bluuebunny/crossref_metadata_2025 huggingface dataset:
The Area-law of Molecular Entropy: Moving Beyond Harmonic Approximation
Authors: Venkatraman Vishwesh , Roy Amitava , Ali Tibra
Published: April 2024

Inspired by black hole thermodynamics, the area law that entropy is proportional to horizon area has been proposed in quantum entanglement entropy and has largely maintained its validity. This article shows that the area law is also valid for the thermodynamic entropy of molecules. We showed that the gas-phase entropy of molecules obeys the area law with our proposed correction for the different curvatures of the molecular surface. The coefficient for the ultraviolet cutoff for the molecular entropy, calculated from our curated experimental data, is tantalizingly close to the value $\frac{1}{4}$ proposed by Hawking [Hawking, 1976]. The ability to estimate gas-phase entropy by the area law also allows us to calculate molecular entropy faster and more accurately than currently popular methods of estimating molecular entropy with harmonic oscillator approximation. The speed and accuracy of our method will open up new possibilities for the explicit inclusion of entropy in various computational biology methods.
Identification of COVID-19 Infection from Features Extraction of Exhaled Breath Using Signal Processing Methods
Authors: Malarvili M. B. , Ramanathan Santheraleka , Manikam Rishya , Ramli Ahmad Adib , Ruslay Rafi’Uddin Radzi , Kamarudin Anhar , Tarmizi Aina Amalina Ahmad
Published: April 2024

The goal of the exhaled breath waveform used in ventilation monitoring is to improve COVID-19 illness detection. Using exhaled breath patterns to differentiate between COVID and non-COVID healthy individuals, an algorithm for valid exhaled breath waveform segmentation and feature computation is created to identify the COVID-19 infection. A two-minute exhaled breath pattern was recorded using a device and a nasal cannula sampling tube, resulting in the collection of exhaled breath waveforms from each subject. The developed algorithm is utilized to evaluate the valid exhaled breath waveforms and compute the features classified to distinguish between individuals who contracted COVID-19 infection and this who are healthy. Slope e2, activity e2 and intersection angle of expiration and inspiration phase showed p-value of 0.000, denoting the strong significance difference between COVID-19 patients and non-COVID healthy individuals. The statistical analyses revealed p-values of 0.039, 0.008, and 0.024 for area e2, mobility of e2 and complexity e3, indicating its significance in differentiating COVID-19 patients with non-COVID healthy individuals. The slope, area, and intersection angle as significant features showed good predictive power for compliance with p-value analysis with area under the receiver operating characteristic curve with 0.667, 0.693, and 0.775. Slope of e2, area of e2, intersection angle of expiration and inspiration phases are identified as the promising features to be chosen in discriminating COVID and non-COVID individuals.
Trial registration: Clinical trial approval by Medical Research and Ethics Committee (MREC), 53 Malaysia, NMRR-21-763-59692. Registered 9th June 2021 and valid till 8th June 2023.
Seasonal biases in fluorescence estimated chlorophyll-a derived from biogeochemical profiling floats
Authors: Long Jacqueline
Published: April 2024

Marine phytoplankton biomass and chlorophyll-a concentration are often estimated from pigment fluorescence measurements, which have become routine despite known variability in the fluorescent response for a given amount of chlorophyll-a. Here, we present a near-global, monthly climatology of chlorophyll-a fluorescence measurements from profiling floats combined with ocean color satellite estimates of chlorophyll-a concentration to illuminate seasonal biases in the fluorescent response and expand upon previously observed regional patterns in this bias. Global biases span over an order of magnitude, are highest in iron-limited zones, and can vary seasonally by a factor of 10. An independent estimate of chlorophyll-a from light attenuation shows similar global patterns in the chlorophyll-fluorescence bias when compared to biases derived from satellite estimates. Without accounting for these biases, studies or models using fluorescence-estimated chlorophyll-a will inherit the seasonal and regional biases described here.
Induction of systemic resistance through calcium signaling in Arabidopsis exposed to air plasma-generated dinitrogen pentoxide
Authors: Sasaki Shota , Iwamoto Hiroto , Takashima Keisuke , Toyota Masatsugu , Higashitani Atsushi , Kaneko Toshiro
Published: April 2024

Plasma technology, which can instantaneously transform air molecules into reactive species stimulating plants, potentially contributes to the development of a sustainable agricultural system with high productivity and low environmental impact. In fact, plant immunity activation by exposure to a reactive gas mainly consisting of dinitrogen pentoxide (N2O5) was recently discovered, while physiological responses to N2O5 are rarely known. Here, we demonstrate early physiological responses to N2O5 in Arabidopsis. Exposure to N2O5 gas induced an increase in cytosolic Ca2+ concentration within seconds in directly exposed leaves, followed by systemic long-distance Ca2+-based signaling within tens of seconds. In addition, jasmonic acid (JA)-related gene expression was induced within 10 minutes, and a significant upregulation of the defense-related gene PDF1.2 was observed after 1 day of exposure to N2O5 gas. These systemic resistant responses to N2O5 were found unique among air-plasma-generated species such as ozone (O3) and nitric oxide (NO)/nitrogen dioxide (NO2). Our results provide new insights into understanding of plant physiological responses to air-derived reactive species, in addition to facilitating development of plasma applications in agriculture.
Ultrasensitive piezoelectric sensor based on two-dimensional Na2Cl crystals with periodic atom vacancies
Authors: Chen Liang , Wang Tao , Fan Yan , Jiang Jie , Zhang Yangyang , Huang Yingying , Zhu Liuyuan , Zhan Haifei , Zhang Chunli , Peng Bingquan , Gu Zhen , Pan Qiubo , Wu Junjie , Chen Junlang , Li Pei , Zhang Lei , Lü Chaofeng , Fang Haiping
Published: April 2024

