bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Tea Tree Oil on Production Performance, Serum Parameter Indices, and Immunity in Postpartum Dairy Cows
Authors: Yuan Cong , Ma Xiaoyu , Jiang Maocheng , Yang Tianyu , Lin Miao , Zhao Guoqi , Zhan Kang
Published: February 2023

Tea tree oil (TTO) plays an important role in regulating lipid metabolism and has anti-inflammatory properties. In postpartum dairy cows, dry matter intake (DMI) is dramatically decreased, resulting in lipid metabolism disorder and the systemic pro-inflammatory response. However, the effects of TTO on glucolipid metabolism and immunity in postpartum dairy cows remain uninvestigated. Therefore, this study aimed to evaluate the effects of TTO on production performance, serum biochemical indicators, and immunity in postpartum dairy cows. Our results demonstrate that DMI tended to increase (p = 0.07) in the total mixed ration (TMR) diets supplemented with 0.01% TTO/dry matter (DM) basis relative to that in the control group. The 4% fat-corrected milk (FCM) content in the 0.01% and 0.02% TTO groups showed an increase (p = 0.09) compared with that in the control. Remarkably, the levels of globulin (GLO) and immunoglobulin G (IgG) were elevated (p < 0.05) in the TMR diet supplemented with 0.02% TTO compared to those in the control group. The TTO caused no profound changes in cholesterol (CHO), triglyceride (TG), high-density lipoprotein (HDL), or low-density lipoprotein (LDL). Notably, 0.02% TTO increased (p < 0.05) the serum glucose concentration relative to that in the control group. In conclusion, our results demonstrate that TTO could improve glucolipid metabolism and enhance immunity in postpartum dairy cows. It may be a novel resolution strategy for body condition recovery and the improvement of milk performance.
Physicochemical Properties of Black Korean Goat Meat with Various Slaughter Ages
Authors: Choi Da-Mi , Kang Kyu-Min , Kang Sun-Moon , Kim Hack-Youn
Published: February 2023

This study was conducted to analyze the physicochemical properties of black goat meat according to the slaughter age (3, 6, 9, 12, 24, 36 months). The moisture content tended to decrease, whereas the fat content, pH, and free amino acid composition tended to increase with increasing slaughter age. The collagen content increased significantly with the increasing slaughter age (p < 0.05). The cooking yield showed a tendency to increase up to 12 months of age, and there was no significant difference after 12 months of age. In all mineral contents, the sample for 12 months of age showed higher values than the others. Considering fatty acid composition, the saturated fatty acid content of the 12-month sample had a lower value than the other samples. However, the unsaturated fatty acid of the 12-month sample had higher values than the other samples. Therefore, the best slaughter age for black goats occurs at 12 months of age when nutrition is excellent.
Dietary Supplementation of Eubiotic Fiber Based on Lignocellulose on Performance and Welfare of Gestating and Lactating Sows
Authors: Odakura Agnês Markiy , Caldara Fabiana Ribeiro , Burbarelli Maria Fernanda de Castro , Almeida Paz Ibiara Correia de Lima , Garcia Rodrigo Garófallo , Oliveira dos Santos Viviane Maria , de Brito Mandu Daniella Ferreira , Braz Jaqueline Murback , Lourenço da Silva Marconi Italo
Published: February 2023

The present study aimed to evaluate the effects of partially fermentable insoluble dietary fiber supplementation on the behavior, surface temperature, and reproductive parameters of gestating and lactating sows, as well as on the performance of their litters. Four hundred hyper-prolific sows were assigned in a randomized block design with two treatment groups during the gestation phase: Control (C), corn-soy based diets, or corn-soy based diets with daily 55 g supplementation of eubiotic fiber (F) from the 85th day of gestation until the farrowing (late pregnancy). During the lactation phase, the sows were assigned in a 2 × 2 factorial design using the following treatment groups: (1) CC, no fiber included during gestation and lactation. (2) FC, daily inclusion of 55 g of fiber only during late pregnancy. (3) CF, daily inclusion of 55 g of fiber only during lactation. (4) FF, daily inclusion of 55 g of fiber during late pregnancy and lactation. Sows that received dietary fiber supplementation during the final third of gestation increased feed intake during lactation. Piglets from sows supplemented in both phases showed a significant increase in weight at weaning. The dietary supplementation of eubiotic fiber for sows in the end period of gestation and lactation improved performance and welfare, with positive consequences for developing their litters.
Mercury in Selected Abiotic and Biotic Elements in Two Lakes in Poland: Implications for Environmental Protection and Food Safety
Authors: Rajkowska-Myśliwiec Monika , Protasowicki Mikołaj
Published: February 2023

