bluuebunny/crossref_metadata_2025 huggingface dataset:
Description and Whole-Genome Sequencing of Mariniflexile litorale sp. nov., Isolated from the Shallow Sediments of the Sea of Japan
Authors: Romanenko Lyudmila , Bystritskaya Evgeniya , Savicheva Yuliya , Eremeev Viacheslav , Otstavnykh Nadezhda , Kurilenko Valeriya , Velansky Peter , Isaeva Marina
Published: July 2024

A Gram-negative, aerobic, rod-shaped, non-motile, yellow-pigmented bacterium, KMM 9835T, was isolated from the sediment sample obtained from the Amur Bay of the Sea of Japan seashore, Russia. Phylogenetic analyses based on the 16S rRNA gene and whole genome sequences positioned the novel strain KMM 9835T in the genus Mariniflexile as a separate line sharing the highest 16S rRNA gene sequence similarities of 96.6% and 96.2% with Mariniflexile soesokkakense RSSK-9T and Mariniflexile fucanivorans SW5T, respectively, and similarity values of <96% to other recognized Mariniflexile species. The average nucleotide identity and digital DNA–DNA hybridization values between strain KMM 9835T and M. soesokkakense KCTC 32427T, Mariniflexile gromovii KCTC 12570T, M. fucanivorans DSM 18792T, and M. maritimum M5A1MT were 83.0%, 82.5%, 83.4%, and 78.3% and 30.7%, 29.6%, 29.5%, and 24.4%, respectively. The genomic DNA GC content of strain KMM 9835T was 32.5 mol%. The dominant menaquinone was MK-6, and the major fatty acids were iso-C15:0, iso-C15:1ω10c, and C15:0. The polar lipids of strain KMM 9835T consisted of phosphatidylethanolamine, two unidentified aminolipids, an unidentified phospholipid, and six unidentified lipids. A pan-genome analysis showed that the KMM 9835T genome encoded 753 singletons. The annotated singletons were more often related to transport protein systems (SusC), transcriptional regulators (AraC, LytTR, LacI), and enzymes (glycosylases). The KMM 9835T genome was highly enriched in CAZyme-encoding genes, the proportion of which reached 7.3%. Moreover, the KMM 9835T genome was characterized by a high abundance of CAZyme gene families (GH43, GH28, PL1, PL10, CE8, and CE12), indicating its potential to catabolize pectin. This may represent part of an adaptation strategy facilitating microbial consumption of plant polymeric substrates in aquatic environments near shorelines and freshwater sources. Based on the combination of phylogenetic and phenotypic characterization, the marine sediment strain KMM 9835T (=KCTC 92792T) represents a novel species of the genus Mariniflexile, for which the name Mariniflexile litorale sp. nov. is proposed.
Comparing the Performance of Hydrocyclones and High-Frequency Screens in an Industrial Grinding Circuit: Part I—Size Separation Assessments
Authors: Costa Bruna Silveira , Bergerman Maurício Guimarães , Delboni Júnior Homero
Published: July 2024

Industrial ball milling circuits usually include hydrocyclones in a closed configuration to achieve a specified grinding size. Although hydrocyclones are relatively simple to operate, their classification performance is generally low, leading to significant fines recirculation within the circuit, consequently overgrinding the product. Conversely, high-frequency screening potentially shows a relatively higher separation efficiency, as the entrainment of fines to the coarse product is significantly reduced. The present work compares the performance of hydrocyclones—HC and high-frequency screens—HFS based on four surveys conducted in Nexa’s Vazante Zinc ore industrial grinding circuit in Vazante, Brazil, which processes zinc silicate ore. The comparisons included the partition of solids, water split, and particle size distributions. Whiten’s partition curve model was adopted to obtain the selected performance parameters through mass balancing the experimental data. The industrial surveys comprised three different size separation configurations, i.e., HC-Only, HFS-Only, and a combined HC-HFS setup. In all cases, the assessments consistently indicated higher separation performances with HFS compared to the HC operation. The final product associated with the HC+HFS configuration showed a narrower size distribution around the grinding size.
Inhibitory Effect of Selected Guaianolide and Germacranolide Sesquiterpene Lactones on Nitric Oxide Production
Authors: Harmatha Juraj , Zídek Zdeněk , Kmoníčková Eva
Published: July 2024

Trilobolide and its analogues belong to the guaianolide type of sesquiterpene lactones, which are characteristic and widely distributed within the families Asteraceae and Apiaceae. Certain guaianolides are receiving continuously increasing attention for their promising sarco-endoplasmic reticulum Ca2+-ATPase (SERCA)-inhibitory activity. However, because of their alkylation capabilities, they are generally toxic. Therefore, the search for compounds with significant immunobiological properties but with decreased cytotoxicities suitable for use in immune-based pharmacotherapy is ongoing. Therefore, we extended our previous investigation of the immunobiological effects of trilobolide to a series of structurally related guaianolides and germacranolides. To evaluate the relationship, we tested a series of selected derivatives containing α-methyl lactone or exomethylene lactone ring. For a wider comparison, we also included some of their glycosidic derivatives. We assessed the in vitro immunobiological effects of the tested compounds on nitric oxide (NO) production, cytokine secretion, and prostaglandin E2 (PGE2) release by mouse peritoneal cells, activated primarily by lipopolysaccharide (LPS), and evaluated their viability. The inhibitory effects of the apparently most active substance, 8-deoxylactucin, seem to be the most promising.
Dual Inhibitors of P-gp and Carbonic Anhydrase XII (hCA XII) against Tumor Multidrug Resistance with Piperazine Scaffold
Authors: Braconi Laura , Riganti Chiara , Parenti Astrid , Cecchi Marta , Nocentini Alessio , Bartolucci Gianluca , Menicatti Marta , Contino Marialessandra , Colabufo Nicola Antonio , Manetti Dina , Romanelli Maria Novella , Supuran Claudiu T. , Teodori Elisabetta
Published: July 2024

