bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-Time Risk Assessment for Road Transportation of Hazardous Materials Based on GRU-DNN with Multimodal Feature Embedding
Authors: Yu Shanchuan , Li Yi , Xuan Zhaoze , Li Yishun , Li Gang
Published: November 2022

In this paper, a gated recurrent unit–deep neural network (GRU-DNN) model integrated with multimodal feature embedding (MFE) is developed to evaluate the real-time risk of hazmat road transportation based on various types of data for contributing factors. MFE was incorporated into the framework of a deep learning model in which discrete variables, continuous variables, and images were uniformly embedded. GRU is a pre-trained sub-model, and the DNN is able to directly use the relative structure and weights of the GRU, improving the poor classification and recognition results due to insufficient samples. Additionally, the model is trained and validated based on hazmat road transportation database consisting of 2100 samples with 20 real-time contributing factors and four risk levels in China. The accuracy (ACC), precision (PR), recall (RE), F1-score (F1), and areas under receiver-operating-characteristic curves (AUC) of the proposed model and other commonly used models are compared as performance measurements in numerical examples. Finally, Carlini & Wagner attack and three defenses of adversarial training, dimensionality reduction and prediction similarity are proposed in the training to improve the robustness of the model, alleviating the impact of noise and error on small-sized samples. The results demonstrate that the average ACC of the model reaches 93.51% and 87.6% on the training and validation sets, respectively. The prediction of accidents resulting in injury is the most accurate, followed by fatal accidents. Combined with the RE of 89.0%, the model exhibits excellent performance. In addition, the proposed model outperforms other widely used models based on the overall comparisons of ACC, AUC, F1 and PR-RE curve. Finally, prediction similarity can be used as an effective approach for robustness improvement, with the launched adversarial attacks being detected at a high success rate.
Identification and Classification of Aluminum Scrap Grades Based on the Resnet18 Model
Authors: Huang Bo , Liu Jianhong , Zhang Qian , Liu Kang , Li Kun , Liao Xinyu
Published: November 2022

In order to reduce the elemental species produced in the recycling and melting of aluminum scrap and to improve the quality of pure aluminum and aluminum alloys, it is necessary to classify the different grades of aluminum scrap before melting. For the problem of classifying different grades of aluminum scrap, most existing studies are conducted using laser-induced breakdown spectroscopy for identification and classification, which requires a clean and flat metal surface and enormous equipment costs. In this study, we propose a new classification and identification method for different grades of aluminum scrap based on the ResNet18 network model, which improves the identification efficiency and reduces the equipment cost. The objects of this research are three grades of aluminum scrap: 1060, 5052, and 6061. The surface features of the three grades were compared using a machine vision algorithm; three different datasets, using RGB, HSV, and LBP, were built for comparison to find the best training dataset for subsequent datasets, and the hyperparameters of learning rate and batch size were tuned for the ResNet18 model. The results show that there was a differentiation threshold between different grades through the comparison of surface features; the ResNet18 network model trained the three datasets, and the results showed that RGB was the best dataset. With hyperparameter optimization of the ResNet18 model, the accuracy of final classification and recognition could reach 100% and effectively achieve the classification of different grades of aluminum scrap.
A Multi-Scale Contextual Information Enhancement Network for Crack Segmentation
Authors: Zhang Lili , Liao Yang , Wang Gaoxu , Chen Jun , Wang Huibin
Published: November 2022

In recent years, convolutional neural-network-based crack segmentation methods have performed excellently. However, existing crack segmentation methods still suffer from background noise interference, such as dirt patches and pitting, as well as the imprecise segmentation of fine-grained spatial structures. This is mainly due to the fact that convolutional neural networks dilute low-level spatial information in the process of extracting deep semantic features, and the network cannot obtain accurate context awareness because of the limitation of the actual receptive field size. To address these problems, an encoder–decoder crack segmentation network based on multi-scale contextual information enhancement is proposed. First, a new architecture of skip connection is proposed, enabling the network to obtain refined crack segmentation results; then, a contextual feature enhancement module is designed to make the network more effective at distinguishing between cracks and background noise; finally, the deformable convolution is introduced into the encoder network to further enhance its ability to extract the diverse morphological features of cracks by adaptively adjusting the sampling area and the receptive field size. Experiments show that the proposed method is effective in crack segmentation and outperforms mainstream segmentation networks such as DeepLab V3+ and UNet++.
Image Quality for Near-Eye Display Based on Holographic Waveguides
Authors: Solomashenko Artem , Lushnikov Dmitrii , Shishova Maria , Afanaseva Olga , Zlokazov Evgenii
Published: November 2022

The paper analyzes the image quality in augmented reality display based on holographic waveguides. Brightness, brightness non-uniformity, image noise, etc., depend on the parameters of the waveguide substrate, the configuration, and the relief shape of diffraction optical elements. The optimal structure of holographic waveguides obtained by analog holography has been studied. The presented recommendations to achieve the best image quality are based on experimental results for different configurations of holographic waveguides.
A Smart Handheld Welding Torch Device for Manual Spot Laser Welding
Authors: Reis Murat , Şerifağaoğlu Emre
Published: November 2022