Pursuing ultrasensitivity in pressure sensors that offer precise mechano-electric transduction of tiny mechanical stimuli under complex ambient conditions, is of great importance and has been a long-standing goal1-10. The introduction of microstructures at micro- and nano-scale, can effectively improve the sensitivity, detection limit, and pressure-response range due to their structural asymmetries and compressibility5,6,11-19. However, numerous atom vacancies anticipated in sensors that are expected to exhibit giant asymmetries may make it difficult to maintain stability under ambient conditions. Here, we report a piezoelectric sensor that exhibits supreme pressure-sensing performance, including a peak sensitivity up to 3.5×106 kPa−1 in the pressure range of 1-100 mPa and a detection limit of less than 1 mPa, superior to the current state-of-the-art pressure sensors. These properties are attributed to the high percentage of periodic atom vacancies in the two-dimensional Na2Cl crystals formed within multilayered graphene oxide membrane in the sensor, which provides giant polarization with high stability. The sensor can even clearly detect the airflow fluctuations surrounding a flapping butterfly, which have long been the elusive tiny signals mentioned in the famous “butterfly effect”. The finding represents a step towards next-generation pressure sensors for various precision applications.
SARS-CoV-2 infected human ACE2 transgenic pigs develop severe COVID-19-like pathology.
Authors: Grey Finn , Chau Long Fung , Lillico Simon , Opriessnig Tanja , Blake Rose , Tardy Luc , Lee Chen-Hsuin , Maxwell Scott , Warren Claire , Thornton Elisabeth , McLaughlin Catherine , McLachlan Gerry , Tait-Burkard Christine , Fletcher Sarah , Anderson Stephen , Brown Sharon , Gibbard Louise , Tzelos Thomas , MacMillan Dawn , Dorward David , Baillie J , Griffiths David
Published: April 2024

COVID-19 continues to cause significant morbidity and mortality, with emerging strains rapidly spreading despite substantial immunity through vaccination and previous exposure. Animal models that accurately reflect COVID-19 are vital for testing mechanisms of disease, enabling development of improved vaccines and therapeutics. We have developed human ACE2 transgenic pigs that are highly susceptible to SARS-CoV-2 and display clinical signs, disease progression, and lung inflammation that faithfully replicate severe COVID-19 in humans.
It is Not a Small World for Psychiatric Patients
Authors: Akin Ata , Yorgancigil Emre , Ozturk Ozan , Sutcubasi Bernis , Kirimli Ceyhun , Kirimli Elcim Elgun , Dumlu Seda , Yukselen Gulnaz , Erdogan Sinem
Published: April 2024

Individuals suffering from Obsessive Compulsive Disorder (OCD) and Schizophrenia (SCZ) frequently exhibit symptoms of cognitive disassociations, which are linked to poor functional integration among brain regions. The loss of functional integration can be assessed using graph metrics computed from functional connectivity matrices (FCMs) derived from neuroimaging data. A healthy brain at rest is known to exhibit small-world features with high clustering coefficients and shorter path lengths in contrast to random networks. The aim of this study was to compare the small-world properties of prefrontal cortical functional networks of healthy subjects with OCD and SCZ patient groups by use of hemodynamic data obtained with functional near infrared spectroscopy (fNIRS). 13 healthy subjects and 47 patients who were clinically diagnosed with either OCD (N=21) or SCZ (N=26) completed a Stroop test while their prefrontal cortex (PFC) hemodynamics were monitored with fNIRS. The Stroop test had a block design consisting of neutral, congruent and incongruent stimuli. For each subject and stimuli type, FCMs were derived separately which were then used to compute small world features that included i) Global Efficiency (GE), ii) Clustering Coefficient (CC), iii) Modularity (Q), and iv) small-world parameter (σ). Small-world features of patients exhibited random networks which were indicated by higher GE and lower CC values when compared to healthy controls, implying a higher neuronal operational cost.
Development of the Technical Assistance Engagement Scale: A Modified Delphi Study
Authors: Scott Victoria , Temple Jasmine , Jilani Zara
Published: April 2024

Background: Technical assistance (TA) is a tailored approach to capacity building that is commonly used to support implementation of evidence based interventions. Despite its widespread applications, measurement tools for assessing critical components of TA are scant. In particular, the field lacks a robust measure for examining relationship quality between TA providers and recipients. TA relationships are central to TA and significantly associated with program implementation outcomes. The current study seeks to address the gap in TA measurement tools by providing a scale for assessing TA relationships.
Methods: We utilized a modified Delphi approach involving two rounds of Delphi surveys and a panel discussion with TA experts to garner feedback and consensus on the domains and items that compose the TA Engagement Scale.
Results: TA experts represented various U.S. organizations and TA roles (e.g., provider, recipient, researcher) with 25 respondents in the first survey and 26 respondents in the second survey. The modified Delphi process resulted in a scale composed of six domains and 22 items relevant and important TA relationships between providers and recipients.
Conclusion: The TA Engagement Scale is a formative evaluation tool intended to offer TA providers the ability to identify strengths and areas for growth in the provider-recipient relationship and to communicate about ongoing needs. As a standard measurement tool, it lends a step toward more systematic collection of TA data, the ability to generate a more coherent body of TA evidence, and enables comparisons of TA relationships across settings.
Study on the Prevalence and Influencing Factors of Anemia among Three Ethnic Minorities in the Southwest Border Area of China
Authors: Wang Chenlei , Yin Rongrong , Zhao Jiang , Liu Zhitao
Published: April 2024

