bluuebunny/crossref_metadata_2025 huggingface dataset:
Whole Genome Sequencing of Avian Pathogenic Escherichia coli Causing Bacterial Chondronecrosis and Osteomyelitis in Australian Poultry
Authors: Cummins Max L. , Li Dmitriy , Ahmad Aeman , Bushell Rhys , Noormohammadi Amir H. , Wijesurendra Dinidu S. , Stent Andrew , Marenda Marc S. , Djordjevic Steven P.
Published: June 2023

Bacterial chondronecrosis with osteomyelitis (BCO) impacts animal welfare and productivity in the poultry industry worldwide, yet it has an understudied pathogenesis. While Avian Pathogenic Escherichia coli (APEC) are known to be one of the main causes, there is a lack of whole genome sequence data, with only a few BCO-associated APEC (APECBCO) genomes available in public databases. In this study, we conducted an analysis of 205 APECBCO genome sequences to generate new baseline phylogenomic knowledge regarding the diversity of E. coli sequence types and the presence of virulence associated genes (VAGs). Our findings revealed the following: (i) APECBCO are phylogenetically and genotypically similar to APEC that cause colibacillosis (APECcolibac), with globally disseminated APEC sequence types ST117, ST57, ST69, and ST95 being predominate; (ii) APECBCO are frequent carriers of ColV-like plasmids that carry a similar set of VAGs as those found in APECcolibac. Additionally, we performed genomic comparisons, including a genome-wide association study, with a complementary collection of geotemporally-matched genomes of APEC from multiple cases of colibacillosis (APECcolibac). Our genome-wide association study found no evidence of novel virulence loci unique to APECBCO. Overall, our data indicate that APECBCO and APECcolibac are not distinct subpopulations of APEC. Our publication of these genomes substantially increases the available collection of APECBCO genomes and provides insights for the management and treatment strategies of lameness in poultry.
Eight Up-Coming Biotech Tools to Combat Climate Crisis
Authors: Fuchs Werner , Rachbauer Lydia , Rittmann Simon K.-M. R. , Bochmann Günther , Ribitsch Doris , Steger Franziska
Published: June 2023

Biotechnology has a high potential to substantially contribute to a low-carbon society. Several green processes are already well established, utilizing the unique capacity of living cells or their instruments. Beyond that, the authors believe that there are new biotechnological procedures in the pipeline which have the momentum to add to this ongoing change in our economy. Eight promising biotechnology tools were selected by the authors as potentially impactful game changers: (i) the Wood–Ljungdahl pathway, (ii) carbonic anhydrase, (iii) cutinase, (iv) methanogens, (v) electro-microbiology, (vi) hydrogenase, (vii) cellulosome and, (viii) nitrogenase. Some of them are fairly new and are explored predominantly in science labs. Others have been around for decades, however, with new scientific groundwork that may rigorously expand their roles. In the current paper, the authors summarize the latest state of research on these eight selected tools and the status of their practical implementation. We bring forward our arguments on why we consider these processes real game changers.
Production of Antioxidant Transfersomes by a Supercritical CO2 Assisted Process for Transdermal Delivery Applications
Authors: Squittieri Raffaella , Baldino Lucia , Reverchon Ernesto
Published: June 2023

Transfersomes are deformable vesicles that can transport drugs across difficult-to-permeate barriers in human tissues. In this work, nano-transfersomes were produced for the first time by a supercritical CO2 assisted process. Operating at 100 bar and 40 °C, different amounts of phosphatidylcholine (2000 and 3000 mg), kinds of edge activators (Span® 80 and Tween® 80), and phosphatidylcholine to edge activator weight ratio (95:5, 90:10, 80:20) were tested. Formulations prepared using Span® 80 and phosphatidylcholine at an 80:20 weight ratio produced stable transfersomes (−30.4 ± 2.4 mV ζ-potential) that were characterized by a mean diameter of 138 ± 55 nm. A prolonged ascorbic acid release of up to 5 h was recorded when the largest amount of phosphatidylcholine (3000 mg) was used. Moreover, a 96% ascorbic acid encapsulation efficiency and a quasi-100% DPPH radical scavenging activity of transfersomes were measured after supercritical processing.
Non-Isothermal Crystallization Kinetics of Montmorillonite/Polyamide 610 Nanocomposites
Authors: Fu Yang , Huo Cuimeng , Liu Shuangyan , Li Keqing , Meng Yuezhong
Published: June 2023

Non-isothermal crystallization kinetics of montmorillonite (MMT)/polyamide 610 (PA610) composites were readily prepared by in situ melt polymerization followed by a full investigation in terms of their microstructure, performance, and crystallization kinetics. The kinetic models of Jeziorny, Ozawa, and Mo were used in turn to fit the experimental data, in all of which Mo’s analytical method was found to be the best model for the kinetic data. Differential scanning calorimetry (DSC) and transmission electron microscopy (TEM) studies were used to investigate the isothermal crystallization behavior and MMT dispersion levels in the MMT/PA610 composites. The experiment results revealed that low MMT content can promote the PA610 crystallization, whilst high MMT content result in MMT agglomeration, and reduce the PA610 crystallization rate.
Salt Substitutes—An Important Tool to Increase Potassium and Reduce Sodium Intakes?
Authors: McLean Rachael Mira
Published: June 2023