A new series of piperazine derivatives were synthesized and studied with the aim of obtaining dual inhibitors of P-glycoprotein (P-gp) and carbonic anhydrase XII (hCA XII) to synergistically overcome the P-gp-mediated multidrug resistance (MDR) in cancer cells expressing the two proteins, P-gp and hCA XII. Indeed, these hybrid compounds contain both P-gp and hCA XII binding groups on the two nitrogen atoms of the heterocyclic ring. All compounds showed good inhibitory activity on each protein (P-gp and hCA XII) studied individually, and many of them showed a synergistic effect in the resistant HT29/DOX and A549/DOX cell lines which overexpress both the target proteins. In particular, compound 33 displayed the best activity by enhancing the cytotoxicity and intracellular accumulation of doxorubicin in HT29/DOX and A549/DOX cells, thus resulting as promising P-gp-mediated MDR reverser with a synergistic mechanism. Furthermore, compounds 13, 27 and 32 induced collateral sensitivity (CS) in MDR cells, as they were more cytotoxic in resistant cells than in the sensitive ones; their CS mechanisms were extensively investigated.
Coffee Bean and Its Chemical Constituent Caffeine and Chlorogenic Acid as Promising Chemoprevention Agents: Updated Biological Studies against Cancer Cells
Authors: Aborziza Mohamed , Amalia Riezki , Zuhrotun Ade , Ikram Nur Kusaira Khairul , Novitasari Dhania , Muchtaridi Muchtaridi
Published: July 2024

Cancer is a complicated and ever-evolving disease that remains a significant global cause of disease and mortality. Its complexity, which is evident at the genetic and phenotypic levels, contributes to its diversity and resistance to treatment. Numerous scientific investigations on human and animal models demonstrate the potential of phytochemicals in cancer prevention. Coffee has been shown to possess potent anti-carcinogenic properties, and studies have documented the consumption of coffee as a beverage reduces the risk of cancer occurrence. The major secondary metabolites of coffee, named caffeine and chlorogenic acid, have been linked to anti-inflammatory and antineoplastic effects through various signaling. In light of this, this review article provides a comprehensive analysis based on studies in anticancer effects of coffee, chlorogenic acid, and caffeine published between 2010 and 2023, sourced from Scopus, Pubmed, and Google Scholar databases. We summarize recent advances and scientific evidence on the association of phytochemicals found in coffee with a special emphasis on their biological activities against cancer and their molecular mechanism deemed potential to be used as a novel therapeutic target for cancer prevention and therapy.
Mapping or no Mapping: The Influence of Controller Interaction Design in an Immersive Virtual Reality Tutorial in Two Different Age Groups
Authors: Urech Andreas , Meier Pascal Valentin , Gut Stephan , Duchene Pascal , Christ Oliver
Published: July 2024

Navigation and interaction in the virtual world will occur via controllers. Previous literature suggests that not all buttons on these controllers are suitable for all functions and that unclear or uncomfortable operations can lead to frustration. This study aimed to determine if an operation with freely selectable buttons differs from one with mapped buttons, in which human-factor differences can be identified, and if there are differences between primary and advanced training. A field experiment with professionals employed by Swiss Federal Railways and apprentices and future apprentices (N = 60) was conducted in a VR tutorial that was previously developed using design cues from existing literature. Controller operation was varied in the groups. The results show significant differences and interaction effects, which indicate that a different operation is more appropriate for apprentices than for professionals in further education.
Fluorescence-Based Multimodal DNA Logic Gates
Authors: Algama Chamika Harshani , Basir Jamil , Wijesinghe Kalani M. , Dhakal Soma
Published: July 2024

The use of DNA structures in creating multimodal logic gates bears high potential for building molecular devices and computation systems. However, due to the complex designs or complicated working principles, the implementation of DNA logic gates within molecular devices and circuits is still quite limited. Here, we designed simple four-way DNA logic gates that can serve as multimodal platforms for simple to complex operations. Using the proximity quenching of the fluorophore–quencher pair in combination with the toehold-mediated strand displacement (TMSD) strategy, we have successfully demonstrated that the fluorescence output, which is a result of gate opening, solely relies on the oligonucleotide(s) input. We further demonstrated that this strategy can be used to create multimodal (tunable displacement initiation sites on the four-way platform) logic gates including YES, AND, OR, and the combinations thereof. The four-way DNA logic gates developed here bear high promise for building biological computers and next-generation smart molecular circuits with biosensing capabilities.
Nonaqueous Synthesis of Pd/PdO-Functionalized NiFe2O4 Nanoparticles Enabled Enhancing n-Butanol Detection
Authors: Wu Hongyang , Chen Chen
Published: July 2024

