bluuebunny/crossref_metadata_2025 huggingface dataset:
Cultivation of Crops in Strip-Till Technology and Microgranulated Fertilisers Containing a Gelling Agent as a Farming Response to Climate Change
Authors: Jaskulski Dariusz , Jaskulska Iwona , Różniak Emilian , Radziemska Maja , Brtnický Martin
Published: October 2023

Climatic and soil conditions are changing in response to the increasing human impact. This requires the introduction of low-cost, low-emission, but effective technologies in the field cultivation of crops, in turn requiring and justifying research in this area. In laboratory tests and field studies, the production and environmental effects of strip-till and the application of microgranular fertilisers with a gelling component were determined (and, in particular, their use in combination as a plant cultivation technology). These effects were measured in terms of soil properties, the biomass production, and the yields of maize (Zea mays L.), spring barley (Hordeum vulgare L.), and winter rape (Brassica napus L.). Fertiliser microgranules with a gelling agent absorbed water in the amount of 118.6–124.7% of fertiliser mass and increased the volumetric moisture content of the soil in the layer in which they were applied (0–7.5 cm) by 3.0–3.9 percentage points compared to the soil moisture without fertiliser. Strip tillage with the application of fertilisers with a gelling agent significantly increased the amount of water in the soil during the sowing period for winter and spring plants and reduced the CO2 emissions from the soil relative to the conventional tillage without microgranular fertiliser. The biomass of maize, spring barley, and winter rape before flowering, as well as the yields of these plants, were higher when cultivated using strip-till and fertilisers with gelling agents than when ploughed with a mouldboard plough without the use of microgranulated fertilisers. This technology also increased the number of microorganisms, including bacteria, actinobacteria, and filamentous fungi in the soil after harvesting compared to the unfertilised, ploughed soil. Strip tillage and microgranulated fertilisers containing a gelling agent can thus reduce the environmental pressure exerted by agriculture and reduce the risk of climate change, as well as being a way of adapting agriculture to climate change.
Artificial Neural Networks for Modeling and Optimizing Egg Cost in Second-Cycle Laying Hens Based on Dietary Intakes of Essential Amino Acids
Authors: Morales-Suárez Walter , Daza Luis Daniel , Váquiro Henry A.
Published: October 2023

Egg production is a significant source of animal protein for human consumption. Feed costs significantly impact the profitability of egg production, representing more than 70% of the variable costs. This study evaluated the effect of dietary intakes of three essential amino acids (EAAs) on the egg cost for H&N Brown second-cycle laying hens. The hens were fed for 20 weeks with 23 diets that varied in their lysine, methionine + cystine, and threonine contents. These amino acids were derived from both dietary and synthetic sources. Zootechnical results were used to calculate the feed cost per kilogram of egg (FCK), considering the cost of raw materials and the diet composition. Multivariate polynomial models and artificial neural networks (ANNs) were validated to predict FCK as a function of the EAAs and time. The EAA intakes that minimize FCK over time were optimized using the best model, a cascade-forward ANN with a softmax transfer function. The optimal scenario for FCK (0.873 USD/kg egg) at 20 weeks was achieved at 943.7 mg lysine/hen-day, 858.3 mg methionine + cystine/hen-day, and 876.8 mg threonine/hen-day. ANNs could be a valuable tool for predicting the egg cost of laying hens based on the nutritional requirements. This could help improve economic efficiency and reduce the feed costs in poultry companies.
Heavy Metals Can Affect Plant Morphology and Limit Plant Growth and Photosynthesis Processes
Authors: Hu Zhewei , Zhao Caiyi , Li Qi , Feng Yanhong , Zhang Xiaoyu , Lu Yuanyuan , Ying Rongrong , Yin Aijing , Ji Wenbing
Published: October 2023

Soil heavy metal pollution caused by human activities has become one of the most critical environmental issues with a global concern. Phytoremediation is widely used due to its low cost and environmental friendliness. However, the impact of heavy metals on plant growth remains unclear. This study investigated the effects on the growth and photosynthetic activity of Picris divaricata Vant. under different cadmium concentrations using a hydroponics cultivation system. The results showed that the growth and photosynthetic processes of P. divaricata exhibited a phenomenon of promotion in low Cd concentrations and inhibition in high Cd concentrations. Under a low to medium Cd concentration (≤25 μM), there was no Cd toxicity in terms of plant growth, but high concentrations of Cd inhibited plant growth. The Fe content of leaves gradually increased as the Cd concentration increased; it reached 201.8 mg kg−1 in 75 μM Cd. However, there was no significant difference in Mn between the 75 μM Cd treatment and the control (p > 0.05). The contents of carotenoid ranged between 3.06 and 3.26 mg/g across the different Cd treatments, showing no significant differences. The treatment with 5–75 μM Cd did not directly affect the photosynthesis of P. divaricata. Higher Cd concentrations reduced the stomatal density on the of P. divaricata leaves, resulting in stomatal and mesophyll conductance limitations, indirectly affecting P. divaricata photosynthesis. These research results provide a reference for evaluating and selecting heavy metal tolerant plants and provide environmentally friendly approaches to remediate heavy metal pollution.
Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review
Authors: Alahmad Tarek , Neményi Miklós , Nyéki Anikó
Published: October 2023