In producing custom-made systems, using a robotic welding line that can fine-tune welding parameters is not economical, and laser welding is usually done manually. The most common operator error in manual welding operations is the angular positioning error between the laser beam and the plate surface. This study introduces a smart handheld welding torch device that assists the welding operator with visual warnings. It measures the sheet surface angle to eliminate angular positioning errors, calculates the appropriate torch holding angles accordingly, and helps the laser welding process with the right angle. For this purpose, this study focused on micro-laser spot welding applications of stainless (inox) kitchen and hotel equipment, and the effect of angular positioning errors on the welding quality was investigated experimentally. Experiments show that when the angle between the surface normal and the welding torch is smaller than the critical welding angle, heat-induced traces or micro-deformations occur on the visible surface of the thin stainless material. In addition, there is a significant decrease in the weld quality, since a large enough weld area cannot be created at large values of this angle. The optimum torch angle range was determined using experimental results for the available laser welding parameters. With a standard welding torch and the smart torch, the welding operator was allowed to repeat the same task, and the payloads of the samples prepared in this way were measured. Test results show that using a smart welding torch with an angular positioning assist system significantly improves welding quality. Breaking force values vary in a wide range of welds made with a standard welding torch, and visual problems such as burning, puncture, and swelling are encountered on the visible surfaces of many samples with high strength values. When the developed smart torch was used, the breaking force remained within the desired reference range, and no visual defects were found in any sample.
Local Allergic Rhinitis: A Different Rhinitis Endotype? Literature Overview
Authors: Cantone Elena , Detoraki Aikaterini , De Corso Eugenio
Published: November 2022

Chronic rhinitis (CR) is commonly divided into allergic rhinitis (AR) and nonallergic rhinitis (NAR). AR is triggered by the immunoglobulin E (IgE)-mediated response to allergens, whereas NAR is characterized by the absence of allergic sensitization. Previous studies have demonstrated the presence of local IgE in the nasal mucosa of patients suffering from typical allergic rhinitis (AR) symptoms but without a history of atopy and a positive response to a nasal allergen challenge (NAC). This condition was recently defined as local allergic rhinitis (LAR), which is supposed to be a different CR characterized by a type 2 (T2) inflammation response with the release of typical T2 mediators. LAR is defined as a phenotype of AR characterized by a localized nasal allergic response that is negative skin prick testing to allergens in the absence of serum-specific IgE. Diagnosis is based on a positive response to NAC. This review is an update of LAR literature, focusing on the definition of LAR as an independent endotype. LAR, AR, and NAR are characterized by the same clinical symptoms, although there are some differences between these three subtypes. However, the literature data are not yet univocal in defining LAR as an independent endotype.
Biometric Performance as a Function of Gallery Size
Authors: Friedman Lee , Stern Hal , Prokopenko Vladyslav , Djanian Shagen , Griffith Henry , Komogortsev Oleg
Published: November 2022

Many developers of biometric systems start with modest samples before general deployment. However, they are interested in how their systems will work with much larger samples. To assist them, we evaluated the effect of gallery size on biometric performance. Identification rates describe the performance of biometric identification, whereas ROC-based measures describe the performance of biometric authentication (verification). Therefore, we examined how increases in gallery size affected identification rates (i.e., Rank-1 Identification Rate, or Rank-1 IR) and ROC-based measures such as equal error rate (EER). We studied these phenomena with synthetic data as well as real data from a face recognition study. It is well known that the Rank-1 IR declines with increasing gallery size, and that the relationship is linear against log(gallery size). We have confirmed this with synthetic and real data. We have shown that this decline can be counteracted with the inclusion of additional information (features) for larger gallery sizes. We have also described the curves which can be used to predict how much additional information would be required to stabilize the Rank-1 IR as a function of gallery size. These equations are also linear in log(gallery size). We have also shown that the entire ROC-curve was not systematically affected by gallery size, and so ROC-based scalar performance metrics such as EER are also stable across gallery size. Unsurprisingly, as additional uncorrelated features are added to the model, EER decreases. We were interested in determining the impact of adding more features on the median, spread and shape of similarity score distributions. We present evidence that these decreases in EER are driven primarily by decreases in the spread of the impostor similarity score distribution.
Robotic Peg-in-Hole Assembly Strategy Research Based on Reinforcement Learning Algorithm
Authors: Li Shaodong , Yuan Xiaogang , Niu Jie
Published: November 2022

To improve the robotic assembly effects in unstructured environments, a reinforcement learning (RL) algorithm is introduced to realize a variable admittance control. In this article, the mechanisms of a peg-in-hole assembly task and admittance model are first analyzed to guide the control strategy and experimental parameters design. Then, the admittance parameter identification process is defined as the Markov decision process (MDP) problem and solved with the RL algorithm. Furthermore, a fuzzy reward system is established to evaluate the action–state value to solve the complex reward establishment problem, where the fuzzy reward includes a process reward and a failure punishment. Finally, four sets of experiments are carried out, including assembly experiments based on the position control, fuzzy control, and RL algorithm. The necessity of compliance control is demonstrated in the first experiment. The advantages of the proposed algorithms are validated by comparing them with different experimental results. Moreover, the generalization ability of the RL algorithm is tested in the last two experiments. The results indicate that the proposed RL algorithm effectively improves the robotic compliance assembly ability.
Some Properties of a Concircular Curvature Tensor on Generalized Sasakian-Space-Forms
Authors: Chavan Vasant
Published: November 2022