The efficient detection of n-butanol, which is in demand for highly sensitive materials, is essential for multiple applications. A nonaqueous method was applied to prepare NiFe2O4 nanoparticles (NPs) using benzyl alcohol as a solvent, which shows a size of 7.9 ± 1.6 nm and a large surface area of 82.23 m2/g. To further improve the sensing performance for n-butanol, Pd/PdO functionalization was sensitized with NiFe2O4 NPs. Gas sensing results demonstrate that the Pd/PdO-NiFe2O4 exhibits an enhanced response of 36.9 to 300 ppm n-butanol and a fast response and recovery time (18.2/17.6 s) at 260 °C. Furthermore, the Pd/PdO-NiFe2O4-based sensor possesses a good linear relationship between responses and the n-butanol concentration from 1 to 1000 ppm, and great selectivity against other volatile organic compounds (VOCs). The excellent sensing enhancement is attributed to the catalytic effects of Pd/PdO, the increase of oxygen vacancies, and the formation of heterojunction between PdO and NiFe2O4. Thus, this study offers an effective route for the synthesis of Pd/PdO-functionalized NiFe2O4 NPs to achieve n-butanol detection with excellent sensing performance.
MoO3 with the Synergistic Effect of Sulfur Doping and Oxygen Vacancies: The Influence of S Doping on the Structure, Morphology, and Optoelectronic Properties
Authors: Yu Jian , Zheng Zhaokang , Wang Aiwu , Humayun Muhammad , Attia Yasser A.
Published: July 2024

Molybdenum trioxide (MoO3) is an attractive semiconductor. Thus, bandgap engineering toward photoelectronic applications is appealing yet not well studied. Here, we report the incorporation of sulfur atoms into MoO3, using sulfur powder as a source of sulfur, via a self-developed hydrothermal synthesis approach. The formation of Mo-S bonds in the MoO3 material with the synergistic effect of sulfur doping and oxygen vacancies (designated as S-MoO3−x) is confirmed using Fourier-transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and electron paramagnetic resonance (EPR). The bandgap is tuned from 2.68 eV to 2.57 eV upon sulfur doping, as confirmed by UV-VIS DRS spectra. Some MoS2 phase is identified with sulfur doping by referring to the photoluminescence (PL) spectra and electrochemical impedance spectroscopy (EIS), allowing significantly improved charge carrier separation and electron transfer efficiency. Therefore, the as-prepared S-MoO3−x delivers a sensitive photocurrent response and splendid cycling stability. This study on the synergistic effect of sulfur doping and oxygen vacancies provides key insights into the impact of doping strategies on MoO3 performance, paving new pathways for its optimization and development in relevant fields.
Grade C Molar-Incisor Pattern Periodontitis in Young Adults: What Have We Learned So Far?
Authors: Miguel Manuela Maria Viana , Shaddox Luciana Macchion
Published: July 2024

Grade C molar-incisor pattern periodontitis (C-MIP) is a disease that affects specific teeth with an early onset and aggressive progression. It occurs in systemically healthy patients, mostly African descendants, at an early age, with familial involvement, minimal biofilm accumulation, and minor inflammation. Severe and rapidly progressive bone loss is observed around the first molars and incisors. This clinical condition has been usually diagnosed in children and young adults with permanent dentition under 30 years of age. However, this disease can also affect the primary dentition, which is not as frequently discussed in the literature. Radiographic records have shown that most patients diagnosed in the permanent dentition already presented disease signs in the primary dentition. A hyperresponsive immunological profile is observed in local (gingival crevicular fluid-GCF) and systemic environments. Siblings have also displayed a heightened inflammatory profile even without clinical signs of disease. A. actinomycetemcomitans has been classified as a key pathogen in C-MIP in both dentitions. Scaling and root planning associated with systemic antibiotics is the current gold standard to treat C-MIP, leading to GCF biomarker reduction, some systemic inflammatory response modulation and microbiome profile changes to a healthy-site profile. Further studies should focus on other possible disease-contributing risk factors.
Treatment of Prepubertal Labial Adhesions with Topical Estriol + Testosterone: A Case Report
Authors: Murina Filippo , Fochesato Cecilia , Savasi Valeria Maria
Published: July 2024

Background: Labial adhesions, a frequent gynecological condition in prepubertal girls, occur when the labia minora adhere along the midline. The prevailing hypothesis about their etiology suggests that labial adhesion may occur when the delicate and non-estrogenized labia minora undergo an inflammatory response, triggered by exposure to an irritant environment. Therefore, conservative treatment involves the application of topical estrogen or betamethasone cream. The role of androgens has not been considered yet in the pathophysiology or therapy of this condition. However, some studies have shown that androgen receptors are prevalent in the labia minora and vulvar vestibule. Case summary: We present the case of a 29-month-old girl with symptomatic labial adhesions. She was first ineffectively treated with topical estriol, and then she was treated with a galenic cream containing both estriol and testosterone with complete recovery and without side-effects. Conclusions: Both androgens and estrogens play a significant role in maintaining the physiological trophic state of the vulva and vagina, even during childhood. Topical estriol+testosterone could be considered an alternative treatment for prepubertal labial adhesions refractory to standard topical therapy.
Impact of Imbalanced Modulation on Security of Continuous-Variable Measurement-Device-Independent Quantum Key Distribution
Authors: Liu Wenyuan , Liu Zehui , Bai Jiandong , Jie Qi , Zhang Guangwei , Tian Yan , Jin Jingjing
Published: July 2024