Potassium is an essential mineral and is the main cation in intracellular fluid [...]
Recent Progress in the Management of Obesity
Authors: Gómez-Ambrosi Javier
Published: June 2023

Obesity represents the most prevalent metabolic disease nowadays, posing a significant public health risk [...]
Alleviation of Pain, PAIN Interference, and Oxidative Stress by a Novel Combination of Hemp Oil, Calamari Oil, and Broccoli: A Randomized, Double-Blind, Placebo-Controlled Trial
Authors: Carlisle Carolina , Polley Kristine , Panda Chinmayee , Barron Keri , Hamrock Meghan , Dominique Ashley , Metzger Brandon , Le Brun-Blashka Sara , Komarnytsky Slavko
Published: June 2023

Chronic pain is a critical health issue in the US that is routinely managed pharmacologically with diminishing results. The widespread misuse and abuse of prescription opioid pain medications have caused both healthcare providers and patients to seek alternative therapeutic options. Several dietary ingredients have been traditionally used for pain relief and are known to have potential analgesic properties. This double-blind, placebo-controlled randomized clinical trial aimed to test whether a novel combination of full spectrum hemp oil (phytocannabinoids), calamari oil (omega-3 fatty acids), and broccoli (glucosinolates) could reduce chronic pain and attenuate damage from oxidative stress in adults seeking chiropractic care. Participants (average age = 54.8 ± 13.6 years old) were randomly assigned to consume a whole-food, multi-ingredient supplement (n = 12, intervention and standard chiropractic care) or placebo (n = 13, mineral oil and standard chiropractic care) daily for 12 weeks. The subjects’ self-reported perceived pain, pain interference, and reactive oxygen species (ROS) status in the peripheral blood mononuclear cells (PBMC) were quantified at baseline, mid-checkpoint, and postintervention. The intervention was positively associated with a 52% decrease in pain intensity and several parameters of pain interference, including quality of sleep. Decreases in the markers of oxidative stress were also observed in the participants from the intervention group (29.4% decrease in PMBC ROS). Our findings indicated that supplementation with a novel combination of hemp oil, calamari oil, and broccoli has the potential to manage chronic pain when combined with standard chiropractic care, as suggested by its effects on pain intensity and oxidative stress.
Effects of Preoperative Sarcopenia-Related Parameters on Cardiac Autonomic Function in Women with Obesity Following Bariatric Surgery: A One-Year Prospective Study
Authors: Crispim Carvalho Nara Nóbrega , Baccin Martins Vinícius José , da Nóbrega Vinícius Almeida , de Arruda Neta Adélia da Costa Pereira , Cavalcante da Fonseca Luís Antônio , Bandeira Francisco , de Brito Alves José Luiz
Published: June 2023

Objectives: Investigate changes in blood pressure (BP) and heart rate variability (HRV) in women with and without sarcopenia-related parameters who underwent bariatric surgery (BS) during a one-year follow-up. Subjects and Methods: Women were separated into obesity (OB, n = 20) and women with obesity displaying sarcopenia-related parameters (SOP, n = 14) and evaluated before BS and 3, 6, and 12 months after BS. SOP was defined as low handgrip strength (HS) and/or low appendicular skeletal mass adjusted for weight (ASM/wt × 100, %) in the lowest quartile of the sample. ASM/wt × 100, % and HS were significantly lower in SOP than OB over a one-year follow-up of BS (p < 0.05). Results: There was a reduction in diastolic BP, heart rate (HR), SDHR, LF, and the LF/HF ratio (p < 0.05) and an increase in the HF band in both groups during the follow-up period (p < 0.05). SOP women had reduced root mean square differences of successive RR intervals (RMSSD) and HF band and an increased LF band and SD2/SD1 ratio compared to the OB group during the one-year follow-up (p < 0.05). ASM/wt × 100, % was negatively associated with the LF band (r = −0.24, p = 0.00) and positively associated with the HF band (r = 0.22, p = 0.01). Conversely, HS had no association with LF (r = −0.14, p = 0.09) and HF (r = 0.11, p = 0.19). ASM/wt × 100, % and HS were negatively associated with the LF/HF ratio (p < 0.05). Conclusions: Women who underwent BS had an improved HRV over a one-year follow-up. However, the improvement in HRV variables was less pronounced in women with low muscle mass and/or HS during the follow-up period.
Factors Influencing the Intention to Sign Up for Advanced Care Planning in Day Care for Psychiatric Patients
Authors: Chen Yi-Chien , Huang Chin-Yu , Lee Chao-Hsien
Published: June 2023

