bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence and Genomic Characterization of Rotavirus A from Domestic Pigs in Zambia: Evidence for Possible Porcine–Human Interspecies Transmission
Authors: Ndebe Joseph , Harima Hayato , Chambaro Herman Moses , Sasaki Michihito , Yamagishi Junya , Kalonda Annie , Shawa Misheck , Qiu Yongjin , Kajihara Masahiro , Takada Ayato , Sawa Hirofumi , Saasa Ngonda , Simulundu Edgar
Published: September 2023

Rotavirus is a major cause of diarrhea globally in animals and young children under 5 years old. Here, molecular detection and genetic characterization of porcine rotavirus in smallholder and commercial pig farms in the Lusaka Province of Zambia were conducted. Screening of 148 stool samples by RT-PCR targeting the VP6 gene revealed a prevalence of 22.9% (34/148). Further testing of VP6-positive samples with VP7-specific primers produced 12 positives, which were then Sanger-sequenced. BLASTn of the VP7 positives showed sequence similarity to porcine and human rotavirus strains with identities ranging from 87.5% to 97.1%. By next-generation sequencing, the full-length genetic constellation of the representative strains RVA/pig-wt/ZMB/LSK0137 and RVA/pig-wt/ZMB/LSK0147 were determined. Genotyping of these strains revealed a known Wa-like genetic backbone, and their genetic constellations were G4-P[6]-I5-R1-C1-M1-A8-N1-T1-E1-H1 and G9-P[13]-I5-R1-C1-M1-A8-N1-T1-E1-H1, respectively. Phylogenetic analysis revealed that these two viruses might have their ancestral origin from pigs, though some of their gene segments were related to human strains. The study shows evidence of reassortment and possible interspecies transmission between pigs and humans in Zambia. Therefore, the “One Health” surveillance approach for rotavirus A in animals and humans is recommended to inform the design of effective control measures.
Click Reactions in Medicinal Chemistry
Authors: Bosc Damien
Published: September 2023

Two decades after K [...]
Supplementary Effects of Allium hookeri Extract on Glucose Tolerance in Prediabetic Subjects and C57BL/KsJ-db/db Mice
Authors: Kim Ji-Su , Kim Hyun-Ju , Lee Eun-Byeol , Choi Ji-Hye , Jung Jieun , Jang Hwan-Hee , Park Shin-Young , Ha Ki-Chan , Park Yu-Kyung , Joo Jong-Cheon , Lee Sung-Hyen
Published: September 2023

Allium hookeri (AH) has been used as a nutritional and medicinal food in Asia for many years. Our previous studies have described its anti-diabetic, anti-obesity, and anti-inflammatory activities in animal models and prediabetes. This study investigated whether AH could improve glycemia by modulating insulin secretion in prediabetic subjects through an in-depth study. Eighty prediabetic subjects (100 ≤ fasting plasma glucose < 140 mg/dL) were randomly assigned to a placebo (n = 40) group or an ethanol AH extract (500 mg/day, n = 40) group for 12 weeks. Dietary intake and physical activity, blood glucose (an oral glucose tolerance test for 120 min), insulin (insulin response to oral glucose for 120 min), area under the curve (AUC) of glucose or insulin after oral glucose intake, insulin sensitivity markers, C-peptide, adiponectin, glycated hemoglobin A1c (HbA1c) levels, hematological tests (WBC, RBC, hemoglobin, hematocrit, and platelet count), blood biochemical parameters (ALP, AST, total bilirubin, total protein, albumin, gamma-GT, BUN, creatinine, LD, CK, and hs-CRP), and urine parameters (specific gravity and pH) were examined at both baseline and 12 weeks after supplementation with placebo or AH capsules. Fifty-eight participants (placebo group: 20 men and 10 women; AH group: 13 men and 15 women) completed the study. AH supplementation moderately reduced postprandial blood glucose at 60 min (−6.14 mg/dL, p = 0.061), postprandial insulin levels at 90 min (−16.69 µU/mL, p = 0.017), the glucose AUC at 90 min (−412.52 mg*min/dL, p = 0.021), as well as the insulin AUC at 90 min (−978.77 µU*min/mL, p = 0.021) and 120 min (−1426.41 µU*min/mL, p = 0.015) when compared with the placebo group. However, there were no effects of AH on dietary intake and physical activity; HOMA index; HbAlc; C-peptide; or adiponectin, hematological-, blood biochemical-, and urinary markers. To confirm the effects of AH extract on blood glucose insulin sensitivity, C57BL/6J or C57BL/KsJ-db/db mice were used (n = 8/group). Body weight, fasting plasma glucose level, lipid profiles, liver and renal function, pancreatic histology, and insulin immunoreactivity were assessed. In the diabetic db/db mice, hyperglycemia, which was accompanied by an increase in insulin secretion in diabetic mice, was significantly reduced by AH treatment, resulting in the alleviation of β-cell overcompensation and insulin resistance. We confirmed that AH supplementation can effectively control blood glucose and insulin levels by improving insulin sensitivity and may be a potential agent for glycemic control in subjects with prediabetes and type 2 diabetes mellitus.
Role of Resolvins in Inflammatory and Neuropathic Pain
Authors: Park Jaeik , Roh Jueun , Pan Jingying , Kim Yong Ho , Park Chul-Kyu , Jo Youn Yi
Published: September 2023