Continuous variable measurement-device-independent quantum key distribution (CV-MDI-QKD) removes all known or unknown side-channel attacks on detectors. However, it is difficult to fully implement assumptions in the security demonstration model, which leads to potential security vulnerabilities inevitably existing in the practical system. In this paper, we explore the impact of imbalanced modulation at transmitters on the security of the CV-MDI-QKD system mainly using a coherent state and squeezed state under symmetric and asymmetric distances. Assuming two different modulation topologies of senders, we propose a generalized theoretical scheme and evaluate the key parameter achievable of the protocol with the mechanism of imbalanced modulation. The presented results show that imbalanced modulation can achieve a relatively nonlinearly higher secret key rate and transmission distances than the previous protocol which is the balanced modulation variance used by transmitters. The advantage of imbalanced modulation is demonstrated for the system key parameter estimation using numerical simulation under different situations. In addition, the consequences indicate the importance of imbalanced modulation on the performance of CV-MDI-QKD protocol and provide a theoretical framework for experimental implementation as well as the optimal modulated mode.
Adaptive Responses of Hormones to Nitrogen Deficiency in Citrus sinensis Leaves and Roots
Authors: Hua Dan , Rao Rong-Yu , Chen Wen-Shu , Yang Hui , Shen Qian , Lai Ning-Wei , Yang Lin-Tong , Guo Jiuxin , Huang Zeng-Rong , Chen Li-Song
Published: July 2024

Some citrus orchards in China often experience nitrogen (N) deficiency. For the first time, targeted metabolomics was used to examine N-deficient effects on hormones in sweet orange (Citrus sinensis (L.) Osbeck cv. Xuegan) leaves and roots. The purpose was to validate the hypothesis that hormones play a role in N deficiency tolerance by regulating root/shoot dry weight ratio (R/S), root system architecture (RSA), and leaf and root senescence. N deficiency-induced decreases in gibberellins and indole-3-acetic acid (IAA) levels and increases in cis(+)-12-oxophytodienoic acid (OPDA) levels, ethylene production, and salicylic acid (SA) biosynthesis might contribute to reduced growth and accelerated senescence in leaves. The increased ethylene formation in N-deficient leaves might be caused by increased 1-aminocyclopropanecarboxylic acid and OPDA and decreased abscisic acid (ABA). N deficiency increased R/S, altered RSA, and delayed root senescence by lowering cytokinins, jasmonic acid, OPDA, and ABA levels and ethylene and SA biosynthesis, increasing 5-deoxystrigol levels, and maintaining IAA and gibberellin homeostasis. The unchanged IAA concentration in N-deficient roots involved increased leaf-to-root IAA transport. The different responses of leaf and root hormones to N deficiency might be involved in the regulation of R/S, RSA, and leaf and root senescence, thus improving N use efficiency, N remobilization efficiency, and the ability to acquire N, and hence conferring N deficiency tolerance.
Hydrogen Production in Microbial Electrolysis Cells Using an Alginate Hydrogel Bioanode Encapsulated with a Filter Bag
Authors: Hirsch Lea Ouaknin , Gandu Bharath , Chiliveru Abhishiktha , Dubrovin Irina Amar , Jukanti Avinash , Schechter Alex , Cahan Rivka
Published: July 2024

The bacterial anode of microbial electrolysis cells (MECs) is the limiting factor in a high hydrogen evolution reaction (HER). This study focused on improving biofilm attachment to a carbon-cloth anode using an alginate hydrogel. In addition, the modified bioanode was encapsulated by a filter bag that served as a physical barrier, to overcome its low mechanical strength and alginate degradation by certain bacterial species in wastewater. The MEC based on an encapsulated alginate bioanode (alginate bioanode encapsulated by a filter bag) was compared with three controls: an MEC based on a bare bioanode (non-immobilized bioanode), an alginate bioanode, and an encapsulated bioanode (bioanode encapsulated by a filter bag). At the beginning of the operation, the Rct value for the encapsulated alginate bioanode was 240.2 Ω, which decreased over time and dropped to 9.8 Ω after three weeks of operation when the Geobacter medium was used as the carbon source. When the MECs were fed with wastewater, the encapsulated alginate bioanode led to the highest current density of 9.21 ± 0.16 A·m−2 (at 0.4 V), which was 20%, 95%, and 180% higher, compared to the alginate bioanode, bare bioanode, and encapsulated bioanode, respectively. In addition, the encapsulated alginate bioanode led to the highest reduction currents of (4.14 A·m−2) and HER of 0.39 m3·m−3·d−1. The relative bacterial distribution of Geobacter was 79%. The COD removal by all the bioanodes was between 62% and 88%. The findings of this study demonstrate that the MEC based on the encapsulated alginate bioanode exhibited notably higher bio-electroactivity compared to both bare, alginate bioanode, and an encapsulated bioanode. We hypothesize that this improvement in electron transfer rate is attributed to the preservation and the biofilm on the anode material using alginate hydrogel which was inserted into a filter bag.
Keratin from Animal By-Products: Structure, Characterization, Extraction and Application—A Review
Authors: Banasaz Shahin , Ferraro Vincenza
Published: July 2024