Anemia is one of the most common nutritional deficiencies in the world. At present, anemia is still one of the serious nutrition-related diseases in China. This study aimed to conduct an exploratory investigation of the prevalence and factors related to anemia among three ethnic minorities in the Southwest Border Area of China. Multi-stage stratified cluster sampling method was used to conduct field questionnaire and physical examination for resident of ethnic minorities aged 15 years or above. Anemia was defined as a hemoglobin concentration level less than 120 g/L in non-pregnant women and less than 130 g/L in men. Participants over 55 had a higher risk of anemia than those aged 17–34. More than 7 hours of outdoor activities during the daytime in the winter was associated with a reduced risk of anemia. Alcohol drinking and central obesity was associated with increased hemoglobin and red blood cells.
Missing Evidence: Tracking Academic Data Use around the World
Authors: Stacy Brian , Kitzmüller Lucas , Wang Xiaoyu , Mahler Daniel , Serajuddin Umar
Published: April 2024

Data-driven research is key to producing evidence-based public policies, yet little is known about where data-driven research is lacking and how it can be expanded. We propose a method for tracking academic data use by country of subject, applying natural language processing to open-access research papers. The model’s predictions produce country estimates of the number of articles using data that are highly correlated with a human-coded approach, with a correlation of 0.99. Analyzing more than 1 million academic articles, we find that high-income countries are the subject of nearly 50% of all papers, despite only making up around 17% of the world’s population. Finally, we classify countries by whether they could most benefit from increasing their supply of or demand for data, with the former applying to many poorer countries and the latter to many wealthier countries.
AlexCapsNet: an integrated architecture for image classification with noise and many categories
Authors: Bao Muyi , Jin Nanlin , Xu Ming
Published: April 2024

Capsule network (CapsNet) is a pioneering architecture that can encode the image properties into vectors rather than scalars, addressing the limitations of traditional Convolutional Neural Networks (CNNs). This process is achieved by dynamic routing algorithms to maintain the spatial hierarchies. However CapsNet may decreases its efficacy in complex datasets, such as CIFAR-10. To address this problem, we propose AlexCapsNet architecture, in which the classic classification model AlexNet is used as the feature extraction layer. Such a layer allows CapsNet to capture deeper and more semantic features. Comprehensive evaluation with five datasets shows that AlexCapsNet has achieved improved performance compared to the baseline and other variants of CapsNet. In addition, we also introduce the Shallow-AlexNet module, revealing that deeper feature extraction layers are suitable for datasets with fewer categories and shallower feature extraction layers are more effective for datasets with many categories, owing to inherent category differences. Moreover, our investigation into the reconstruction module shows that noise in the datasets helps degrade the performance of the reconstruction module.
Unveiling the Microscopic World of Enamel: A Groundbreaking Study on Dental Remineralization
Authors: Zecca Piero Antonio , Carganico Andrea , Presti Doriana Lo , Reguzzoni Marcella , Scurati Eleonora Ivonne , Caccia Margherita , Levrini Luca
Published: April 2024

AIM: This study explores dental enamel remineralization, employing Scanning Electron Microscopy (SEM) to unveil the microstructural changes induced by various dental care products. Focusing on Mentadent Professional Resilience, the research investigates its impact on enamel surfaces at a microscopic level.
MATERIALS AND METHODS: The experimental approach involved precise tooth sectioning to preserve enamel integrity, followed by dehydration and SEM preparation. SEM analysis was conducted at multiple magnifications, revealing significant enamel texture and structure post-treatment variations.
RESULTS: The findings demonstrate distinct differences in enamel surfaces, ranging from rough and rugged textures indicative of demineralization to smooth, intact surfaces suggesting effective remineralization. These observations provide crucial insights into the mechanisms of action of dental care products and their potential to promote enamel health.
CONCLUSIONS: This study contributes to a deeper understanding of enamel remineralization processes and underscores the importance of microscopic analysis in evaluating and developing oral care products. The implications of these findings are significant for both dental research and clinical practice, offering a new perspective on the selection and efficacy of dental care products in enamel protection and caries prevention.
CLINICAL RELEVANCE: The current investigations suggest that Mentadent Professional Resilience could be beneficial as a remineralizing agent.
PH-SIFT with PSO Algorithm: A Novel Approach to Detecting Forgery in High- Resolution Images
Authors: Mishra Manuj , Jain Neelesh Kumar , Kumar Ajay
Published: April 2024

The use of machine learning for forgery detection in image forgeries poses a significant danger to modern multimedia technologies. These forgery detectors appear promising; however they are known to be vulnerable to evasion attacks. A "forgery" is a malicious user established by an attacker that may change its appearance while spreading; this is known as polymorphism and metamorphosis. Common behavioral characteristics showing the source and intended use of multimedia devices are displayed by image forgeries. However, the majority of novel forgery detection variations frequently elude detection by traditional forgery detection methods. This paper proposes a new approach to improve the utility of an existing framework. We need to create a unique model, PH-SIFT using PSO Algorithm, in order to improve the overall forgery analysis because the current deep learning algorithm forgery detection and analysis. Applying the PH-SIFT utilizing PSO Algorithm technique, which also aims to improve its accuracy and other metrics, achieves this. This method can get around the complexity and challenges presented by different concerns related to forgery detection and analysis. Here, the datasets from forgery detection and analysis are used to train the proposed algorithm. Following training, the datasets are pre-processed by reducing training mistakes. The PSO Algorithm-built PH-SIFT then carries out the detection procedure to anticipate any forgery activity.
Symmetric perfect state transfer on bipartite graphs
Authors: Li Xi , Chen Xiao , Hu Shouwei , Liu Zhihao
Published: April 2024