Chronic pain is an unpleasant experience associated with actual or potential tissue damage. Inflammatory pain alerts the body to inflammation and promotes healing; however, unresolved inflammation can lead to chronic pain. Conversely, neuropathic pain, due to somatosensory damage, can be a disease in itself. However, inflammation plays a considerable role in the progression of both types of pain. Resolvins, derived from omega-3 fatty acids, actively suppress pro-inflammatory mediators and aid in the resolution of inflammation. Resolvins alleviate various inflammatory and neuropathic pain models by reducing hypersensitivity and regulating inflammatory cytokines and glial activation in the spinal cord and dorsal root ganglia. Thus, resolvins are a promising alternative for pain management with the potential to reduce the side effects associated with conventional medications. Continued research is crucial to unlock the therapeutic potential of resolvins and integrate them into effective clinical pain management strategies. This review aimed to evaluate the literature surrounding the resolvins in inflammatory and neuropathic pain.
Immunomodulatory Effect of Proteasome Inhibitors via the Induction of Immunogenic Cell Death in Myeloma Cells
Authors: Matsushita Maiko , Kashiwazaki Sho , Kamiko Satoshi , Kobori Michio , Osada Makoto , Kunieda Hisako , Hirao Maki , Ichikawa Daiju , Hattori Yutaka
Published: September 2023

Several anti-cancer drugs are known to have immunomodulatory effects, including immunogenic cell death (ICD) of cancer cells. ICD is a form of apoptosis which is caused by the release of damage-associated molecular patterns (DAMPs), the uptake of cancer antigens by dendritic cells, and the activation of acquired immunity against cancer cells. ICD was originally reported in solid tumors, and there have been few reports on ICD in multiple myeloma (MM). Here, we showed that proteasome inhibitors, including carfilzomib, induce ICD in myeloma cells via an unfolded protein response pathway distinct from that in solid tumors. Additionally, we demonstrated the potential impact of ICD on the survival of patients with myeloma. ICD induced by proteasome inhibitors is expected to improve the prognosis of MM patients not only by its cytotoxic effects, but also by building strong immune memory response against MM cells in combination with other therapies, such as chimeric antigen receptor—T cell therapy.
Synergistic Antihyperglycemic and Antihyperlipidemic Effect of Polyherbal and Allopolyherbal Formulation
Authors: Alhamhoom Yahya , Ahmed Syed Sagheer , M. Rupesh Kumar , Salahuddin MD. , D. R. Bharathi , Ahmed Mohammed Muqtader , Farhana Syeda Ayesha , Rahamathulla Mohamed
Published: September 2023

Polyherbal formulation (PHF) enhances therapeutic efficacy and minimizes side effects by reducing individual herb dosages. Allopolyherbal formulation (APHF) combines polyherbal extracts with allopathic medication, effectively reducing the latter’s required dose and mitigating associated adverse effects. The current study intends to assess the anti-diabetic effects of PHF and APHF in-vivo. Dried raw powders of Cassia auriculata leaf, Centella asiatica leaf, and Zingiber officinale rhizome were extracted by cold maceration process using 70% ethanol. These extracts were combined in three different ratios to make PHF. PHF was subjected to qualitative and quantitative phytochemical investigations. APHF has been prepared by combining a potent ratio of PHF with metformin in three different ratios. The compatibility of APHF has been confirmed by differential scanning calorimetry (DSC). In vivo activity was also evaluated in streptozotocin-induced diabetic albino rats. PHF (3 different ratios at a dose of 200–400 mg/kg b.w), APHF (combination of PHF and metformin in 3 different ratios, 200 + 22.5, 200 + 45, and 200 + 67.5 mg/kg b.w), and metformin (90 mg/kg b.w) were administered to albino rats for 21 consecutive days. Blood glucose levels were estimated on the 1st, 7th, 14th, and 21st days of treatment. On the 21st day, blood was collected by cardiac puncture for biochemical analysis. The liver and pancreas were isolated and subjected to histopathological analysis. PHF and APHF showed significant anti-diabetic and antihyperlipidemic efficacy. In comparison to PHF, APHF had the most promising action. The current study demonstrated that PHF and APHF are safe and efficacious drugs in the treatment of diabetes mellitus as they help to replace or lower the dose of metformin, thereby decreasing the risks of metformin.
Nucleoside Analog 2′,3′-Isopropylidene-5-Iodouridine as Novel Efficient Inhibitor of HIV-1
Authors: Glumakova Ksenia , Ivanov Georgy , Vedernikova Valeria , Shyrokova Lena , Lebedev Timofey , Stomakhin Andrei , Zenchenko Anastasia , Oslovsky Vladimir , Drenichev Mikhail , Prassolov Vladimir , Spirin Pavel
Published: September 2023

