bluuebunny/crossref_metadata_2025 huggingface dataset:
Synaptic Dysfunction by Mutations in GRIN2B: Influence of Triheteromeric NMDA Receptors on Gain-of-Function and Loss-of-Function Mutant Classification
Authors: Elmasri Marwa , Lotti James S. , Aziz Wajeeha , Steele Oliver G. , Karachaliou Eirini , Sakimura Kenji , Hansen Kasper B. , Penn Andrew C.
Published: June 2022

GRIN2B mutations are rare but often associated with patients having severe neurodevelopmental disorders with varying range of symptoms such as intellectual disability, developmental delay and epilepsy. Patient symptoms likely arise from mutations disturbing the role that the encoded NMDA receptor subunit, GluN2B, plays at neuronal connections in the developing nervous system. In this study, we investigated the cell-autonomous effects of putative gain- (GoF) and loss-of-function (LoF) missense GRIN2B mutations on excitatory synapses onto CA1 pyramidal neurons in organotypic hippocampal slices. In the absence of both native GluN2A and GluN2B subunits, functional incorporation into synaptic NMDA receptors was attenuated for GoF mutants, or almost eliminated for LoF GluN2B mutants. NMDA-receptor-mediated excitatory postsynaptic currents (NMDA-EPSCs) from synaptic GoF GluN1/2B receptors had prolonged decays consistent with their functional classification. Nonetheless, in the presence of native GluN2A, molecular replacement of native GluN2B with GoF and LoF GluN2B mutants all led to similar functional incorporation into synaptic receptors, more rapidly decaying NMDA-EPSCs and greater inhibition by TCN-201, a selective antagonist for GluN2A-containing NMDA receptors. Mechanistic insight was gained from experiments in HEK293T cells, which revealed that GluN2B GoF mutants slowed deactivation in diheteromeric GluN1/2B, but not triheteromeric GluN1/2A/2B receptors. We also show that a disease-associated missense mutation, which severely affects surface expression, causes opposing effects on NMDA-EPSC decay and charge transfer when introduced into GluN2A or GluN2B. Finally, we show that having a single null Grin2b allele has only a modest effect on NMDA-EPSC decay kinetics. Our results demonstrate that functional incorporation of GoF and LoF GluN2B mutants into synaptic receptors and the effects on EPSC decay times are highly dependent on the presence of triheteromeric GluN1/2A/2B NMDA receptors, thereby influencing the functional classification of NMDA receptor variants as GoF or LoF mutations. These findings highlight the complexity of interpreting effects of disease-causing NMDA receptor missense mutations in the context of neuronal function.
MVI-Mind: A Novel Deep-Learning Strategy Using Computed Tomography (CT)-Based Radiomics for End-to-End High Efficiency Prediction of Microvascular Invasion in Hepatocellular Carcinoma
Authors: Wang Liyang , Wu Meilong , Li Rui , Xu Xiaolei , Zhu Chengzhan , Feng Xiaobin
Published: June 2022

Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) directly affects a patient’s prognosis. The development of preoperative noninvasive diagnostic methods is significant for guiding optimal treatment plans. In this study, we investigated 138 patients with HCC and presented a novel end-to-end deep learning strategy based on computed tomography (CT) radiomics (MVI-Mind), which integrates data preprocessing, automatic segmentation of lesions and other regions, automatic feature extraction, and MVI prediction. A lightweight transformer and a convolutional neural network (CNN) were proposed for the segmentation and prediction modules, respectively. To demonstrate the superiority of MVI-Mind, we compared the framework’s performance with that of current, mainstream segmentation, and classification models. The test results showed that MVI-Mind returned the best performance in both segmentation and prediction. The mean intersection over union (mIoU) of the segmentation module was 0.9006, and the area under the receiver operating characteristic curve (AUC) of the prediction module reached 0.9223. Additionally, it only took approximately 1 min to output a prediction for each patient, end-to-end using our computing device, which indicated that MVI-Mind could noninvasively, efficiently, and accurately predict the presence of MVI in HCC patients before surgery. This result will be helpful for doctors to make rational clinical decisions.
The Breast Cancer Protein Co-Expression Landscape
Authors: Ruhle Martín , Espinal-Enríquez Jesús , Hernández-Lemus Enrique
Published: June 2022

Breast cancer is a complex phenotype (or better yet, several complex phenotypes) characterized by the interplay of a large number of cellular and biomolecular entities. Biological networks have been successfully used to capture some of the heterogeneity of intricate pathophenotypes, including cancer. Gene coexpression networks, in particular, have been used to study large-scale regulatory patterns. Ultimately, biological processes are carried out by proteins and their complexes. However, to date, most of the tumor profiling research has focused on the genomic and transcriptomic information. Here, we tried to expand this profiling through the analysis of open proteomic data via mutual information co-expression networks’ analysis. We could observe that there are distinctive biological processes associated with communities of these networks and how some transcriptional co-expression phenomena are lost at the protein level. These kinds of data and network analyses are a broad resource to explore cellular behavior and cancer research.
Examples of Inverse Comorbidity between Cancer and Neurodegenerative Diseases: A Possible Role for Noncoding RNA
Authors: Salemi Michele , Mogavero Maria Paola , Lanza Giuseppe , Mongioì Laura M. , Calogero Aldo E. , Ferri Raffaele
Published: June 2022