Continuous-time quantum walks (CTQW) becoming more significant for quantum information and quantum computation. The perfect state transfer (PST) on graphs is a specific phenomena of CTQW which is widely used in quantum communication of small system, and be found critical for quantum algorithm design recently, such as quantum approximate optimization algorithms and quantum search. If a network $G$ contains $2N$ vertices, and PST occurs between $N$ pairs of vertices at the same time $T$, then we say $G$ admits symmetric PST (SPST). In this work, we will study the SPST on bipartite graphs via spectra. And then, we will present how to set couplings of special bipartite graphs such as cycles, grids and chains to admit SPST is given. For cycles with 6, 8, 10, 12 vertices, we give the analytical method to obtain the couplings to admit SPST. Analogously, the couplings for chains and grids to admit SPST are analytical obtained. We also present a typical approach by using the graph tensor product to construct new quantum networks that admit SPST, in which the new quantum networks are derived from special kinds of integral graphs, such as complete graphs, strongly regular graphs and distance regular graphs.
An easy to implement strategy for improving organic electrochemical transistor stability: Combining chemical doping with solvent degassing.
Authors: Paterson Alexandra , Le Vianna , Baustert Kyle N. Baustert Kyle N. , Brown Megan , Bombile Joel , Flagg Lucas , Thorley Karl , Kousseff Christina , Solomeshch Olga , McCulloch Iain , Tessler Nir , Risko Chad , Graham Kenneth
Published: April 2024

Although p-type organic mixed ionic electronic conductors (OMIECs) are susceptible to oxidation, it has not yet been considered as to whether oxygen could behave as an uncontrolled p-dopant. Here, oxygen dissolved in solvents is shown to be behave as a p-dopant, that fills traps to enable more effective electrochemical doping in OMIECs and organic electrochemical transistors (OECTs). Yet the presence of oxygen also jeopardizes OECT stability. A two-step strategy is introduced to solve this contradictory problem, where first the solvent is degassed, and second the OMIEC is doped in a controlled manner using a chemical p-dopant. This strategy has a remarkable impact on OECT stability in air and water, while simultaneously increasing on-off ratio, tuning the threshold voltage, and enhancing the transconductance, mobility and the µC* product. This simple solution-processing technique is easily implemented, low-cost, highly effective in air and water, and effective in materials systems with different polymers, solvent and dopants. Overall, the data herein suggests that combining chemical doping with solvent degassing could be a broadly applicable technique to improve essential criteria needed to realize organic bioelectronics and more complex OMIEC circuitry.
Synthesis and evaluation of acaricidal activity of zinc oxide nanoparticles against phytophagous and predatory mites in bell pepper cultivation
Authors: Al-Azzazy Mahmoud M , Alhewairini Saleh S , Gheni Sherif B. Abdel , Qureshi Muhammad Zahid
Published: April 2024

Bell Pepper plants are widely grown and utilized all over the world. A number of phytophagous mites are associated with this plant and the control over these pests has been a challenge to growers due to its development of resistance to synthetic chemicals and short reproduction cycle. The agriculture sector is currently embracing nanotechnology as a target-specific, relatively safe, and effective alternative to traditional pest management tools. The main goal of undertaking the current study was to evaluate the effectiveness of different doses (200, 400, 600, 1000, 1250 and 1500 ppm) of zinc oxide nanoparticles (ZnONPs) at all growth stages of the mites; Polyphagotarsonemus latus (Banks) (Acari: Tarsonemidae) and the two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae). Simultaneous impacts on predatory mites, Neoseiulus cucumeris (Oudemans) and Euseius scutalis (Athias-Henriot) (Acari: Phytoseiidae) was also observed. All trails were carried out under field and laboratory conditions. The obtained results have shown that an increase in zinc oxide nanoparticle concentrations was related to a higher mortality rate of both phytophagous mites. While negligible impact on N. cucumeris and E. scutalis was observed. zinc oxide nanoparticles demonstrated great efficacy in eliminating P. latus and T. urticae. The percentages of deaths were 25.59, 42.36, 56.43, 72.02, 85.47 and 97.07% for P. latus and 22.61, 39.79, 52.66, 69.35, 82.22 and 95.24% for T. urticae, while the mortality percentage was 1.78, 3.60, 4.44, 15.30, 16.67 and 19.59% for N. cucumeris and 3.68, 5.33, 7.21, 17.92 and 20.26% for E. scutalis three days after exposure to 200, 400, 600, 1000, 1250 and 1500 ppm of zinc oxide nanoparticles, respectively. Additionally, the findings showed that the use of zinc oxide nanoparticles reduced the percentage of egg hatching. The percentages of eggs that hatch into larvae were 79.33, 69.51, 62.66, 46.54, 43.62 and 39.08% for P. latus and 83.17, 71.60, 67.26, 48.94, 46.95 and 38.26 for T. urticae three days after exposure to 200, 400, 600, 1000, 1250 and 1500 ppm of zinc oxide nanoparticles respectively, compared with the control (well water). Lethal concentration; LC50 (µg/ml) at confidence level 95 (CL95) was found to be 556.4 and 611.8 for P. latus and T. urticae and 2304.6 and 2259.7 for N. cucumeris and E. scutalis. Similarly, LC95 (µg/ml) was found to be 1325.9 and 1404.9 for P. latus and T. urticae and 33671.2 and 3773.8 for N. cucumeris and E. scutalis. The investigation proved that zinc oxide nanoparticles are a useful tool for controlling P. latus and T. urticae.
Knowledge，attitudes and practices related to AIDS among transgender women in Chongqing，China: a cross-sectional study
Authors: Tan Yangxi , Yang Jiajie , Cui Yuting , Zhou Hailong , Zhao Jing , Ouyang Lin , Zhou Chao , Chen Fei
Published: April 2024