Nucleoside reverse transcriptase inhibitors are the first class of drugs to be approved by the FDA for the suppression of HIV-1 and are widely used for this purpose in combination with drugs of other classes. Despite the progress in HIV-1 treatment, there is still the need to develop novel efficient antivirals. Here the efficiency of HIV-1 inhibition by a set of original 5-substituted uridine nucleosides was studied. We used the replication deficient human immunodeficiency virus (HIV-1)-based lentiviral particles and identified that among the studied compounds, 2′,3′-isopropylidene-5-iodouridine was shown to cause anti-HIV-1 activity. Importantly, no toxic action of this compound against the cells of T-cell origin was found. We determined that this compound is significantly more efficient at suppressing HIV-1 compared to Azidothymidine (AZT) when taken at the high non-toxic concentrations. We did not find any profit when using AZT in combination with 2′,3′-isopropylidene-5-iodouridine. 2′,3′-Isopropylidene-5-iodouridine acts synergistically to repress HIV-1 when combined with the CDK4/6 inhibitor Palbociclib in low non-toxic concentration. No synergistic antiviral action was detected when AZT was combined with Palbociclib. We suggest 2′,3′-isopropylidene-5-iodouridine as a novel perspective non-toxic compound that may be used for HIV-l suppression.
Combination of Phenethyl Isothiocyanate and Dasatinib Inhibits Hepatocellular Carcinoma Metastatic Potential through FAK/STAT3/Cadherin Signalling and Reduction of VEGF Secretion
Authors: Strusi Gabriele , Suelzu Caterina M. , Weldon Shannon , Giffin Jennifer , Münsterberg Andrea E. , Bao Yongping
Published: September 2023

Cancerous cells are characterised by their ability to invade, metastasise, and induce angiogenesis. Tumour cells use various molecules that can be targeted to reverse these processes. Dasatinib, a potent Src inhibitor, has shown promising results in treating hepatocellular carcinoma (HCC) in vitro and in vivo. However, its effectiveness is limited by focal adhesion kinase (FAK) activation. Isothiocyanates, on the other hand, are phytochemicals with broad anticancer activity and FAK inhibition capabilities. This study evaluated the synergistic effect of dasatinib and phenethyl isothiocyanate (PEITC) on HCC. The combination was tested using various assays, including MTT, adhesion, scratch, Boyden chamber, chorioallantoic membrane (CAM), and yolk sac membrane (YSM) assays to evaluate the effect of the drug combination on HCC metastatic potential and angiogenesis in vitro and in vivo. The results showed that the combination inhibited the adhesion, migration, and invasion of HepG2 cells and reduced xenograft volume in the CAM assay. Additionally, the combination reduced angiogenesis in vitro, diminishing the growth of vessels in the tube formation assay. The inhibition of FAK/STAT3 signalling led to increased E-cadherin expression and reduced VEGF secretion, reducing HCC metastatic potential. Therefore, a combination of PEITC and dasatinib could be a potential therapeutic strategy for the treatment of HCC.
Preparation and Characterization of Transethosome Formulation for the Enhanced Delivery of Sinapic Acid
Authors: Bin Jardan Yousef A. , Ahad Abdul , Raish Mohammad , Al-Jenoobi Fahad I.
Published: September 2023

Sinapic acid (SA) is a bioactive phenolic acid; its diverse properties are its anti-inflammatory, antioxidant, anticancer, and antibacterial activities. The bioactive compound SA is poorly soluble in water. Our goal was to formulate SA-transethosomes using thin-film hydration. The prepared formulations were examined for various parameters. In addition, the optimized formulation was evaluated for surface morphology, in-vitro penetration studies across the Strat M®, and its antioxidant activity. The optimized formulation (F5) exhibited 74.36% entrapment efficacy. The vesicle size, zeta potential, and polydispersity index were found to be 111.67 nm, −7.253 mV, and 0.240, respectively. The surface morphology showed smooth and spherical vesicles of SA-transethosomes. In addition, the prepared SA-transethosomes exhibited enhanced antioxidant activity. The SA-transethosomes demonstrated considerably greater penetration across the Strat M® membrane during the study. The flux of SA and SA-transethosomes through the Strat M® membrane was 1.03 ± 0.07 µg/cm2/h and 2.93 ± 0.16 µg/cm2/h. The enhancement ratio of SA-transethosomes was 2.86 ± 0.35 compared to the control. The SA-transethosomes are flexible nano-sized vesicles and are able to penetrate the entrapped drug in a higher concentration. Hence, it was concluded that SA-transethosome-based approaches have the potential to be useful for accentuating the penetrability of SA across the skin.
A Novel Nutrient- and Antioxidant-Based Formulation Can Sustain Tomato Production under Full Watering and Drought Stress in Saline Soil
Authors: Abd El-Mageed Taia A. , Ihab Radwa , Rady Mostafa M. , Belal Hussein E. E. , Mostafa Fatma A. , Galal Tarek M. , Masoudi Luluah M. Al , Ali Esmat F. , Roulia Maria , Mahmoud Amr E. M.
Published: September 2023

