bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Polymannuronic Acid on the Intestinal Microbiota in Mice after Long-Term Intragastric Administration
Authors: Zhang E , Wei Qiang , Li Xia , Song Shuliang
Published: March 2024

Polymannuronic acid (PM) is an alginate oligosaccharide derived from brown algae with a characterized structure and excellent biological activities. Herein, mice were given different doses of PM through 30-day-long-term intragastric administration, and the contents of the jejunum, ileum, and colon were analyzed by 16S rRNA gene sequencing technology for microbial diversity, and relevant experiments were verified according to the analysis results so as to comprehensively evaluate the effects of PM on the intestinal flora. The PM (400 mg/kg and 100 mg/kg) could regulate the microflora balance at the phylum level and increase the microflora richness in the jejunum, ileum, and colon of the mice. The PM could induce more strains that are negatively correlated with Escherichia, thereby reducing the relative abundance of Escherichia. Analysis of bacterial function showed that high and low doses of PM could promote lipid metabolism in the bacterial communities. Moreover, the PM could reduce serum total cholesterol and cholesterol ester levels in a concentration-dependent manner. High-dose PM could lead to colonic intestinal inflammation by increasing the relative abundance of multiple bacterial groups in the jejunum, ileum, and colon. Moreover, high-dose PM could increase lipopolysaccharide-binding protein and interleukin-1β levels. Therefore, the dose of PM plays an important role in its efficacy, and its biological activity is dosedifferent.
Sepsis-Associated Acute Kidney Injury: Where Are We Now?
Authors: Kounatidis Dimitris , Vallianou Natalia G. , Psallida Sotiria , Panagopoulos Fotis , Margellou Evangelia , Tsilingiris Dimitrios , Karampela Irene , Stratigou Theodora , Dalamaga Maria
Published: March 2024

Worldwide, sepsis is a well-recognized cause of death. Acute kidney injury (AKI) may be related to sepsis in up to 70% of AKI cases. Sepsis-associated AKI (SA-AKI) is defined as the presence of AKI according to the Kidney Disease: Improving Global Outcomes criteria in the context of sepsis. SA-AKI is categorized into early, which presents during the first 48 h of sepsis, and late, presenting between 48 h and 7 days of sepsis. SA-AKI is associated with a worse prognosis among patients with sepsis. However, there are different SA-AKI phenotypes as well as different pathophysiological pathways of SA-AKI. The aim of this review is to provide an updated synopsis of the pathogenetic mechanisms underlying the development of SA-AKI as well as to analyze its different phenotypes and prognosis. In addition, potential novel diagnostic and prognostic biomarkers as well as therapeutic approaches are discussed. A plethora of mechanisms are implicated in the pathogenesis of SA-AKI, including inflammation and metabolic reprogramming during sepsis; various types of cell death such as apoptosis, necroptosis, pyroptosis and ferroptosis; autophagy and efferocytosis; and hemodynamic changes (macrovascular and microvascular dysfunction). Apart from urine output and serum creatinine levels, which have been incorporated in the definition of AKI, several serum and urinary diagnostic and prognostic biomarkers have also been developed, comprising, among others, interleukins 6, 8 and 18, osteoprotegerin, galectin-3, presepsin, cystatin C, NGAL, proenkephalin A, CCL-14, TIMP-2 and L-FABP as well as biomarkers stemming from multi-omics technologies and machine learning algorithms. Interestingly, the presence of long non-coding RNAs (lncRNAs) as well as microRNAs (miRNAs), such as PlncRNA-1, miR-22-3p, miR-526b, LncRNA NKILA, miR-140-5p and miR-214, which are implicated in the pathogenesis of SA-AKI, may also serve as potential therapeutic targets. The combination of omics technologies represents an innovative holistic approach toward providing a more integrated view of the molecular and physiological events underlying SA-AKI as well as for deciphering unique and specific phenotypes. Although more evidence is still necessary, it is expected that the incorporation of integrative omics may be useful not only for the early diagnosis and risk prognosis of SA-AKI, but also for the development of potential therapeutic targets that could revolutionize the management of SA-AKI in a personalized manner.
Factors Associated with Daily Fruit and Vegetable Intakes among Children Aged 1–5 Years in the United States
Authors: Noiman Adi , Lee Seung , Marks Kristin , Grap Mary , Dooyema Carrie , Hamner Heather
Published: March 2024