The potential benefits of applying information and communication technology (ICT) in precision agriculture to enhance sustainable agricultural growth were discussed in this review article. The current technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), as well as their applications, must be integrated into the agricultural sector to ensure long-term agricultural productivity. These technologies have the potential to improve global food security by reducing crop output gaps, decreasing food waste, and minimizing resource use inefficiencies. The importance of collecting and analyzing big data from multiple sources, particularly in situ and on-the-go sensors, is also highlighted as an important component of achieving predictive decision making capabilities in precision agriculture and forecasting yields using advanced yield prediction models developed through machine learning. Finally, we cover the replacement of wired-based, complicated systems in infield monitoring with wireless sensor networks (WSN), particularly in the agricultural sector, and emphasize the necessity of knowing the radio frequency (RF) contributing aspects that influence signal intensity, interference, system model, bandwidth, and transmission range when creating a successful Agricultural Internet of Thing Ag-IoT system. The relevance of communication protocols and interfaces for presenting agricultural data acquired from sensors in various formats is also emphasized in the paper, as is the function of 4G, 3G, and 5G technologies in IoT-based smart farming. Overall, these research sheds light on the significance of wireless sensor networks and big data in the future of precision crop production
Evaluation of Post-Larval Diets for Indoor Weaned Largemouth Bass (Micropterus salmoides)
Authors: Lukić Jovanka , Gyalog Gergő , Horváth Zoltán , Szűcs Anita Annamária , Ristović Tijana , Terzić-Vidojević Amarela , Sándor Zsuzsanna J. , Ljubobratović Uroš
Published: October 2023

This study aimed to evaluate different commercial diets (Otohime C1, Aller Futura (AF), Biomar Inicio Plus (BIP)) and one experimental feed (EF) in terms of their effectiveness as post-larval diets for indoor weaned largemouth bass, LMB (Micropterus salmoides). Key variations in the content of nutritive values were monounsaturated fatty acid (MUFA) and highly unsaturated FA (HUFA) ω3. Fish were fed with one of four tested diets from the 33rd to the 40th day post-hatch (DPH). Biometric indices, digestive enzyme-specific activities, thyroid hormone status, and mRNA expression of genes coding for skeleton, neuron, and muscle growth were analyzed. The lowest skeletal deformity rate and highest survival among the treatments were seen in BIP-fed fish. Dietary lipids, with an appropriate balance between MUFA and polyunsaturated FA (PUFA), alongside amino acid balance, were shown to be the main contributors to the growth of the skeleton and/or fish survival. On the other hand, fish growth is correlated with fish digestive capacity and feed moisture percent rather than feed quality. Unexpectedly, BIP-fed fish were attributed with the lowest expression of skeleton differentiation markers, which may reflect the sacrifice of scale and/or cranium growth at the expense of somatic growth. This study highlights the role of non-marine ingredients in the nutrition of post-larval LMB.
The Distribution of IgT mRNA+ Cells in the Gut of the Atlantic Salmon (Salmo salar L.)
Authors: Castro Pedro Luis , Barac Fran , Hansen Tom Johnny , Fjelldal Per Gunnar , Hordvik Ivar , Bjørgen Håvard , Koppang Erling Olaf
Published: October 2023

The newly discovered IgT+ B cell is thought to play a dominant role in mucosal immunity, but limited studies have examined its distribution in fish species, hindering our understanding of its function. This study investigated IgT and poly Ig receptor (pIgR) mRNA+ cell distribution in Atlantic salmon (Salmo salar) gut using RNAscope in situ hybridization (ISH) and assessed the effects of vaccination. The pyloric caeca, mid-intestine (first and second parts), and posterior segment in two weight stages (Group 1: avg. 153 g, Group 2: avg. 1717 g) were examined in both vaccinated and unvaccinated fish. ISH revealed more IgT mRNA+ cells in the second part of the midgut compared to other intestinal segments, as well as a higher number of positive cells in Group 2 (older fish). In line with previous findings, intraperitoneal vaccination had no significant impact on the number of IgT+ transcripts. IgT mRNA+ cells were found mostly in the lamina propria and near capillaries, while pIgR was registered in both the lamina propria and mucosa. Interestingly, vaccinated fish presented adhesions and granulomatous tissue in the peritoneum, with both IgT and pIgR mRNA+ cells. Taken together, these results suggest that the distribution of IgT mRNA+ cells in the intestine of Atlantic salmon is region-specific and is not affected by intraperitoneal vaccination but varies with fish age.
The Role of Biofilms in Contact Lens Associated Fungal Keratitis
Authors: Yi Jipan , Sun Yao , Zeng Chenghong , Kostoulias Xenia , Qu Yue
Published: October 2023

Biofilm formation is an important microbial strategy for fungal pathogens, such as Fusarium, Aspergillus, and Candida, to establish keratitis in patients wearing soft contact lenses. Despite the well-documented 2006 outbreak of Fusarium keratitis that eventually led to the withdrawal of the Bausch & Lomb multipurpose lens care solution ReNu with MoistureLoc (“MoistureLoc”) from the global market, contact lens care systems and solutions currently available on the market do not specifically target fungal biofilms. This is partially due to the lack of recognition and understanding of important roles that fungal biofilms play in contact lens associated fungal keratitis (CLAFK). This review aims to reemphasize the link between fungal biofilms and CLAFK, and deepen our comprehension of its importance in pathogenesis and persistence of this medical device-related infection.
Ligilactobacillus salivarius 7247 Strain: Probiotic Properties and Anti-Salmonella Effect with Prebiotics
Authors: Abramov Vyacheslav M. , Kosarev Igor V. , Machulin Andrey V. , Deryusheva Evgenia I. , Priputnevich Tatiana V. , Panin Alexander N. , Chikileva Irina O. , Abashina Tatiana N. , Manoyan Ashot M. , Ahmetzyanova Anna A. , Ivanova Olga E. , Papazyan Tigran T. , Nikonov Ilia N. , Suzina Nataliya E. , Melnikov Vyacheslav G. , Khlebnikov Valentin S. , Sakulin Vadim K. , Samoilenko Vladimir A. , Gordeev Alexey B. , Sukhikh Gennady T. , Uversky Vladimir N.
Published: October 2023