(1) Background: Currently, Taiwan has adopted a “person-centered” approach to Advance Care, including Hospice Palliative Care and Advance Decisions, both of which are intended to enhance the right of individuals to choose their own end-of-life care; however, it is extremely challenging and difficult to implement the principle of autonomy for psychiatric patients. (2) Methodology: The aim in this study is to investigate the factors affecting the intention of day ward patients to sign up for hospice and palliative care by using the questionnaire content of the “Survey on Knowledge, Attitude Toward, Experience, and Behavior Intention to Sign Up for Hospice and Palliative Care”. A cross-sectional design compliant with STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) was employed. An independent sample t-test, Pearson’s correlation analysis, and stepwise regression analysis were used to determine the factors influencing the intention of psychiatric patients to sign up for advanced care planning. (3) Results: The relationships between knowledge of and attitude toward advanced care planning, knowledge of and behavior intention to sign up for advanced care planning, and attitude toward and behavior intention to sign up for advanced care planning were all positive (p-value < 0.001). The final three most relevant indicators were attitude toward hospice and palliative care, hospitalization of family members during the previous five years, and death of a close friend within the previous five years. (4) Conclusions: The results of the study show that the hospice and palliative care attitude and past experience of psychiatric patients affect the intention to sign up, reminding us that psychiatric patients are at an increased risk of decision-making disability as their illness progresses and that, in addition to initiating the discussion of Advance Care Planning as soon as possible, it may be an opportune time for medical professionals to actively promote Advance Care Planning among their patients.
Photonic-Enabled Image Rejection Mixer with Simultaneous Wideband Self-Interference Cancellation for In-Band Full-Duplex System
Authors: Li He , Zhu Zihang , Gao Congrui , Wang Guodong , Zhou Tao , Li Xuan , Meng Qingqing , Zhou Yixiao , Zhao Shanghong
Published: June 2023

In this paper, a photonic-enabled image rejection mixer (IRM) that features an ultrawideband self-interference cancellation (SIC) function and a compact configuration is proposed. The parameter tuning of SIC is realized in an optical domain, which avoids the use of electrically tuned devices with limited bandwidth and precision, so that high-precision parameter matching can be realized in the optical domain to realize deep and ultrawideband SIC. The key point of image rejection (IR) is to construct a pair of orthogonal local oscillation (LO) signals through DC-bias-induced phase shift. This not only avoids a high-frequency electrical 90-degree hybrid coupler (HC) applied in the traditional Hartley structure, but also compensates the phase deviation in the electrical intermediate frequency (IF) 90-degree HC flexibly, ensuring wideband and deep IR operation. The simulation results show that the proposed IRM can achieve ultrawideband SIC and IR with the simultaneous high-efficiency recovery of useful signals. They also verify that the scheme has good resistance to strong interference, and can cope with the phase imbalance of the IF 90-degree electrical HC, ensuring the good performance of the system, which has a wide application prospect in various in-band full-duplex (IBFD) systems.
Dynamic Translational Landscape Revealed by Genome-Wide Ribosome Profiling under Drought and Heat Stress in Potato
Authors: Jian Hongju , Wen Shiqi , Liu Rongrong , Zhang Wenzhe , Li Ziyan , Chen Weixi , Zhou Yonghong , Khassanov Vadim , Mahmoud Ahmed M. A. , Wang Jichun , Lyu Dianqiu
Published: June 2023

The yield and quality of potatoes, an important staple crop, are seriously threatened by high temperature and drought stress. In order to deal with this adverse environment, plants have evolved a series of response mechanisms. However, the molecular mechanism of potato’s response to environmental changes at the translational level is still unclear. In this study, we performed transcriptome- and ribosome-profiling assays with potato seedlings growing under normal, drought, and high-temperature conditions to reveal the dynamic translational landscapes for the first time. The translational efficiency was significantly affected by drought and heat stress in potato. A relatively high correlation (0.88 and 0.82 for drought and heat stress, respectively) of the fold changes of gene expression was observed between the transcriptional level and translational level globally based on the ribosome-profiling and RNA-seq data. However, only 41.58% and 27.69% of the different expressed genes were shared by transcription and translation in drought and heat stress, respectively, suggesting that the transcription or translation process can be changed independently. In total, the translational efficiency of 151 (83 and 68 for drought and heat, respectively) genes was significantly changed. In addition, sequence features, including GC content, sequence length, and normalized minimal free energy, significantly affected the translational efficiencies of genes. In addition, 28,490 upstream open reading frames (uORFs) were detected on 6463 genes, with an average of 4.4 uORFs per gene and a median length of 100 bp. These uORFs significantly affected the translational efficiency of downstream major open reading frames (mORFs). These results provide new information and directions for analyzing the molecular regulatory network of potato seedlings in response to drought and heat stress.
Population Structure of Modern Winter Wheat Accessions from Central Asia
Authors: Amalova Akerke , Yermekbayev Kanat , Griffiths Simon , Winfield Mark Owen , Morgounov Alexey , Abugalieva Saule , Turuspekov Yerlan
Published: June 2023