As a result of the climate changes that are getting worse nowadays, drought stress (DS) is a major obstacle during crop life stages, which ultimately reduces tomato crop yields. So, there is a need to adopt modern approaches like a novel nutrient- and antioxidant-based formulation (NABF) for boosting tomato crop productivity. NABF consists of antioxidants (i.e., citric acid, salicylic acid, ascorbic acid, glutathione, and EDTA) and nutrients making it a fruitful growth stimulator against environmental stressors. As a first report, this study was scheduled to investigate the foliar application of NABF on growth and production traits, physio-biochemical attributes, water use efficiency (WUE), and nutritional, hormonal, and antioxidative status of tomato plants cultivated under full watering (100% of ETc) and DS (80 or 60% of ETc). Stressed tomato plants treated with NABF had higher DS tolerance through improved traits of photosynthetic efficiency, leaf integrity, various nutrients (i.e., copper, zinc, manganese, calcium, potassium, phosphorus, and nitrogen), and hormonal contents. These positives were a result of lower levels of oxidative stress biomarkers as a result of enhanced osmoprotectants (soluble sugars, proline, and soluble protein), and non-enzymatic and enzymatic antioxidant activities. Growth, yield, and fruit quality traits, as well as WUE, were improved. Full watering with application of 2.5 g NABF L−1 collected 121 t tomato fruits per hectare as the best treatment. Under moderate DS (80% of ETc), NABF application increased fruit yield by 10.3%, while, under severe DS (40% of ETc), the same fruit yield was obtained compared to full irrigation without NABF. Therefore, the application of 60% ETc × NABF was explored to not only give a similar yield with higher quality compared to 100% ETc without NABF as well as increase WUE.
A Self-Healing Thermoset Epoxy Modulated by Dynamic Boronic Ester for Powder Coating
Authors: Liu Yongqi , Li Ziyuan , Zhang Caifu , Yang Biru , Ren Hua
Published: September 2023

Thermoset powder coatings exhibit distinctive characteristics such as remarkable hardness and exceptional resistance to corrosion. In contrast to conventional paints, powder coatings are environmentally friendly due to the absence of volatile organic compounds (VOCs). However, their irreversible cross-linking structures limit their chain segment mobility, preventing polymers from autonomously repairing cracks. Dynamic cross-linking networks have garnered attention for their remarkable self-healing capabilities, facilitated by rapid internal bond exchange. Herein, we introduce an innovative method for synthesizing thermoset epoxy containing boronic ester moieties which could prolong the life of the powder coating. The epoxy resin system relies on the incorporation of two curing agents: one featuring small-molecule diamines with boronic bonds and the other a modified polyurethane prepolymer. A state of equilibrium in mechanical properties was achieved via precise manipulation of the proportions of these agents, with the epoxy composite exhibiting a fracture stress of 67.95 MPa while maintaining a stable glass transition temperature (Tg) of 51.39 °C. This imparts remarkable self-healing ability to the coating surface, capable of returning to its original state even after undergoing 1000 cycles of rubbing (using 1200-grit abrasive paper). Furthermore, the introduction of carbon nanotube nanoparticles enabled non-contact sequential self-healing. Subsequently, we introduce this method into powder coatings of different materials. Therefore, this work provides a strategy to develop functional interior decoration and ensure its potential for broad-ranging applications, such as aerospace, transportation, and other fields.
A Review of Polymer Dielectrics for Redistribution Layers in Interposers and Package Substrates
Authors: Nimbalkar Pratik , Bhaskar Pragna , Kathaperumal Mohanalingam , Swaminathan Madhavan , Tummala Rao R.
Published: September 2023

The ever-increasing demand for faster computing has led us to an era of heterogeneous integration, where interposers and package substrates have become essential components for further performance scaling. High-bandwidth connections are needed for faster communication between logic and memory dies. There are several limitations to current generation technologies, and dielectric buildup layers are a key part of addressing those issues. Although there are several polymer dielectrics available commercially, there are numerous challenges associated with incorporating them into interposers or package substrates. This article reviewed the properties of polymer dielectric materials currently available, their properties, and the challenges associated with their fabrication, electrical performance, mechanical reliability, and electrical reliability. The current state-of-the-art is discussed, and guidelines are provided for polymer dielectrics for the next-generation interposers.
Designing an Oxygen Scavenger Multilayer System Including Volatile Organic Compound (VOC) Adsorbents for Potential Use in Food Packaging
Authors: López-de-Dicastillo Carol , López-Carballo Gracia , Vázquez Pedro , Schwager Florian , Aragón-Gutiérrez Alejandro , Alonso José M. , Hernández-Muñoz Pilar , Gavara Rafael
Published: September 2023

Oxygen scavengers are valuable active packaging systems because several types of food deterioration processes are initiated by oxygen. Although the incorporation of oxygen scavenger agents into the polymeric matrices has been the trend in recent years, the release of volatile organic compounds (VOC) as a result of the reaction between oxygen and oxygen scavenger substances is an issue to take into account. This is the case of an oxygen scavenger based on a trans-polyoctenamer rubber (TOR). In this work, the design of an oxygen scavenger multilayer system was carried out considering the selection of appropriate adsorbents of VOCs to the proposed layer structure. Firstly, the retention of some representative organic compounds by several adsorbent substances, such as zeolites, silicas, cyclodextrins and polymers, was studied in order to select those with the best performances. A hydrophilic silica and an odor-adsorbing agent based on zinc ricinoleate were the selected adsorbing agents. The principal VOCs released from TOR-containing films were carefully identified, and their retention first by the pure adsorbents, and then by polyethylene incorporated with the selected compounds was quantified. Detected concentrations decreased by 10- to 100-fold, depending on the VOC.
Clinical Protocol for Implant-Assisted Partial Removable Dental Prostheses in Kennedy Class I: A Case Report
Authors: Karakas-Stupar Irina , Zaugg Lucia K. , Zitzmann Nicola U. , Joda Tim , Wolfart Stefan , Tuna Taskin
Published: September 2023