The Ligilactobacillus salivarius 7247 (LS7247) strain, originally isolated from a healthy woman’s intestines and reproductive system, has been studied for its probiotic potential, particularly against Salmonella Enteritidis (SE) and Salmonella Typhimurium (ST) as well as its potential use in synbiotics. LS7247 showed high tolerance to gastric and intestinal stress and effectively adhered to human and animal enterocyte monolayers, essential for realizing its probiotic properties. LS7247 showed high anti-Salmonella activity. Additionally, the cell-free culture supernatant (CFS) of LS7247 exhibited anti-Salmonella activity, with a partial reduction upon neutralization with NaOH (p < 0.05), suggesting the presence of anti-Salmonella factors such as lactic acid (LA) and bacteriocins. LS7247 produced a high concentration of LA, reaching 124.0 ± 2.5 mM after 48 h of cultivation. Unique gene clusters in the genome of LS7247 contribute to the production of Enterolysin A and metalloendopeptidase. Notably, LS7247 carries a plasmid with a gene cluster identical to human intestinal strain L. salivarius UCC118, responsible for class IIb bacteriocin synthesis, and a gene cluster identical to porcine strain L. salivarius P1ACE3, responsible for nisin S synthesis. Co-cultivation of LS7247 with SE and ST pathogens reduced their viability by 1.0–1.5 log, attributed to cell wall damage and ATP leakage caused by the CFS. For the first time, the CFS of LS7247 has been shown to inhibit adhesion of SE and ST to human and animal enterocytes (p < 0.01). The combination of Actigen prebiotic and the CFS of LS7247 demonstrated a significant combined effect in inhibiting the adhesion of SE and ST to human and animal enterocytes (p < 0.001). These findings highlight the potential of using the LS7247 as a preventive strategy and employing probiotics and synbiotics to combat the prevalence of salmonellosis in animals and humans caused by multidrug resistant (MDR) strains of SE and ST pathogens.
Differential Effects of Very-Low-Volume Exercise Modalities on Telomere Length, Inflammation, and Cardiometabolic Health in Obese Metabolic Syndrome Patients: A Subanalysis from Two Randomized Controlled Trials
Authors: Reljic Dejan , Koller Adriana , Herrmann Hans J. , Ekici Arif B. , Neurath Markus F. , Zopf Yurdagül
Published: October 2023

Oxidative stress (OS) and inflammation are features of metabolic syndrome (MetS) that can contribute to the shortening of telomere length (TL), a marker of cellular ageing. Research indicates that exercise can positively influence MetS-associated conditions and TL. However, the effects of low-volume exercise types on TL are still unknown. We investigated the impact of very-low-volume high-intensity interval training (LV-HIIT), one-set resistance training (1-RT), and whole-body electromyostimulation (WB-EMS) on TL, inflammation, and cardiometabolic indices in 167 MetS patients. Data were derived from two randomized controlled trials where patients were allocated to an exercise group (2 sessions/week, for 12 weeks) or a control group. All groups received standard-care nutritional weight loss counselling. TL was determined as the T/S ratio (telomere to single-copy gene amount). All groups significantly reduced body weight (p < 0.05), but the T/S-ratio (p < 0.001) only increased with LV-HIIT. OS-related inflammatory markers (C-reactive protein, interleukin-6, and lipopolysaccharide-binding protein) only decreased (p < 0.05) following LV-HIIT. The MetS severity z-score improved with LV-HIIT (p < 0.001) and 1-RT (p = 0.014) but not with WB-EMS. In conclusion, very-low-volume exercise modalities have differential effects on telomeres, inflammation, and cardiometabolic health. Only LV-HIIT but not strength-based low-volume exercise increased TL in MetS patients, presumably due to superior effects on OS-related inflammatory markers.
Quinoline Derivatives: Promising Antioxidants with Neuroprotective Potential
Authors: Hernández-Ayala Luis Felipe , Guzmán-López Eduardo Gabriel , Galano Annia
Published: October 2023

Quinoline has been proposed as a privileged molecular framework in medicinal chemistry. Although by itself it has very few applications, its derivatives have diverse biological activities. In this work, 8536 quinoline derivatives, strategically designed using the CADMA-Chem protocol, are presented. This large chemical space was sampled, analyzed and reduced using selection and elimination scores that combine their properties of bioavailability, toxicity and manufacturability. After applying several filters, 25 derivatives were selected to investigate their acid–base, antioxidant and neuroprotective properties. The antioxidant activity was predicted based on the ionization potential and bond dissociation energies, parameters directly related to the transfer of hydrogen atoms and of a single electron, respectively. These two mechanisms are typically involved in the radical scavenging processes. The antioxidant efficiency was compared with reference compounds, and the most promising antioxidants were found to be more efficient than Trolox but less efficient than ascorbate. In addition, based on molecular docking simulations, some derivatives are expected to act as inhibitors of catechol-O methyltransferase (COMT), acetylcholinesterase (AChE) and monoamine oxidase type B (MAO-B) enzymes. Some structural insights about the compounds were found to enhance or decrease the neuroprotection activity. Based on the results, four quinoline derivatives are proposed as candidates to act as multifunctional antioxidants against Alzheimer’s (AD) and Parkinson’s (PD) diseases.
Assessment of Thermal Comfort in an Electric Bus Based on Machine Learning Classification
Authors: Santoyo Alum Anuar , Fay Tu-Anh , Cigarini Francesco , Göhlich Dietmar
Published: October 2023