Cancer is one of the most common causes of death; in parallel, the incidence and prevalence of central nervous system diseases are equally high. Among neurodegenerative diseases, Alzheimer’s dementia is the most common, while Parkinson’s disease (PD) is the second most frequent neurodegenerative disease. There is a significant amount of evidence on the complex biological connection between cancer and neurodegeneration. Noncoding RNAs (ncRNAs) are defined as transcribed nucleotides that perform a variety of regulatory functions. The mechanisms by which ncRNAs exert their functions are numerous and involve every aspect of cellular life. The same ncRNA can act in multiple ways, leading to different outcomes; in fact, a single ncRNA can participate in the pathogenesis of more than one disease—even if these seem very different, as cancer and neurodegenerative disorders are. The ncRNA activates specific pathways leading to one or the other clinical phenotype, sometimes with obvious mechanisms of inverse comorbidity. We aimed to collect from the existing literature examples of inverse comorbidity in which ncRNAs seem to play a key role. We also investigated the example of mir-519a-3p, and one of its target genes Poly (ADP-ribose) polymerase 1, for the inverse comorbidity mechanism between some cancers and PD. We believe it is very important to study the inverse comorbidity relationship between cancer and neurodegenerative diseases because it will help us to better assess these two major areas of human disease.
Computerized Texture Analysis of Optical Coherence Tomography Angiography of Choriocapillaris in Normal Eyes of Young and Healthy Subjects
Authors: Movahedan Asadolah , Vargas Phillip , Moir John , Kaufmann Gabriel , Chun Lindsay , Smith Claire , Massamba Nathalie , La Riviere Patrick , Skondra Dimitra
Published: June 2022

Computerized texture analysis uses higher-order mathematics to identify patterns beyond what the naked eye can recognize. We tested its feasibility in optical coherence tomography angiography imaging of choriocapillaris. Our objective was to determine sets of parameters that provide coherent and consistent output when applied to a homogeneous, healthy group of patients. This observational cross-sectional study involved 19 eyes of 10 young and healthy Caucasian subjects. En-face macular optical coherence tomography angiography of superficial choriocapillaris was obtained by the RTVue-XR Avanti system. Various algorithms were used to extract texture features. The mean and standard deviation were used to assess the distribution and dispersion of data points in each metric among eyes, which included: average gray level, gray level yielding 70% threshold and 30% threshold, balance, skewness, energy, entropy, contrast, edge mean gradient, root-mean-square variation, and first moment of power spectrum, which was compared between images, showing a highly concordant homology between all eyes of participants. We conclude that computerized texture analysis for en-face optical coherence tomography angiography images of choriocapillaris is feasible and provides values that are coherent and tightly distributed around the mean in a homogenous, healthy group of patients. Homology of blob size among subjects may represent a “repeat pattern” in signal density and thus a perfusion in the superficial choriocapillaris of healthy young individuals of the same ethnic background.
Treatment for Retinopathy of Prematurity in Twins: The Small Twin without High Birth Weight Discordant Is Not at Increased Risk
Authors: Jin Enzhong , Wang Zongyi , Yao Lu , Yin Hong , Zhao Mingwei
Published: June 2022

Purpose: As common retinopathy is observed in low-birth infants, the characteristics of ROP in twins are worth exploring. The present study tried to demonstrate the risk factors of treatment for retinopathy of prematurity (ROP) in twins both diagnosed with ROP. Methods: A retrospective, institution-based cohort study of 62 premature ROP twin pairs with a mean gestational age (GA) younger than 35 weeks and a birth weight (BW) lower than 2500 g. Only infants with a follow-up period longer than 6 months and complete treatment records were included. The demographic data, treatment requirements and further rescue treatments were all collected and analyzed for all infants according to whether they accepted treatments. Moreover, all twin infants were divided into small and large twin groups according to birth weight, and they were also categorized as three groups according to the treatment requirement including both twins receiving treatment (BT group), one of the twins receiving treatment (ST group) and none of the twins receiving treatment (NT group). Comparisons of demographic data, treatment requirements and further rescue treatments were all conducted according to the different grouping methods. Results: The mean GA of the enrolled infants was (29.29 ± 2.45) weeks with a mean BW of (1335.77 ± 390.36) grams. Among them, 110 infants were mechanically ventilated. Fifty-one of the infants did not receive any treatment and 73 infants received laser or intravitreal injection of anti-VEGF agents. In total, 64 infants only underwent intravitreal injection of anti-VEGF agents or laser treatment, while the other nine infants received scleral buckling or vitrectomy as a necessary treatment when the retinal detachment was observed. No significantly different mechanical ventilation or treatment requirements could be observed between the small twin group and the large twin group (p = 0.73, 0.94). The twins in the BT groups showed the lowest BW, while the NT group infants had the highest BW. The GA for the BT, ST and NT groups were (27.86 ± 1.87) weeks, (29.60 ± 1.52) weeks and (31.33 ± 2.39) weeks, respectively, and showed significant differences as well (p < 0.001). Conclusion: Being a small twin in twin-paired ROP without a high BW discordant will not increase the risk for treatment requirement or additional surgery necessity with a much more severe stage of ROP.
Review on the Use of Kojic Acid—A Skin-Lightening Ingredient
Authors: Phasha Vivey , Senabe Jeremiah , Ndzotoyi Phatheka , Okole Blessed , Fouche Gerda , Chuturgoon Anil
Published: June 2022