Despite the importance of winter wheat in Central Asian countries, there are limited reports describing their diversity within this region. In this study, the population structures of 115 modern winter wheat cultivars from four Central Asian countries were compared to germplasms from six other geographic origins using 10,746 polymorphic single-nucleotide polymorphism (SNP) markers. After applying the STRUCTURE package, we found that in terms of the most optimal K steps, samples from Kazakhstan and Kyrgyzstan were grouped together with samples from Russia, while samples from Tajikistan and Uzbekistan were grouped with samples from Afghanistan. The mean value of Nei’s genetic diversity index for the germplasm from four groups from Central Asia was 0.261, which is comparable to that of the six other groups studied: Europe, Australia, the USA, Afghanistan, Turkey, and Russia. The Principal Coordinate Analysis (PCoA) showed that samples from Kyrgyzstan, Tajikistan, and Uzbekistan were close to samples from Turkey, while Kazakh accessions were located near samples from Russia. The evaluation of 10,746 SNPs in Central Asian wheat suggested that 1006 markers had opposing allele frequencies. Further assessment of the physical positions of these 1006 SNPs in the Wheat Ensembl database indicated that most of these markers are constituents of genes associated with plant stress tolerance and adaptability. Therefore, the SNP markers identified can be effectively used in regional winter wheat breeding projects for facilitating plant adaptation and stress resistance.
Effect of Biochar Type, Concentration and Washing Conditions on the Germination Parameters of Three Model Crops
Authors: Carril Pablo , Ghorbani Majid , Loppi Stefano , Celletti Silvia
Published: June 2023

Biochar has been recognized as a promising and efficient material for soil amendment. However, its effects on seed germination are variable due to its alkaline pH and/or the presence of phytotoxic substances. In this study, two types of biochar (B1 and B2) were mixed with soil at different concentrations (0%, 5%, 10%, 25%, 50% and 100%, w:w), and both the solid and liquid fractions of these mixtures were tested on the germination of basil, lettuce and tomato seeds. Furthermore, solid fractions subjected to a pre-washing treatment (B1W and B2W) were also investigated for their effects on seed germination. Three germination parameters were then measured: seed germination number (GN), radicle length (RL) and germination index (GI). Biochar B2W at 10% increased both RL and GI in basil by 50% and 70%, respectively, while B1 at 25% increased these parameters in tomato by 25%. No effects or negative effects were recorded for lettuce. Liquid fractions (L1 and L2) generally hampered seed germination, suggesting the presence of potentially water-soluble phytotoxic compounds in biochar. These results point to biochar as a suitable component for germination substrates and highlight that germination tests are critical to select the best performing biochar according to the target crop.
Transcriptome-Based Study on the Phylogeny and Hybridization of Marattialean Ferns (Marattiaceae)
Authors: Zhao Jing , Zhou Xinmao , Fang Shaoli , Zhu Zhangming , Li Yuxin , Yu Hong , He Zhaorong
Published: June 2023

Marattiaceae is a phylogenetically isolated family of tropical eusporangiate ferns including six genera with more than one-hundred species. In Marattiaceae, monophyly of genera has been well-supported phylogenetically. However, the phylogenetic relationships among them were elusive and controversial. Here, a dataset of 26 transcriptomes (including 11 newly generated) were used to assess single-copy nuclear genes and to obtain the organelle gene sequences. Through phylotranscriptomic analysis, the phylogeny and hybridization events of Marattiaceae were explored and a robust phylogenomic framework for the evolution of Marattiaceae was provided. Using both concatenation- and coalescent-based phylogenies, the gene-tree discordance, incomplete lineage sorting (ILS) simulations, and network inference were examined. Except the low support with mitochondrial genes of Marattiaceae, nuclear genes and chloroplast genes strongly supported a sister relationship between Marattiaceae and leptosporangiate ferns. At the genus level, all phylogenetic analysis based on nuclear genes datasets recovered five genera in Marattiaceae as monophyletic with strong support. Danaea and Ptisana were the first two diverged clades in turn. Christensenia was a sister clade to the clade Marattia + Angiopteris s.l. In Angiopteris s.l., three clades (Angiopteris s.s., the Archangiopteris group, and An. sparsisora) were well identified with maximum support. The Archangiopteris group was derived from Angiopteris s.s. at ca. 18 Ma. The putative hybrid species An. sparsisora between Angiopteris s.s. and the Archangiopteris group was verified by the species network analyses and the maternal plastid genes. This study will improve our understanding for using the phylotranscriptomic method to explore phylogeny and investigate hybridization events for difficult taxa in ferns.
Study on Multi-Objective Optimization of Logistics Distribution Paths in Smart Manufacturing Workshops Based on Time Tolerance and Low Carbon Emissions
Authors: Wu Chao , Xiao Yongmao , Zhu Xiaoyong , Xiao Gongwei
Published: June 2023

In the Industry 4.0 environment, an ideal smart factory should be intelligent, green, and humanized, and the logistics transportation from raw materials to final products in the factory should be completed by smart logistics. In order to address the problems of low efficiency, poor workstation service satisfaction, high distribution costs, and non-greening during the logistics distribution processes in discrete smart manufacturing workshops are required. A mathematical model of optimized multi-objective green logistics distribution paths in a smart manufacturing workshop has been constructed in this study, with low costs, high efficiency, and workstation service satisfaction taken into consideration. Then, this mathematical model was solved with an improved ant colony optimization algorithm. A “time window span” was introduced in the basic ant colony optimization algorithm to prioritize the services to workstations with a relatively high urgency in material demand, with the aim of improving workstation service satisfaction. Lastly, in order to verify the effectiveness of the model and algorithm proposed in this study, a simulation experiment has been conducted on the workstation logistics distribution system in a smart manufacturing workshop to provide convincing evidence for optimizing workstation logistics distribution paths in workshops of discrete manufacturing enterprises.
Crude Glycerol Hydrogenolysis to Bio-Propylene Glycol: Effect of Its Impurities on Activity, Selectivity and Stability
Authors: Gatti Martín , Pompeo Francisco , Nichio Nora , Santori Gerardo
Published: June 2023