In electric buses, heating, ventilation and air conditioning are responsible for up to 50% of the energy consumption. It is therefore necessary to identify improved thermal settings to minimize the energy consumption, while guaranteeing good thermal comfort. Hence, an accurate prediction of the passengers’ thermal sensation (TS) is needed. One of the most widely used models for TS prediction is the PMV-PPD model, which has been shown to provide reliable results in uniform, steady-state climatic conditions. Since these are not present in an urban bus, the accuracy of the PMV-PPD model diminishes. Additionally, some of the parameters needed are difficult to obtain (i.e., clothing insulation). This paper presents seven different machine learning models (ML) for the prediction of TS using three different sets of parameters. The first set comprises five parameters similar to the PMV-PPD model, the second uses only two, and the third uses all parameters available. To obtain the necessary data, climatic measurements in an electric bus in Berlin, Germany, were made. These measurements were performed in summer for ambient temperatures between 14.7 °C and 32.0 °C. Person-related information as well as the thermal comfort assessment were obtained via surveys. Despite the relatively small data set, four of our seven ML models performed well with a median accuracy between 70.3% and 69.4%. This could also be observed when using only two parameters. Hence, the efforts to gain experimental data can be reduced significantly. For the PMV-PPD model, a median shift of +1 was observed for mild and warm TS. The median accuracy rises from 48.8% without shift to 68.8% with shift.
Approximate Global Energy Management Based on Macro–Micro Mixed Traffic Model for Plug-in Hybrid Electric Vehicles
Authors: He Zhisheng , Peng Haiyong , Gao Yanfei , Yang Jun , Hao Shenxue , Han Guangde , Wang Jian
Published: October 2023

A multi-scale physical process management system is presented in this paper, taking the plug-in hybrid electric vehicle system as the physical interface connecting the macro traffic system to the micro energy conversion process, with the ultimate goal of global energy management in the full temporal–spatial domain for autonomous plug-in hybrid electric vehicles. This novel method adopts a macro traffic flow model at a large time scale, in which only the initial conditions and the traffic information of key road sections are required, and a car following model at the micro scale. Furthermore, local replanning of energy management is carried out by adjusting the power threshold and the efficiency weight through the type of reinforcement learning that is closest to human learning, once a short term speed disturbance is induced by unknown disturbances in the macro traffic flow. Due to the nonlinear relationship between speed fluctuation and power fluctuation, it is necessary to map the vehicle speed and acceleration characteristics to the power characteristics, instead of directly utilizing the traffic model characterized by the speed and acceleration characteristics. The results show that novel multi-scale physical management can achieve a smaller deviation from the global optimal solution and enhanced robustness of global energy management. Additionally, close coupling between the dynamic characteristics of vehicle components and speed fluctuation ensures correct tracking of the optimized target value.
Reconstructed Prototype Network Combined with CDC-TAGCN for Few-Shot Action Recognition
Authors: Wu Aihua , Ding Songyu
Published: October 2023

Research on few-shot action recognition has received widespread attention recently. However, there are some blind spots in the current research: (1) The prevailing practice in many models is to assign uniform weights to all samples; nevertheless, such an approach may yield detrimental consequences for the model in the presence of high-noise samples. (2) Samples with similar features but different classes make it difficult for the model to be distinguished. (3) Skeleton data harbors rich temporal features, but most encoders face challenges in effectively extracting them. In response to these challenges, this study introduces a reconstructed prototype network (RC-PN) based on a prototype network framework and a novel spatiotemporal encoder. The RC-PN comprises two enhanced modules: Sample coefficient reconstruction (SCR) and a reconstruction loss function (LRC). SCR leverages cosine similarity between samples to reassign sample weights, thereby generating prototypes robust to noise interference and more adept at conveying conceptual essence. Simultaneously, the introduction of LRC enhances the feature similarity among samples of the same class while increasing feature distinctiveness between different classes. In the encoder aspect, this study introduces a novel spatiotemporal convolutional encoder called CDC-TAGCN. The temporal convolution operator is redefined in CDC-TAGCN. The vanilla temporal convolution operator can only capture the surface-level characteristics of action samples. Drawing inspiration from differential convolution (CDC), this research enhances TCN to CDC-TGCN. CDC-TGCN allows for the fusion of discrepant features from action samples into the features extracted by the vanilla convolutional operator. Extensive feasibility and ablation experiments are performed on the skeleton action dataset NTU-RGB + D 120 and Kinetics and compared with recent research.
Influence of Silver Nanoparticles on Color Stability of Room-Temperature-Vulcanizing Maxillofacial Silicone Subjected to Accelerated Artificial Aging
Authors: Mohammed Kaml , Zardawi Faraedon , Azhdar Bruska
Published: October 2023