Background: Transgender women (MTF) are one of the key populations for HIV prevention and control and one of the high-risk groups for lack of health services. This study aimed to investigate the knowledge, attitudes and practices (KAP) about HIV and knowledge access and needs among transgender women in Chongqing, China.
Methods: A cross-sectional study was conducted from October 2022 to August 2023, in which 128 self-identified MTF were recruited in Chongqing, China, using snowball sampling to complete a KAP-related questionnaire via Questionnaire Star.
Results: For the 128 MTF effectively surveyed, the total knowledge of AIDS-related knowledge was 82.03%, with significant differences in age, education level, marital status, occupation and average monthly income (P<0.05); personal attitudes towards AIDS, with significant differences in place of domicile and education level (P<0.05), and subjective norms, with significant difference (P<0.05); there was no statistical difference between the groups of HIV-related practices. Corresponding values were assigned to knowledge, attitude and practice, and the total scores of the three aspects were 6.77±1.47 (95% CI: 3.89-9.65) (range: 0~ 8), 14.22±2.37 (95% CI: 9.57-18.87) (range: 0~ 18) and 6.66±1.79 (95% CI: 3.16-10.17) (range: 0~ 9), respectively. The main ways of acquiring HIV knowledge in MTF were "Internet/smartphone" (81.68%), "TV/radio" (49.62%), "education on HIV prevention topics in school" (48.09%); more likely to receive publicity activities "WeChat push" (58.02%), "peer education" (44.27%) and "mobile phone app management" (37.40%); and more likely to receive publicity activities "Internet/smartphone" (81.68%), "TV/radio" (49.62%) and "school education on AIDS prevention" (48.09%). "(37.40%); the points of knowledge about AIDS that need to be strengthened include "means of transmission" (71.76%) and "knowledge of voluntary counselling and testing" (67.94%), "Knowledge of the virus" (64.89%).
Conclusions: There is still room for improvement in the knowledge rate of AIDS among MTF in Chongqing, China, and there is a separation between knowledge and behaviour; attitudes towards AIDS are more positive, and the awareness of prevention is stronger; pay attention to the middle-aged, low-income and low educated groups in MTF, and further strengthen health education and publicity on AIDS from the perspective of knowledge acquisition ways and needs.
IoT-based Smart Drip Irrigation Scheduling and Wireless Monitoring of Microclimate in Sweet Corn Crop under Plastic Mulching
Authors: s Vinod Kumar , Singh C D , Rao K V Ramana , Rajwade Yogesh A , Kumar Mukesh , D. Jawaharlal , R Asha K
Published: April 2024

Precision irrigation with IoT-based decision-making technologies has proven effective in optimizing agricultural production irrigation. The Internet of Things (IoT) is crucial for monitoring the real-time data from sensors and automatically activating irrigation systems. This study evaluated the effectiveness of a drip irrigation system based on IoT and soil moisture sensors in a field experiment with sweet corn between 2020 and 2022. There were nine treatments with three replications: ETc-based drip irrigation (ETc 100%) and IoT-based drip irrigation scheduling with two soil moisture levels under three mulches: black plastic mulch, silver plastic mulch, and control (bare soil). IoT-based drip irrigation scheduling (100% FC) applied irrigation when soil moisture reached a lower threshold (≤ 33.1%) and ended when the field capacity was reached (≥ 43.5). With IoT-based drip irrigation scheduling (80% FC), irrigation was applied when the soil moisture content reached the threshold (≤ 33.1%) and ended when the field capacity reached 80% (≥ 34.8). Growth variables (root biomass, yield, corn length, cob weight, and water productivity) were compared for each irrigation method. Results showed that the ET-based irrigation method was easier to implement with less infrastructure and could result in lower yields than the IoT-based drip irrigation method with 100% FC. Grain and stalk yields increased by more than 12.05% and 14.97% for the IoT irrigation with 100% FC. It was found that IoT-based drip irrigation with 100% FC and 80% FC used 12.7% and 24.5% less irrigation water, respectively, and provided IoT-based drip irrigation with 100% FC, there was a 12.8% increase in marketable yield than ETc and IoT-based drip irrigation with 80% FC. The results show that the developed IoT system can potentially monitor the microclimate of plants in real time under different conditions of using plastic mulch. The IoT system is rugged and water-resistant, making it suitable for outdoor agriculture. Solar panels power the system, so there is no need for cabling and sensor nodes can be efficiently monitored. Research conducted on the IoT system shows that it can record and display environmental parameters to users via the cloud (ThingSpeak).
Sequencing and Characterization of NDM-1 and ORN-1 -Producing Multi-drug resistant Raoultella ornithinolytica Clinical Isolate from China
Authors: Yu Chunfang , Wang Zuhua , Wu Lingling , Liu Long , Sha Longhua , Yan Tingwei , Tuo Juan , Cao Guangxin , Wang Jinlei , Li Jinpeng , Wang Pei , Liu Xingyu , Zhou Zhipei , Liu Zhixin , Jin Zhixiong
Published: April 2024