Mercury, which tends to bioaccumulate and biomagnify in aquatic food webs, poses a potential health risk to wildlife and to consumers of predatory fish in particular. Its concentration in biota can be high even at low environmental concentrations. Therefore, the aim of this study was to determine mercury in both abiotic (water and sediment) and biotic elements (common reed (Phragmites australis) and fish: pike (Esox lucius), bream (Abramis brama) and roach (Rutilus rutilus)) in the context of assessing the pollution of two lakes in Poland and the safety of fish consumers. The possibility of Hg biomagnification in fish was also considered. Mercury was determined by means of cold vapor atomic absorption spectrometry (CVAAS). The concentrations of Hg in water and bottom sediments of Lake Ińsko were lower than in Lake Wisola. In the bottom sediments of both lakes, a positive correlation was found between the Hg content and organic matter. The concentration of mercury in the organs of common reed did not exceed 0.017 mg/kg dry weight (dw), and its distribution can be presented as follows: root > leaves > stems > rhizomes. In fish organs from both lakes, the average mercury content did not exceed 0.086 mg/kg of wet weight (ww) and in most cases it was the highest in pike. Higher values were only observed in the muscles and skin of roach. This indicates a lack of biomagnification in the relationships between planktivorous-predatory and benthivores-predatory fish. Based on the maximum levels of mercury in fish and the calculated parameters, i.e., estimated daily intake (EDI), target hazard quotient (THQ) and tolerable weekly intake (TWI), the muscles of the examined fish were found to be safe for consumption. The average dietary exposure to total mercury (THg) and methylmercury (MeHg) was below 0.3% of the TWI.
A Comparative Study on the Effect of Euthanasia Methods and Sample Storage Conditions on RNA Yield and Quality in Porcine Tissues
Authors: Chakkingal Bhaskaran Bimal , Meyermans Roel , Gorssen Wim , Maes Gregory Erich , Janssens Steven , Buys Nadine
Published: February 2023

Animals used in research often have to be euthanised, especially when tissue sampling is essential. Recently, a euthanasia method, utilizing an inhalant anaesthetic ‘nitrogen gas in foam’ in an anoxia box (ANOXIATM), has gained considerable interest as it claimed to be more animal-friendly. However, it is not clear whether the use of this euthanasia method has an influence on RNA measurements. Moreover, there are no studies on the interaction effect of different euthanasia methods on the tissue sample storage conditions. The current study compared RNA measurements from two euthanasia methods (ANOXIATM vs. T-61® injection) and two storage conditions (RNAlater™ vs. snap freezing) in 12 male piglets. The nitrogen anoxia method had a significantly higher RNA yield (p < 0.01) compared to the T-61® method. However, no effect of the euthanasia methods on the A260/230 ratio and RIN value was observed. Tissues stored in RNAlater™ had significantly higher RIN values (p < 0.001) compared to snap frozen samples. The present study could not find a significant difference between the two euthanasia methods in piglets, with regard to RNA quality measurements. Hence, the nitrogen anoxia technique (ANOXIATM) might be considered as a suitable alternative to T-61® for euthanasia of piglets used in research.
CD38-Induced Metabolic Dysfunction Primes Multiple Myeloma Cells for NAD+-Lowering Agents
Authors: Becherini Pamela , Soncini Debora , Ravera Silvia , Gelli Elisa , Martinuzzi Claudia , Giorgetti Giulia , Cagnetta Antonia , Guolo Fabio , Ivaldi Federico , Miglino Maurizio , Aquino Sara , Todoerti Katia , Neri Antonino , Benzi Andrea , Passalacqua Mario , Nencioni Alessio , Perrotta Ida , Gallo Cantafio Maria Eugenia , Amodio Nicola , De Flora Antonio , Bruzzone Santina , Lemoli Roberto M. , Cea Michele
Published: February 2023

Cancer cells fuel growth and energy demands by increasing their NAD+ biosynthesis dependency, which therefore represents an exploitable vulnerability for anti-cancer strategies. CD38 is a NAD+-degrading enzyme that has become crucial for anti-MM therapies since anti-CD38 monoclonal antibodies represent the backbone for treatment of newly diagnosed and relapsed multiple myeloma patients. Nevertheless, further steps are needed to enable a full exploitation of these strategies, including deeper insights of the mechanisms by which CD38 promotes tumorigenesis and its metabolic additions that could be selectively targeted by therapeutic strategies. Here, we present evidence that CD38 upregulation produces a pervasive intracellular-NAD+ depletion, which impairs mitochondrial fitness and enhances oxidative stress; as result, genetic or pharmacologic approaches that aim to modify CD38 surface-level prime MM cells to NAD+-lowering agents. The molecular mechanism underlying this event is an alteration in mitochondrial dynamics, which decreases mitochondria efficiency and triggers energetic remodeling. Overall, we found that CD38 handling represents an innovative strategy to improve the outcomes of NAD+-lowering agents and provides the rationale for testing these very promising agents in clinical studies involving MM patients.
Automatic Configuration of an Order as an Integral Part of a Cyber-Physical System in a Manufacturing Operating According to Mass-Customisation Strategy
Authors: Dudek Adam , Patalas-Maliszewska Justyna , Kowalczewska Katarzyna
Published: February 2023

The contemporary consumer market determines the use of mass customisation by manufacturers. Therefore, from the point of view of Industry 4.0 (I4.0), concept data and communications and analytics are relevant to the implementation of the mass-customisation strategy. The problem involves at least three subjects: how to connect the currently available information system within an enterprise with new I4.0 technologies, how new information solutions can support the verification of the feasibility of tailoring an order to the needs of the customer, and, finally, how to model a knowledge base for a cyber-physical system containing a formal record of the knowledge acquired regarding customer preferences. Therefore, in this paper, we developed a new algorithm that will enable, on one hand, the collection and recording of customer preferences, and, on the other hand, the integration of those data and information that are available within the Enterprise Resource Planning (ERP) system. The main contribution of this work is the use of specialist knowledge and data from ERP regarding production capabilities implemented in a manufacturing enterprise in order to model the scenario of generating possible orders for a client, and finally applying the new solution for the operation of manufacturing according to mass-customisation strategy in a real company that manufactures mattresses.
Phase Shifting Enhancement of a Substrate-Integrated Waveguide Phase Shifter Based on Liquid Crystal
Authors: Shin Hyun-Ji , Ma Jun-Seok , Choi Jin-Young , Kim Wook-Sung
Published: February 2023