This article reviews the use of Kojic Acid (KA) as a skin-lightening ingredient in the cosmetics industry. In 1907, Saito discovered KA, a natural product; it has since become one of the most investigated skin-lightening agents. This paper highlights the findings of the research conducted on this agent. It has been found that KA has certain disadvantages, and researchers have attempted to mitigate these disadvantages by designing new equivalents of KA that are more efficient in tyrosinase inhibition. These equivalents are also safe to use and have improved properties and solubility. The Cosmeceutical Ingredient Review (CIR) indicates that this ingredient can be safely used at a concentration not higher than 1% due to its cytotoxicity. Other scientific data also support its safety at a concentration of 2% or less. It was shown to be helpful in the treatment of hyper pigmentary disorders, such as freckles, age spots, post-inflammatory hyperpigmentation, and melasma, which has been proven clinically.
Probabilistic Logic Models for the Lightning Network
Authors: Azzolini Damiano , Riguzzi Fabrizio
Published: June 2022

The Lightning Network (LN) has emerged as one of the prominent solutions to overcome the biggest limit of blockchain based on PoW: scalability. LN allows for creating a layer on top of an existing blockchain where users can send payments and micro-payments without waiting long confirmation times. One of the key features of LN is that payments can also be sent towards nodes that are not directly connected. From the routing perspective, the balance of an edge that connects two nodes is known, but the distribution between the two involved ends is unknown. Thus, the process of sending payments is based on a trial and error approach, and the routing can be considered probabilistic. Probabilistic Logic Programming (PLP) is a powerful formalism that allows the representation of complex relational domains characterized by uncertainty. In this paper, we study the problem of reasoning about the existence of a path between two nodes that can route a payment of a given size leveraging multiple models based on PLP. We adopt some recently proposed extensions of PLP and develop several models that can be adapted to represent multiple scenarios.
Preparation of Cerium Oxide via Microwave Heating: Research on Effect of Temperature Field on Particles
Authors: Lv Chao , Yin Hong-Xin , Liu Yan-Long , Chen Xu-Xin , Sun Ming-He , Zhao Hong-Liang
Published: June 2022

Micro–nano cerium oxide particles with regular morphology and good dispersity have been widely used in polishing and other industrial fields. Microwave heating is an effective, controllable and green heating technology. The Venturi reactor used for microwave heating developed by our team was the core equipment utilized to study the effects of pyrolysis conditions on the purity and microstructure of cerium oxide particles. The experiments were carried out and the products were characterized using XRD, SEM and EDS. Microwave heating, fluid flow and chemical reaction were coupled using numerical simulation, the effects of microwave power, reactor location and waveguide arrangement on temperature fields were investigated. The results showed that with the microwave power increasing, the degree of crystallinity and purity of cerium oxide improved. The morphology gradually became sphere-like. Varied reactor locations and waveguide arrangements changed the gradient and dispersity of temperature fields. Bulk particles and agglomeration could be avoided, and cerium oxide particles with average size of 80 nm were produced when the reactor was located in the center of the cavity. Vertical arrangement of waveguides had the advantages of higher temperature value, gentle gradient and better dispersity.
Effects of Microstructural Properties on Damage Evolution and Edge Crack Sensitivity of DP1000 Steels
Authors: Habibi Niloufar , Mathi Santhosh , Beier Thorsten , Könemann Markus , Münstermann Sebastian
Published: June 2022

In the present work, the microstructural damage behavior of two DP1000 steel test subjects through various stress states was studied to thoroughly learn the interaction between microstructure, damage evolution, and edge stretchability. In addition, microstructural changes at the fracture sites and fracture surfaces were observed using a scanning electron microscope. The distinctive mechanical and damage behaviors of the materials were revealed. However, the steels were slightly different in chemical composition, microstructural characteristics, and yield stress. The results showed that when microstructural and mechanical properties of phases were more similar, i.e., the microstructure was more homogenous, the damage was initiated by cracking at ferrite-martensite interfaces, and it propagated along the loading direction. This allowed the material to represent high local formability and significant necking. In contrast, by increasing the dissimilarity between ferrite and martensite phases, damage propagated by the shear linking of the voids hindered local deformation of the material and led it to sudden fracture after negligible necking. These distinct damage evolutions noticeably influenced the materials’ edge stretchability. Since higher local formability favors the edges with higher resistance to cracking, the hole expansion ratio increases, as clearly observed throughout the current study.
Spatial-Temporal Change for Ecological Intactness of Giant Panda National Park and Its Adjacent Areas in Sichuan Province, China
Authors: Luo Chuan , Yang Hao , Luo Peng , Liu Shiliang , Wang Jun , Wang Xu , Li Honglin , Mou Chengxiang , Mo Li , Jia Honghong , Wu Sujuan , Cheng Yue , Huang Yu , Xie Wenwen
Published: June 2022

