , Boldeanu Mihai , Antonescu Bogdan , O’Connor Ewan J. , Ştefan Sabina
Published: September 2022

Data collected over a period of 18 months (December 2019–May 2021) at the Bucharest–Măgurele Cloudnet station were analysed for the first time to determine the macrophysical and microphysical cloud properties over this site. A total number of 1,327,680 vertical profiles containing the target classification based on the Cloudnet algorithm were analysed, of which 1,077,858 profiles contained hydrometeors. The highest number of profiles with hydrometeors (>60%) was recorded in December 2020, with hydrometeors being observed mainly below 5 km. Above 5 km, the frequency of occurrence of hydrometeors was less than <20%. Based on the initial Cloudnet target classification, a cloud classification scheme was implemented. Clouds were more frequently observed during winter compared with other seasons (45% of all profiles). Ice clouds were the most frequent type of cloud (468,463 profiles) during the study period, followed by mixed phases (220,280 profiles) and mixed phased precipitable clouds (164,868 profiles). The geometrical thickness varied from a median value of 244 m for liquid clouds during summer to 3362 m for mix phased precipitable clouds during spring.
Testicular Glycogen Metabolism: An Overlooked Source of Energy for Spermatogenesis?
Authors: Silva Ricardo , Carrageta David F. , Alves Marco G. , Oliveira Pedro F.
Published: September 2022

The incidence of male infertility has been increasing over the years and is now becoming a serious health problem. This trend has been followed by an increase in metabolic diseases, which are known to induce clear alterations in testicular metabolism, although the underlying mechanismremain unclear. Testicular metabolism displays several unique features, with testicular somatic cells being central in providing the conditions needed for spermatogenesis, including its nutritional and hormonal support. In addition to glucose and lactate, the two main energy sources used by the testis, glycogen is also present in testicular cells. Glycogen metabolism is a potential source of glucose to both testicular somatic (namely Sertoli and Leydig cells) and germ cells. Many of the enzymes involved in the pathways of the synthesis and degradation of glycogen were identified in these cells, emphasising the relevance of this complex carbohydrate. Glycogen, however, has other non-canonical functions in testicular cells; besides its role as a source of energy, it is also associated with events such as cellular differentiation and apoptosis. In this review, we address the relevance of testicular glycogen metabolism, focusing on its role in Sertoli and Leydig cells and spermatogenesis. In addition, all the available information on the role of glycogen and related pathways in male infertility cases is discussed. Our discussion highlights that glycogen metabolism has been somewhat overlooked in testis and its contribution to spermatogenesis may be underestimated.
The Role of Intrinsically Disordered Proteins in Liquid–Liquid Phase Separation during Calcium Carbonate Biomineralization
Authors: Tarczewska Aneta , Bielak Klaudia , Zoglowek Anna , Sołtys Katarzyna , Dobryszycki Piotr , Ożyhar Andrzej , Różycka Mirosława
Published: September 2022

Some animal organs contain mineralized tissues. These so-called hard tissues are mostly deposits of calcium salts, usually in the form of calcium phosphate or calcium carbonate. Examples of this include fish otoliths and mammalian otoconia, which are found in the inner ear, and they are an essential part of the sensory system that maintains body balance. The composition of ear stones is quite well known, but the role of individual components in the nucleation and growth of these biominerals is enigmatic. It is sure that intrinsically disordered proteins (IDPs) play an important role in this aspect. They have an impact on the shape and size of otoliths. It seems probable that IDPs, with their inherent ability to phase separate, also play a role in nucleation processes. This review discusses the major theories on the mechanisms of biomineral nucleation with a focus on the importance of protein-driven liquid–liquid phase separation (LLPS). It also presents the current understanding of the role of IDPs in the formation of calcium carbonate biominerals and predicts their potential ability to drive LLPS.
Oral Absorbent AST-120 Is Associated with Compositional and Functional Adaptations of Gut Microbiota and Modification of Serum Short and Medium-Chain Fatty Acids in Advanced CKD Patients
Authors: Hsu Cheng-Kai , Su Shih-Chi , Chang Lun-Ching , Yang Kai-Jie , Lee Chin-Chan , Hsu Heng-Jung , Chen Yih-Ting , Sun Chiao-Yin , Wu I-Wen
Published: September 2022