The aim of the present paper is to study and investigate the geometrical properties of a concircular curvature tensor on generalized Sasakian-space-forms. In this manner, we obtained results for ϕ-concircularly flat, ϕ-semisymmetric, locally concircularly symmetric and locally concircularly ϕ-symmetric generalized Sasakian-space-forms. Finally, we construct examples of the generalized Sasakian-space-forms to verify some results.
Influence of pH, N, P, N: P Ratio, and Dissolved Inorganic Carbon on Ulva ohnoi Growth and Biomass Quality: Potential Implications in IMTA-RAS
Authors: Alamrousi Ahmed , Casais Eduardo , García-Cardesín Érika , Masaló Ingrid , Pintado José , Cremades Javier
Published: November 2022

Ulva ohnoi has a big potential in IMTA-RAS fish–seaweed systems. In order to design the best production strategy in these systems, the effect of the main environmental factors, such as pH, nutrient concentration (N, P, and N: P ratios) and dissolved inorganic carbon (DIC), on the productivity, bio filtration capacity, and quality of the biomass obtained was studied. It is concluded that in closed systems, strong pH variations (7.9–10.1) do not influence the growth of U. ohnoi and growth is slowed down due to the depletion of DIC. This fact would not be a problem in IMTA-RAS fish–macroalgae systems, due to the physiological activity of the fish contributing CO2 to the medium and replenishing it. The results obtained in the wide range of N: P ratios tested (2–410), allow us to conclude that this ratio should not be a limiting factor for the cultivation of Ulva ohnoi in IMTA-RAS systems. Based on those results, the best strategy to follow in an IMTA-RAS sole–sea lettuce would be to maintain the algae with highest level of nitrogen. This procedure implies a high rate of water renewal, which would also guarantee the maintenance of an adequate DIC and the best commercial quality of seaweed.
Generalized Mathematical Model of Brinkman Fluid with Viscoelastic Properties: Case over a Sphere Embedded in Porous Media
Authors: Kanafiah Siti Farah Haryatie Mohd , Kasim Abdul Rahman Mohd , Zokri Syazwani Mohd
Published: November 2022

The process of heat transfer that involves non-Newtonian fluids in porous regions has attracted considerable attention due to its practical application. A mathematical model is proposed for monitoring fluid flow properties and heat transmission in order to optimize the final output. Thus, this attempt aims to demonstrate the behavior of fluid flow in porous regions, using the Brinkman viscoelastic model for combined convective transport over a sphere embedded in porous medium. The governing partial differential equations (PDEs) of the proposed model are transformed into a set of less complex equations by applying the non-dimensional variables and non-similarity transformation, before they are numerically solved via the Keller-Box method (KBM) with the help of MATLAB software. In order to validate the model for the present issue, numerical values from current and earlier reports are compared in a particular case. The studied parameters such as combined convection, Brinkman and viscoelastic are analyzed to obtain the velocity and temperature distribution. Graphs are used to illustrate the variation in local skin friction and the Nusselt number. The results of this study showcase that when the viscoelastic and Brinkman parameters are enlarged, the fluid velocity drops and the temperature increases, while the combined convection parameter reacts in an opposite manner. Additionally, as the Brinkman and combined convection parameters are increased, the physical magnitudes of skin friction and Nusselt number are increased across the sphere. Of all the parameters reported in this study, the viscoelastic parameter could delay the separation of boundary layers, while the Brinkman and combined convection parameters show no effect on the flow separation. The results obtained can be used as a foundation for other complex boundary layer issues, particularly in the engineering field. The findings also can help researchers to gain a better understanding of heat transfer analysis and fluid flow properties.
Lithium-Ion Batteries Aging Mechanisms
Authors: Sgroi Mauro Francesco
Published: November 2022

Lithium batteries (including lithium-ion, lithium-sulfur and lithium-air cells) are considered a technology enabling industrial sectors, including electrified vehicles, consumer electronics and stationary energy storage [...]
Effects of Excessive Prelithiation on Full-Cell Performance of Li-Ion Batteries with a Hard-Carbon/Nanosized-Si Composite Anode
Authors: Abe Yusuke , Saito Ippei , Tomioka Masahiro , Kabir Mahmudul , Kumagai Seiji
Published: November 2022

The effects of excessive prelithiation on the full-cell performance of Li-ion batteries (LIBs) with a hard-carbon/nanosized-Si (HC/N-Si) composite anode were investigated; HC and N-Si simply mixed at mass ratios of 9:1 and 8:2 were analyzed. CR2032-type half- and full-cells were assembled to evaluate the electrochemical LIB anode behavior. The galvanostatic measurements of half-cell configurations revealed that the composite anode with an 8:2 HC/N-Si mass ratio exhibited a high capacity (531 mAh g−1) at 0.1 C and superior current-rate dependence (rate performance) at 0.1–10 C. To evaluate the practical LIB anode performance, the optimally performing composite anode was used in the full cell. Prior to full-cell assembly, the composite anodes were prelithiated via electrochemical Li doping at different cutoff anodic specific capacities (200–600 mAh g−1). The composite anode was paired with a LiNi0.5Co0.2Mn0.3O2 cathode to construct full-cells, the performance of which was evaluated by conducting sequential rate and cycling performance tests. Prelithiation affected only the cycling performance, without affecting the rate performance. Excellent capacity retention was observed in the full-cells with prelithiation conducted at cutoff anodic specific capacities greater than or equal to 500 mAh g−1.
Nanostructured Lead Electrodes with Reduced Graphene Oxide for High-Performance Lead–Acid Batteries
Authors: Rossini Matteo , Ganci Fabrizio , Zanca Claudio , Patella Bernardo , Aiello Giuseppe , Inguanta Rosalinda
Published: November 2022