Human activities change the natural ecosystem and cause the decline of the intact ecosystem. Establishing an applicable and efficient human activity monitoring indicator system benefits China’s ambitious national park system construction. In this study, we established a refined technique for ecological intactness scores (EIS) and applied it in the area of Giant Panda National Park (GPNP) from 1980 to 2020 by quantifying four types of human interferences including land use and cover change (LUCC), road construction, water reservoir and hydropower construction, and mining. The results show the following: (1) Under the ecological intactness score range of 0–10, the GPNP with about 92.6% area of the EIS was above 6.0, and the mean baseline level of intactness was 7.1 when it was established in 2018. (2) The EIS in the east of Qionglaishan and south of Minshan were relatively lower than the rest of the study area. (3) During the past 40 years, 80% of the GPNP’s ecological intactness has remained stable. (4) In total, 14% of the GPNP was degraded mainly in the areas below 1200 m with severe human activities. (5) LUCC and road construction were the main driving factors for the decrease of ecological intactness in the GPNP. (6) The habitat of the giant panda is mainly distributed in the areas with an EIS above 6.0, and this is a key link between ecological intactness and habitat suitability. Our research proved that the ecological intactness score (EIS) is an effective indicator for monitoring and assessing the impact of human activities on the regional natural ecosystem and could be helpful for ecological restoration and human activities management GPNP in the future.
Diversity Loss of Epigeic Collembola after Grassland Conversion into Eucalyptus Forestry in Brazilian Pampa Domain
Authors: da Silva Clécio Danilo Dias , Bellini Bruno Cavalcante , Rigotti Vitor Mateus , Nunes Rudy Camilo , Menezes Luciana da Silva , Winck Bruna Raquel
Published: June 2022

The Brazilian Pampa is a rich domain mainly represented by grasslands. Conversion of native vegetation into Eucalyptus plantation leads to soil degradation and losses on local fauna and flora. The objectives of this study were to compare the taxonomic structure and abundance of epigeic springtails (Collembola) in two different types of land-use in the Brazilian Pampa, native grassland and Eucalyptus plantation, as well as to understand the processes that may cause species loss after grassland afforestation. Specimens were sampled in 10 paired plots of grasslands and Eucalyptus in southern Brazil. After sampling, all specimens were sorted, counted and identified. We evaluated the taxonomic composition, alpha and beta diversity, and used Random Forest Analysis to understand the influence of environmental factors on the structure and composition of Collembola communities. We sampled 1249 specimens in 26 morphospecies, and our data support there are significant losses in native Collembola communities after the conversion of grasslands into Eucalyptus plantations regarding abundance, species composition, richness, and alpha diversity. Species turnover better explained the beta diversity, and plant richness and dominance were the main environmental factors driving the Collembola diversity. These results deepen the knowledge of the impacts of native grassland conversion on soil fauna.
Multi-Resolution Discrete Cosine Transform Fusion Technique Face Recognition Model
Authors: AlFawwaz Bader M. , AL-Shatnawi Atallah , Al-Saqqar Faisal , Nusir Mohammad
Published: June 2022

This work presents a Multi-Resolution Discrete Cosine Transform (MDCT) fusion technique Fusion Feature-Level Face Recognition Model (FFLFRM) comprising face detection, feature extraction, feature fusion, and face classification. It detects core facial characteristics as well as local and global features utilizing Local Binary Pattern (LBP) and Principal Component Analysis (PCA) extraction. MDCT fusion technique was applied, followed by Artificial Neural Network (ANN) classification. Model testing used 10,000 faces derived from the Olivetti Research Laboratory (ORL) library. Model performance was evaluated in comparison with three state-of-the-art models depending on Frequency Partition (FP), Laplacian Pyramid (LP) and Covariance Intersection (CI) fusion techniques, in terms of image features (low-resolution issues and occlusion) and facial characteristics (pose, and expression per se and in relation to illumination). The MDCT-based model yielded promising recognition results, with a 97.70% accuracy demonstrating effectiveness and robustness for challenges. Furthermore, this work proved that the MDCT method used by the proposed FFLFRM is simpler, faster, and more accurate than the Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT). As well as that it is an effective method for facial real-life applications.
Indoor Temperature and Relative Humidity Dataset of Controlled and Uncontrolled Environments
Authors: Botero-Valencia Juan , Castano-Londono Luis , Marquez-Viloria David
Published: June 2022