A novel technique to enhance the phase shifting range of a liquid crystal (LC)-based, substrate-integrated waveguide (SIW) phase shifter by inserting inductive posts (IPs) is presented for the first time. The IPs inserted in the LC-based SIW phase shifter produce a phase advance based on the relative permittivity of the LC, resulting in an additional differential phase shift. At 28 GHz, the proposed structure with IPs achieves a ratio of maximum differential phase shift (∆ϕmax) to maximum insertion loss (ILmax) (FoM1) = 52.82 °/dB and ratio of maximum differential phase shift to length (FoM2) = 2.62 °/mm. Compared with conventional LC-based SIW phase shifters that lack an IP and use the same amount of LC, the FoM1 increased by 16% and the FoM2 increased by 55%. In addition, compared to the typical structure that uses additional LCs instead of IPs, the FoM1 decreased by 7%, and FoM2 increased by 21%. Therefore, inserting IPs into the LC-based SIW phase shifter can reduce the dimensions of the phase shifter and the amount of LCs required to achieve the desired differential phase shift. We believe this work can contribute to the design of compact and efficient SIW phase shifters for future telecommunication systems.
Experimental Investigation of Enhancement of Natural Convective Heat Transfer in Air Using Ultrasound
Authors: Musielak Grzegorz , Mierzwa Dominik , Łechtańska Joanna
Published: February 2023

One of the methods to improve convective heat exchange is the application of ultrasound assistance. However, little is known about ultrasound application in the air. The main purpose of this study is to investigate the effect of ultrasound on natural convection cooling. The tests are based on the cooling of the metal samples (in four different shapes) preheated to a temperature of 60 °C. Cooling takes place in free convection without and with the use of ultrasound at different powers (50 W, 100 W, 150 W, and 200 W). The study uses a mathematical model based on a small Biot’s number assumption. The values of the convective heat exchange coefficients are determined by using an approximation of the experimental results. The coefficients obtained are an increasing exponential function of the applied ultrasound power. This study indicates the possibility of using ultrasound to improve heat transfer by free convection.
Moving Model Experimental Study on a Slipstream of a High-Speed Train Running on the Bridge Suffering a Crosswind
Authors: Zou Simin , He Xuhui , Wang Hanfeng
Published: February 2023

A running train induces a slipstream around it, which is closely related to its aerodynamic features and crucial for the safety of people and structures near the track. However, the effect of crosswinds is almost inevitable when the train runs on a bridge. In this work, an experimental study using moving model testing technology was conducted to investigate the effects of wind speeds, train speeds, and yaw angles on the aerodynamic performance of a Fuxing Hao high-speed train running on a bridge under the influence of crosswind. The results show that, for the crosswind cases, the slipstream velocities on the leeward side of the train are generally higher than those in the no-crosswind cases. Moreover, the results were compared for the cases with the same effective yaw angle of 21.8° but different wind speeds (6 m/s, 8 m/s) and train speeds (15 m/s, 20 m/s), which suggests the method of the resultant wind’s yaw angle is no longer valid when the train runs on a bridge due to the aerodynamic interactions.
The Implementation of a Smart Lifejacket for Assisting Passengers in the Evacuation of Large Passenger Ships
Authors: Stamou Angelos , Kuqo Paul , Douklias Athanasios , Antonopoulos Markos , Kostovasili Margarita , Karagiannidis Lazaros , Amditis Angelos
Published: February 2023

The evacuation and abandonment of large passenger ships, involving thousands of passengers, is a safety-critical task where techniques and systems that can improve the complex decision-making process and the timely response to emergencies on board are of vital importance. Current evacuation systems and processes are based on predefined and static exit signs, information provided to the passengers in the form of evacuation drills, emergency information leaflets and public announcements systems. It is mandatory for passengers to wear lifejackets during an evacuation, which are made of buoyant or inflatable material to keep them afloat in the water. Time is the most critical attribute in ship evacuation and can significantly affect the overall evacuation process in case passengers do not reach their embarkation stations in a timely manner. Moreover, extreme conditions and hazards, such as fire or flooding, can prevent and hinder the timely evacuation process. To improve the current evacuation systems onboard large passenger ships, a smart lifejacket has been designed and implemented within the context of the project SafePASS. The proposed smart lifejacket integrates indoor localization and navigation functionality to assist passengers during the evacuation process. Once the passenger location is calculated within the ship, the navigation feature guides the passengers along an escape route using vibration motors attached to the lifejacket. This is done in the form of haptic cues to help passengers reach their destination, especially in low-visibility conditions and in case they are left behind or lost. This can increase passenger safety and reduce the total evacuation time, as well as support dynamic evacuation scenarios where the predefined routes and static exit routes may not be available due to fire or flooding incidents.
Comparative Analysis on Phytochemical Properties, Anti-Oxidative, and Anti-Inflammatory Activities of the Different Organs of the Common Ice Plant Mesembryanthemum crystallinum L.
Authors: Kang Yeo-Wool , Joo Na-Mi
Published: February 2023