Nanostructured Pb electrodes consisting of nanowire arrays were obtained by electrodeposition, to be used as negative electrodes for lead–acid batteries. Reduced graphene oxide was added to improve their performances. This was achieved via the electrochemical reduction of graphene oxide directly on the surface of nanowire arrays. The electrodes with and without reduced graphene oxide were tested in a 5 M sulfuric acid solution using a commercial pasted positive plate and an absorbed glass mat separator in a zero-gap configuration. The electrodes were tested in deep cycling conditions with a very low cut-off potential. Charge–discharge tests were performed at 5C. The electrode with reduced graphene oxide outperformed the electrode without reduced graphene oxide, as it was able to work with a very high utilization of active mass and efficiency. A specific capacity of 258 mAhg−1–very close to the theoretical one–was achieved, and the electrode lasted for more than 1000 cycles. On the other hand, the electrode without reduced graphene oxide achieved a capacity close to 230 mAhg−1, which corresponds to a 90% of utilization of active mass.
Non-Thermal Processing of a Protein Functional Beverage Using Pulsed Electric Fields: Escherichia coli Inactivation and Effect on Proteins
Authors: Alzahrani Mona , Silva Filipa V. M. , Alkhafaji Sally
Published: November 2022

The application of pulsed electric fields (PEFs) for the inactivation of Escherichia coli, suspended in a protein shake beverage and diluted with sterilized distilled water was carried out. Square bipolar pulses in the range of 25–40 kV/cm electric field intensities were applied at different frequencies (400–900 Hz) to investigate the effect of different PEF conditions on the microbial population and proteins relevant to this functional beverage. The treatment temperature was kept below the lethal temperature of the microorganism under investigation. As power consumption plays an important role in the efficiency of the PEF application, the dissipated power was also estimated. Four log reductions in the E. coli population were obtained with 10 pulses at a 40 kV/cm field intensity and 25 pulses at a 25 kV/cm field intensity. PEF-treated whey-protein concentrates showed less denaturation in proteins than thermally treated concentrates, especially for lower electric field intensities (0% denaturation ± 0.007 at 25 kV/cm and 900 Hz, 4.41% denaturation ± 0.008 at 40 kV/cm and 400 Hz). Soy protein isolates manifested high sensitivity to PEF processing and resulted in denaturation and aggregation in the protein structure.
A Narrative Review on Means to Promote Oxygenation and Angiogenesis in Oral Wound Healing
Authors: Ngeow Wei Cheong , Tan Chuey Chuan , Goh Yet Ching , Deliberador Tatiana Miranda , Cheah Chia Wei
Published: November 2022

Oral mucosa serves as the primary barrier against pathogen invasions, mechanical stresses, and physical trauma. Although it is generally composed of keratinocytes and held in place by desmosomes, it shows variation in tissue elasticity and surface keratinization at different sites of the oral cavity. Wound healing undergoes four stages of tissue change sequences, namely haemostasis, inflammation, proliferation, and remodelling. The wound healing of oral hard tissue and soft tissue is largely dependent on the inflammatory response and vascular response, which are the targets of many research. Because of a less-robust inflammatory response, favourable saliva properties, a unique oral environment, and the presence of mesenchymal stem cells, oral wounds are reported to demonstrate rapid healing, less scar formation, and fewer inflammatory reactions. However, delayed oral wound healing is a major concern in certain populations with autoimmune disorders or underlying medical issues, or those subjected to surgically inflicted injuries. Various means of approach have been adopted to improve wound tissue proliferation without causing excessive scarring. This narrative review reappraises the current literature on the use of light, sound, mechanical, biological, and chemical means to enhance oxygen delivery to wounds. The current literature includes the use of hyperbaric oxygen and topical oxygen therapy, ultrasounds, lasers, platelet-rich plasma (PRP)/platelet-rich fibrin (PRF), and various chemical agents such as hyaluronic acid, astaxanthin, and Centella asiatica to promote angiogenesis in oral wound healing during the proliferation process. The arrival of a proprietary oral gel that is reported to improve oxygenation is highlighted.
Enhancing Bioenergy Production from the Raw and Defatted Microalgal Biomass Using Wastewater as the Cultivation Medium
Authors: Li Gang , Hao Yuhang , Yang Tenglun , Xiao Wenbo , Pan Minmin , Huo Shuhao , Lyu Tao
Published: November 2022