The large volume of data generated with the increasing development of Internet of Things applications has encouraged the development of a large number of works related to data management, wireless communication technologies, the deployment of sensor networks with limited resources, and energy consumption. Different types of new or well-known algorithms have been used for the processing and analysis of data acquired through sensor networks, algorithms for compression, filtering, calibration, analysis, or variables being common. In some cases, databases available on the network, public government databases, data generated from sensor networks deployed by the authors themselves, or values generated by simulation are used. In the case that the work approach is more related to the algorithm than to the characteristics of the sensor networks, these data source options may have some limitations such as the availability of databases, the time required for data acquisition, the need for the deployment of a real sensors network, and the reliability or characteristics of acquired data. The dataset in this article contains 4,164,267 values of timestamp, indoor temperature, and relative humidity acquired in the months of October and November 2019, with twelve temperature and humidity sensors Xiaomi Mijia at the laboratory of Control Systems and Robotics, and the De La Salle Museum of Natural Sciences, both of the Instituto Tecnológico Metropolitano, Medellín—Colombia. The devices were calibrated in a Metrology Laboratory accredited by the National Accreditation Body of Colombia (Organismo Nacional de Acreditación de Colombia—ONAC). The dataset is available in Mendeley Data repository.
Secured Multi-Dimensional Robust Optimization Model for Remotely Piloted Aircraft System (RPAS) Delivery Network Based on the SORA Standard
Authors: Mahmoodi Armin , Hashemi Leila , Laliberté Jeremy , Millar Richard C.
Published: June 2022

The range of applications of RPAs in various industries indicates that their increased usage could reduce operational costs and time. Remotely piloted aircraft systems (RPASs) can be deployed quickly and effectively in numerous distribution systems and even during a crisis by eliminating existing problems in ground transport due to their structure and flexibility. Moreover, they can also be useful in data collection in damaged areas by correctly defining the condition of flight trajectories. Hence, defining a framework and model for better regulation and management of RPAS-based systems appears necessary; a model that could accurately predict what will happen in practice through the real simulation of the circumstances of distribution systems. Therefore, this study attempts to propose a multi-objective location-routing optimization model by specifying time window constraints, simultaneous pick-up and delivery demands, and the possibility of recharging the used batteries to reduce, firstly, transport costs, secondly, delivery times, and thirdly, estimated risks. Furthermore, the delivery time of the model has been optimized to increase its accuracy based on the uncertain conditions of possible traffic scenarios. It is also imperative to note that the assessment of risk indicators was conducted based on the Specific Operations Risk Assessment (SORA) standard to define the third objective function, which was conducted in a few previous studies. Finally, it shows how the developed NSGA-II algorithm in this study performed successfully and reduced the objective function by 31%. Comparing the obtained results using an NSGA-II meta-heuristic approach, through the rigorous method GAMS, indicates that the results are valid and reliable.
A Hybrid Model and Data-Driven Vision-Based Framework for the Detection, Tracking and Surveillance of Dynamic Coastlines Using a Multirotor UAV
Authors: Aspragkathos Sotirios N. , Karras George C. , Kyriakopoulos Kostas J.
Published: June 2022

A hybrid model-based and data-driven framework is proposed in this paper for autonomous coastline surveillance using an unmanned aerial vehicle. The proposed approach comprises three individual neural network-assisted modules that work together to estimate the state of the target (i.e., shoreline) to contribute to its identification and tracking. The shoreline is first detected through image segmentation using a Convolutional Neural Network. The part of the segmented image that includes the detected shoreline is then fed into a CNN real-time optical flow estimator. The position of pixels belonging to the detected shoreline, as well as the initial approximation of the shoreline motion, are incorporated into a neural network-aided Extended Kalman Filter that learns from data and can provide on-line motion estimation of the shoreline (i.e., position and velocity in the presence of waves) using the system and measurement models with partial knowledge. Finally, the estimated feedback is provided to a Partitioned Visual Servo tracking controller for autonomous multirotor navigation along the coast, ensuring that the latter will always remain inside the onboard camera field of view. A series of outdoor comparative studies using an octocopter flying along the shoreline in various weather and beach settings demonstrate the effectiveness of the suggested architecture.
Colored Texture Analysis Fuzzy Entropy Methods with a Dermoscopic Application
Authors: Hilal Mirvana , Gaudêncio Andreia S. , Vaz Pedro G. , Cardoso João , Humeau-Heurtier Anne
Published: June 2022

Texture analysis is a subject of intensive focus in research due to its significant role in the field of image processing. However, few studies focus on colored texture analysis and even fewer use information theory concepts. Entropy measures have been proven competent for gray scale images. However, to the best of our knowledge, there are no well-established entropy methods that deal with colored images yet. Therefore, we propose the recent colored bidimensional fuzzy entropy measure, FuzEnC2D, and introduce its new multi-channel approaches, FuzEnV2D and FuzEnM2D, for the analysis of colored images. We investigate their sensitivity to parameters and ability to identify images with different irregularity degrees, and therefore different textures. Moreover, we study their behavior with colored Brodatz images in different color spaces. After verifying the results with test images, we employ the three methods for analyzing dermoscopic images of malignant melanoma and benign melanocytic nevi. FuzEnC2D, FuzEnV2D, and FuzEnM2D illustrate a good differentiation ability between the two—similar in appearance—pigmented skin lesions. The results outperform those of a well-known texture analysis measure. Our work provides the first entropy measure studying colored images using both single and multi-channel approaches.
Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy
Authors: de Prince Diogo , Marçal Emerson Fernandes , Valls Pereira Pedro L.
Published: June 2022