To describe child, caregiver, and household characteristics associated with fruit and vegetable intakes among US children aged 1–5 years, we examined fruit and vegetable intakes (less than daily vs. daily) using data from the 2021 National Survey of Children’s Health among children aged 1–5 years. Multiple logistic regression provided adjusted odds ratios for factors associated with (1) daily fruit and (2) daily vegetable intakes. Among children aged 1–5 years, 68% (n = 11,124) consumed fruit daily, and 51% (n = 8292) consumed vegetables daily. Both daily fruit and daily vegetable intake were associated with child age, child race and ethnicity, and frequency of family meals. For example, children who ate a family meal 4–6 days/week (aOR 0.69; 95% CI 0.57, 0.83) or 0–3 days/week (aOR 0.57; 95% CI 0.46, 0.72) were less likely to consume fruit daily compared to children who had a family meal every day. Participation in food assistance programs, food insufficiency, and household income were not significantly associated with odds of daily fruit or daily vegetable intake in the adjusted models. Several factors were associated with daily fruit and vegetable intake among children aged 1–5. Strategies aimed at increasing fruit and vegetable consumption in early childhood may consider these child, caregiver, and household characteristics. Pediatric healthcare providers, early childhood education centers, and families of young children may be important partners in this work.
Shorter and Longer Antibiotic Durations for Respiratory Infections: To Fight Antimicrobial Resistance—A Retrospective Cross-Sectional Study in a Secondary Care Setting in the UK
Authors: Abdelsalam Elshenawy Rasha , Umaru Nkiruka , Aslanpour Zoe
Published: March 2024

As antimicrobial resistance (AMR) escalates globally, examining antibiotic treatment durations for respiratory infections becomes increasingly pertinent, especially in the context of the COVID-19 pandemic. In a UK secondary care setting, this retrospective study was carried out to assess the appropriateness of antibiotic treatment durations—shorter (≤5 days) versus longer (6–7 days and >8 days)—for respiratory tract infections (RTIs) in 640 adults across 2019 and 2020, in accordance with local antimicrobial guidelines. The analysis employed these guidelines and clinical evidence to examine the effectiveness and suitability of antibiotic prescribing practices. This study considered the ‘Shorter Is Better’ approach, noting an increased rate of patient discharges associated with shorter antibiotic regimens (≤5 days). It further demonstrates that shorter treatments are as effective as longer ones for conditions such as COPD exacerbation, COVID-19 pneumonia, and hospital-acquired pneumonia (HAP), except in cases of community-acquired pneumonia (CAP) and unspecified diagnoses. Nevertheless, this study raises concerns over an observed increase in mortality risk with shorter treatment durations. Although these mortality differences were not statistically significant and might have been influenced by the COVID-19 pandemic, the need for extended research with a larger sample size is highlighted to confirm these findings. This study also emphasises the critical need for accurate and specific diagnoses and considering risk assessments at admission, advocating for tailored, evidence-based antibiotic prescribing to ensure patient safety. It contributes to antimicrobial stewardship efforts by reinforcing the importance of adapting antibiotic use to current healthcare challenges and promoting a global commitment to fight antimicrobial resistance. This approach is crucial for enhancing patient outcomes and saving lives on a global scale.
A Cross-Sectional Study of How Harm Avoidance, Incompleteness and Intolerance of Uncertainty Contribute to Obsessive–Compulsive Disorder in University Students
Authors: Nisyraiou Anna , Simou Meropi , Simos Gregoris
Published: March 2024

Research suggests that certain cognitive factors increase the likelihood of developing and maintaining obsessive–compulsive disorder (OCD). Such factors that are often associated with OCD are harm avoidance (HA), incompleteness (INC), and intolerance of uncertainty (IU). The present study aimed to examine the associations of intolerance of uncertainty, incompleteness, and harm avoidance with dimensions of obsessive–compulsive symptoms. Participants were 1128 university students (Mage = 19.42 St.d. = 2.02). Results showed that all subscales of the OCI-R correlated significantly with HA, INC, and IU, confirming the findings of previous studies. HA and INC appear to predict OC symptoms in a significant way. IU appears to correlate and improve the models, although to a lesser degree. The present findings contribute to our better understanding of the relationship between OCD symptoms and underlying cognitive variables and the nature of OCD heterogeneity.
Drought Dynamics in the Nile River Basin: Meteorological, Agricultural, and Groundwater Drought Propagation
Authors: Nigatu Zemede M. , You Wei , Melesse Assefa M.
Published: March 2024