Patients with Kennedy Class I are usually treated with clasp-retained removable partial dentures (RPDs) as the prosthetic gold standard. For additional stabilization of the RPD, clinicians are often confronted with the question of secondary implant placement, which requires the fabrication of new prostheses. This case report is part of an ongoing multi-center randomized controlled study (RCT) investigating conventional RPDs without and with supplementary implants. A design of the RPD framework, including matrix housings, is crucial to enable subsequent implant retention or support. Ultra-short implants (Straumann TL 4.1 × 4 mm) offer the opportunity for additional support and retention in the edentulous posterior region, where bone availability is often reduced. This future-oriented and minimally invasive approach with virtual treatment planning and guided implant surgery offers the possibility of simplified functional and cost-effective aftercare.
Kierkegaardian Virtues and the Problem of Self-Effacement
Authors: Stokes Patrick
Published: September 2023

One of the more well-known objections to Kierkegaard’s moral philosophy is that he presents a view of moral life that is self-absorbed almost to the point of solipsism, focused on the subject’s own moral status rather than acting from responsiveness to others. Kierkegaard commentators have gone to great lengths to debunk such readings, to demonstrate that Kierkegaard is indeed a far more other-oriented ethicist than such critiques would suggest. At the same time, many—though not all—commentators have come to read Kierkegaard as a Christian virtue ethicist. Yet virtue ethics itself has been objected to on the grounds that it is (1) self-effacing (it requires us to act for reasons or from motives other than those virtue ethics itself endorses), (2) egoistic (it serves the benefit of the agent themselves), and (3) self-absorbed (it causes the agent to focus on themselves rather than others). This paper considers whether and how these objections might apply to Kierkegaard, and argues that his moral psychology has specific resources for answering these objections in distinctive ways.
“A Special Form of Derangement”: Karl Barth’s Approach to Sport Rooted in Prayer
Authors: Whitmore William
Published: September 2023

In The Christian Life, his unfinished volume of Church Dogmatics, Karl Barth describes sport as “a special form of derangement”. Barth identifies sport as a lordless power, an element of society that humans believe they control, but ends up dictating the terms of engagement. Situating his discussion of these powers in his discourse on the third petition of the Lord’s Prayer, Barth calls on Christians to revolt against these things. Readers may shake their heads at Barth’s rhetoric regarding sport and the labeling of it as ‘lordless power’; however, in situating his remarks on the topic in the Lord’s Prayer, Barth provides a new lens through which Christians might view sport. This paper focuses on Barth’s approach to sport, suggesting that Christians can, through invocation and correspondence, rebel against the lordless power that is sport. It begins by situating Barth’s approach to sport within the context of the sport and Christianity interface, the wider corpus of Barth studies, and his own work. After assessing Barth’s writings on sport, the paper shifts to a discussion of what Barth suggests God does and what we, as humans, are called to do when we pray “Thy kingdom come”. The paper concludes with reflections on how Barth’s approach to sport, rooted in prayer, can affect our understanding of the subject.
Assessing the Impact of Climate and Human Activities on Ecosystem Services in the Loess Plateau Ecological Screen, China
Authors: Wei Changwen , Zeng Jiaqin , Wang Jiping , Jiang Xuebing , You Yongfa , Wang Luying , Zhang Yiming , Liao Zhihong , Su Kai
Published: September 2023

The ecosystem services (ES) can be influenced by various environmental factors. In order to efficiently allocate resources and manage ecosystems, it is important to understand the mechanisms by which these environmental effects impact the interactions and trade-offs among different ES. While previous studies have primarily examined the impact of individual environmental factors on ES, the intricate mechanisms underlying the effects of multiple environmental factors have been largely overlooked. In this study, we adopted a path analysis approach that considered interactions among explanatory variables. We analyzed multiple geospatial datasets from various sources, including remote sensing and climate data, to examine the main drivers—precipitation, temperature, FVC (fractional vegetation cover), NPP (net primary productivity), human activities, and altitude—affecting five ecosystem services: carbon sequestration service (C), habitat provision service (HP), soil conservation service (SCS), sand-stabilization service (SSS), and water conservation service (WCS) in arid and semi-arid mountainous regions. Our investigation found that all five ES have shown an upward trajectory over the past two decades. The most significant growth was observed in C, which increased by 39.4%. Among the environmental factors examined, precipitation has been identified as the predominant factor influencing the ES and the synergies and trade-offs among ES. The influence of precipitation on SCS reached a coefficient of 0.726. Human activity factors had the greatest influence on HP of the five ES with a path coefficient of 0.262. Conversely, temperature exhibited a suppressive influence on ES. The impact of factors such as NPP and altitude on ES was comparatively modest. Notably, human activities assumed a substantial contributory role in shaping the relationship encompassing WCS. It is worth noting that individual factors exerted differential effects on ES along distinct environmental gradients, including anthropogenic gradients. In this context, the combination of high altitude and substantial FVC demonstrated a notable contribution to WCS. Our study can provide valuable insights for the management of ES which can be utilized to optimize the regulation of the Loess Plateau Ecological Screen (LPES) ecological construction and promote regional sustainable development.
RADAR Echo Recognition of Squall Line Based on Deep Learning
Authors: Xie Peilong , Hu Zhiqun , Yuan Shujie , Zheng Jiafeng , Tian Hanyuan , Xu Fen
Published: September 2023