Keratin is a structural fibrous protein and the core constituent of animal by-products from livestock such as wool, feathers, hooves, horns, and pig bristles. This natural polymer is also the main component of human hair and is present at an important percentage in human and animal skin. Significant amounts of keratin-rich animal tissues are discarded worldwide each year, ca. 12 M tons, and the share used for keratin extraction and added-value applications is still very low. An important stream of new potential raw materials, represented by animal by-products and human hair, is thus being lost, while a large-scale valorization could contribute to a circular bioeconomy and to the reduction in the environmental fingerprint of those tissues. Fortunately, scientific research has made much important progress in the last 10–15 years in the better understanding of the complex keratin architecture and its variability among different animal tissues, in the development of tailored extraction processes, and in the screening of new potential applications. Hence, this review aims at a discussion of the recent findings in the characterization of keratin and keratin-rich animal by-product structures, as well as in keratin recovery by conventional and emerging techniques and advances in valorization in several fields.
Morphological, Thermal, and Mechanical Properties of Nanocomposites Based on Bio-Polyamide and Feather Keratin–Halloysite Nanohybrid
Authors: Teodorescu George Mihail , Vuluga Zina , Ioniță Andreea , Nicolae Cristian Andi , Ghiurea Marius , Gabor Augusta Raluca , Rădițoiu Valentin , Raduly Monica , Brezeştean Ioana Andreea , Marconi Daniel , Turcu Ioan
Published: July 2024

One solution to comply with the strict regulations of the European Commission and reduce the environmental footprint of composites is the use of composite materials based on bio-polymers and fillers from natural resources. The aim of our work was to obtain and analyze the properties of bio-polymer nanocomposites based on bio-PA (PA) and feather keratin–halloysite nanohybrid. Keratin (KC) was mixed with halloysite (H) as such or with the treated surface under dynamic conditions, resulting in two nanohybrids: KCHM and KCHE. The homogenization of PA with the two nanohybrids was conducted using the extrusion processing process. Two types of nanocomposites, PA–KCHM and PA–KCHE, with 5 wt.% KC and 1 wt.% H were obtained. The properties were analyzed using SEM, XRD, FTIR, RAMAN, TGA, DSC, tensile/impact tests, DMA, and nanomechanical tests. The best results were obtained for PA–KCHE due to the stronger interaction between the components and the uniform dispersion of the nanohybrid in the PA matrix. Improvements in the modulus of elasticity and of the surface hardness by approx. 75% and 30%, respectively, and the resistance to scratch were obtained. These results are promising and constitute a possible alternative to synthetic polymer composites for the automotive industry.
An Accurate Calculation Method on Blasingame Production Decline Model of Horizontal Well with Dumbbell-like Hydraulic Fracture in Tight Gas Reservoirs
Authors: Xiang Zuping , Jia Ying , Xu Youjie , Ao Xiang , Liu Zhezhi , Zhu Shijie , Chen Zhonghua
Published: July 2024

Blasingame production decline is an effective method to obtain permeability and single-well controlled reserves. The accurate Blasingame production decline curve needs an accurate wellbore pressure approximate solution of the real-time domain. Therefore, the aim of this study is to present a simple and accurate wellbore pressure approximate solution and Blasingame production decline curves calculation method of a multi-stage fractured horizontal well (MFHW) with complex fractures. A semi-analytical model of MFHWs in circle-closed reservoirs is presented. The wellbore pressure and dimensionless pseudo-steady productivity index JDpss (1/bDpss) are verified with a numerical solution. The comparison result reaches a good match. Wellbore pressure and Blasingame production decline curves are used to analyze parameter sensitivity. Results show that when the crossflow from matrix to natural fracture appears after the pseudo-state flow regime, the value of the inter-porosity coefficient has an obvious influence on the pressure approximate solution of the pseudo-steady flow regime in naturally fractured gas reservoirs. The effects of relevant parameters on wellbore pressure and the Blasingame decline curve are also analyzed. The method of pseudo-steady productivity index JDpss can applied to all well and reservoir models.
Investigation of Partial Oxidation of Methane at Different Reaction Parameters by Adding Ni to CeO2 and ZrO2 Supported Cordierite Monolith Catalyst
Authors: Ilicak Bayraktar Ilke , Figen Halit Eren
Published: July 2024

The climate crisis, driven by increasing CO2 levels in the atmosphere, has heightened the need for new, environmentally friendly energy sources. Hydrogen gas, which can meet our energy needs, has become a particularly intriguing topic. This study investigated the partial oxidation reaction of methane with cordierite monolith catalysts. The Ni-coated catalysts were supported with γ-Al2O3, CeO2, ZrO2, and CeO2-ZrO2. The catalysts were tested at temperatures of 750, 800, and 850 °C with different flow rates and methane feed concentrations (2%, 5%, and 10%). It was demonstrated that catalyst activity varies depending on these parameters. It has been found that high gas hourly space velocity (GHSV) and CH4 feed rates decrease catalyst activity. The obtained reaction results indicated that the optimal reaction parameters were 800 °C, a GHSV of 1 × 104 h−1, and a CH4 feed concentration of 2%. By optimizing these parameters, catalysts with high CH4 conversion and selectivity for H2 and CO were achieved. The prepared catalysts were characterized using scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET), and temperature-programmed reduction (TPR).
People with Disabilities and Their Families in the Roman Catholic Church in Poland: An Analysis of Barriers to Participation in Religious Practices
Authors: Zielińska-Król Katarzyna
Published: July 2024