Background Raoultella ornithinolytica poses an urgent threat in antimicrobial resistance threat due to its global emergence, associated high mortality rates, and persistent transmissions. Nevertheless, the resistance and infectivity mechanism, as well as genomic epidemiology, remain poorly understood at present. To elucidate the antibiotic resistance and infectivity mechanisms of R. ornithinolytica, whole genome sequencing was performed on a multi-drug-resistance strain, R. ornithinolytica B1645-1B, isolated from an inpatient.
Methods The genome sequence was completed using Illumina Hiseq 4000 and Pacbio RSII procedures. Phylogenetic genomic analysis, combined with a geographical region, isolation source, and host information. The conjugation transfer experiment were performed using the mating-out assay in the intestine of mice.
Results The isolate B1645-1B was resistant to five major classes of antibacterial agents including β-lactams, aminoglycosides, chloramphenicols, sulfonamides, and quinolones, but sensitive to tetracyclines. A close phylogenetic relationship was identified between B1645-1B, isolated from blood, and R. ornithinolytica NCTC9164, isolated from pus of the nose, in United Kingdom. A chromosome, designated as chromosome 01, was identified. The annotated chromosomal genome contained 127 genes that were potentially involved in virulence, disease and defense. The isolate B1645-1B contained chromosome-encoded β-lactamase blaORN-1, and plasmid-encoded metallo-β-lactamase blaNDM-1, respectively. A resistance region, designated B1645-1B-RR, carrying the β-lactamase blaORN-1 gene on the chromosome, was identified. The prophage analysis revealed that chromosome 01 contained three intact prophages. The occurrence of the blaORN-1 gene might transfer from R. ornithinolytica B1645-1B to Escherichia coli B1645-1B1 and Klebsiella pneumoniae B1645-1B11 in mice.
Conclusions The genomic analysis of R. ornithinolytica B1645-1B partially elucidated its antibiotic resistance mechanisms and virulence factors. Patients at high risk for drug-resistant R. ornithinolytica might require novel therapeutic strategies.
FLAP: A Semi-Supervised Few-Shot Learning Algorithm via Pseudo-Labeling
Authors: Yan Xin , Ma Zhiqiang , Liang Xijun , Chen Yuelin , Jian Ling , Song Yunquan
Published: April 2024

Few-shot learning addresses the challenge of training models with limited samples, striving to achieve robust classification performance with only a few examples, particularly for novel objects. One challenging aspect of few-shot learning is the cross-domain learning scenario, characterized by significant differences in data distribution between the target and source domains. To bridge this gap and improve domain adaptation, we introduce unlabeled samples from new categories within the target domain during training. Our proposed semi-supervised few-shot classification algorithm, FLAP, employs clustering methods to predict labels for unlabeled samples, enabling it to adapt to new unlabeled categories. We have also integrated a distance-based loss to consider clustering characteristics during the training of feature encoders and classifiers. This approach, combined with the symmetric cross-entropy loss, ensures robustness against incorrect labels introduced during pseudo-labeling. Experimental studies validate the effectiveness of our method, demonstrating significant accuracy improvements across various cross-domain and domain-constrained few-shot learning tasks.
Robust Planning of Irrigation Considering Water Consumption and Revenue
Authors: Turgut Ozgu
Published: April 2024

Water scarcity is a problem for many regions which requires immediate action and solutions cannot be postponed for a long time. It is known that farming consumes a significant portion of usable water. In this study, a decision support model of bi-objective stochastic linear formulation is proposed. The model is generating annual planting plans together with water consumption projections for each farmer in the region while taking revenue of the overall harvest into account. The structure of the proposed model maintains robustness against the volatilities in precipitation, yield, and market price. The inherent trade-off between water consumption and revenue lends itself to multi-objective planning. This is a perspective especially useful for regional administrations to plan next year's crop pattern together with agricultural incomes and irrigation expenses. Furthermore, it is also shown that how the model can be used to investigate the potential of rainwater harvesting or switching to water-efficient irrigation methodologies. The decision support model is especially unique in the sense that it can generate a set of Pareto optimum solutions as opposed to a single objective counterpart. This property is helpful in terms of not only providing a broader perspective to evaluate and project the possibilities but also increasing the applicability of the results by providing flexible design framework.
Walter Fischer : Auswahlbibliographie
Authors: Kelletat Andreas F.
Published: April 2024

In seiner 1986 veröffentlichten Autobiographie erwähnt Fischer, dass er aus dem Russischen Gedichte übersetzt habe. Nachweisen ließen sich die in "Sinn und Form" erschienenen Texte. Seine im "Wiener Tagebuch" und der "Volksstimme" veröffentlichten Nachdichtungen konnten bisher nicht ermittelt werden.
Retrospektive Analyse der Transplantat-Nephrektomie am Universitätsklinikum Frankfurt
Authors:   , Lammers Ingrid
Published: April 2024

Vergleichsstudie zu Operationszeitpunkt und -technik der Transplantat-Nephrektomien am Universitätsklinikum Frankfurt am Main als monozentrische Studie.
Måleegenskaper ved den norske versjonen av KATES Omsorgsgiver: Kartlegging av traumatiske erfaringer og posttraumatiske symptomer (KATES Omsorgsgiver)
Authors: Borren Ingrid , Bania Elisabeth Valmyr
Published: April 2024