Improving the efficiency of using energy and decreasing impacts on the environment will be an inevitable choice for future development. Based on this direction, three kinds of medium (modified anaerobic digestion wastewater, anaerobic digestion wastewater and a standard growth medium BG11) were used to culture microalgae towards achieving high-quality biodiesel products. The results showed that microalgae culturing with anaerobic digestate wastewater could increase lipid content (21.8%); however, the modified anaerobic digestion wastewater can boost the microalgal biomass production to 0.78 ± 0.01 g/L when compared with (0.35–0.54 g/L) the other two groups. Besides the first step lipid extraction, the elemental composition, thermogravimetric and pyrolysis products of the defatted microalgal residues were also analysed to delve into the utilisation potential of microalgae biomass. Defatted microalgae from modified wastewater by pyrolysis at 650 °C resulted in an increase in the total content of valuable products (39.47%) with no significant difference in the content of toxic compounds compared to other groups. Moreover, the results of the life cycle assessment showed that the environmental impact (388.9 mPET2000) was lower than that of raw wastewater (418.1 mPET2000) and standard medium (497.3 mPET2000)-cultivated groups. Consequently, the method of culturing microalgae in modified wastewater and pyrolyzing algal residues has a potential to increase renewable energy production and reduce environmental impact.
Gait Initiation Impairment in Patients with Parkinson’s Disease and Freezing of Gait
Authors: Palmisano Chiara , Beccaria Laura , Haufe Stefan , Volkmann Jens , Pezzoli Gianni , Isaias Ioannis U.
Published: November 2022

Freezing of gait (FOG) is a sudden episodic inability to produce effective stepping despite the intention to walk. It typically occurs during gait initiation (GI) or modulation and may lead to falls. We studied the anticipatory postural adjustments (imbalance, unloading, and stepping phase) at GI in 23 patients with Parkinson’s disease (PD) and FOG (PDF), 20 patients with PD and no previous history of FOG (PDNF), and 23 healthy controls (HCs). Patients performed the task when off dopaminergic medications. The center of pressure (CoP) displacement and velocity during imbalance showed significant impairment in both PDNF and PDF, more prominent in the latter patients. Several measurements were specifically impaired in PDF patients, especially the CoP displacement along the anteroposterior axis during unloading. The pattern of segmental center of mass (SCoM) movements did not show differences between groups. The standing postural profile preceding GI did not correlate with outcome measurements. We have shown impaired motor programming at GI in Parkinsonian patients. The more prominent deterioration of unloading in PDF patients might suggest impaired processing and integration of somatosensory information subserving GI. The unaltered temporal movement sequencing of SCoM might indicate some compensatory cerebellar mechanisms triggering time-locked models of body mechanics in PD.
A Bioinformatics View on Acute Myeloid Leukemia Surface Molecules by Combined Bayesian and ABC Analysis
Authors: Thrun Michael C. , Mack Elisabeth K. M. , Neubauer Andreas , Haferlach Torsten , Frech Miriam , Ultsch Alfred , Brendel Cornelia
Published: November 2022

“Big omics data” provoke the challenge of extracting meaningful information with clinical benefit. Here, we propose a two-step approach, an initial unsupervised inspection of the structure of the high dimensional data followed by supervised analysis of gene expression levels, to reconstruct the surface patterns on different subtypes of acute myeloid leukemia (AML). First, Bayesian methodology was used, focusing on surface molecules encoded by cluster of differentiation (CD) genes to assess whether AML is a homogeneous group or segregates into clusters. Gene expressions of 390 patient samples measured using microarray technology and 150 samples measured via RNA-Seq were compared. Beyond acute promyelocytic leukemia (APL), a well-known AML subentity, the remaining AML samples were separated into two distinct subgroups. Next, we investigated which CD molecules would best distinguish each AML subgroup against APL, and validated discriminative molecules of both datasets by searching the scientific literature. Surprisingly, a comparison of both omics analyses revealed that CD339 was the only overlapping gene differentially regulated in APL and other AML subtypes. In summary, our two-step approach for gene expression analysis revealed two previously unknown subgroup distinctions in AML based on surface molecule expression, which may guide the differentiation of subentities in a given clinical–diagnostic context.
Holistic Design of Experiments Using an Integrated Process Model
Authors: Oberleitner Thomas , Zahel Thomas , Pretzner Barbara , Herwig Christoph
Published: November 2022

Statistical experimental designs such as factorial, optimal, or definitive screening designs represent the state of the art in biopharmaceutical process characterization. However, such methods alone do not leverage the fact that processes operate as a mutual interplay of multiple steps. Instead, they aim to investigate only one process step at a time. Here, we want to develop a new experimental design method that seeks to gain information about final product quality, placing the right type of run at the right unit operation. This is done by minimizing the simulated out-of-specification rate of an integrated process model comprised of a chain of regression models that map process parameters to critical quality attributes for each unit operation. Unit operation models are connected by passing their response to the next unit operation model as a load parameter, as is done in real-world manufacturing processes. The proposed holistic DoE (hDoE) method is benchmarked against standard process characterization approaches in a set of in silico simulation studies where data are generated by different ground truth processes to illustrate the validity over a range of scenarios. Results show that the hDoE approach leads to a >50% decrease in experiments, even for simple cases, and, at the same time, achieves the main goal of process development, validation, and manufacturing to consistently deliver product quality.
A Biocultural Study on Gaoligongshan Pig (Sus scrofa domesticus), an Important Hog Landrace, in Nujiang Prefecture of China
Authors: Chu Yanan , Lin Chen , Cheng Zhuo , Zhao Xingcen , Fan Yanxiao , Luo Binsheng , Long Chunlin
Published: November 2022