Background: Animal studies have demonstrated that an oral absorbent AST-120 modulates gut environment. However, this phenomenon remains unclear in humans. This study aimed to assess the effects of AST-120 on the gut microbiota, related functional capability and metabolomic profiling in advanced chronic kidney diseases (CKD) patients. Methods: Eight advanced CKD patients with AST-120 (CKD+AST), 24 CKD patients (CKD), and 24 non-CKD controls were enrolled. We analyzed 16S rRNA pyrosequencing of feces and serum metabolomics profiling. Results: The CKD+AST group exhibited dispersed microbial community structure (β-diversity, p < 0.001) compared to other groups. The relative abundances of at least 16 genera were significantly different amongst the three groups. Increases of fatty acids-producing bacteria (Clostridium_sensu_stricto_1, Ruminococcus_2, Eubacterium_nodatum and Phascolarctobacterium) associated with elevated serum acetic acid and octanoic acid levels were found in CKD+AST group. Analysis of microbial gene function indicated that pathway modules relevant to metabolisms of lipids, amino acids and carbohydrates were differentially enriched between CKD+AST and CKD groups. Specifically, enrichments of gene markers of the biosynthesis of fatty acids were noted in the CKD+AST group. Conclusion: Advanced CKD patients exhibited significant gut dysbiosis. AST-120 can partially restore the gut microbiota and intervenes in a possible signature of short- and medium-chain fatty acids metabolism.
Typology of Latvian Churches and Preliminary Study on Indoor Air Temperature and Moisture Behavior
Authors: Metals Martins , Palcikovskis Arturs , Borodinecs Anatolijs , Lesinskis Arturs
Published: September 2022

When dealing with the indoor microclimates of cultural and historical heritage cult buildings, it is important to know the types of these buildings by their spatial volumes and by the types of enclosing structures, and it is also important to understand the moisture transfer processes in these buildings, which would allow one to generate solutions on how to more effectively control the indoor microclimate. Due to the antiquity and specific load of these buildings, the existing standards are not applicable. This study summarizes 275 churches in Latvia, dividing them both according to five spatial volumes and according to the types of the materials used, which makes it possible to create potential air flows for all spatial volumes and to predict condensation risks in the future. Additionally, the results of temperature and humidity measurements in two different churches from one region of Latvia are given and the absolute humidity was calculated, and the data were analyzed depending on the outside air temperature. These measurements have yet to be followed up with the data of a full year.
A Review of Simplified Numerical Beam-like Models of Multi-Storey Framed Buildings
Authors: Greco Annalisa , Caddemi Salvatore , Caliò Ivo , Fiore Ilaria
Published: September 2022

Modern computational techniques have greatly influenced the numerical analyses of structures, not only in terms of calculation speed, but also in terms of procedural approach. In particular, great importance has been given to structural modelling, that is, the process by which a structure and the actions to which it is subjected are reduced to a simplified scheme. The use of a simplified calculation scheme is necessary since the structures are, in general, considerably complex physical systems whose behaviour is influenced by a large number of variables. The definition of a structural scheme that is at the same time simple enough to be easily computable as well as sufficiently reliable in reproducing the main characteristics of the behaviour of the analysed structure is, therefore, a crucial task. In particular, with reference to multi-storey framed buildings, the extensive use of three-dimensional finite element models (FEM) has been made in recent decades by researchers and structural engineers. However, an interesting and alternative research field concerns the possibility of studying multi-storey buildings through the use of equivalent beam-like models in which the number of degrees of freedom and the required computational effort are reduced with respect to more demanding FEM models. Several researchers have proposed single or coupled continuous beams to simulate either the static or dynamic response of multi-storey buildings assuming elastic or inelastic behaviour of the constitutive material. In this paper, a review of several scientific papers proposing elastic or inelastic beam-like models for the structural analyses of framed multi-storey buildings is presented. Considerations about limits and potentialities of these models are also included.
The Current Role of Stereotactic Body Radiation Therapy (SBRT) in Hepatocellular Carcinoma (HCC)
Authors: Kimura Tomoki , Fujiwara Toshiki , Kameoka Tsubasa , Adachi Yoshinori , Kariya Shinji
Published: September 2022