Squall line (SL) is a convective weather process that often causes disasters. The automatic recognition and early warning of SL are important objectives in the field of meteorology. By collecting the new-generation weather RADARs (CINRAD/SA and CINRAD/SAD) base data during 12 SL weather events occurred in Jiangsu, Shanghai, Shandong, Hebei, and other regions of China from 2019 to 2021, the dataset has a total of 49,920 samples with a window size of 40 km. The 40 km area was labeled by employing manual classification and data augmentation to construct the deep learning dataset with a positive and negative sample ratio of 1:1, of which 80% and 20% are separated as the training and test set, respectively. Based on the echo height of each elevation beam at different distances, three deep learning-based models are trained for SL automatic recognition, which include a near-distance model (M1) trained by the data in nine RADAR elevation angles within 45 km from RADARs, a mid-distance model (M2) by the data in six elevations from 45 to 135 km, and a far-distance model (M3) by the data in three elevations from 135 to 230 km. A confusion matrix and its derived metrics including receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) are introduced as the indicators to evaluate the models by the test dataset. The results indicate that the accuracy of models are over 86% with the hit rates over 87%, the false alarm rates less than 21%, and the critical success indexes (CSI) surpass 78%. All the optimal critical points on the ROC curves are close to (0, 1), and the AUC values are above 0.95, so the three models have high hit rates and low false alarm rates for ensuring SL discrimination. Finally, the effectiveness of the models is further demonstrated through two SL events detected with Nanjing, Yancheng and Qingpu RADARs.
River Discharge Inversion Algorithm Based on the Surface Velocity of Microwave Doppler Radar
Authors: Chen Zezong , Wang Tao , Zhao Chen , He Zheyuan
Published: September 2023

Non-contact methods, which are of great significance to the measurement of river discharge, can not only improve the efficiency of measurement but can also ensure the safety of equipment and personnel. However, owing to their inherent drawbacks such as the requirement of riverbed topography measurements and the difficulty in determining hydrological parameters such as equivalent roughness height, velocity index, etc., there are still challenges for measuring river discharge with high levels of efficiency and accuracy using non-contact methods. To overcome the aforementioned challenges, a new river discharge inversion method is proposed in this paper. In this method, vertical velocities are divided into inner and outer region velocities which can be described by the logarithmic law and the parabolic law, respectively. Applying the river surface velocities collected by microwave Doppler radar and the vertical velocity distributions, the water depths are estimated according to the continuity of the vertical velocities and the shear stresses, and then, the river discharges are obtained by the velocity–area method. The proposed method not only has a simple formula but also comprehensively considers the influence of different hydrological conditions, making it suitable for different river widths and water depths. In this paper, surface velocities collected by microwave Doppler radar on the Yangtze River and the San Joaquin River are used to invert the river discharge, and the results show that for wide–shallow, wide–deep, and narrow–shallow river conditions, the mean percent error (MPE) values of the discharges invertedby the proposed method are 3.91%, 3.82%, and 3.6%, respectively; the root mean square error (RMSE) values are 4.53%, 5.19%, and 4.81%, respectively; and the maximum percent error (MaPE) is less than 15%. The results prove that the proposed method can invert the river discharge with high efficiency and high accuracy under different river widths and water depths without measuring water depth in advance, making it is possible to automatically measure the river discharge in real time.
Residual Attention Mechanism for Remote Sensing Target Hiding
Authors: Yuan Hao , Shen Yongjian , Lv Ning , Li Yuheng , Chen Chen , Zhang Zhouzhou
Published: September 2023

In this paper, we investigate deep-learning-based image inpainting techniques for emergency remote sensing mapping. Image inpainting can generate fabricated targets to conceal real-world private structures and ensure informational privacy. However, casual inpainting outputs may seem incongruous within original contexts. In addition, the residuals of original targets may persist in the hiding results. A Residual Attention Target-Hiding (RATH) model has been proposed to address these limitations for remote sensing target hiding. The RATH model introduces the residual attention mechanism to replace gated convolutions, thereby reducing parameters, mitigating gradient issues, and learning the distribution of targets present in the original images. Furthermore, this paper modifies the fusion module in the contextual attention layer to enlarge the fusion patch size. We extend the edge-guided function to preserve the original target information and confound viewers. Ablation studies on an open dataset proved the efficiency of RATH for image inpainting and target hiding. RATH had the highest similarity, with a 90.44% structural similarity index metric (SSIM), for edge-guided target hiding. The training parameters had 1M fewer values than gated convolution (Gated Conv). Finally, we present two automated target-hiding techniques that integrate semantic segmentation with direct target hiding or edge-guided synthesis for remote sensing mapping applications.
Incipient Fault Detection in a Hydraulic System Using Canonical Variable Analysis Combined with Adaptive Kernel Density Estimation
Authors: Wang Jinxin , Zhao Shenglei , Wang Enyuan , Zhao Jiyun , Liu Xiaofei , Li Zhonghui
Published: September 2023