In this paper, we address whether using a disaggregated series or combining an aggregated and disaggregated series improves the forecasting of the aggregated series compared to using the aggregated series alone. We used econometric techniques, such as the weighted lag adaptive least absolute shrinkage and selection operator, and Exponential Triple Smoothing (ETS), as well as the Autometrics algorithm to forecast industrial production in Brazil one to twelve months ahead. This is the novelty of the work, as is the use of the average multi-horizon Superior Predictive Ability (aSPA) and uniform multi-horizon Superior Predictive Ability (uSPA) tests, used to select the best forecasting model by combining different horizons. Our sample covers the period from January 2002 to February 2020. The disaggregated ETS has a better forecast performance when forecasting horizons that are more than one month ahead using the mean square error, and the aggregated ETS has better forecasting ability for horizons equal to 1 and 2. The aggregated ETS forecast does not contain information that is useful for forecasting industrial production in Brazil beyond the information already found in the disaggregated ETS forecast between two and twelve months ahead.
Preliminary Results of Biomass Gasification Obtained at Pilot Scale with an Innovative 100 kWth Dual Bubbling Fluidized Bed Gasifier
Authors: Di Carlo Andrea , Savuto Elisa , Foscolo Pier Ugo , Papa Alessandro Antonio , Tacconi Alessandra , Del Zotto Luca , Aydin Bora , Bocci Enrico
Published: June 2022

Biomass gasification is a favourable process to produce a H2-rich fuel gas from biogenic waste materials. In particular, the dual bubbling fluidized bed (DBFB) technology consists of the separation of the combustion chamber, fed with air, from the gasification chamber, fed with steam, allowing to obtain a concentrated syngas stream without N2 dilution. In a previous work, an innovative design of a DBFB reactor was developed and its hydrodynamics tested in a cold model; in this work, the novel gasifier was realized at pilot scale (100 kWth) and operated for preliminary biomass gasification tests. The results showed a high-quality syngas, composed of H2 = 35%, CO = 23%, CO2 = 20%, and CH4 = 11%, as a confirmation of the design efficacy in the separation of the reaction chambers. The dry gas yield obtained was 1.33 Nm3/kg of biomass feedstock and the carbon conversion was 73%. Tars were sampled and measured both in the raw syngas, giving a content of 12 g/Nm3, and downstream from a traditional conditioning system composed of a cyclone and a water scrubber, showing a residual tar content of 3 g/Nm3, mainly toluene. The preliminary tests showed promising results; further gasification tests are foreseen to optimize the main process parameters.
Engineered Microbial Cell Factories for Sustainable Production of L-Lactic Acid: A Critical Review
Authors: Liu Tiantian , Xu Xianhao , Liu Yanfeng , Li Jianghua , Du Guocheng , Lv Xueqin , Liu Long
Published: June 2022

With the increasing demand for the biodegradable polymer material polylactic acid and its advantage of being metabolized by the human body, L-lactic acid (L-LA) is becoming increasingly attractive in environmental protection and food industry applications. However, the supply of L-LA is not satisfied, and the price is still high. Compared to enzymatic and chemical synthesis methods, L-LA production by microbial fermentation has the advantages of low cost, large yield, simple operation, and environmental protection. This review summarizes the advances in engineering microbial cell factories to produce L-LA. First, the synthetic pathways and microorganisms for L-LA production are outlined. Then, the metabolic engineering strategies for constructing cell factories to overproduce L-LA are summarized and fermentation modes for L-LA production are also given. Finally, the challenges and prospects of the microbial production of L-LA are discussed. This review provides theoretical guidance for researchers engaged in L-LA production.
Changes and Driving Mechanism of Microbial Community Structure during Paocai Fermentation
Authors: Yan Pingmei , Jia Jingjing , Zhao Huwei , Wu Chendong
Published: June 2022

Fermentation of paocai is a dynamic process of the microbial community structure, and the interaction between community structure and physicochemical factors endows paocai with unique taste and flavor. The study of bacterial and fungal community structure changes and the driving mechanism of physicochemical factors induced changes in community structure, showing that Pseudomonas belonging to Proteobacteria and Lactobacillus belonging to Firmicutes were the dominant bacteria in the process of paocai fermentation. The correlation analysis of physicochemical factors with bacterial community showed that titratable acid was significantly positively correlated with Lactobacillus and negatively correlated with Pseudomonas, while nitrite was the opposite. Redundancy analysis (RDA) showed that pH was positively correlated with the bacterial community in the early fermentation stage, amino acid nitrogen was positively correlated with the bacterial community in the middle fermentation stage, and titratable acid was positively correlated with the bacterial community in the late fermentation stage. Variance partitioning analysis (VPA) showed that environmental factors, pH and metabolites, were the main driving forces of bacterial community diversity, which jointly explained 32.02% of the bacterial community structure variation. To study the glucolysis and nitrogen metabolism in the process of paocai fermentation, we found that in the early stage of the fermentation, the nitrite reductase enzyme of Pseudomonas activity was high, with high nitrite content in the prophase, but by the end of fermentation, lactic acid bacteria rapidly increased, the content of L−lactic acid through the glycolysis pathway, making paocai fermentation environment become acidic, then Pseudomonas decreased. Ascomycota and Basidiomycota were the main phylum fungi in the fermentation process. RDA analysis showed that the fungal community was positively correlated with pH, nitrite, and soluble protein at the early fermentation stage, amino acid nitrogen was positively correlated with the fungal community at the middle fermentation stage, titratable acid and reducing sugar were positively correlated with the fungal community at the late fermentation stage. VPA analysis showed that metabolites were the main driving force of fungal community diversity and accounted for 45.58% of fungal community diversity. These results had a certain guiding significance for the production and preservation of naturally fermented paocai.
Multilayer Backbones for Internet of Battlefield Things
Authors: Fragkou Evangelia , Papakostas Dimitrios , Kasidakis Theodoros , Katsaros Dimitrios
Published: June 2022