The available research suggests that the rate of involvement of people with disabilities and their families in the life of the Church is significantly lower than that of people without disabilities. The engagement of people with disabilities is largely dependent on (a) the level of religiosity; (b) intrinsic motivation; (c) the level of trust in the institutions of the Church; and (d) broadly understood accessibility factors. Barriers experienced by people with disabilities are complex in nature, and make these people dependent on the help of others. Overcoming them requires significant investment, commitment, and change in the Church institution. These issues are relatively rarely addressed in the literature. The few, usually partial studies tend to concentrate on specific disabilities, discussed with no reference to the family context. However, it is usually the case that the religiosity and church activity of a person with a disability are firmly rooted in their family reality, shaped by the level of religiosity of their parents, and sometimes dependent on their presence and involvement. The aim of this article, which is both theoretical and empirical in nature, is to answer the question of which barriers form an obstacle to participation in religious life for people with disabilities and their families in Poland. This study uses the results of a nationwide qualitative research (focus group interview method) conducted among people with physical and intellectual disabilities, the hard-of-hearing and the deaf, the visually impaired, and their carers. Data analysis enabled the identification of the following barriers: infrastructural, personal and organizational (family-related and extra-familial). These research results can provide guidance in pastoral work with people with disabilities and their families, improving not only the quality of their religious experience, but also the number of the faithful in the Church community.
Ensemble Learning for the Land Cover Classification of Loess Hills in the Eastern Qinghai–Tibet Plateau Using GF-7 Multitemporal Imagery
Authors: Shi Feifei , Gao Xiaohong , Li Runxiang , Zhang Hao
Published: July 2024

The unique geographic environment, diverse ecosystems, and complex landforms of the Qinghai–Tibet Plateau make accurate land cover classification a significant challenge in plateau earth sciences. Given advancements in machine learning and satellite remote sensing technology, this study investigates whether emerging ensemble learning classifiers and submeter-level stereoscopic images can significantly improve land cover classification accuracy in the complex terrain of the Qinghai–Tibet Plateau. This study utilizes multitemporal submeter-level GF-7 stereoscopic images to evaluate the accuracy of 11 typical ensemble learning classifiers (representing bagging, boosting, stacking, and voting strategies) and 3 classification datasets (single-temporal, multitemporal, and feature-optimized datasets) for land cover classification in the loess hilly area of the Eastern Qinghai–Tibet Plateau. The results indicate that compared to traditional single strong classifiers (such as CART, SVM, and MLPC), ensemble learning classifiers can improve land cover classification accuracy by 5% to 9%. The classification accuracy differences among the 11 ensemble learning classifiers are generally within 1% to 3%, with HistGBoost, LightGBM, and AdaBoost-DT achieving a classification accuracy comparable to CNNs, with the highest overall classification accuracy (OA) exceeding 93.3%. All ensemble learning classifiers achieved better classification accuracy using multitemporal datasets, with the classification accuracy differences among the three classification datasets generally within 1% to 3%. Feature selection and feature importance evaluation show that spectral bands (e.g., the summer near-infrared (NIR-S) band), topographic factors (e.g., the digital elevation model (DEM)), and spectral indices (e.g., the summer resident ratio index (RRI-S)) significantly contribute to the accuracy of each ensemble learning classifier. Using feature-optimized datasets, ensemble classifiers can improve classification efficiency. This study preliminarily confirms that GF-7 images are suitable for land cover classification in complex terrains and that using ensemble learning classifiers and multitemporal datasets can improve classification accuracy.
Integrated Use of Synthetic Aperture Radar and Optical Data in Mapping Native Vegetation: A Study in a Transitional Brazilian Cerrado–Atlantic Forest Interface
Authors: Santos Allita R. , Barbosa Mariana A. G. A. , Anjinho Phelipe S. , Parizotto Denise , Mauad Frederico F.
Published: July 2024

This study develops a structure for mapping native vegetation in a transition area between the Brazilian Cerrado and the Atlantic Forest from integrated spatial information of Sentinel-1 and Sentinel-2 satellites. Most studies use integrated data to improve classification accuracy in adverse atmospheric conditions, in which optical data have many errors. However, this method can also improve classifications carried out in landscapes with favorable atmospheric conditions. The use of Sentinel-1 and Sentinel-2 data can increase the accuracy of mapping algorithms and facilitate visual interpretation during sampling by providing more parameters that can be explored to differentiate land use classes with complementary information, such as spectral, backscattering, polarimetry, and interferometry. The study area comprises the Lobo Reservoir Hydrographic Basin, which is part of an environmental conservation unit protected by Brazilian law and with significant human development. LULC were classified using the random forest deep learning algorithm. The classifying attributes were backscatter coefficients, polarimetric decomposition, and interferometric coherence for radar data (Sentinel-1), and optical spectral data, comprising bands in the red edge, near-infrared, and shortwave infrared (Sentinel-2). The attributes were evaluated in three settings: SAR and optical data in separately settings (C1 and C2, respectively) and in an integrated setting (C3). The study found greater accuracy for C3 (96.54%), an improvement of nearly 2% compared to C2 (94.78%) and more than 40% in relation to C1 (55.73%). The classification algorithm encountered significant challenges in identifying wetlands in C1, but performance improved in C3, enhancing differentiation by stratifying a greater number of classes during training and facilitating visual interpretation during sampling. Accordingly, the integrated use of SAR and optical data can improve LULC mapping in tropical regions where occurs biomes interface, as in the transitional Brazilian Cerrado and Atlantic Forest.
Assessment of Land Suitability Potential Using Ensemble Approaches of Advanced Multi-Criteria Decision Models and Machine Learning for Wheat Cultivation
Authors: Nabiollahi Kamal , M. Kebonye Ndiye , Molani Fereshteh , Tahari-Mehrjardi Mohammad Hossein , Taghizadeh-Mehrjardi Ruhollah , Shokati Hadi , Scholten Thomas
Published: July 2024