Beskrivelse: Kartlegging av traumeerfaringer og symptomer (KATES Omsorgsgiver) er et screeninginstrument som kan gi foreløpig prognostisk informasjon om mulig posttraumatisk stress hos barn og unge i alderen 3–17 år. KATES Omsorgsgiver kommer i to alderstilpassede versjoner med tilsvarende oppbygning for omsorgsgivere til hhv. barn 3–6 år og barn og unge 7–17 år. KATES består av to deler: Traumatiske hendelser kartlegges i del 1, og symptomer på posttraumatisk stress hos barna måles i del 2. De fire symptomkategoriene i del 2 matcher de diagnostiske endringene som ble gjort i traumediagnosen i DSM-5. Sachser med flere (2017) utviklet og validerte KATES Omsorgsgiver, og forskere fra Nasjonalt Kunnskapssenter om Vold og Traumatisk Stress (NKVTS) var involvert i dette arbeidet og ansvarlige for den norske oversettelsen. Litteratursøk: Litteratursøket resulterte i én inkludert artikkel som omfattet et norsk utvalg med relevant psykometrisk informasjon. Psykometri: Tilstrekkelig/god indre konsistens ble funnet for alle fire subskalaer. Faktorstrukturen ble funnet å være i henhold til DSM-5s firefaktorteori for posttraumatisk stresslidelse (PTSD) basert på konfirmerende faktoranalyse på et blandet utvalg av foreldre/omsorgsgivere fra Norge, USA og Tyskland. Resultatene indikerer også støtte for konvergent validitet og for konstruktvaliditet for KATES Omsorgsgiver for barn/unge mellom 7 og 17 år. Dette ble ikke testet for foreldre/omsorgsgivere til barn i aldersgruppen 3–6 år i det norske utvalget. Det foreligger ingen test–retest skår, heller ikke mål for endringssensitivitet eller norske normdata. Konklusjon: På grunn av utilstrekkelig dokumentasjonsgrunnlag er det ikke mulig å trekke sikre konklusjoner om måleegenskapene til KATES Omsorgsgiver til barn/ungdom i alderen 7–17 år. Flere studier på skandinaviske utvalg trengs, særlig test–retest resultater og normdata samt dokumentasjon for foreldreversjonen av skalaen for 3–6-åringer. Samlet sett tilsier dette at kartleggingsverktøyet må brukes med forsiktighet i Norge.
Conhecimentos matemáticos para o ensino: um olhar para o conceito de função na perspectiva docente
Authors: Cardoso Mikaelle Barboza , Barreto Marcilia Chagas , Pinheiro Joserlene Lima
Published: April 2024

O presente estudo tem como objetivo analisar os conhecimentos revelados e reelaborados por professores de matemática, acerca do trabalho com o conceito de função. Estes conhecimentos foram trabalhados durante entrevista reflexiva com três professores de Matemática. De natureza qualitativa e com características de designer de Estudo de Caso, utilizou-se como metodologia de análise de dados os Eventos Críticos. Concluiu-se que os docentes demonstraram domínio interconectado dos conhecimentos essenciais para ensinar o conceito de função. Reconheceram a complexidade intrínseca do tema e sua relação com outros conceitos matemáticos e disciplinas. Destacaram a importância do planejamento pedagógico adaptativo, considerando as necessidades dos estudantes, e da integração com os documentos curriculares oficiais para aprimorar o ensino de Matemática. Entretanto, ainda foi possível perceber lacunas no que se refere ao reconhecimento da representação em Língua Materna como parte integrante dos processos de ensino e aprendizagem matemática, sendo necessário um maior desenvolvimento de estratégias que incorporem efetivamente esta representação como meio facilitador para a compreensão dos conceitos matemáticos.
Palavras-chave: Professor de Matemática; Conhecimento docente; Entrevista reflexiva; Ensino; Função.
Withdrawn: Evaluation of prospective surface water potential zones and their suitability for drinking purposes in Mahanadi River Basin, Odisha (India)
Authors: Das Abhijeet
Published: April 2024

AQUA — Water Infrastructure, Ecosystems and Society issues a formal withdrawal in relation to the above article by Abhijeet Das. This decision has been taken as the authors failed to address satisfactorily concerns over the originality of the research.
The hydraulic characteristics of a subsurface flow stone biofilter for treating polluted runoff from an informal settlement
Authors: Maraj Kalpana , Winter Kevin , Harrison Susan T. L.
Published: April 2024

Polluted runoff from informal settlements in developing countries poses a growing challenge due to the elevated and variable nature of contaminants, particularly nutrients and pathogens, introduced to the environment. Cost-effective and scalable treatment systems with the ability to reduce nutrient and other pollutant concentrations in contaminated runoff are desirable. Biofilters are passive water treatment systems that have the potential to achieve this. The Franschhoek Water Hub, a research site for nature-based solutions, features six large biofiltration cells designed to remediate runoff from an informal settlement. Due to their large size, understanding hydraulic behaviour and validating the design proves challenging. To address this, a scaled-down version of the Water Hub's biofilters was constructed to inform design criteria for purpose-built filters. The pilot-scale subsurface flow biofilter, filled with 8–11 mm aggregate stone, had an available volume of 225 L. Pulse tracer studies conducted at various flow rates demonstrated that the system approximated plug flow behaviour. Lower flow rates resulted in deeper tracer infiltration, which is crucial for maximising the distribution of nutrients within the filter bed. This research contributes to the effective design and operation of biofiltration systems, which hold promise for addressing surface water contamination issues in resource-constrained regions.
Current trends and directions in teaching English as a foreign language online
Authors: Hurskaya Volha Andreevna
Published: April 2024