Over 80% proteins consumed by the local people in Nujiang Prefecture of Southwest China, a remote and mountainous area in the Eastern Himalayas, are from pork, or Gaoligongshan pig (a landrace of Sus scrofa domestica Brisson). Previous research on the Gaoligongshan pig has focused on nutritional composition, production performance, and genetic resource characteristics, but neglected the reasons behind the local people’s practice. From 2019 to 2022, we have used ethnobiological research methods to comprehensively document the traditional rearing and management patterns and the traditional culture associated with Gaoligongshan pigs. The results show that Gaoligongshan pigs graze in mixed herds with cattle and sheep during the day and prefer to eat 23 wild plant species, in which 17 species have medicinal values. At night, the pigs are artificially fed and rest in the pigsty. The local Bai and Lisu people have developed a creative food culture, rituals, and festivals culture associated with Gaoligongshan pigs. Overall, the biocultural diversity of Gaoligongshan pig contributes to the in situ conservation of genetic diversity of this important hog landrace, and supports rural development in this remote area.
Associations among Maturity, Accumulated Workload, Physiological, and Body Composition Factors in Youth Soccer Players: A Comparison between Playing Positions
Authors: Nobari Hadi , Eken Özgür , Prieto-González Pablo , Brito João Paulo , Oliveira Rafael
Published: November 2022

The purposes of this study were: (i) to analyze the correlation between accumulated workload (AW)—based on season periods—with maturity, linear sprints, maximum oxygen uptake (VO2max), maximum heart rate, and body composition; and (ii) to compare the playing positions based on the mentioned parameters. Twenty-one elite soccer players under the age of 14 participated in the study. They were divided into five groups based on playing positions. The in-season weekly AW was recorded for 26 weeks into two separated periods of 13 weeks (AW-1 and AW-2). Similarly, the following parameters were assessed: body mass, standing and sitting height, body mass index, body fat percentage, maturity offset, age at peak height velocity (PHV), sprinting ability (10 m and 30 m), and VO2max. The main significant differences between playing positions were found for weight, height, sitting height, and sprinting at 10 m and 30 m. No correlation was observed between AW (based on periods) and maturity or between VO2max and AW-2. AW-1 denoted a large positive correlation with AW-2. AW-1 had a moderate negative correlation with VO2max, whereas PHV and maturity presented a strong negative correlation. Young soccer players’ maturity statuses and fitness levels do not imply differences between AW-1 and AW-2. However, the higher the AW in the first half of the season, the higher the AW in the second half. The absence of significant differences between player positions could be associated with the similar training regardless of the playing position. Moreover, soccer positively influences performance in short sprints (10 m), midfielders being the fastest.
2-Cell-like Cells: An Avenue for Improving SCNT Efficiency
Authors: Fu Bo , Ma Hong , Liu Di
Published: November 2022

After fertilization, the zygote genome undergoes dramatic structural reorganization to ensure the establishment of totipotency, and then the totipotent potential of the zygote or 2-cell-stage embryo progressively declines. However, cellular potency is not always a one-way street. Specifically, a small number of embryonic stem cells (ESCs) occasionally overcome epigenetic barriers and transiently convert to a totipotent status. Despite the significant potential of the somatic cell nuclear transfer (SCNT) technique, the establishment of totipotency is often deficient in cloned embryos. Because of this phenomenon, the question arises as to whether strategies attempting to induce 2-cell-like cells (2CLCs) can provide practical applications, such as reprogramming of somatic cell nuclei. Inspired by strategies that convert ESCs into 2CLCs, we hypothesized that there will be a similar pathway by which cloned embryos can establish totipotent status after SCNT. In this review, we provide a snapshot of the practical strategies utilized to induce 2CLCs during investigations of the development of cloned embryos. The 2CLCs have similar transcriptome and chromatin features to that of 2-cell-stage embryos, and we propose that 2CLCs, already a valuable in vitro model for dissecting totipotency, will provide new opportunities to improve SCNT efficiency.
Computational Investigation of 1, 3, 4 Oxadiazole Derivatives as Lead Inhibitors of VEGFR 2 in Comparison with EGFR: Density Functional Theory, Molecular Docking and Molecular Dynamics Simulation Studies
Authors: Bilal Muhammad Sajjad , Ejaz Syeda Abida , Zargar Seema , Akhtar Naveed , Wani Tanveer A. , Riaz Naheed , Aborode Adullahi Tunde , Siddique Farhan , Altwaijry Nojood , Alkahtani Hamad M. , Umar Haruna Isiyaku
Published: November 2022