In this in vitro study, we assessed the color stability of an A-2186 room-temperature-vulcanizing (RTV) silicone elastomer by incorporating silver nanoparticles during accelerated artificial aging. Using five intrinsic silicone pigment types, including no pigment (colorless), red, blue, mocha, and a combination of the three, we created 160 disk-shaped specimens. These were evenly distributed across 20 experimental groups, each containing 8 samples (n = 8). The specimens underwent aging for 250 and 500 h in an artificial aging chamber. A colorimeter was used to measure the values of L*a*b* according to the Commission Internationale de L’Éclairage (CIE) standards. The 50:50% perceptibility threshold (∆E* = 1.1) and acceptability threshold (∆E* = 3.0) were used in the interpretation of the recorded color differences. At the 0.05 level of significance, the one-way analysis of variance (ANOVA) and Tukey post hoc test were used in the statistical analysis. Fourier-transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) showed that 0.2% AgNPs after 500 h of aging protected the silicone elastomer matrix and all characteristic bonds of the silicone elastomer. In contrast, silicone without AgNPs showed the distortion of all bonds after 500 h. Chromatic alterations (∆E* > 0) were observed in all specimen groups, surpassing the perceptible threshold (1.1 units), except for mocha, with 0.2% AgNPs after 250 h of aging, which remained below the perceptible threshold (∆E* = 0.97). All groups demonstrated ∆E* values below the acceptable threshold, except for the red color, which exhibited a highly significant color change (p = 0.000). This study determined that all specimens, including colorless silicone, underwent color changes (∆E* > 0), with red displaying a notably significant chromatic alteration. Additionally, AgNPs demonstrated substantial protection of the silicone and reduced the color change across all groups and colors, with enhanced efficacy corresponding to higher AgNP concentrations (0.2% AgNPs > 0.15% AgNPs > 0.1% AgNPs).
Neuroprotective Potential of Isoquinoline Alkaloids from Glaucium grandiflorum Boiss. and A. Huet subsp. refractum (Nábelek) Mory: Role of NRF2-KEAP1 Pathway
Authors: Niğdelioğlu Dolanbay Serap , Şirin Seda , Aslim Belma
Published: October 2023

The extracts of Glaucium grandiflorum have been used to treat neurodegenerative diseases. Nonetheless, no former study has investigated whether the alkaloid extracts of G. grandiflorum have antioxidative effects against oxidative stress. The aim of the present study was to determine the antioxidative effects of the alkaloid extracts of G. grandiflorum with a variety of targets and probable mechanisms. First, we used spectrophotometry to investigate alkaloid extracts with respect to their alkaloid amounts. Then, we determined the alkaloid extracts’ impact on thiol/disulfide homeostasis, total oxidant status/total antioxidant status/oxidative stress index, and antioxidant enzyme activities. Finally, the effects of alkaloid extracts on the genes in the NRF2-KEAP1 pathway were determined via qRT-PCR. We conducted molecular docking analyses to determine the potential binding of isoquinoline alkaloids found within the alkaloid extracts with target proteins. We observed the best results from chloroform alkaloid extract and methanol alkaloid extract. Chloroform alkaloid extract was prominent in DPPH radical scavenging and metal ions chelating, and methanol alkaloid extract showed significant hydroxyl radical scavenging, lipid peroxidation, and superoxide anion radical scavenging activity. Alkaloid extract groups substantially increased in total thiol activity, native thiol activity, disulfide activity, total antioxidant status level, antioxidant enzyme levels, and gene expression levels (GCLC, HO-1, NRF2, and NQO1) compared to the H2O2 group. Also, alkaloid extract groups led to a significant drop in total oxidant status level, oxidative stress index level, and KEAP1 gene expression level relative to the H2O2 group. According to our study results, oxidative stress brought about by H2O2 was regulated by alkaloid extracts. As a result, a phytochemical-based therapeutic that regulates H2O2-induced oxidative stress was brought to the neurochemical field.
Lead Tolerance and Enrichment Characteristics of Three Hydroponically Grown Ornamental Plants
Authors: Shao Zeqiang , Li Mei , Zheng Juan , Zhang Jinjing , Lu Wenlong
Published: October 2023

Phytoremediation of lead (Pb) in contaminated soils using hyper-enriched plants is an important task. It is a green and sustainable measure. Studies have revealed that three ornamental plants, Tagetes patula (T. patula), Solanum nigrum (S. nigrum), and Mirabilis jalapa (M. jalapa), have the ability to enrich for Pb; however, studies on difference between them and root morphology and the relationship between tolerance and capacity are lacking. The ability of three lead-enriching plants, T. patula, S. nigrum, and M. jalapa, to cope with Pb stress was assessed in hydroponic experiments using five Pb stress concentrations (0–1000 mg/L). Under different Pb stress conditions, the growth of the shoots and roots of three tested ornamental plants was inhibited to varying degrees. In the three tested ornamental plants, Pb mainly accumulated in the roots, and the highest levels of Pb observed in the shoots of T. patula, S. nigrum, and M. jalapa were 1074.1 mg/kg, 958.7 mg/kg, and 975.3 mg/kg, respectively. All plants reached a critical level of Pb hyperaccumulation. Redundancy analysis showed that changes in the root architecture of the three tested ornamental plants were significantly and positively correlated with tolerance as well as the enrichment and transfer ability of the heavy metal Pb. Therefore, these three ornamental plants have the potential to remediate Pb-contaminated water and soil and can increase the tolerance and enrichment characteristics of Pb by regulating the root biomass and root length of the three test ornamental plants via various agronomic measures. In addition, more research should be conducted to assess their effectiveness as phytoextractants under field conditions.
Experimental Stability Analysis of Vertical Takeoff and Landing System Based on Robust Control Strategy
Authors: Ilyas Muhammad , Aziz Shahid , Shah Imran , Khan Awais , Jung Dong-Won
Published: October 2023