In today's fast-paced and globalized world, communicating effectively in English has become essential for individuals and businesses. However, learning a new language can be challenging for non-native speakers. But with the development of Internet technologies, learning English has become more accessible and conven-ient. Recent years have seen the potential to revolutionize the education system by introducing new teaching, learning and collaboration methods. The COVID-19 pandemic, which began in 2020, has accelerated the introduction of the online format in teaching English as a foreign language, which has become an important aspect of providing methodological support to students and teachers for a more effective and efficient learning process.
The study's purpose is to, through theoretical analysis, determine current trends and directions in teaching English as a foreign language online.
The methodology is based on analyzing the online platforms «Universari-um» and «Miro.” As a result of the study, data was obtained that with the help of these innovative technologies, teaching English as a foreign language in an online format is facilitated.
The study's author concluded that distance learning is the most current trend in modern education. Distance learning technologies such as the Universarium platform and the Miro virtual board are among the effective methods for teaching English as a foreign language. The effectiveness of learning on the Universarium platform is ensured by the student communicating with the teacher, both orally and in writing. All homework is checked. After completing each block, the stu-dent is tested. The virtual whiteboard «Miro» is an integrated digital tool that al-lows teachers and students to work together.
Checklist as an effective way to increase cognitive activity in mathematics lessons.
Authors: Sycheva Oksana Ivanovna
Published: April 2024

The checklist is designed to simplify the process of work and serves as a reminder, motivator, tool for achieving a result. It is a kind of list with which a large task can be divided into separate sub-paragraphs and their implementation can be controlled.
Based on the above conditions, I developed a checklist that is issued to students before starting to study a topic or section.
Design of PI3K-mTOR Dual Inhibitors for Ovarian Cancer: Are we on the Right Track?
Authors: K. Mangala Shenoy , Rathi Ekta , Udupa Karthik S. , Prasada K. Shama , Pai K. Sreedhara Ranganath , Kini Suvarna Ganesh
Published: April 2024

Ovarian cancer is one of the most familiar kinds of gynecological cancer seen
in women. Though it is not as familiar as breast cancer, the survival rate for ovarian cancer
is very low when compared with breast cancer. Even after being one among the familiar
types, to date, there are no proper treatments available for ovarian cancer. All the
treatments that are present currently show a high rate of recurrence after the treatment.
Therefore, treating this silent killer from the roots is the need of the hour. PI3K/AKT/m-TOR pathway is one of the pathways that get altered during ovarian cancer. Studies are
already going on for the inhibition of PI3K and mTOR separately. Efforts have been
made to inhibit either PI3K or mTOR separately earlier. However, due to its side effects
and resistance to the treatments available, current studies are based on the inhibition of
PI3K and mTOR together. Inhibition of PI3K and mTOR simultaneously reduces the
chances of negative feedback, thus decreasing the toxicity. This review contains the evolution
of PI3K and mTOR drugs that are approved by the FDA and are in the trials for
different cancer types, including ovarian cancer. In this article, how a molecular targeted
therapy can be made successful and free from toxicity for treating ovarian cancer is discussed.
Therefore, this review paves the way for finding an effective scaffold rather than
the clinical part. The scaffold thus selected can be further modified and synthesized in
the future as dual PI3K/mTOR inhibitors specifically for OC.
Novel Natural Inhibitors for Glioblastoma by Targeting Epidermal Growth Factor Receptor and Phosphoinositide 3-kinase
Authors: Ullah Atta , Ullah Saeed , Waqas Muhammad , Khan Majid , Rehman Najeeb Ur , Khalid Asaad , Jan Afnan , Aziz Shahkaar , Naeem Muhammad , Halim Sobia Ahsan , Khan Ajmal , Al-Harrasi Ahmed
Published: April 2024

Background/Aim:

Glioblastoma is an extensively malignant neoplasm of the
brain that predominantly impacts the human population. To address the challenge of
glioblastoma, herein, we have searched for new drug-like candidates by extensive computational
and biochemical investigations.

Methods:

Approximately 950 compounds were virtually screened against the two most
promising targets of glioblastoma, i.e., epidermal growth factor receptor (EGFR) and
phosphoinositide 3-kinase (PI3K). Based on highly negative docking scores, excellent
binding capabilities and good pharmacokinetic properties, eight and seven compounds
were selected for EGFR and PI3K, respectively.

Results:

Among those hits, four natural products (SBEH-40, QUER, QTME-12, and
HCFR) exerted dual inhibitory effects on EGFR and PI3K in our in-silico analysis;
therefore, their capacity to suppress the cell proliferation was assessed in U87 cell line
(type of glioma cell line). The compounds SBEH-40, QUER, and QTME-12 exhibited
significant anti-proliferative capability with IC50 values of 11.97 ± 0.73 μM, 28.27 ±
1.52 μM, and 22.93 ± 1.63 μM respectively, while HCFR displayed weak inhibitory potency
(IC50 = 74.97 ± 2.30 μM).

Conclusion:

This study has identified novel natural products that inhibit the progression
of glioblastoma; however, further examinations of these molecules are required in animal
and tissue models to better understand their downstream targeting mechanisms.