The Nile River Basin (NRB) has experienced a notable rise in drought episodes in recent decades. The propagation of meteorological, agricultural, and groundwater drought dynamics in the NRB was investigated in this study. The following drought indices examined the correlation and propagation among meteorological, agricultural, and groundwater droughts. These are the standardized precipitation evapotranspiration index (SPEI), soil moisture index, Gravity Recovery and Climate Experiment, and GRACE Follow-On (GRACE/GRACE-FO)-derived groundwater drought index (GGDI). These droughts were comprehensively evaluated in the NRB from 2003 to 2022. The cross-wavelet transform approach highlighted the links between droughts. The following are the key findings: (1) In the NRB, the cross-wavelet energy spectrum of wavelet coherence can indicate the internal connection between meteorological versus (vs.) agricultural and agricultural versus (vs.) groundwater drought. The time scale with the most significant correlation coefficient is the drought propagation time. (2) The El Niño–Southern Oscillation (ENSO) correlated with agricultural and groundwater drought much more than the Indian Ocean Dipole (IOD), demonstrating that ENSO has an important impact on drought advancement. (3) The R2 values were 0.68 for GGDI vs. standardized soil moisture index (SSI), 0.71 for Blue Nile Region (BNR) GGDI vs. SSI, and 0.55 for SSI vs. Standardized Precipitation Evapotranspiration Index (SPEI). Similarly, in the Lake Victoria Region (LVR), GGDI vs. SSI was 0.51 and SSI vs. SPEI was 0.55, but in the Bahr-el-Ghazal Region (BER), GGDI vs. SSI was 0.61 and SSI vs. SPEI was 0.27 during the whole research period with varied lag durations ranging from 1 to 6 months. Thus, the propagation of drought (i.e., meteorological, agricultural, and groundwater drought) dynamics has the potential to reshape our understanding of drought evolution, which could lead to early drought forecasting across the NRB and similar climatic regions.
Improving Seismic Fault Recognition with Self-Supervised Pre-Training: A Study of 3D Transformer-Based with Multi-Scale Decoding and Fusion
Authors: Zhang Zeren , Chen Ran , Ma Jinwen
Published: March 2024

Seismic fault interpretation holds great significance in the fields of geophysics and geology. However, conventional methods of seismic fault recognition encounter various issues. For example, models trained on synthetic data often exhibit inadequate generalization when applied to field seismic data, and supervised learning is heavily dependent on the quantity and quality of annotated data, being susceptible to the subjectivity of interpreters. To address these challenges, we propose applying self-supervised pre-training methods to seismic fault recognition, exploring the transfer of 3D Transformer-based backbone networks and different pre-training methods on fault recognition tasks, thereby enabling the model to learn more powerful feature representations from extensive unlabeled datasets. Additionally, we propose an innovative pre-training strategy for the entire segmentation network based on the characteristics of seismic data and introduce a multi-scale decoding and fusion module that significantly improves recognition accuracy. Specifically, during the pre-training stage, we compare various self-supervision methods, like MAE, SimMIM, SimCLR, and a joint self-supervised learning approach. We adopt multi-scale decoding step-by-step fitting expansion targets during the fine-tuning stage. Ultimately merging features to refine fault edges, the model displays superior adaptability when handling narrow, elongated, and unevenly distributed fault annotations. Experiments demonstrate that our proposed method achieves state-of-the-art performance on Thebe, the currently largest publicly annotated dataset in this field.
Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS
Authors: Ryan Robert E. , Pagnutti Mary , Ryan Hannah , Burch Kara , Manriquez Kimberly
Published: March 2024

The satellite imagery of nighttime lights (NTLs) has been studied to understand human activities, economic development, and more recently, the ecological impact of brighter night skies. The Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) offers perhaps the most advanced nighttime imaging capabilities to date, but its large pixel size and single band capture large-scale changes in NTL while missing granular but important details, such as lighting type and brightness. To better understand individual NTL sources in a region, the spectra of nighttime lights captured by the DLR Earth Sensing Imaging Spectrometer (DESIS) were extracted and compared against near-coincident VIIRS DNB imagery. The analysis shows that DESIS’s finer spatial and spectral resolutions can detect individual NTL locations and types beyond what is possible with the DNB. Extracted night light spectra, validated against ground truth measurements, demonstrate DESIS’s ability to accurately detect and identify narrow-band atomic emission lines that characterize the spectra of high-intensity discharge (HID) light sources and the broader spectral features associated with different light-emitting diode (LED) lights. These results suggest the possible application of using hyperspectral data from moderate-resolution sensors to identify lamp construction details, such as illumination source type and light quality in low-light contexts. NTL data from DESIS and other hyperspectral sensors may improve the scientific understanding of light pollution, lighting quality, and energy efficiency by identifying, evaluating, and mapping individual and small groups of light sources.
Windshear Detection in Rain Using a 30 km Radius Coherent Doppler Wind Lidar at Mega Airport in Plateau
Authors: Xia Haiyun , Chen Yixiang , Yuan Jinlong , Su Lian , Yuan Zhu , Huang Shengjun , Zhao Dexian
Published: March 2024