The Vertical Take-Off and Landing (VTOL) system is a multi-variable system subjected to harsh weather conditions, which creates challenges in proving the stability of the system before takeoff, which is essential for a flight dynamics system. The presented research work is based on the experimental results of the VTOL system to investigate and prove the stability using Lyapunov theory. This is achieved by tracking the pitch along the x-axis using cascaded control and integral super twisting sliding mode control (ISTSMC) algorithms. The motor current of the propeller assembly is regulated based on proportional integral (PI) and proportional integral derivative (PID) controllers. The cascaded control shows the maximum tracking error due to high-frequency fluctuations in the controller input signal, which lead to expensive mechanical losses for the actuators. The comparison of the results shows that ISTSMC outperforms the cascaded control strategy by reducing the tracking error to less than 1% percent and reducing the high-frequency fluctuations in the controller input signal. The hardware results show a minor delay in the transient response during vertical takeoff due to the inertia of the system and the tracking error due to air friction, etc., of the external environment, compared to the simulation results obtained in MATLAB.
A Novel Distributed Optical Fiber Temperature Sensor Based on Raman anti-Stokes Scattering Light
Authors: Lu Lidong , Wang Yishan , Liang Ce , Fan Jiaming , Su Xingchen , Huang Minnan
Published: October 2023

In this paper, a novel distributed optical fiber temperature sensor based on Raman anti-Stokes scattering light is proposed and experimentally demonstrated. The Raman anti-Stokes scattering light is sensitive to temperature parameters that are detected by the fiber under test conditions (FUT), and this allowed the temperature demodulation algorithm to be obtained through the relationship between the temperature and the power of the back-scattered Raman anti-Stokes light. In addition, we propose a new temperature calibration method to ensure accurate temperature measurement, which is greatly affected by the stability of a pulse laser. The experimental system is constructed with an optical fiber length of approximately 3.5 km. The proposed system obtains a 24 dB dynamic range with a pulse width of 20 ns and temperature testing ranges of 30.0 °C to 80.0 °C. The results demonstrate that the maximum temperature deviation range is −1.5 °C to +1.6 °C and the root mean square (RMS) error of the whole temperature range is 0.3 °C, which means it has the potential for practical engineering applications. More importantly, it avoids the walk-off effect that must be corrected in commonly used temperature demodulation schemes adopting both Raman Stokes light and anti-Stokes light. It also saves a signal channel, which is more suitable for the integration of hybrid distributed optical fiber sensing systems for multi-parameter monitoring.
Predictive Modeling of Urban Lake Water Quality Using Machine Learning: A 20-Year Study
Authors: Miller Tymoteusz , Durlik Irmina , Adrianna Krzemińska , Kisiel Anna , Cembrowska-Lech Danuta , Spychalski Ireneusz , Tuński Tomasz
Published: October 2023

Water-quality monitoring in urban lakes is of paramount importance due to the direct implications for ecosystem health and human well-being. This study presents a novel approach to predicting the Water Quality Index (WQI) in an urban lake over a span of two decades. Leveraging the power of Machine Learning (ML) algorithms, we developed models that not only predict, but also provide insights into, the intricate relationships between various water-quality parameters. Our findings indicate a significant potential in using ML techniques, especially when dealing with complex environmental datasets. The ML methods employed in this study are grounded in both statistical and computational principles, ensuring robustness and reliability in their predictions. The significance of our research lies in its ability to provide timely and accurate forecasts, aiding in proactive water-management strategies. Furthermore, we delve into the potential explanations behind the success of our ML models, emphasizing their capability to capture non-linear relationships and intricate patterns in the data, which traditional models might overlook.
Coal Gangue Target Detection Based on Improved YOLOv5s
Authors: Wang Shuxia , Zhu Jiandong , Li Zuotao , Sun Xiaoming , Wang Guoxin
Published: October 2023

Coal gangue sorting is a necessary process in coal mine production, and removing gangue is the basis for the coal production of clean energy; it is also an important approach to reduce the cost of washing, improve the grade of finished coal and increase the economic efficiency of coal mining enterprises. For the problem of high similarity and low-degree dynamic recognition of coal and gangue, a coal gangue target detection method based on improved YOLOv5s is proposed. Based on the YOLOv5s network, the decoupled head and SimAM attention mechanism are introduced and the CSP module in the neck part of YOLOv5s is replaced with the VoV-GSCSP structure. The experimental results show that the proposed method improves the mAP value by 6.1% over YOLOv5s in the gangue target detection task, while maintaining a higher detection speed. The coal gangue classification precision reaches 99.7% when tested on 1479 images. Compared with YOLOv5 series, YOLOv7 series, SSD and Faster-RCNN, the proposed method invariably yields higher precision and detection speed to meet the requirements of real-time detection. The experiments prove that the method proposed in this paper can be applied to the coal gangue sorting industry for fast and high-precision identification of coal gangue.
Lithological Mapping Research Based on Feature Selection Model of ReliefF-RF
Authors: Xi Jing , Jiang Qigang , Liu Huaxin , Gao Xin
Published: October 2023