The ice plant (Mesembryanthemum crystallinum L.) is a type of succulent known to contain various minerals and beneficial compounds and is enriched in compounds exhibiting a diversity of bioactivity. This study aims to determine the potential antioxidant and anti-inflammatory effects of the ice plant by organs (cotyledon, stem, and leaf). The ice plant ethanol extract showed that antioxidant activity, measured by the DPPH radical scavenging ability (51.79 ± 4.18%), and hydroxyl radical scavenging activities (6.57 ± 0.29%) had lower levels than those of control BHT, but had higher antioxidant activity in the leaves of the ice plant, while ABTS+ (58.91 ± 7.23%) and Fe2+ chelating activity (16.89 ± 1.68%) showed high antioxidant activity in the cotyledon. Total polyphenols (115.43 ± 0.47 mg QE/g) and flavonoid contents (1218.07 ± 1.00 mg GAE/g) were notably high in the cotyledon. UHPLC-TOF/HRMS analyses identified 17 polyphenolic compounds of ice plants. The main constituents of the extracts obtained in this study were flavonoids, including their O-glycosides, and compounds not previously described were found. The production of NO as a major indicator of the inflammatory response was found to decrease at 100 and 300 μg/mL (p < 0.05). The levels of the inflammatory cytokines TNF-α in 10 μg/mL (p < 0.05), 50, 100, and 300 μg/mL (p < 0.000); IL-6 in 100 and 300 μg/mL (p < 0.01); and IL-1β in 50, 100 μg/mL (p < 0.01), and 300 μg/mL (p < 0.05) confirmed that the anti-inflammatory effect was exhibited by inhibiting the production of inflammatory cytokines according to the concentration of each organ of the ice plant.
Influence of Sample Preparation/Extraction Method on the Phytochemical Profile and Antimicrobial Activities of 12 Commonly Consumed Medicinal Plants in Romania
Authors: Horablaga Nicolae Marinel , Cozma Antoanela , Alexa Ersilia , Obistioiu Diana , Cocan Ileana , Poiana Mariana-Atena , Lalescu Dacian , Pop Georgeta , Imbrea Ilinca Merima , Buzna Ciprian
Published: February 2023

This paper aims to evaluate the influence of preparation and extraction methods on the phytochemical profile and microbiological activity of 12 medicinal plants from the west side of Romania. First, the proximate composition (humidity, proteins, lipids, and ash) and elemental composition of the raw material were evaluated. Two levels of plant shredding were used: coarse shredding (CS) and fine grinding of plants to obtain powder (FG), and three extraction methods: conventional solvent extraction (CES), ultrasound-assisted extraction (UAE), and microwave extraction (MWE). The phytochemical profile investigated referred to antioxidant activity (AA), total polyphenol content (TPC), and flavonoid content (TFC), using spectrophotometric methods, and individual polyphenols detected using the LC/MS method. The preparation/extraction method for each medicinal plant was optimized using statistical analysis. The optimized extracts for each medicinal plant were tested to evaluate the antimicrobial potential against 9 standard strains. The results showed that the sample preparation method before extraction (shredding or grinding) influences the content of phytocompounds by increasing them in powder form. The use of green technologies, especially MWE, leads to the highest content of TPC, TFC, and AA. The TPC value ranged between 4.83–19.2 mgGAE/g DM in the samples CS and between 19.00–52.85 mgGAE/g DM in the samples FG. The highest antioxidant value was found in the Origanum vulgare extract, both in the case of the crushed sample (22.66 mM Fe2+/100 g) and the powder sample (81.36 mM Fe2+/100 g), followed by Melissa officinalis, The TFC values varied in the range of 1.02–3.46 mgQE/g DM when CES was used, between 2.36–12.09 mgQE/g DM for UAE, and between 1.22–9.63 mgQE/g DM in the case of the MWE procedure. The antimicrobial activity highlighted the effectiveness of the extracts, especially on the strains of H. influenzae, C. albicans, C. parapsilosis, S. aureus, and S. flexneri. Reduced antimicrobial activity was recorded for the strains of S. pyogenes and P. aeruginosa. The best antimicrobial activity was registered by Thymus serpyllum, with an inhibition rate of 132.93% against E. coli and 78.40% against C. albicans.
Extraordinary Field Emission of Diamond Film Developed on a Graphite Substrate by Microwave Plasma Jet Chemical Vapor Deposition
Authors: Hsu Hua-Yi , Yen Jing-Shyang , Lin Chun-Yu , Liu Chi-Wen , Aranganadin Kaviya , Lin Chii-Ruey , Sun Jwo-Shiun , Lin Ming-Chieh
Published: February 2023