The wide availability of crude glycerol and its low market price make this by-product of the biodiesel industry a promising raw material for obtaining high-value-added products through catalytic conversion processes. This work studied the effect of the composition of different industrial crude glycerol samples on the catalytic hydrogenolysis to 1,2-propylene glycol. A nickel catalyst supported on a silica–carbon composite was employed with this purpose. This catalyst proved to be active, selective to 1,2-propylene glycol and stable in the glycerol hydrogenolysis reaction in the liquid phase when analytical glycerol (99% purity) was employed. In order to determine the effect of crude glycerol composition on the activity, selectivity and stability of this catalyst, industrial crude glycerol samples were characterized by identifying and quantifying the impurities present in them (methanol, NaOH, NaCl and NaCOOH). Reaction tests were carried out with aqueous solutions of analytical glycerol, adding different impurities one by one in their respective concentration range. These results allowed for calculating activity factors starting from the ratio between the rate of glycerol consumption in the presence and in the absence of impurities. Finally, catalyst performance was evaluated employing the industrial crude glycerol samples, and a kinetic model based on the power law was proposed, which fitted the experimental results taking into account the effect of glycerol impurities. The fit allowed for predicting conversion values with an average error below 8%.
Using Direct Solar Energy Conversion in Distillation via Evacuated Solar Tube with and without Nanomaterials
Authors: Saleh Bahaa , Essa Fadl A. , Omara Zakaria M. , Ahmed Mohamed H. , El-Sebaey Mahmoud S. , Stephen Mogaji Taye , Sundar Lingala Syam , Qasim Mohammed A. , Ramana Eskilla Venkata , Shanmugan Sengottiyan , Elsheikh Ammar H.
Published: June 2023

As is widely known, the issue of freshwater scarcity affects practically all people, and all are looking for innovative and workable ways to attempt to solve this issue. In this work, a novel method of desalination is proposed. The proposed system consists of a solar collector (PTSC), evacuated pipe (EP), condenser (CU), and separation unit (SU). The working principle of the system is heating the feed saline water using the PTSC and EP and controlling the water flow rate to control the output conditions of the EP. The produced vapor is therefore separated from salty water using the SU. In addition, the generated steam is condensed into the CU to produce a freshwater distillate. Consequently, the effect of solar radiation on the affecting temperatures was tested. In addition, the effect of using different water flow rates (6, 7.5, 10, 20, 40, and 60 L/h) inside the EP on the system productivity was investigated. The primary findings of this work may be highlighted in relation to the experiments conducted. At midday, when ultraviolet irradiance reached its highest, the EP’s water flow entrance and outflow had the largest temperature differential. In addition, the lower the water flow rate inside the EP, the higher the water temperature, the higher the evaporation rate of the system, and the greater the freshwater productivity of the system. At 6 L/h, the water’s highest temperature was 92 °C. Moreover, the best performance of the system was obtained at 7.5 L/h, where the freshwater production and average daily effectiveness of the distillate process were 44.7 L/daytime and 59.6%, respectively. As well, the productivity of EP was augmented by around 11.86% when using graphite nanoparticles. Additionally, the distilled freshwater from the system operating at the flow rate of 7.5 L/h costs 0.0085 $/L.
A Review on the Full Chain Application of 3D Printing Technology in Precision Medicine
Authors: Wu Shenglin , Zeng Jinbin , Li Haoxin , Han Chongyang , Wu Weibin , Zeng Wenyi , Tang Luxin
Published: June 2023

Personalized precision medicine is a new direction for medical development, and advanced manufacturing technology can provide effective support for the development of personalized precision medicine. Based on the layered accumulation manufacturing principle, 3D printing technology has unique advantages in personalized rapid manufacturing, and can form complex geometric shape parts at low cost and high efficiency. This article introduces the application progress of 3D printing technology in medical models, surgical navigation templates, invisible aligners, and human implants, analyzes their advantages and limitations, and provides an outlook for the development trend of 3D printing technology in precision medicine.
Thermal Stability and Kinetics of Degradation of Moxonidine as Pure Ingredient vs. Pharmaceutical Formulation
Authors: Baul Bianca , Ledeţi Adriana , Cîrcioban Denisa , Ridichie Amalia , Vlase Titus , Vlase Gabriela , Peter Francisc , Ledeţi Ionuţ
Published: June 2023