Multispectral satellite data allow experts to discriminate rock units based on their spectral signature characteristics. Here, Sentinel-2, ASTER and the Landsat-8 Operational Land Imager (OLI) were assessed for lithological mapping by using a random forest (RF) classifier for a study area located in Xitieshan, Northwest China. The classification accuracy of Sentinel-2 was 60.71%, which was 5.24% and 4.77% higher than the accuracies for ASTER and the Landsat-8 OLI, respectively. Three image enhancement techniques, namely, principal component analysis (PCA), independent component analysis (ICA) and minimum noise fraction (MNF), were used with grey-level cooccurrence matrices (GLCMs) to increase the quality of the input datasets. The ICA could discriminate between rock unit datasets better than the other approaches. In contrast, GLCM performed poorly when used independently. The overall classification accuracies were 60.71%, 62.63%, 64.34%, 65.21% and 58.87% for the 10 bands of Sentinel-2, PCA, MNF, ICA and GLCM, respectively. Then, five datasets were combined as a single group and applied in RF classification. Sentinel-2 obtained an overall accuracy of 73.96% and performed better than the other single-dataset approaches used in this study. Furthermore, the classification result of RF was achieved better performance than that of the support vector machine algorithm (SVM). During feature selection processing, ReliefF, the most successful pre-processing algorithm, was employed to preliminarily perform feature screening. Then, the optimal dataset was selected on the basis of the importance ranking of RF. A total of 20 more important predictors were selected from 114 original features using the ReliefF-RF model. These predictors were used in the lithological mapping, and an overall accuracy of 77.63% was reached.
Train Rescheduling for Large Transfer Passenger Flow by Adding Cross-Line Backup Train in Urban Rail Transit
Authors: Yuan Jianjun , Zhao Xiaoqun , Chu Pengzi
Published: October 2023

The cross-line operation mode, based on interoperability technology, is becoming increasingly common in urban rail transits (URTs). Compared to trains running on a single line, cross-line trains can greatly facilitate transfer passengers. Taking the scenario of emergent large transfer passenger flow as an example, this paper explores the train rescheduling problem for serving transfer passengers by adding a cross-line backup train. To maximize the number of transfer passengers served by the cross-line backup train, a nonlinear optimization model is constructed by taking into account the operation parameters of planned trains on relevant lines, the deviation degree of the planned timetable, the utilization of the cross-line backup train, and the passenger flow calculation as constraints, and some linearization lemmas are proposed to transform it into a mixed integer programming (MIP) model with quadratic terms. A case study is conducted to discuss the impact of parameter changes on the objective function value and the applicability of different solution approaches. The results suggest that the operation trajectory of the cross-line backup train has an effect on the objective function value, which is related to the demand, the deviation tolerance of the planned timetable, and the running efficiency tolerance of the cross-line backup train. The corresponding methods help guide the organization of the cross-line backup train for large transfer passenger flow scenarios.
Geothermal Resource Mapping in Northern Botswana Inferred from Three-Dimensional Magnetotelluric Inversion
Authors: Ramotoroko Calistus , Thiede Anneke , Junge Andreas , Shemang Elisha
Published: October 2023

A set of magnetotelluric (MT) data collected from 28 stations at the Kasane Hot Spring in northern Botswana was used to derive a 3-D model of the electrical resistivity distribution around deep geologic structures that we associated with geothermal resources. The dimensionality analysis results revealed that 3-D modeling should be used to determine the electrical structure. The resistivity models revealed a conductive layer with an average thickness of 200 m, representing the overlying sediments of the Proterozoic volcanic rocks. The thick high-resistivity zone (>100 Ωm) below the conductive layer can be associated with Mesoproterozoic bedrock. The MT measurements in this area show a tube-shaped conductive anomaly that could serve as a fluid pathway feeding the hot spring. A fracture-controlled meteoric fluid circulation presumably determines the existence of the Kasane Hot Spring system.
Adipose Stromal Cell Spheroids for Cartilage Repair: A Promising Tool for Unveiling the Critical Maturation Point
Authors: Sargenti Azzurra , Pasqua Simone , Leu Marco , Dionisi Laura , Filardo Giuseppe , Grigolo Brunella , Gazzola Daniele , Santi Spartaco , Cavallo Carola
Published: October 2023

Articular cartilage lacks intrinsic regenerative capabilities, and the current treatments fail to regenerate damaged tissue and lead only to temporary pain relief. These limitations have prompted the development of tissue engineering approaches, including 3D culture systems. Thanks to their regenerative properties and capacity to recapitulate embryonic processes, spheroids obtained from mesenchymal stromal cells are increasingly studied as building blocks to obtain functional tissues. The aim of this study was to investigate the capacity of adipose stromal cells to assemble in spheroids and differentiate toward chondrogenic lineage from the perspective of cartilage repair. Spheroids were generated by two different methods (3D chips vs. Ultra-Low Attachment plates), differentiated towards chondrogenic lineage, and their properties were investigated using molecular biology analyses, biophysical measurement of mass density, weight, and size of spheroids, and confocal imaging. Overall, spheroids showed the ability to differentiate by expressing specific cartilaginous markers that correlate with their mass density, defining a critical point at which they start to mature. Considering the spheroid generation method, this pilot study suggested that spheroids obtained with chips are a promising tool for the generation of cartilage organoids that could be used for preclinical/clinical approaches, including personalized therapy.
Development of an Anti-HER2 Single-Chain Variable Antibody Fragment Construct for High-Yield Soluble Expression in Escherichia coli and One-Step Chromatographic Purification
Authors: Byun Kyu Tae , Kim Boram , Cho Junmin , Lee Inbeom , Lee Myung Gu , Park Dongsun , Kang Tae-Bong , Won Hyung-Sik , Kim Chan Gil
Published: October 2023