Incipient fault detection in a hydraulic system is a challenge in the condition monitoring community. Existing research mainly monitors abnormal working conditions in hydraulic systems by separately detecting the key working parameter, which often causes a high miss warning rate for incipient faults due to the oversight of parameter dependence. A principal component analysis provides an effective method for incipient fault detection by taking the correlation of multiple parameters into consideration, but this technique assumes the systems are Gaussian-distributed, making it invalid for a dynamic non-Gaussian system. In this paper, we combine a canonical variable analysis (CVA) and adaptive kernel density estimation (AKDE) for the early fault detection of nonlinear dynamic hydraulic systems. The collected hydraulic system data set was used to construct the typical variable space, and the state space and residual space are divided to represent the characteristics of different correlations between the two variables, which are quantitatively described using Hotelling’s T2 and Q. In order to investigate the proper upper control limits, AKDE was utilised to estimate the underlying probability density functions of T2 and Q by taking the nonlinearity of the hydraulic system variables into consideration. The advantages of the proposed approach for incipient fault detection are illustrated via a marine power plant lubrication system.
A Novel Bird Sound Recognition Method Based on Multifeature Fusion and a Transformer Encoder
Authors: Zhang Shaokai , Gao Yuan , Cai Jianmin , Yang Hangxiao , Zhao Qijun , Pan Fan
Published: September 2023

Birds play a vital role in the study of ecosystems and biodiversity. Accurate bird identification helps monitor biodiversity, understand the functions of ecosystems, and develop effective conservation strategies. However, previous bird sound recognition methods often relied on single features and overlooked the spatial information associated with these features, leading to low accuracy. Recognizing this gap, the present study proposed a bird sound recognition method that employs multiple convolutional neural-based networks and a transformer encoder to provide a reliable solution for identifying and classifying birds based on their unique sounds. We manually extracted various acoustic features as model inputs, and feature fusion was applied to obtain the final set of feature vectors. Feature fusion combines the deep features extracted by various networks, resulting in a more comprehensive feature set, thereby improving recognition accuracy. The multiple integrated acoustic features, such as mel frequency cepstral coefficients (MFCC), chroma features (Chroma) and Tonnetz features, were encoded by a transformer encoder. The transformer encoder effectively extracted the positional relationships between bird sound features, resulting in enhanced recognition accuracy. The experimental results demonstrated the exceptional performance of our method with an accuracy of 97.99%, a recall of 96.14%, an F1 score of 96.88% and a precision of 97.97% on the Birdsdata dataset. Furthermore, our method achieved an accuracy of 93.18%, a recall of 92.43%, an F1 score of 93.14% and a precision of 93.25% on the Cornell Bird Challenge 2020 (CBC) dataset.
Deep Learning Approach for the Localization and Analysis of Surface Plasmon Scattering
Authors: Lee Jongha , Moon Gwiyeong , Ka Sukhyeon , Toh Kar-Ann , Kim Donghyun
Published: September 2023

Surface plasmon resonance microscopy (SPRM) combines the principles of traditional microscopy with the versatility of surface plasmons to develop label-free imaging methods. This paper describes a proof-of-principles approach based on deep learning that utilized the Y-Net convolutional neural network model to improve the detection and analysis methodology of SPRM. A machine-learning based image analysis technique was used to provide a method for the one-shot analysis of SPRM images to estimate scattering parameters such as the scatterer location. The method was assessed by applying the approach to SPRM images and reconstructing an image from the network output for comparison with the original image. The results showed that deep learning can localize scatterers and predict other variables of scattering objects with high accuracy in a noisy environment. The results also confirmed that with a larger field of view, deep learning can be used to improve traditional SPRM such that it localizes and produces scatterer characteristics in one shot, considerably increasing the detection capabilities of SPRM.
Multi-Scale FPGA-Based Infrared Image Enhancement by Using RGF and CLAHE
Authors: Liu Jialong , Zhou Xichuan , Wan Zhenlong , Yang Xuefei , He Wei , He Rulong , Lin Yingcheng
Published: September 2023

Infrared sensors capture thermal radiation emitted by objects. They can operate in all weather conditions and are thus employed in fields such as military surveillance, autonomous driving, and medical diagnostics. However, infrared imagery poses challenges such as low contrast and indistinct textures due to the long wavelength of infrared radiation and susceptibility to interference. In addition, complex enhancement algorithms make real-time processing challenging. To address these problems and improve visual quality, in this paper, we propose a multi-scale FPGA-based method for real-time enhancement of infrared images by using rolling guidance filter (RGF) and contrast-limited adaptive histogram equalization (CLAHE). Specifically, the original image is first decomposed into various scales of detail layers and a base layer using RGF. Secondly, we fuse detail layers of diverse scales, then enhance the detail information by using gain coefficients and employ CLAHE to improve the contrast of the base layer. Thirdly, we fuse the detail layers and base layer to obtain the image with global details of the input image. Finally, the proposed algorithm is implemented on an FPGA using advanced high-level synthesis tools. Comprehensive testing of our proposed method on the AXU15EG board demonstrates its effectiveness in significantly improving image contrast and enhancing detail information. At the same time, real-time enhancement at a speed of 147 FPS is achieved for infrared images with a resolution of 640 × 480.
Multi-Scale Attention Feature Enhancement Network for Single Image Dehazing
Authors: Dong Weida , Wang Chunyan , Sun Hao , Teng Yunjie , Xu Xiping
Published: September 2023