This work reports both numerical and experimental studies of the reconditioning of a microwave plasma jet chemical vapor deposition (MPJCVD) system for the growth of diamond film. A three-dimensional plasma fluid model is constructed for investigating and conditioning the MPJCVD system and optimizing its operating conditions. The methodology solves electromagnetic wave and plasma dynamics self-consistently using an adaptive finite element method as implemented in COMSOL Multiphysics. The whole system has been modeled under varying parameters, including the reactor geometry, microwave power, and working gas pressure. Using an operating condition identical to the optimized simulation results, the MPJCVD system successfully fabricates a diamond-thin film on a graphite substrate. The SEM image reveals the presence of a diamond film uniformly distributed with particles of a size of ~1 μm. The field emission from the diamond film grown from our homemade MPJCVD system on the graphite substrate presents extraordinary properties, i.e., extremely high current density and relatively low turn-on voltage. The turn-on electric field observed could be as low as ~4 V/μm. This developed model provides valuable physical insights into the MPJCVD system, which guided performance improvements. The work may find applications in surface hardening and provide a better cold cathode for field electron emission.
Calibrated Q-Matrix-Enhanced Deep Knowledge Tracing with Relational Attention Mechanism
Authors: Li Linqing , Wang Zhifeng
Published: February 2023

With the development of online educational platforms, numerous research works have focused on the knowledge tracing task, which relates to the problem of diagnosing the changing knowledge proficiency of learners. Deep-neural-network-based models are used to explore the interaction information between students and their answer logs in the current field of knowledge tracing studies. However, those models ignore the impact of previous interactions, including the exercise relation, forget factor, and student behaviors (the slipping factor and the guessing factor). Those models also do not consider the importance of the Q-matrix, which relates exercises to knowledge points. In this paper, we propose a novel relational attention knowledge tracing (RAKT) to track the students’ knowledge proficiency in exercises. Specifically, the RAKT model incorporates the students’ performance data with corresponding interaction information, such as the context of exercises and the different time intervals between exercises. The RAKT model also takes into account the students’ interaction behaviors, including the slipping factor and the guessing factor. Moreover, consider the relationship between exercise sets and knowledge sets and the relationship between different knowledge points in the same exercise. An extension model of RAKT is called the Calibrated Q-matrix relational attention knowledge tracing model (QRAKT), which was developed using a Q-matrix calibration method based on the hierarchical knowledge levels. Experiments were conducted on two public educational datasets, ASSISTment2012 and Eedi. The results of the experiments indicated that the RAKT model and the QRAKT model outperformed the four baseline models.
Measurement and Modeling of a Cargo Bicycle Tire for Vehicle Dynamics Simulation
Authors: Miller Marius , Pfeil Markus , Reick Benedikt , Murri Raphael , Stetter Ralf , Kennel Ralph
Published: February 2023

In the field of inner-city cargo transportation, solutions such as electrified cargo trailers are increasingly being used. To provide an intelligent drivetrain control system that improves driving dynamics and enables safety, it is necessary to know the characteristics of the trailer system. This includes the behavior of the tires. Existing investigations of bicycle tires focus on camber-angle-dependent models. However, in most trailers, a rigid mounting of the tires without camber is used. For this reason, a bicycle tire model is created within the scope of this study using real measurement data that represent a 20 in tire with typical wheel loads and without camber. The measurements were collected with the mobile tire measurement laboratory of the Bern University of Applied Sciences on an asphalt test site under real conditions. Crosstalk occurring in the measurement hub during the data collection was successfully corrected using a matrix method. With help of the so-called Magic Formula, a tire model was created that can be used for driving dynamics simulations and controller design.
Performance Analysis of Deep Convolutional Network Architectures for Classification of Over-Volume Vehicles
Authors: Reka S. Sofana , Murthy Voona Venkata Dhanvanthar , Sai Nithish Puvvada Venkata , Paavan Kumar Dornadula Sai , Venugopal Prakash , Ravi Visvanathan
Published: February 2023

The number of vehicle accidents has increased in recent years due to overloaded goods carriers. Off-road driving, mountain roads, and sharp edges on a road are the main causes of an imbalance in overloaded trucks. In rural areas, where smaller roads cannot accommodate high volume vehicles, such vehicles cause many problems for cars, bikes, bicycles, and other small vehicles, as well as an increase in traffic congestion in those areas. This has become a major problem in the daily lives of drivers in rural areas as well as major urban areas. Solutions are needed to detect over-volume goods carriers and alert drivers to slow down or control the volume in their trucks. This work mainly focuses on a solution that uses deep CNN models. In this work, different deep convolutional architectures are evaluated for their ability to classify goods based on their volume. The model implemented is based on a dataset-specific transfer learning process with CNN layers generated in ImageNet in which only dense layers are learned. The primary objective of this work is to identify a classification method that exhibits proven results with respect to the accuracy parameters. In this work, different deep architectures were tested, and among the efficient networks, Net-B3 was found to perform with 95% accuracy on average. The different architectures were evaluated based on their accuracy, confusion matrix, ROC curve, and AUC score with a real-time dataset.
A Survey: Network Feature Measurement Based on Machine Learning
Authors: Sun Muyi , He Bingyu , Li Ran , Li Jinhua , Zhang Xinchang
Published: February 2023