The role of stereotactic body radiotherapy (SBRT), which can deliver high radiation doses to focal tumors, has greatly increased in not only early-stage hepatocellular carcinoma (HCC), but also in portal vein or inferior vena cava thrombi, thus expanding this therapy to pre-transplantation and the treatment of oligometastases from HCC in combination with immune checkpoint inhibitors (ICI). In early-stage HCC, many promising prospective results of SBRT have been reported, although SBRT is not usually indicated as a first treatment potion in localized HCC according to several guidelines. In the treatment of portal vein or inferior vena cava tumor thrombi, several reports using various dose-fraction schedules have shown relatively good response rates with low toxicities and improved survival due to the rapid advancements in systemic therapy. Although SBRT is regarded as a substitute therapy when conventional bridging therapies to transplantation, such as transarterial chemoembolization (TACE) and radiofrequency ablation (RFA), are not applicable or fail in controlling tumors, SBRT may offer advantages in patients with borderline liver function who may not tolerate TACE or RFA, according to several reports. For oligometastases, the combination of SBRT with ICI could potentially induce an abscopal effect in patients with HCC, which is expected to provide the rationale for SBRT in the treatment of oligometastatic disease in the near future.
Golgi Dysfunctions in Ciliopathies
Authors: Masson Justine , El Ghouzzi Vincent
Published: September 2022

The Golgi apparatus (GA) is essential for intracellular sorting, trafficking and the targeting of proteins to specific cellular compartments. Anatomically, the GA spreads all over the cell but is also particularly enriched close to the base of the primary cilium. This peculiar organelle protrudes at the surface of almost all cells and fulfills many cellular functions, in particular during development, when a dysfunction of the primary cilium can lead to disorders called ciliopathies. While ciliopathies caused by loss of ciliated proteins have been extensively documented, several studies suggest that alterations of GA and GA-associated proteins can also affect ciliogenesis. Here, we aim to discuss how the loss-of-function of genes coding these proteins induces ciliary defects and results in ciliopathies.
Phytochemical Screening, and In Vitro Evaluation of the Antioxidant and Dermocosmetic Activities of Four Moroccan Plants: Halimium antiatlanticum, Adenocarpus artemisiifolius, Pistacia lentiscus and Leonotis nepetifolia
Authors: Mechqoq Hicham , Hourfane Sohaib , Yaagoubi Mohamed El , Hamdaoui Abdallah El , Msanda Fouad , Almeida Jackson Roberto Guedes da Silva , Rocha Joao Miguel , Aouad Noureddine El
Published: September 2022

In this study, four Moroccan plants, Halimium antiatlanticum, Adenocarpus artemisiifolius, Pistacia lentiscus and Leonotis nepetifolia, were evaluated for their phytoconstituents and biological activities. Methanolic extracts of these plants were obtained by Soxhlet apparatus, phytochemical screening was performed, and the total phenolic and flavonoid contents were determined. Then, the antioxidant and dermocosmetic activities of the methanolic extracts were evaluated. The obtained results revealed that the leaves and/or aerial parts contained tannins, polyphenols, flavonoids, coumarins, carotenoids, terpenoids and saponins. The higher total phenolic content values were recorded on Pistacia lentiscus and Halimium antiatlanticum with 396.64 ± 30.79 and 304.96 ± 55.61 mgGAE/gDW, respectively. The antioxidant activity was measured by DPPH, ABTS and FRAP assays, and showed that Pistacia lentiscus and Halimium antiatlanticum were the most active extracts, with, respectively, IC50 values of 3.705 ± 0.445 and 5.037 ± 0.122 µg/mL for DPPH. The same results were observed for the FRAP and ABTS assays. Those extracts also showed a strong collagenase inhibitory activity at 200 µg/mL, with 78.51 ± 2.27% for Pistacia lentiscus and 73.10 ± 8.52% for Halimium antiatlanticum. Adenocarpus artemisiifolius showed the highest elastase inhibition rate, with 76.30 ± 5.29%. This study disclosed the dermocosmetic potential of Halimium antiatlanticum and Adenocarpus artemisiifolius, two Moroccan endemic plants that can be traditionally used by local populations or exploited by the cosmetic industry.
Improved Single Breath-Hold SSFSE Sequence for Liver MRI Based on Compressed Sensing: Evaluation of Image Quality Compared with Conventional T2-Weighted Sequences
Authors: Lee Hyun Kyung , Song Ji Soo , Jang Weon , Nickel Dominik , Paek Mun Young
Published: September 2022