Land suitability assessment, as an important process in modern agriculture, involves the evaluation of numerous aspects such as soil properties, climate, relief, hydrology and socio-economic aspects. The aim of this study was to evaluate the suitability of soils for wheat cultivation in the Gavshan region, Iran, as the country is facing the task of becoming self-sufficient in wheat. Various methods were used to evaluate the land, such as multi-criteria decision-making (MCDM), which is proving to be important for land use planning. MCDM and machine learning (ML) are useful for decision-making processes because they use complicated spatial data and methods that are widely available. Using a geomorphological map, seventy soil profiles were selected and described, and ten soil properties and wheat yields were determined. Three MCDM approaches, including the technique of preference ordering by similarity to the ideal solution (TOPSIS), gray relational analysis (GRA), and simple additive weighting (SAW), were used and evaluated. The criteria weights were extracted using Shannon’s entropy method. Random forest (RF) model and auxiliary variables (remote sensing data, terrain data, and geomorphological maps) were used to represent the land suitability values. Spatial autocorrelation analysis as a statistical method was applied to analyze the spatial variability of the spatial data. Slope, CEC (cation exchange capacity), and OC (organic carbon) were the most important factors for wheat cultivation. The spatial autocorrelation between the key criteria (slope, CEC, and OC) and wheat yield confirmed these results. These results also showed a significant correlation between the land suitability values of TOPSIS, GRA, and SAW and wheat yield (0.74, 0.72, and 0.57, respectively). The spatial distribution of land suitability values showed that the areas classified as good according to TOPSIS and GRA were larger than those classified as moderate and weak according to the SAW approach. These results were also confirmed by the autocorrelation of the MCDM techniques with wheat yield. In addition, the RF model showed its effectiveness in processing complex spatial data and improved the accuracy of land suitability assessment. In this study, by integrating advanced MCDM techniques and ML, an applicable land evaluation approach for wheat cultivation was proposed, which can improve the accuracy of land suitability and be useful for considering sustainability principles in land management.
A Smart Visual Sensor for Smoke Detection Based on Deep Neural Networks
Authors: Carletti Vincenzo , Greco Antonio , Saggese Alessia , Vento Bruno
Published: July 2024

The automatic detection of smoke by analyzing the video stream acquired by traditional surveillance cameras is becoming a more and more interesting problem for the scientific community thanks to the necessity to prevent fires at the very early stages. The adoption of a smart visual sensor, namely a computer vision algorithm running in real time, allows one to overcome the limitations of standard physical sensors. Nevertheless, this is a very challenging problem, due to the strong similarity of the smoke with other environmental elements like clouds, fog and dust. In addition to this challenge, data available for training deep neural networks is limited and not fully representative of real environments. Within this context, in this paper we propose a new method for smoke detection based on the combination of motion and appearance analysis with a modern convolutional neural network (CNN). Moreover, we propose a new dataset, called the MIVIA Smoke Detection Dataset (MIVIA-SDD), publicly available for research purposes; it consists of 129 videos covering about 28 h of recordings. The proposed hybrid method, trained and evaluated on the proposed dataset, demonstrated to be very effective by achieving a 94% smoke recognition rate and, at the same time, a substantially lower false positive rate if compared with fully deep learning-based approaches (14% vs. 100%). Therefore, the proposed combination of motion and appearance analysis with deep learning CNNs can be further investigated to improve the precision of fire detection approaches.
Assessment of PM2.5 Concentration at University Transit Bus Stops Using Low-Cost Aerosol Monitors by Student Commuters
Authors: Murray Will , Wu Qiang , Balanay Jo Anne G. , Sousan Sinan
Published: July 2024

Particulate matter of 2.5 µm and smaller (PM2.5) is known to cause many respiratory health problems, such as asthma and heart disease. A primary source of PM2.5 is emissions from cars, trucks, and buses. Emissions from university transit bus systems could create zones of high PM2.5 concentration at their bus stops. This work recruited seven university students who regularly utilized the transit system to use a low-cost personal aerosol monitor (AirBeam) each time they arrived at a campus bus stop. Each participant measured PM2.5 concentrations every time they were at a transit-served bus stop over four weeks. PM2.5 concentration data from the AirBeam were compared with an ADR-1500 high-cost monitor and EPA PM2.5 reference measurements. This methodology allowed for identifying higher-than-average concentration zones at the transit bus stops compared to average measurements for the county. By increasing access to microenvironmental data, this project can contribute to public health efforts of personal protection and prevention by allowing individuals to measure and understand their exposure to PM2.5 at the bus stop. This work can also aid commuters, especially those with pre-existing conditions who use public transportation, in making more informed health decisions and better protecting themselves against new or worsening respiratory conditions.
A New Approach for Super Resolution Object Detection Using an Image Slicing Algorithm and the Segment Anything Model
Authors: Telçeken Muhammed , Akgun Devrim , Kacar Sezgin , Bingol Bunyamin
Published: July 2024