The Internet of Battlefield Things is a newly born cyberphysical system and, even though it shares a lot with the Internet of Things and with ad hoc networking, substantial research is required to cope with its scale and peculiarities. This article examines a fundamental problem pertaining to the routing of information, i.e., the calculation of a backbone network. We model an IoBT network as a network with multiple layers and employ the concept of domination for multilayer networks. This is a significant departure from earlier works, and in spite of the huge literature on the topic during the past twenty years, the problem in IoBT networks is different since these networks are multilayer networks, thus making inappropriate all the past, related literature because it deals with single layer (flat) networks. We establish the computational complexity of our problem, and design a distributed algorithm for computing connected dominating sets with small cardinality. We analyze the performance of the proposed algorithm on generated topologies, and compare it against two—the only existing—competitors. The proposed algorithm establishes itself as the clear winner in all experiments concerning the dominating set from a size-wise and an energy-wise perspective achieving a performance gain of about 15%.
Omics Analyses of Trichomonas vaginalis Actin and Tubulin and Their Participation in Intercellular Interactions and Cytokinesis
Authors: Lorenzo-Benito Sebastián , Rivera-Rivas Luis Alberto , Sánchez-Ayala Lizbeth , Ortega-López Jaime , Montes-Flores Octavio , Talamás-Lara Daniel , Arroyo Rossana
Published: June 2022

Actin and tubulin proteins from Trichomonas vaginalis are crucial for morphogenesis and mitosis. This parasite has 10 and 11 genes coding bonafide actin and tubulin proteins, respectively. Hence, the goal of this work was to analyze these actin and tubulin genes, their expression at the mRNA and protein levels, and their parasite localization in intercellular interaction and cytokinesis. Representative bonafide actin (tvact1) and tubulin (tvtubα1) genes were cloned into and expressed in Escherichia coli. The recombinant proteins TvACT1r and TvTUBα1r were affinity purified and used as antigens to produce polyclonal antibodies. These antibodies were used in 1DE and 2DE WB and indirect immunofluorescence assays (IFA). By IFA, actin was detected as a ring on the periphery of ameboid, ovoid, and cold-induced cyst-like parasites, on pseudopods of amoeboid parasites, and in cytoplasmic extensions (filopodia) in cell–cell interactions. Tubulin was detected in the axostyle, flagellum, undulating membrane, and paradesmose during mitosis. Paradesmose was observed by IFA mainly during cytokinesis. By scanning electron microscopy, a tubulin-containing nanotubular structure similar to the tunneling nanotubes (TNTs) was also detected in the last stage of cytokinesis. In conclusion, actin and tubulin are multigene families differentially expressed that play important roles in intercellular interactions and cytokinesis.
Caring for Homebound Veterans during COVID-19 in the U.S. Department of Veterans Affairs Medical Foster Home Program
Authors: Haverhals Leah M. , Manheim Chelsea E. , Katz Maya , Levy Cari R.
Published: June 2022

The onset of the COVID-19 pandemic made older, homebound adults with multiple chronic conditions increasingly vulnerable to contracting the virus. The United States (US) Department of Veterans Affairs (VA) Medical Foster Home (MFH) program cares for such medically complex veterans residing in the private homes of non-VA caregivers rather than institutional care settings like nursing homes. In this qualitative descriptive study, we assessed adaptations to delivering safe and effective health care during the early stages of the pandemic for veterans living in rural MFHs. From December 2020 to February 2021, we interviewed 37 VA MFH care providers by phone at 16 rural MFH programs across the US, including caregivers, program coordinators, and VA health care providers. Using both inductive and deductive approaches to thematic analysis, we identified themes reflecting adaptations to caring for rural MFH veterans, including care providers rapidly increased communication and education to MFH caregivers while prioritizing veteran safety. Telehealth visits also increased, MFH veterans were prioritized for in-home COVID-19 vaccinations, and strategies were applied to mitigate the social isolation of veterans and caregivers. The study findings illustrate the importance of clear, regular communication and intentional care coordination to ensure high-quality care for vulnerable, homebound populations during crises like the COVID-19 pandemic.
Screening for Mild Cognitive Impairment in the Preoperative Setting: A Narrative Review
Authors: Pas Mariska te , Olde Rikkert Marcel , Bouwman Arthur , Kessels Roy , Buise Marc
Published: June 2022