Aiming to solve the problem of color distortion and loss of detail information in most dehazing algorithms, an end-to-end image dehazing network based on multi-scale feature enhancement is proposed. Firstly, the feature extraction enhancement module is used to capture the detailed information of hazy images and expand the receptive field. Secondly, the channel attention mechanism and pixel attention mechanism of the feature fusion enhancement module are used to dynamically adjust the weights of different channels and pixels. Thirdly, the context enhancement module is used to enhance the context semantic information, suppress redundant information, and obtain the haze density image with higher detail. Finally, our method removes haze, preserves image color, and ensures image details. The proposed method achieved a PSNR score of 33.74, SSIM scores of 0.9843 and LPIPS distance of 0.0040 on the SOTS-outdoor dataset. Compared with representative dehazing methods, it demonstrates better dehazing performance and proves the advantages of the proposed method on synthetic hazy images. Combined with dehazing experiments on real hazy images, the results show that our method can effectively improve dehazing performance while preserving more image details and achieving color fidelity.
A Comprehensive Study of the Impact of Waste Fires on the Environment and Health
Authors: Jakhar Rakshit , Samek Lucyna , Styszko Katarzyna
Published: September 2023

The escalating crisis of environmental degradation, with waste fires acting as a potent accelerant, has reached a critical juncture that demands immediate attention. This crisis disproportionately affects developing and low-income nations, where unregulated disposal and incineration in open areas have become rampant. These open waste fires serve as hotbeds for many environmental hazards ranging from air and water pollution to soil degradation. In addition, they contribute to the growing threat of marine litter and are a significant source of greenhouse gas emissions, exacerbating global climate change. Beyond their environmental toll, waste fires present an immediate and long-term threat to human health, causing respiratory problems and skin conditions and potentially leading to more serious health outcomes, such as cancer. Their impacts are multidimensional, affecting not only the environment but also pose severe health risks to communities, especially those near waste-burning sites. In this technologically advanced era, the application of artificial intelligence (AI), Machine Learning (ML), and deep learning technologies has the potential to revolutionize waste fire management. These technologies can significantly improve the accuracy of identifying, monitoring, and ultimately mitigating waste fires, making them indispensable tools in the fight against this complex issue. This article offers a comprehensive and in-depth examination of the historical evolution of waste fires, with the aim of shedding light on the critical factors that contribute to their occurrence. We explore the scientific mechanisms by which waste fires lead to environmental pollution and public health crises, providing a holistic understanding of their far-reaching impacts. We present an overview of significant research initiatives, policy interventions, and technological solutions that have been proposed or implemented by authoritative bodies around the world. By synthesizing existing research and offering new insights, this paper aims to facilitate a deeper understanding of the intricacies of waste fires and spur innovative solutions for their sustainable management and eventual eradication. Therefore, this article focuses on environmental and human health problems while outlining the comprehensive approach and potential contributions to solving this critical issue.
Stochastic Optimization Model of Capacity Configuration for Integrated Energy Production System Considering Source-Load Uncertainty
Authors: Miao Ankang , Yuan Yue , Huang Yi , Wu Han , Feng Chao
Published: September 2023

China’s carbon neutrality strategy has expedited a transition towards greener and lower-carbon integrated energy systems. Faced with the problem that the central position of thermal power cannot be transformed quickly, utilizing traditional thermal power units in a low-carbon and efficient manner is the premise to guarantee green energy development. This study focuses on the integrated energy production system (IEPS) and a stochastic optimization model for capacity configuration that integrates carbon capture storage and power-to-gas while considering source-load uncertainty. Firstly, carbon capture storage and power-to-gas technologies are introduced, and the architecture and models of the IEPS are established. The carbon and hydrogen storage equipment configuration enhances the system’s flexibility. Also, source-load uncertainty is considered, and a deterministic transformation is applied using the simultaneous backward reduction algorithm combined with K-means clustering. The paper simulates the optimal capacity configuration of the IEPS in a park energy system in Suzhou, China. Furthermore, the research performs a sensitivity analysis on coal, natural gas, and carbon tax prices. Case studies verified that IEPS can realize the recycling of electricity, gas, hydrogen, and carbon, with remarkable characteristics of low-carbon, flexibility, and economical. Stochastic optimized capacity allocation results considering source-load uncertainty are more realistic. Sensitivity intervals for energy prices can reference pricing mechanisms in energy markets. This study can provide ideas for the transition of China’s energy structure and offer directions to the low-carbon sustainable development of the energy system.
The Influence of Commitment to Change and Change-Related Behaviour among Academics of Malaysian-Islamic Higher Learning Institutions
Authors: Mohd Noor Azrena , Dorasamy Magiswary , Raman Murali
Published: September 2023

The implementation of change in higher learning institutions is rapidly becoming a norm. Academics have to grapple with the changes imposed in order to remain relevant. With the introduction of the Malaysian Education Blueprint (2013–2025) and other factors, academics in higher learning institutions have had to change and ensure that change is sustainable. In line with this, one of the issues in the area of organisational change is commitment to change. The purpose of this paper is to determine the link between the academics’ level of commitment to change and change-related behaviour in selected Islamic higher learning institutions in Malaysia. A survey method was applied, and questionnaires were distributed. Responses from 103 respondents were analysed using PLS-SEM. Results indicated that academics’ level of affective commitment to change has an influence on cooperation and championing, while continuance commitment to change only influenced compliance. Normative commitment to change only has an influence on cooperation. Other than being the only study that focuses on Malaysian-Islamic higher learning institutions in studying commitment to change, the results of this research also provide insights on the behavioural outcomes of commitment to change, which is crucial for the success of change implementation.