In network management, network measuring is crucial. Accurate network measurements can increase network utilization, network management, and the ability to find network problems promptly. With extensive technological advancements, the difficulty for network measurement is not just the growth in users and traffic but also the increasingly difficult technical problems brought on by the network’s design becoming more complicated. In recent years, network feature measurement issues have been extensively solved by the use of ML approaches, which are ideally suited to thorough data analysis and the investigation of complicated network behavior. However, there is yet no favored learning model that can best address the network measurement issue. The problems that ML applications in the field of network measurement must overcome are discussed in this study, along with an analysis of the current characteristics of ML algorithms in network measurement. Finally, network measurement techniques that have been used as ML techniques are examined, and potential advancements in the field are explored and examined.
Long-Term Structural State Trend Forecasting Based on an FFT–Informer Model
Authors: Ma Jihao , Dan Jingpei
Published: February 2023

Machine learning has been widely applied in structural health monitoring. While most existing methods, which are limited to forecasting structural state evolution of large infrastructures. forecast the structural state in a step-by-step manner, extracting feature of structural state trends and the negative effects of data collection under abnormal conditions are big challenges. To address these issues, a long-term structural state trend forecasting method based on long sequence time-series forecasting (LSTF) with an improved Informer model integrated with Fast Fourier transform (FFT) is proposed, named the FFT–Informer model. In this method, by using FFT, structural state trend features are represented by extracting amplitude and phase of a certain period of data sequence. Structural state trend, a long sequence, can be forecasted in a one-forward operation by the Informer model that can achieve high inference speed and accuracy of prediction based on the Transformer model. Furthermore, a Hampel filter that filters the abnormal deviation of the data sequence is integrated into the Multi-head ProbSparse self-attention in the Informer model to improve forecasting accuracy by reducing the effect of abnormal data points. Experimental results on two classical data sets show that the FFT–Informer model achieves high and stable accuracy and outperforms the comparative models in forecasting accuracy. It indicates that this model can effectively forecast the long-term state trend change of a structure and is proposed to be applied to structural state trend forecasting and early damage warning.
DDRCN: Deep Deterministic Policy Gradient Recommendation Framework Fused with Deep Cross Networks
Authors: Gao Tianhan , Gao Shen , Xu Jun , Zhao Qihui
Published: February 2023

As an essential branch of artificial intelligence, recommendation systems have gradually penetrated people’s daily lives. It is the active recommendation of goods or services of potential interest to users based on their preferences. Many recommendation methods have been proposed in both industry and academia. However, there are some limitations of previous recommendation methods: (1) Most of them do not consider the cross-correlation between data. (2) Many treat the recommendation process as a one-time act and do not consider the continuity of the recommendation system. To overcome these limitations, we propose a recommendation framework based on deep reinforcement learning techniques, known as DDRCN: a deep deterministic policy gradient recommendation framework incorporating deep cross networks. We use a Deep network and a Cross network to fit the cross relationships between the data, to obtain a representation of the user interaction data. The Actor-Critic network is designed to simulate the continuous interaction behavior of users through a greedy strategy. A deep deterministic policy gradient network is also used to train the recommendation model. Finally, we conduct experiments with two publicly available datasets and find that our proposed recommendation framework outperforms the baseline approach in the recall and ranking phases of recommendations.
Desertification and Related Climate Change in the Alashan Plateau since the Last 40 ka of the Last Glacial Period
Authors: Zhu Bingqi , Yang Limin
Published: February 2023

Clues of climate change on the Alashan Plateau since the last glacial period (40 ka) are important for revealing the mechanism of desertification of middle-latitude deserts in the Northern Hemisphere (NH). Studies are still rare for the understanding of the specific relationship of climate changes between the Alashan Plateau and the global. Based on a systematic and comparative analysis of the existing research in China and the international academic community, this paper reviews the environmental evolution history of the Alashan Plateau since the last glacial period from the records of paleo-environment and geomorphological characteristics in different deserts of the plateau (e.g., Badanjilin, Tenggeli, and Wulanbuhe). From about 40 ka to the end of the last glacial maximum, the climate on the plateau was wetter than it is today, and to the end of the Pleistocene, the climate was generally dry and the aeolian activities were enhanced. However, the climate was arid during the whole last glacial period in the Wulanbuhe Desert, evidently different from the overall pattern of the plateau. The Tenggeli Desert was characterized by an arid climate in the early Holocene. The most controversial events for the Alashan Plateau are the drought events in the middle Holocene in the Badanjilin Desert. The role and impact of the westerlies and the East Asian Summer Monsoon (EASM) systems on the climate change of the desert and even the whole plateau is a vexed question that brings different views in different periods. There is still a lack of definite evidence representing the events of global environmental change that occurred on the plateau during the discussed period. The distinctive morphology of dune mountains and the distribution of sand dunes are mutually indicative of the direction and energy of wind systems on the plateau. It is suggested that appropriate wind energy is the significant key to the desertification in these middle-latitude deserts on the plateau. From a global-scale review of climate change, the desertification of the modern-scale sandy desert landscapes on the Alashan Plateau is generally related to the global glacial period and the cold and dry climate during the past 40 ka.
On the Correlations between Particulate Matter: Comparison between Annual/Monthly Concentrations and PM10/PM2.5
Authors: Jurado Xavier , Reiminger Nicolas , Maurer Loïc , Vazquez José , Wemmert Cédric
Published: February 2023