Object detection in high resolution enables the identification and localization of objects for monitoring critical areas with precision. Although there have been improvements in object detection at high resolution, the variety of object scales, as well as the diversity of backgrounds and textures in high-resolution images, make it challenging for detectors to generalize successfully. This study introduces a new method for object detection in high-resolution images. The pre-processing stage of the method includes ISA and SAM to slice the input image and segment the objects in bounding boxes, respectively. In order to improve the resolution in the slices, the first layer of YOLO is designed as SRGAN. Thus, before applying YOLO detection, the resolution of the sliced images is increased to improve features. The proposed system is evaluated on xView and VisDrone datasets for object detection algorithms in satellite and aerial imagery contexts. The success of the algorithm is presented in four different YOLO architectures integrated with SRGAN. According to comparative evaluations, the proposed system with Yolov5 and Yolov8 produces the best results on xView and VisDrone datasets, respectively. Based on the comparisons with the literature, our proposed system produces better results.
Simultaneous Laparoscopic Surgery for Esophageal Achalasia Combined with Epiphrenic Diverticulum: A Case Report
Authors: Okamoto Koichi , Kinoshita Jun , Saito Hiroto , Ninomiya Itasu , Inaki Noriyuki , Takamura Hiroyuki
Published: July 2024

We report a case in which a 74-year-old man suffering from esophageal achalasia complicated with epiphrenic esophageal diverticulum was successfully treated with a simultaneous laparoscopic surgery. The gentleman was referred with symptoms suggestive of a passage disorder in the lower esophagus for the past 5 years. Esophagogastroduodenoscopy demonstrated an epiphrenic diverticulum at the left wall of the lower esophagus, and esophagography led to the suspicion of a combined esophageal achalasia. A simultaneous laparoscopic surgery with an abdominal approach was performed in which, following the opening of the esophageal hiatus, the diverticular wall was separated from the mediastinal organs and diverticulectomy was performed with linear staplers. After Heller’s myotomy, Dor’s fundoplication was subsequently performed in which both the incisional line of muscle layer and the suturing line of diverticulectomy were wrapped by the fornix of the stomach to make up for the wall strength and avoid the suture leakage. It was theoretically considered logical and effective to reinforce this vulnerable site with Dor’s fundoplication. He had an uneventful recovery and a rapid relief from symptoms following surgery.
Reduction of Methane Emissions from Natural Gas Integral Compressor Engines through Fuel Injection Control
Authors: Banji Titilope Ibukun , Arney Gregg , Patterson Mark , Olsen Daniel B.
Published: July 2024

Methane emissions from over 7000 large-bore natural gas engines used for gas compression in the United States result from combustion inefficiency and the escape of unburned methane through the crevices. Methane is a strong greenhouse gas with a warming potential 28 times that of carbon dioxide. The Inflation Reduction Act passed by the Biden administration in 2022 imposes a methane “waste” fee that accumulates yearly to invest in clean energy and climate action starting in 2024. This study aims to reduce the amount of methane emissions from large bore engines through fuel injection techniques, thereby advancing sustainable energy development. The strategies explored investigate fuel injection pressure and timing optimization, crankcase methane emissions quantification and mitigation, and ring-pack methane quantification. While varying injection pressures and injection timing on the engine, the performance and methane emission characteristics were measured. Also, a model of the engine was created for computational fluid dynamics (CFD) simulations using CONVERGE Studio v 3.0. Experimental results showed that methane emissions are minimized with late-cycle fuel injection at 500 psi and 100 degrees BTDC. Computational results showed that the ring pack contributes up to 34% of methane emissions in the large bore engine model.
Multi-Objective Optimization of Bifacial Photovoltaic Sunshade: Towards Better Optical, Electrical and Economical Performance
Authors: Li Chunying , Zhang Wankun , Liu Fang , Li Xiaoyu , Wang Jingwei , Li Cuimin
Published: July 2024

Bifacial photovoltaic sunshade (BiPVS) is an innovative building-integrated photovoltaic (BIPV) technology. Vertically mounted BiPVS is capable of converting part of the incident solar radiation into electricity, regulating the indoor heat gain from solar penetration and improving daylighting. An excellent BiPVS design should comprehensively consider its impact on building performance and economic viability. This study aims to address this issue by proposing a parametric design-based multi-objective optimization (MOO) framework to maximize indoor useful daylight illuminance, minimize air-conditioning energy consumption, and shorten the payback period by optimizing BiPVS design parameters. The framework utilizes the Ladybug, Honeybee, and Wallacei plugins on the Rhino-Grasshopper simulation platform. It validates the optimization potential of BiPVS in a typical office located in a hot summer and warm winter zone. The results indicate that BiPVS has significant energy-saving and daylighting potential. Compared to the baseline model without BiPVS, useful daylight illuminance is increased by 39.44%, air-conditioning energy consumption is reduced by 12.61%, and the economically satisfactory payback period is 4.80 years. This study provides a practical solution for the competing objectives of daylighting and energy saving in buildings with significant renewable energy utilization. The developed framework is highly efficient and versatile and can be applied to other BIPV designs, which benefits the realization of carbon-neutral goals in the building sector.