Cognitive impairment predisposes patients to the development of delirium and postoperative cognitive dysfunction. In particular, in older patients, the adverse sequelae of cognitive decline in the perioperative period may contribute to adverse outcomes after surgical procedures. Subtle signs of cognitive impairment are often not previously diagnosed. Therefore, the aim of this review is to describe the available cognitive screeners suitable for preoperative screening and their psychometric properties for identifying mild cognitive impairment, as preoperative workup may improve perioperative care for patients at risk for postoperative cognitive dysfunction. Electronic systematic and snowball searches of PubMed, PsycInfo, ClinicalKey, and ScienceDirect were conducted for the period 2015–2020. Major inclusion criteria for articles included those that discussed a screener that included the cognitive domain ‘memory’, that had a duration time of less than 15 min, and that reported sensitivity and specificity to detect mild cognitive impairment. Studies about informant-based screeners were excluded. We provided an overview of the characteristics of the cognitive screener, such as interrater and test-retest reliability correlations, sensitivity and specificity for mild cognitive impairment and cognitive impairment, and duration of the screener and cutoff points. Of the 4775 identified titles, 3222 were excluded from further analysis because they were published prior to 2015. One thousand four hundred and forty-eight titles did not fulfill the inclusion criteria. All abstracts of 52 studies on 45 screeners were examined of which 10 met the inclusion criteria. For these 10 screeners, a further snowball search was performed to obtain related studies, resulting in 20 articles. Screeners included in this review were the Mini-Cog, MoCA, O3DY, AD8, SAGE, SLUMS, TICS(-M), QMCI, MMSE2, and Mini-ACE. The sensitivity and specificity range to detect MCI in an older population is the highest for the MoCA, with a sensitivity range of 81–93% and a specificity range of 74–89%. The MoCA, with the highest combination of sensitivity and specificity, is a feasible and valid routine screening of pre-surgical cognitive function. This warrants further implementation and validation studies in surgical pathways with a large proportion of older patients.
Comparison of Measurements of External Load between Professional Soccer Players
Authors: Gholizadeh Roghayyeh , Nobari Hadi , Bolboli Lotfali , Siahkouhian Marefat , Brito João Paulo
Published: June 2022

Background: The excessive and rapid increases in training load (TL) may be responsible for most non-contact injuries in soccer. This study’s aims were to describe, week(w)-by-week, the acute (AW), chronic (CW), acute:chronic workload ratio (wACWR), total distance (wTD), duration training (wDT), sprint total distance (wSTD), repeat sprint (wRS), and maximum speed (wMS) between starter and non-starter professional soccer players based on different periods (i.e., pre-, early-, mid-, and end-season) of a full-season (Persian Gulf Pro League, 2019–2020). Methods: Nineteen players were divided according to their starting status: starters (n = 10) or non-starters (n = 9). External workload was monitored for 43 weeks: pre- from w1–w4; early- from w5–w17; mid- from w18–w30, and end-season from w31–w43. Results: In starters, AW, CW, and wACWR were greater than non-starters (p < 0.05) throughout the periods of early- (CW, p ≤ 0.0001), mid- (AW, p = 0.008; CW, p ≤ 0.0001; wACWR, p = 0.043), or end-season (AW, p = 0.035; CW, p = 0.017; wACWR, p = 0.010). Starters had a greater wTD (p ≤ 0.0001), wSTD (p ≤ 0.0001 to 0.003), wDT (p ≤ 0.0001 to 0.023), wRS (p ≤ 0.0001 to 0.018), and wMS (p ≤ 0.0001) than non-starters during early-, mid-, and end-season. Conclusion: Starters experienced more CW and AW during the season than non-starters, which underlines the need to design tailored training programs accounting for the differences between playing status.
A Comparative Study of Natural Language Processing Algorithms Based on Cities Changing Diabetes Vulnerability Data
Authors: Wang Siting , Song Fuman , Qiao Qinqun , Liu Yuanyuan , Chen Jiageng , Ma Jun
Published: June 2022

(1) Background: Poor adherence to management behaviors in Chinese Type 2 diabetes mellitus (T2DM) patients leads to an uncontrolled prognosis of diabetes, which results in significant economic costs for China. It is imperative to quickly locate vulnerability factors in the management behavior of patients with T2DM. (2) Methods: In this study, a thematic analysis of the collected interview materials was conducted to construct the themes of T2DM management vulnerability. We explored the applicability of the pre-trained models based on the evaluation metrics in text classification. (3) Results: We constructed 12 themes of vulnerability related to the health and well-being of people with T2DM in Tianjin. We considered that Bidirectional Encoder Representation from Transformers (BERT) performed better in this Natural Language Processing (NLP) task with a shorter completion time. With the splitting ratio of 6:3:1 and batch size of 64 for BERT, the test accuracy was 97.71%, the completion time was 10 min 24 s, and the macro-F1 score was 0.9752. (4) Conclusions: Our results proved the applicability of NLP techniques in this specific Chinese-language medical environment. We filled the knowledge gap in the application of NLP technologies in diabetes management. Our study provided strong support for using NLP techniques to rapidly locate vulnerability factors in T2DM management.