Vascular endothelial growth factor (VEGF) is an angiogenic factor involved in tumor growth and metastasis. Gremlin has been proposed as a novel therapeutic pathway for the treatment of renal inflammatory diseases, acting via VEGFR 2 receptor. To date, most FDA-approved tyrosine kinase (TK) inhibitors have been reported as dual inhibitors of EGFR and VEGFR 2. The aim of the present study was to find the potent and selective inhibitor of VEGFR 2 specifically for the treatment of renal cancer. Fourteen previously identified anti-inflammatory compounds i.e., 1, 3, 4 oxadiazoles derivatives by our own group were selected for their anti-cancer potential, targeting the tyrosine kinase (TK) domain of VEGFR2 and EGFR. A detailed virtual screening-based study was designed viz density functional theory (DFT) study to find the compounds’ stability and reactivity, molecular docking for estimating binding affinity, SeeSAR analysis and molecular dynamic simulations to confirm protein ligand complex stability and ADMET properties to find the pharmacokinetic profile of all compounds. The DFT results suggested that among all the derivatives, the 7g, 7j, and 7l were chemically reactive and stable derivatives. The optimized structures obtained from the DFTs were further selected for molecular docking, and the results suggested that 7g, 7j and 7l derivatives as the best inhibitors of VEGFR 2 with binding energy values −46.32, −48.89 and −45.01 kJ/mol. The Estimated inhibition constant (IC50) of hit compound 7j (0.009 µM) and simulation studies of its complexes confirms its high potency and best inhibitor of VEGFR2. All the derivatives were also docked with EGFR, where they showed weak binding energies and poor interactions, important compound 7g, 7j and 7i exhibited binding energy of −31.01, −33.23 and −34.19 kJ/mol respectively. Furthermore, the anticancer potential of the derivatives was confirmed by cell viability (MTT) assay using breast cancer and cervical cancer cell lines. At the end, the results of ADMET studies confirmed these derivatives as drug like candidates. Conclusively, the current study suggested substituted oxadiazoles as the potential anticancer compounds which exhibited more selectivity towards VEGFR2 in comparison to EGFR. Therefore, the identified lead molecules can be used for the synthesis of more potent derivatives of VEGFR2, along with extensive in vitro and in vivo experiments, that can be used to treat various cancers, especially renal cancers, and to prevent angiogenesis due to aberrant expression of VEGFR2.
Molecular Pathways of the Therapeutic Effects of Ayahuasca, a Botanical Psychedelic and Potential Rapid-Acting Antidepressant
Authors: Rossi Giordano Novak , Guerra Lorena T. L. , Baker Glen B. , Dursun Serdar M. , Saiz José Carlos Bouso , Hallak Jaime E. C. , dos Santos Rafael G.
Published: November 2022

Ayahuasca is a psychoactive brew traditionally used in indigenous and religious rituals and ceremonies in South America for its therapeutic, psychedelic, and entheogenic effects. It is usually prepared by lengthy boiling of the leaves of the bush Psychotria viridis and the mashed stalks of the vine Banisteriopsis caapi in water. The former contains the classical psychedelic N,N-dimethyltryptamine (DMT), which is thought to be the main psychoactive alkaloid present in the brew. The latter serves as a source for β-carbolines, known for their monoamine oxidase-inhibiting (MAOI) properties. Recent preliminary research has provided encouraging results investigating ayahuasca’s therapeutic potential, especially regarding its antidepressant effects. On a molecular level, pre-clinical and clinical evidence points to a complex pharmacological profile conveyed by the brew, including modulation of serotoninergic, glutamatergic, dopaminergic, and endocannabinoid systems. Its substances also interact with the vesicular monoamine transporter (VMAT), trace amine-associated receptor 1 (TAAR1), and sigma-1 receptors. Furthermore, ayahuasca’s components also seem to modulate levels of inflammatory and neurotrophic factors beneficially. On a biological level, this translates into neuroprotective and neuroplastic effects. Here we review the current knowledge regarding these molecular interactions and how they relate to the possible antidepressant effects ayahuasca seems to produce.
DAR 16-II Primes Endothelial Cells for Angiogenesis Improving Bone Ingrowth in 3D-Printed BCP Scaffolds and Regeneration of Critically Sized Bone Defects
Authors: Alfayez Eman , Veschini Lorenzo , Dettin Monica , Zamuner Annj , Gaetani Massimiliano , Carreca Anna P. , Najman Stevo , Ghanaati Shahram , Coward Trevor , Di Silvio Lucy
Published: November 2022

Bone is a highly vascularized tissue and relies on the angiogenesis and response of cells in the immediate environmental niche at the defect site for regeneration. Hence, the ability to control angiogenesis and cellular responses during osteogenesis has important implications in tissue-engineered strategies. Self-assembling ionic-complementary peptides have received much interest as they mimic the natural extracellular matrix. Three-dimensional (3D)-printed biphasic calcium phosphate (BCP) scaffolds coated with self-assembling DAR 16-II peptide provide a support template with the ability to recruit and enhance the adhesion of cells. In vitro studies demonstrated prompt the adhesion of both human umbilical vein endothelial cells (HUVEC) and human mesenchymal stem cells (hMSC), favoring endothelial cell activation toward an angiogenic phenotype. The SEM-EDS and protein micro bicinchoninic acid (BCA) assays demonstrated the efficacy of the coating. Whole proteomic analysis of DAR 16-II-treated HUVECs demonstrated the upregulation of proteins involved in cell adhesion (HABP2), migration (AMOTL1), cytoskeletal re-arrangement (SHC1, TMOD2), immuno-modulation (AMBP, MIF), and morphogenesis (COL4A1). In vivo studies using DAR-16-II-coated scaffolds provided an architectural template, promoting cell colonization, osteogenesis, and angiogenesis. In conclusion, DAR 16-II acts as a proactive angiogenic factor when adsorbed onto BCP scaffolds and provides a simple and effective functionalization step to facilitate the translation of tailored 3D-printed BCP scaffolds for clinical applications.
Food Protein-Derived Antioxidant Peptides: Molecular Mechanism, Stability and Bioavailability
Authors: Zhu Yongsheng , Lao Fei , Pan Xin , Wu Jihong
Published: November 2022