Annual concentration is a key element to assess the air quality of an area for long-time exposure effects. Nonetheless, obtaining annual concentrations from sensors is costly since it needs to have a year of measurements for each required pollutant. To overcome this issue, several strategies are studied to assess annual particulate matter concentration from monthly data, with their pros and cons depending on the risk acceptance and measurement campaign costs. When applied on a French dataset, the error spans from 12–14% with one month of measurement to 4–6% for six months of measurement for PM10 and PM2.5, respectively. A relationship between the mean relative error and 95th percentile relative error is provided with an R2 of 0.99. The relationship between PM10 and PM2.5 was also investigated and improved compared to previous work by considering the seasonality and influence on emission reaching a mean relative error of 12%. Thus, this study provides tools for urban planners, engineers, researchers, and public authorities for improved monitoring of annual air pollution at a lower cost for particulate matter.
CXCR1: A Cancer Stem Cell Marker and Therapeutic Target in Solid Tumors
Authors: Molczyk Caitlin , Singh Rakesh K.
Published: February 2023

Therapy resistance is a significant concern while treating malignant disease. Accumulating evidence suggests that a subset of cancer cells potentiates tumor survival, therapy resistance, and relapse. Several different pathways regulate these purported cancer stem cells (CSCs). Evidence shows that the inflammatory tumor microenvironment plays a crucial role in maintaining the cancer stem cell pool. Typically, in the case of the tumor microenvironment, inflammatory pathways can be utilized by the tumor to aid in tumor progression; one such pathway is the CXCR1/2 pathway. The CXCR1 and CXCR2 receptors are intricately related, with CXCR1 binding two ligands that also bind CXCR2. They have the same downstream pathways but potentially separate roles in the tumor microenvironment. CXCR1 is becoming more well known for its role as a cancer stem cell identifier and therapeutic target. This review elucidates the role of the CXCR1 axis as a CSC marker in several solid tumors and discusses the utility of CXCR1 as a therapeutic target.
Non-Canonical WNT/Wnt5a Pathway Activity in Circulating Monocytes of Untreated Psoriatic Patients: An Exploratory Study of Its Association with Inflammatory Cytokines and Cardiovascular Risk Marker-ADAMTS7
Authors: Karsulovic Claudio , Loyola Khanty , Cabrera Raul , Perez Claudio , Hojman Lia
Published: February 2023

The leading cause of death in psoriasis is cardiovascular disease. The determinants that induce the increase in this risk are not known. The systemic inflammatory process is dependent on lymphocytes and monocytes, as has been proposed. However, adaptation modules such as mTOR have recently been mentioned as having a role. Other factors, such as WNT and its non-canonical WNT5a-inducing pathway, are relevant in inflammation, cell migration, and neoangiogenesis. Thus, we studied circulating monocytes from untreated severe psoriatic patients and characterized inflammatory cytokines, chemokines, mTOR activity, and the cardiovascular risk marker ADAMTS7. Peripheral blood from ten severely psoriatic patients (Psoriasis severity index greater than 10) was extracted and age- and sex-matched with healthy subjects. Surface and intracellular flow cytometry were performed for cytokine, chemokine receptors, and mTOR activity. ADAMTS7 was measured using ELISA. Psoriatic patients had a higher frequency of WNT5a+ cells in monocytes, which also had higher levels of IL-1β, IL-6, CXCR3, CCR2, and phosphorylated S6R protein. We found that M1 monocytes are dominant in the WNT5a+ cell group, and intracellular levels of WNT5a were also augmented. Levels of WNT5a were correlated with ADAMTS7, a blood marker related to the pathogenesis of atheromatosis. WNT5a could be relevant to the cardiovascular risk of psoriatic patients considering its association with higher levels of inflammatory cytokines, chemokine receptors and the pro-atherogenic profile of circulating monocytes.
Neuroinflammation, Energy and Sphingolipid Metabolism Biomarkers Are Revealed by Metabolic Modeling of Autistic Brains
Authors: Esvap Elif , Ulgen Kutlu O.
Published: February 2023

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders generally characterized by repetitive behaviors and difficulties in communication and social behavior. Despite its heterogeneous nature, several metabolic dysregulations are prevalent in individuals with ASD. This work aims to understand ASD brain metabolism by constructing an ASD-specific prefrontal cortex genome-scale metabolic model (GEM) using transcriptomics data to decipher novel neuroinflammatory biomarkers. The healthy and ASD-specific models are compared via uniform sampling to identify ASD-exclusive metabolic features. Noticeably, the results of our simulations and those found in the literature are comparable, supporting the accuracy of our reconstructed ASD model. We identified that several oxidative stress, mitochondrial dysfunction, and inflammatory markers are elevated in ASD. While oxidative phosphorylation fluxes were similar for healthy and ASD-specific models, and the fluxes through the pathway were nearly undisturbed, the tricarboxylic acid (TCA) fluxes indicated disruptions in the pathway. Similarly, the secretions of mitochondrial dysfunction markers such as pyruvate are found to be higher, as well as the activities of oxidative stress marker enzymes like alanine and aspartate aminotransferases (ALT and AST) and glutathione-disulfide reductase (GSR). We also detected abnormalities in the sphingolipid metabolism, which has been implicated in many inflammatory and immune processes, but its relationship with ASD has not been thoroughly explored in the existing literature. We suggest that important sphingolipid metabolites, such as sphingosine-1-phosphate (S1P), ceramide, and glucosylceramide, may be promising biomarkers for the diagnosis of ASD and provide an opportunity for the adoption of early intervention for young children.
Pupillary Light Response Deficits in 4-Week-Old Piglets and Adolescent Children after Low-Velocity Head Rotations and Sports-Related Concussions
Authors: Oeur Anna , Mull Mackenzie , Riccobono Giancarlo , Arbogast Kristy B. , Ciuffreda Kenneth J. , Joshi Nabin , Fedonni Daniele , Master Christina L. , Margulies Susan S.
Published: February 2023