The purpose of this study was to evaluate the image quality of compressed-sensing accelerated single-shot fast spin-echo (SSFSECS) sequences acquired within a single breath-hold in comparison with conventional SSFSE (SSFSECONV) and multishot TSE (mTSE). A total of 101 patients who underwent liver MRI at 3 T, including SSFSECONV (acquisition time (TA) = 58–62 s), mTSE (TA = 108 s), and SSFSECS (TA = 18 s), were included in this retrospective study. Two radiologists assessed the three sequences with respect to artifacts, organ sharpness, small structure visibility, overall image quality, and conspicuity of main lesions of liver and pancreas using a five-point evaluation scale system. Descriptive statistics and the Wilcoxon signed-rank test were used for statistical analysis. SSFSECS was significantly better than SSFSECONV and mTSE for artifacts, small structure visibility, overall image quality, and conspicuity of main lesions (p < 0.005). Regarding organ sharpness, mTSE and SSFSECS did not significantly differ (p = 0.554). Conspicuity of liver lesion did not significantly differ between SSFSECONV and mTSE (p = 0.404). SSFSECS showed superior image quality compared with SSFSECONV and mTSE despite a more than three-fold reduction in TA, suggesting a remarkable potential for saving time in liver imaging.
Structure-from-Motion 3D Reconstruction of the Historical Overpass Ponte della Cerra: A Comparison between MicMac® Open Source Software and Metashape®
Authors: Cutugno Matteo , Robustelli Umberto , Pugliano Giovanni
Published: September 2022

In recent years, the performance of free-and-open-source software (FOSS) for image processing has significantly increased. This trend, as well as technological advancements in the unmanned aerial vehicle (UAV) industry, have opened blue skies for both researchers and surveyors. In this study, we aimed to assess the quality of the sparse point cloud obtained with a consumer UAV and a FOSS. To achieve this goal, we also process the same image dataset with a commercial software package using its results as a term of comparison. Various analyses were conducted, such as the image residuals analysis, the statistical analysis of GCPs and CPs errors, the relative accuracy assessment, and the Cloud-to-Cloud distance comparison. A support survey was conducted to measure 16 markers identified on the object. In particular, 12 of these were used as ground control points to scale the 3D model, while the remaining 4 were used as check points to assess the quality of the scaling procedure by examining the residuals. Results indicate that the sparse clouds obtained are comparable. MicMac® has mean image residuals equal to 0.770 pixels while for Metashape® is 0.735 pixels. In addition, the 3D errors on control points are similar: the mean 3D error for MicMac® is equal to 0.037 m with a standard deviation of 0.017 m, whereas for Metashape®, it is 0.031 m with a standard deviation equal to 0.015 m. The present work represents a preliminary study: a comparison between software packages is something hard to achieve, given the secrecy of the commercial software and the theoretical differences between the approaches. This case study analyzes an object with extremely complex geometry; it is placed in an urban canyon where the GNSS support can not be exploited. In addition, the scenario changes continuously due to the vehicular traffic.
An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints
Authors: Schwarz Schuler Joao Paulo , Also Santiago Romani , Puig Domenec , Rashwan Hatem , Abdel-Nasser Mohamed
Published: September 2022

In image classification with Deep Convolutional Neural Networks (DCNNs), the number of parameters in pointwise convolutions rapidly grows due to the multiplication of the number of filters by the number of input channels that come from the previous layer. Existing studies demonstrated that a subnetwork can replace pointwise convolutional layers with significantly fewer parameters and fewer floating-point computations, while maintaining the learning capacity. In this paper, we propose an improved scheme for reducing the complexity of pointwise convolutions in DCNNs for image classification based on interleaved grouped filters without divisibility constraints. The proposed scheme utilizes grouped pointwise convolutions, in which each group processes a fraction of the input channels. It requires a number of channels per group as a hyperparameter Ch. The subnetwork of the proposed scheme contains two consecutive convolutional layers K and L, connected by an interleaving layer in the middle, and summed at the end. The number of groups of filters and filters per group for layers K and L is determined by exact divisions of the original number of input channels and filters by Ch. If the divisions were not exact, the original layer could not be substituted. In this paper, we refine the previous algorithm so that input channels are replicated and groups can have different numbers of filters to cope with non exact divisibility situations. Thus, the proposed scheme further reduces the number of floating-point computations (11%) and trainable parameters (10%) achieved by the previous method. We tested our optimization on an EfficientNet-B0 as a baseline architecture and made classification tests on the CIFAR-10, Colorectal Cancer Histology, and Malaria datasets. For each dataset, our optimization achieves a saving of 76%, 89%, and 91% of the number of trainable parameters of EfficientNet-B0, while keeping its test classification accuracy.