Although single-chain variable fragment (scFv) is recognized as a highly versatile scaffold of recombinant antibody fragment molecules, its overexpression in Escherichia coli often leads to the formation of inclusion bodies. To address this issue, we devised and tested four different constructs, named v21, v22, v23 and v24, for producing anti-human epidermal growth factor receptor 2 (HER2) scFv. Among them, the v24 construct obtained from N-terminal fusion of maltose-binding protein (MBP) and subsequent tobacco etch virus protease (TEV) was identified as the most efficient construct for the production of anti-HER2 scFv. Aided by an MBP tag, high-yield soluble expression was ensured and soluble scFv was liberated in cells via autonomous proteolytic cleavage by endogenously expressed TEV. The isolated scFv containing a C-terminal hexahistidine tag was purified through a one-step purification via nickel-affinity chromatography. The purified scFv exhibited a strong (nanomolar Kd) affinity to HER2 both in vitro and in cells. Structural and functional stabilities of the scFv during storage for more than one month were also assured. Given the great utility of anti-HER2 scFv as a basic platform for developing therapeutic and diagnostic agents for cancers, the v24 construct and methods presented in this study are expected to provide a better manufacturing system for producing anti-HER2 scFv with various industrial applications.
5′-tRF-19-Q1Q89PJZ Suppresses the Proliferation and Metastasis of Pancreatic Cancer Cells via Regulating Hexokinase 1-Mediated Glycolysis
Authors: Cao Wenpeng , Zeng Zhirui , Lei Shan
Published: October 2023

tRNA-derived small RNAs (tDRs) are dysregulated in several diseases, including pancreatic cancer (PC). However, only a limited number of tDRs involved in PC progression are known. Herein, a novel tDR, 5′-tRF-19-Q1Q89PJZ (tRF-19-Q1Q89PJZ), was verified in PC plasma using RNA and Sanger sequencing. tRF-19-Q1Q89PJZ was downregulated in PC tissues and plasma, which was related to advanced clinical characteristics and poor prognosis. tRF-19-Q1Q89PJZ overexpression inhibited the malignant activity of PC cells in vitro, while tRF-19-Q1Q89PJZ inhibition produced an opposite effect. The differentially expressed genes induced by tRF-19-Q1Q89PJZ overexpression were enriched in “pathways in cancer” and “glycolysis”. Mechanistically, tRF-19-Q1Q89PJZ directly sponged hexokinase 1 (HK1) mRNA and inhibited its expression, thereby suppressing glycolysis in PC cells. HK1 restoration relieved the inhibitory effect of tRF-19-Q1Q89PJZ on glycolysis in PC cells and on their proliferation and mobility in vitro. tRF-19-Q1Q89PJZ upregulation inhibited PC cell proliferation and metastasis in vivo and suppressed HK1 expression in tumor tissues. Furthermore, tRF-19-Q1Q89PJZ expression was attenuated under hypoxia. Collectively, these findings indicate that tRF-19-Q1Q89PJZ suppresses the malignant activity of PC cells by regulating HK1-mediated glycolysis. Thus, tRF-19-Q1Q89PJZ may serve as a key target for PC therapy.
Genetic and Pharmacological Blockade of Sigma-1 Receptors Attenuates Inflammation-Associated Hypersensitivity during Acute Colitis in CD1 Mice
Authors: López-Estévez Sergio , Aguilera Mònica , Gris Georgia , de la Puente Beatriz , Carceller Alicia , Martínez Vicente
Published: October 2023

Sigma-1 receptors (σ1Rs) are implicated in nociception, including pain sensitization, and inflammation. We assessed the role of σ1Rs on acute colitis-associated hypersensitivity using both genetic (constitutive knockout) and pharmacological blockade of the receptor. Colitis was induced in CD1 wild-type (WT) and σ1R KO mice (exposure to dextran sodium sulfate, 3%). A von Frey test was used to assess referred mechanosensitivity (abdominal and plantar withdrawal responses). The effects of the selective σ1R antagonists BD1063 and E-52862 were also assessed in WT animals. The expression of immune and sensory-related markers (RT-qPCR, Western blot) was assessed in the colon and lumbosacral spinal cord. The genetic ablation or pharmacological blockade of σ1Rs attenuated acute colonic inflammation in a similar manner. Mechanosensitivity was similar in WT and σ1R KO mice before colitis. In WT mice, but not in σ1R KO, colitis was associated with the development of referred mechanical hypersensitivity, manifested as a reduction in the withdrawal thresholds to mechanical probing (paw and abdominal wall). In WT mice, BD1063 and E-52862 blocked colitis-associated hypersensitivity. A genotype- and treatment-related differential regulation of sensory-related markers was detected locally (colon) and within the spinal cord. σ1Rs are involved in the development of acute intestinal inflammation and its associated referred mechanical hypersensitivity. The selective modulation of sensory-related pathways within the colon and spinal cord might be part of the underlying mechanisms. These observations support the pharmacological use of σ1R antagonists for the treatment of intestinal inflammation-induced hypersensitivity.