The stability of active pharmaceutical ingredients (APIs) and the corresponding pharmaceutical formulations are nowadays of great importance in pharmaceutical research and technology. The quality of an API or of finished pharmaceutical products (FPPs) is time dependent under the influence of several parameters, such as light and air exposure, temperature, and humidity. Additionally, the stability profile of an API is influenced by the formulation composition, due to the presence of excipients or by the characteristic of the packaging materials. In this sense, the main objective of this study was to analyze the degradation kinetics of the antihypertensive drug moxonidine as a pure ingredient (MOX) and in two different solid mixtures, one corresponding to a pharmaceutical formulation (MOXTAB) and the other to an enriched pharmaceutical formulation in MOX (MOXMIX). As investigation techniques, FTIR (Fourier transform infrared) spectroscopy and TG/DTG/HF analysis were employed, while the thermoanalytical data were processed according to the ASTM E698 kinetic method and the isoconversional methods of Flynn–Wall–Ozawa (FWO) and Friedman (FR). The kinetic methods revealed that the excipients have a stabilizing effect on MOX (in terms of Ea values), but the decomposition mechanism of the samples is complex, according to the results suggested by the analysis of Ea vs. α values.
A Combined Deep Learning and Prior Knowledge Constraint Approach for Large-Scale Forest Disturbance Detection Using Time Series Remote Sensing Data
Authors: Du Bing , Yuan Zhanliang , Bo Yanchen , Zhang Yusha
Published: June 2023

The scale and severity of forest disturbances across the globe are increasing due to climate change and human activities. Remote sensing analysis using time series data is a powerful approach for detecting large-scale forest disturbances and describing detailed forest dynamics. Various large-scale forest disturbance detection algorithms have been proposed, but most of them are only suitable for detecting high-magnitude forest disturbances (e.g., fire, harvest). Conversely, more continuous, subtle, and gradual lower-magnitude forest disturbances (e.g., thinning, pests, and diseases) have been subject to less focus. Deep learning (DL) can distinguish subtle differences in information within time series data, offering new opportunities to capture forest disturbances in a complete and detailed way. This study proposes an approach for analyzing forest dynamics across large areas and long time periods by combining DL time series classification and prior knowledge constraint. The approach consists of two stages: (1) an improved self-attention model used for time series classification to identify sequences with forest disturbance characteristics; (2) developed skip-disturbance recovery index (S-DRI) characterizing the temporal context, using prior knowledge constraint to identify forest disturbance years in time series with disturbance characteristics. In this study, the year of forest disturbances in five study areas located in the United States, Canada, and Poland from 2001 to 2020 was mapped. A total of 3082 manually interpreted test data with different disturbance causal agents (such as fire, harvest, conversion, hurricane, and pests) were sampled from five research areas for validation. Our approach was also evaluated against two forest disturbance benchmark datasets derived from LandTrendr and the Global Forest Change (GFC) dataset. The results demonstrate that our approach achieved an overall accuracy of 87.8%, surpassing the accuracy of LandTrendr (84.6%) and the Global Forest Change dataset (81.4%). Furthermore, our approach demonstrated lower omission rates (ranging from 10.0% to 67.4%) in detecting subtle to severe causal agents of forest disturbance, in comparison to LandTrendr (with a range of 18.0% to 81.6%) and GFC (with a range of 15.0% to 88.8%). This study, which involved mapping large-scale and long-term forest disturbance in multiple regions, revealed that our approach can be applied to new areas without a requirement for complex parameter adjustments. These results demonstrate the potential of our approach in generating comprehensive and detailed forest disturbance data, thus providing a new and effective method in this domain.
The Microscopic Mechanisms of Nonlinear Rectification on Si-MOSFETs Terahertz Detector
Authors: Wei Yingdong , Yao Chenyu , Han Li , Zhang Libo , Chen Zhiqingzi , Wang Lin , Lu Wei , Chen Xiaoshuang
Published: June 2023

Studying the nonlinear photoresponse of different materials, including III-V semiconductors, two-dimensional materials and many others, is attracting burgeoning interest in the terahertz (THz) field. Especially, developing field-effect transistor (FET)-based THz detectors with preferred nonlinear plasma-wave mechanisms in terms of high sensitivity, compactness and low cost is a high priority for advancing performance imaging or communication systems in daily life. However, as THz detectors continue to shrink in size, the impact of the hot-electron effect on device performance is impossible to ignore, and the physical process of THz conversion remains elusive. To reveal the underlying microscopic mechanisms, we have implemented drift-diffusion/hydrodynamic models via a self-consistent finite-element solution to understand the dynamics of carriers at the channel and the device structure dependence. By considering the hot-electron effect and doping dependence in our model, the competitive behavior between the nonlinear rectification and hot electron-induced photothermoelectric effect is clearly presented, and it is found that the optimized source doping concentrations can be utilized to reduce the hot-electron effect on the devices. Our results not only provide guidance for further device optimization but can also be extended to other novel electronic systems for studying THz nonlinear rectification.
Precision Denavit–Hartenberg Parameter Calibration for Industrial Robots Using a Laser Tracker System and Intelligent Optimization Approaches
Authors: Khanesar Mojtaba A. , Yan Minrui , Isa Mohammed , Piano Samanta , Branson David T.
Published: June 2023