The antioxidant activity of protein-derived peptides was one of the first to be revealed among the more than 50 known peptide bioactivities to date. The exploitation value associated with food-derived antioxidant peptides is mainly attributed to their natural properties and effectiveness as food preservatives and in disease prevention, management, and treatment. An increasing number of antioxidant active peptides have been identified from a variety of renewable sources, including terrestrial and aquatic organisms and their processing by-products. This has important implications for alleviating population pressure, avoiding environmental problems, and promoting a sustainable shift in consumption. To identify such opportunities, we conducted a systematic literature review of recent research advances in food-derived antioxidant peptides, with particular reference to their biological effects, mechanisms, digestive stability, and bioaccessibility. In this review, 515 potentially relevant papers were identified from a preliminary search of the academic databases PubMed, Google Scholar, and Scopus. After removing non-thematic articles, articles without full text, and other quality-related factors, 52 review articles and 122 full research papers remained for analysis and reference. The findings highlighted chemical and biological evidence for a wide range of edible species as a source of precursor proteins for antioxidant-active peptides. Food-derived antioxidant peptides reduce the production of reactive oxygen species, besides activating endogenous antioxidant defense systems in cellular and animal models. The intestinal absorption and metabolism of such peptides were elucidated by using cellular models. Protein hydrolysates (peptides) are promising ingredients with enhanced nutritional, functional, and organoleptic properties of foods, not only as a natural alternative to synthetic antioxidants.
High-Throughput Molecular Dynamics-Based Alchemical Free Energy Calculations for Predicting the Binding Free Energy Change Associated with the Selected Omicron Mutations in the Spike Receptor-Binding Domain of SARS-CoV-2
Authors: Bhadane Rajendra , Salo-Ahen Outi M. H.
Published: November 2022

The ongoing pandemic caused by SARS-CoV-2 has gone through various phases. Since the initial outbreak, the virus has mutated several times, with some lineages showing even stronger infectivity and faster spread than the original virus. Among all the variants, omicron is currently classified as a variant of concern (VOC) by the World Health Organization, as the previously circulating variants have been replaced by it. In this work, we have focused on the mutations observed in omicron sub lineages BA.1, BA.2, BA.4 and BA.5, particularly at the receptor-binding domain (RBD) of the spike protein that is responsible for the interactions with the host ACE2 receptor and binding of antibodies. Studying such mutations is particularly important for understanding the viral infectivity, spread of the disease and for tracking the escape routes of this virus from antibodies. Molecular dynamics (MD) based alchemical free energy calculations have been shown to be very accurate in predicting the free energy change, due to a mutation that could have a deleterious or a stabilizing effect on either the protein itself or its binding affinity to another protein. Here, we investigated the significance of five spike RBD mutations on the stability of the spike protein binding to ACE2 by free energy calculations using high throughput MD simulations. For comparison, we also used conventional MD simulations combined with a Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) based approach, and compared our results with the available experimental data. Overall, the alchemical free energy calculations performed far better than the MM-GBSA approach in predicting the individual impact of the mutations. When considering the experimental variation, the alchemical free energy method was able to produce a relatively accurate prediction for N501Y, the mutant that has previously been reported to increase the binding affinity to hACE2. On the other hand, the other individual mutations seem not to have a significant effect on the spike RBD binding affinity towards hACE2.
Positive Association between Preserved C-Peptide and Cognitive Function in Pregnant Women with Type-1 Diabetes
Authors: Ivanisevic Marina , Marcinko Darko , Vuckovic-Rebrina Sandra , Delmis Josip
Published: November 2022

This study focused on the cognitive function of women with type 1 diabetes in pregnancy. We investigated risk factors for a low cognitive score such as age, duration of Diabetes, BMI, subclinical hypothyroidism, cardiovascular autonomic neuropathy, the impact of hypo-/hyperglycemia, and C-peptide preservation. Material and methods. Seventy-eight pregnant women with type 1 diabetes (age 31.1 ± 5.4 years, diabetes duration 14.3 ± 8.9 years) were included in the study. Cognitive function was assessed in different domains, such as reasoning, memory, attention, coordination, and perception. Results. The cognitive test values ≥400 were considered high scores, and values <400 were considered low. Relative risks for low scores for general cognitive function were associated with increased BMI > 25 kg/m2 2.208 (95% CI 1.116–4.370), HbA1c > 6.5% RR 0.774 (95% CI 0.366–1.638), subclinical hypothyroidism RR 3.111 (95% CI 1.140–8.491), and impaired cardiovascular autonomic neuropathy RR 2.250 (95% CI 1.000–5.062). Pregnant women with a lower score for general cognitive function had higher BMI and higher leptin levels. Preserved C-peptide reduces the risk for cognitive impairment (RR 0.297 (95% CI 0.097–0.912)) in pregnant women with type 1 diabetes Conclusion. BMI > 25 kg/m2, subclinical hypothyroidism, and cardiovascular autonomic neuropathy are associated with increased risk, and postprandial C-peptide preservation with reduced risk for cognitive impairment in pregnant women with type 1 diabetes.