Neurological disorders and traumatic brain injury (TBI) are among the leading causes of death and disability. The pupillary light reflex (PLR) is an emerging diagnostic tool for concussion in humans. We compared PLR obtained with a commercially available pupillometer in the 4 week old piglet model of the adolescent brain subject to rapid nonimpact head rotation (RNR), and in human adolescents with and without sports-related concussion (SRC). The 95% PLR reference ranges (RR, for maximum and minimum pupil diameter, latency, and average and peak constriction velocities) were established in healthy piglets (N = 13), and response reliability was validated in nine additional healthy piglets. PLR assessments were obtained in female piglets allocated to anesthetized sham (N = 10), single (sRNR, N = 13), and repeated (rRNR, N = 14) sagittal low-velocity RNR at pre-injury, as well as days 1, 4, and 7 post injury, and evaluated against RRs. In parallel, we established human PLR RRs in healthy adolescents (both sexes, N = 167) and compared healthy PLR to values obtained <28 days from a SRC (N = 177). In piglets, maximum and minimum diameter deficits were greater in rRNR than sRNR. Alterations peaked on day 1 post sRNR and rRNR, and remained altered at day 4 and 7. In SRC adolescents, the proportion of adolescents within the RR was significantly lower for maximum pupil diameter only (85.8%). We show that PLR deficits may persist in humans and piglets after low-velocity head rotations. Differences in timing of assessment after injury, developmental response to injury, and the number and magnitude of impacts may contribute to the differences observed between species. We conclude that PLR is a feasible, quantifiable involuntary physiological metric of neurological dysfunction in pigs, as well as humans. Healthy PLR porcine and human reference ranges established can be used for neurofunctional assessments after TBI or hypoxic exposures (e.g., stroke, apnea, or cardiac arrest).
Detection of Rice Fungal Spores Based on Micro- Hyperspectral and Microfluidic Techniques
Authors: Zhang Xiaodong , Song Houjian , Wang Yafei , Hu Lian , Wang Pei , Mao Hanping
Published: February 2023

As rice is one of the world’s most important food crops, protecting it from fungal diseases is very important for agricultural production. At present, it is difficult to diagnose rice fungal diseases at an early stage using relevant technologies, and there are a lack of rapid detection methods. This study proposes a microfluidic chip-based method combined with microscopic hyperspectral detection of rice fungal disease spores. First, a microfluidic chip with a dual inlet and three-stage structure was designed to separate and enrich Magnaporthe grisea spores and Ustilaginoidea virens spores in air. Then, the microscopic hyperspectral instrument was used to collect the hyperspectral data of the fungal disease spores in the enrichment area, and the competitive adaptive reweighting algorithm (CARS) was used to screen the characteristic bands of the spectral data collected from the spores of the two fungal diseases. Finally, the support vector machine (SVM) and convolutional neural network (CNN) were used to build the full-band classification model and the CARS filtered characteristic wavelength classification model, respectively. The results showed that the actual enrichment efficiency of the microfluidic chip designed in this study on Magnaporthe grisea spores and Ustilaginoidea virens spores was 82.67% and 80.70%, respectively. In the established model, the CARS-CNN classification model is the best for the classification of Magnaporthe grisea spores and Ustilaginoidea virens spores, and its F1-core index can reach 0.960 and 0.949, respectively. This study can effectively isolate and enrich Magnaporthe grisea spores and Ustilaginoidea virens spores, providing new methods and ideas for early detection of rice fungal disease spores.
Humor Coping Reduces the Positive Relationship between Avoidance Coping Strategies and Perceived Stress: A Moderation Analysis
Authors: Simione Luca , Gnagnarella Camilla
Published: February 2023

Humor is considered an adaptive coping strategy as it could reduce the burden of perceived stress and increase positive emotional states when dealing with stressful situations. Humor has been reported in several models as a rather independent strategy that can be correlated with both approach-based coping strategies and avoidance-based coping strategies. Humor can be defined as a hedonistic escapism strategy that would work better in the presence of unpredictable or uncontrollable stressors, such as the spread of the COVID-19 pandemic and its related confinement measures. Therefore, during such a stressful event, humor would have increased the positive effect of the approach coping style on mental health and reduced the negative effect of the avoidance coping style. Based on this hypothesis, we conducted a cross-sectional study with a moderation analysis in which we assessed the interaction of humor with both approach-based and avoidance-based coping styles on perceived stress in a large sample of Italian participants collected in April and May 2021. Despite some limitations related to sampling and study design, the results obtained partially support our hypothesis, as we observed that humor had a significant moderating effect on the relationship between avoidance coping and psychological distress, with a reduction of perceived stress while using such a coping style in the presence of a medium to high level of humor. On the other hand, we did not observe a significant moderating effect of humor on the relationship between the approach coping style and perceived stress. In general, our results support the beneficial effect of humor on mental health and highlight a special role for humor as a moderator of other coping strategies.