Precision object handling and manipulation require the accurate positioning of industrial robots. A common practice for performing end effector positioning is to read joint angles and use industrial robot forward kinematics (FKs). However, industrial robot FKs rely on the robot Denavit–Hartenberg (DH) parameter values, which include uncertainties. Sources of uncertainty associated with industrial robot FKs include mechanical wear, manufacturing and assembly tolerances, and robot calibration errors. It is therefore necessary to increase the accuracy of DH parameter values to reduce the impact of uncertainties on industrial robot FKs. In this paper, we use differential evolution, particle swarm optimization, an artificial bee colony, and a gravitational search algorithm to calibrate industrial robot DH parameters. A laser tracker system, Leica AT960-MR, is utilized to register accurate positional measurements. The nominal accuracy of this non-contact metrology equipment is less than 3 μm/m. Metaheuristic optimization approaches such as differential evolution, particle swarm optimization, an artificial bee colony and a gravitational search algorithm are used as optimization methods to perform the calibration using laser tracker position data. It is observed that, using the proposed approach with an artificial bee colony optimization algorithm, the accuracy of industrial robot FKs in terms of mean absolute errors of static and near-static motion over all three dimensions for the test data decreases from its measured value of 75.4 μm to 60.1 μm (a 20.3% improvement).
Deep Voxelized Feature Maps for Self-Localization in Autonomous Driving
Authors: Endo Yuki , Kamijo Shunsuke
Published: June 2023

Lane-level self-localization is essential for autonomous driving. Point cloud maps are typically used for self-localization but are known to be redundant. Deep features produced by neural networks can be used as a map, but their simple utilization could lead to corruption in large environments. This paper proposes a practical map format using deep features. We propose voxelized deep feature maps for self-localization, consisting of deep features defined in small regions. The self-localization algorithm proposed in this paper considers per-voxel residual and reassignment of scan points in each optimization iteration, which could result in accurate results. Our experiments compared point cloud maps, feature maps, and the proposed map from the self-localization accuracy and efficiency perspective. As a result, more accurate and lane-level self-localization was achieved with the proposed voxelized deep feature map, even with a smaller storage requirement compared with the other map formats.
Evaluation of Roadside LiDAR-Based and Vision-Based Multi-Model All-Traffic Trajectory Data
Authors: Guan Fei , Xu Hao , Tian Yuan
Published: June 2023

Trajectory data has gained increasing attention in the transportation industry due to its capability of providing valuable spatiotemporal information. Recent advancements have introduced a new type of multi-model all-traffic trajectory data which provides high-frequency trajectories of various road users, including vehicles, pedestrians, and bicyclists. This data offers enhanced accuracy, higher frequency, and full detection penetration, making it ideal for microscopic traffic analysis. In this study, we compare and evaluate trajectory data collected from two prevalent roadside sensors: LiDAR and camera (computer vision). The comparison is conducted at the same intersection and over the same time period. Our findings reveal that current LiDAR-based trajectory data exhibits a broader detection range and is less affected by poor lighting conditions compared to computer vision-based data. Both sensors demonstrate acceptable performance for volume counting during daylight hours, but LiDAR-based data maintains more consistent accuracy at night, particularly in pedestrian counting. Furthermore, our analysis demonstrates that, after applying smoothing techniques, both LiDAR and computer vision systems accurately measure vehicle speeds, while vision-based data show greater fluctuations in pedestrian speed measurements. Overall, this study provides insights into the advantages and disadvantages of LiDAR-based and computer vision-based trajectory data, serving as a valuable reference for researchers, engineers, and other trajectory data users in selecting the most appropriate sensor for their specific needs.
Does Environmental Policy with Veto Power Lead to Heterogeneous Emission? Evidence from China
Authors: Fu Yan , Cao Jiaxing , Wu Xiaohui , He Jiale , Zhou Zekun , Zhao Yulin
Published: June 2023

Under the high-powered target responsibility system since 2007, with newly added environmental criterion, this study seeks to examine the effectiveness of the target-based performance assessment as an accelerator for local officials to be “greener”. This coercive environmental policy incorporates a stringent “one-vote” veto criterion for cadre promotion, meaning that officials who exceed emissions standards will not be promoted, no matter how outstanding their other performances are. Based on a panel data of 106 observations of provincial party secretaries from 31 provinces, this study examines how the target assessment intervenes in pollutant emissions through a new career incentive mode in China, and the conclusions are as follows: (1) Usually, provincial officials with higher political promotion incentives are characterized as a younger, lower-position cadre during the pre-stage of term, and tend to take GDP growth goals as a priority while treating environmental targets negatively. (2) Target assessment moderates the relationship between officials’ position and SO2 emission. The use of a one-vote veto in environmental pollution assessments has led to a shift of incentive structure, as political actors prioritize environmental protection as a means of increasing their chances of promotion. (3) The moderating effect of target assessment is heterogeneous, being significant only when officials are below 60 or before the third year of their term. This study sheds light on the previously opaque motivations behind green behaviors among officials, and provides empirical support for China’s transition from a GDP-based assessment system to a green GDP-based promotion model.
The Role of Antitranspirants in Mitigating Drought Stress in Plants of the Grass Family (Poaceae)—A Review
Authors: Kocięcka Joanna , Liberacki Daniel , Stróżecki Marcin
Published: June 2023

One of the biggest problems facing agriculture is the occurrence of droughts. Due to ongoing climate change, many regions of the world are exposed to increasingly frequent and prolonged water shortages. The situation may significantly reduce production and the quality of many crops in the Poaceae family, including crucial cereals. Therefore, it is important to find solutions that can help adapt plants to the drought phenomenon and reduce its negative effects. One measure that could potentially improve the condition of plants and help them survive under water deficit conditions is the use of antitranspirants (AT), which are products that reduce transpiration. Antitranspirants are divided into three groups: film-forming, metabolic, and reflective types. This review aimed to the current state of knowledge on the effects of selected AT applications on Poaceae plants under drought conditions. It demonstrated that AT, in many cases, mitigates the negative effects of drought on crops such as maize, wheat, or rice, which are crucial for global food security. Furthermore, AT often improved growth and yield parameters. These results are particularly relevant for countries that are important cereals producers and are more vulnerable to droughts in the future. However, it should be noted that the results obtained often depend on several factors, such as plant species, environment, type of antitranspirant, and applied dose. Therefore, it is advisable to measure further the effects of AT on plants under drought-stress conditions.
Improvement of Computational Efficiency and Accuracy by Firefly Algorithm and Random Forest for Compressive Strength Modeling of Recycled Concrete
Authors: Liu Yong , Wang Yang , Zhou Mengmeng , Huang Jiandong
Published: June 2023

It is an important direction for the sustainable development of pavement to mix the discarded concrete blocks with gradation according to a certain proportion after crushing, cleaning and other technological processes, partially or completely replace aggregate, and then add cement, water, and so on to make recycled concrete for pavement paving, but the traditional evaluation model for the compressive strength (CS) of recycled concrete cannot meet the requirements of efficient calculation. To address such issues, the present research proposed to apply the firefly algorithm (FA) to optimize the random forest (RF) model. The results were demonstrated by comparing the consistency of predicted and actual values, and also by analyzing the correlation coefficient (R) and root-mean-square error (RMSE). Higher R values (0.9756 and 0.9328) and lower RMSE values (3.0752 and 6.4369) for the training and test sets present the reliability of the FA and RF hybrid machine learning model. To understand the influence law of input indexes on the output index, the importance and sensitivity of variables are further analyzed. The results displayed that effective water-cement ratio (WC) and nominal maximum recycled concrete aggregate size (NMR) have the greatest impact on the output variable, with importance scores of 2.5947 and 2.4315, respectively, while the change in the recycled concrete aggregate replacement rate (RCA) has a weak influence, with an importance score of 0.4695. Introducing FA to RF for the compressive strength modeling of recycled concrete can significantly improve the computational efficiency and accuracy.
Adaptability of Koenigia mollis to an Acid Tin Mine Wasteland in Lianghe County in Yunnan Province
Authors: Deng Qi , Wu Hui , Xia Yunni , Wang Bao , Zhang Naiming , Che Lin , Xia Yunsheng , Yue Xianrong
Published: June 2023

To explore the potential of Koenigia mollis as a pioneer plant in acid tin mine wasteland, Koenigia mollis plants and the corresponding rhizosphere soils in different areas in Lianghe County, Yunnan Province were collected, and their chemical properties and heavy metals contents were determined., the adaptability of the plant to the barren tailing environment and its acid resistance and tolerance to heavy metal such as Cu (Cu, CAS. No. 7144-37-8), Cd (Cd, CAS. No. 7440-43-9) and Pb (Pb, CAS. No. 10099-74-8) pollution were analyzed. Results showed that Koenigia mollis growth was normal. The pH value in rhizosphere soils was 3.74–4.30, which was strongly acidic. The organic matter (OM), total nitrogen (TN) (N, CAS. No. 7727-37-9), available potassium (AK) (K, CAS. No. 7440-09-7), and available phosphorus (AP) (P, CAS. No. 7723-14-0) contents in soils of the research area were in low levels. The total contents of Cu, Cd, and Pb in the soil of the research area exceeded the pollution risk screening value for the national risk control standard of soil environmental quality, indicating that Koenigia mollis has a certain resistance to acid and heavy metal pollution. In addition, Koenigia mollis has strong transport and enrichment capacity for Cu, Cd, and Pb and therefore has potential as a pioneer phytoremediation plant for acid tin mine wastelands and a remediated plant for agricultural land around metal mining areas.
Simulation and Optimization of Renewable Energy-Powered Desalination: A Bibliometric Analysis and Highlights of Recent Research
Authors: Pietrasanta Ariana M. , Shaaban Mostafa F. , Aguirre Pio A. , Mussati Sergio F. , Hamouda Mohamed A.
Published: June 2023

Seawater desalination is emerging as one of the preferred systems for dealing with the problems of freshwater scarcity, which makes it necessary to redouble efforts to obtain an optimal and competent production process. For this reason, the coupling of water desalination and renewable energy systems is not surprising. This study applied a bibliometric analysis to evaluate the research trends on desalination systems and renewable energies from an engineering approach using optimizations or simulation techniques. The Scopus database was used for this study, selecting articles published between 2009 and 2022. A general analysis was carried out regarding trends in the number of articles produced, number of citations, subject area, journals, countries, institutes, and authors. Further, a more specific analysis was then performed in terms of renewable energy technologies used and preferred optimization/simulation methods and software used. The results also revealed that the field is growing, based on the number of articles published and the increase in citations. On the other hand, it was found that the most studied renewable energies, in coupling with desalination systems and from an optimization/simulation approach, are solar and wind.