Convective weather is often accompanied by precipitation and windshear, seriously endangering the safety of aircraft during takeoff and landing. However, under rainfall conditions, conventional wind lidars have a limited detection range due to significant signal attenuation. To solve this problem, a 200 mm temperature-controlled telescope coated with a hydrophobic film is applied in the coherent Doppler wind lidar system to improve the detection capability in rain. The maximum detection range of the lidar is extended to 30 km and demonstrated at Kunming Changshui International Airport at an altitude of 2102 m. Firstly, the detection accuracy and maximum detection range of the lidar are verified. Through the analysis of the horizontal wind field under two typical convective weather conditions, it is found that convective weather often accompanies low-level convergence and divergence structures, leading to headwind shear and crosswind shear on the airport runway. From the vertical profile, it is shown that the triggering of convective weather is accompanied by low-level southwest winds and high-altitude northeastern winds. According to the statistics of wind speed and direction on clear and rainy days over 9 months, rainy days are usually caused by the invasion of cold air from Northeast China, resulting in airport windshear. In summary, the enhanced lidar can effectively identify and analyze windshear during rainy days, which is very useful for aviation safety, especially for takeoff and landing in all weather conditions.
Environmentally Induced Snow Transmittance Variations in the Photosynthetic Spectral Domain: Photobiological Implications for Subnivean Vegetation under Climate Warming Conditions
Authors: Baranoski Gladimir V. G. , Varsa Petri M.
Published: March 2024

Variations in the productivity of subnivean vegetation can substantially affect the ecology of regions more susceptible to increasing warming levels and lead to significant feedback effects on the global climate. Due to its importance, this topic is at the center of a broad scope of interdisciplinary studies supported by field and remote sensing observations. However, the current knowledge about environmental factors affecting the penetration of photosynthetically active radiation (PAR) through snow is still constrained by the paucity of transmittance data. In this work, we aim to further the understanding about these interconnected processes. We conduct a systematic investigation about the effects of independent and combined changes in key nivological characteristics, namely thickness, saturation, density and grain size, on snow transmittance in the photosynthetic spectral domain. Our investigation is carried out through controlled in silico (computational) experiments supported by measured radiometric data. Its outcomes unveil fundamental quantitative and qualitative trends related to the role played by these nivological characteristics on the spectral quality of transmitted PAR, which is quantified in terms of red to blue (R/B), red to far-red (R/FR) and blue to far-red (B/FR) ratios. These trends include increases in the R/B ratio as well as decreases in the R/FR and B/FR ratios following thickness reductions or grain size increases, with opposite variations in these ratios being observed for saturation or density increases. Accordingly, the pairing of our findings with in situ and remotely collected information contributes to cement the scientific foundation required for the effective assessment of cause-effect loops linking accentuated vegetation greening to accelerated rates of snow cover recession.
Surface Heat Monitoring with High-Resolution UAV Thermal Imaging: Assessing Accuracy and Applications in Urban Environments
Authors: Henn Katrina Ariel , Peduzzi Alicia
Published: March 2024

The urban heat island (UHI) effect, where urban areas experience higher temperatures than surrounding rural regions, necessitates effective monitoring to estimate and address its diverse impacts. Many existing studies on urban heat dynamics rely on satellite data with coarse resolutions, posing challenges in analyzing heterogeneous urban surfaces. Unmanned aerial vehicles (UAVs) offer a solution by providing thermal imagery at a resolution finer than 1 m. Despite UAV thermal imaging being extensively explored in agriculture, its application in urban environments, specifically for surface temperatures, remains underexplored. A pilot project conducted in Athens, Georgia, utilized a UAV with a FLIR Vue Pro R 640 thermal camera to collect thermal data from two neighborhoods. Ground data, obtained using a handheld FLIR E6-XT infrared imaging camera, were compared with UAV thermal imagery. The study aimed to assess the accuracy of the UAV camera and the handheld camera for urban monitoring. Initial testing revealed the handheld’s accuracy but tendency to underpredict, while UAV camera testing highlighted considerations for altitude in both the rjpg and tiff image pixel conversion models. Despite challenges, the study demonstrates the potential of UAV-derived thermal data for monitoring urban surface temperatures, emphasizing the need for careful model considerations in data interpretation.
Enhancing Robot Task Planning and Execution through Multi-Layer Large Language Models
Authors: Luan Zhirong , Lai Yujun , Huang Rundong , Bai Shuanghao , Zhang Yuedi , Zhang Haoran , Wang Qian
Published: March 2024

Large language models have found utility in the domain of robot task planning and task decomposition. Nevertheless, the direct application of these models for instructing robots in task execution is not without its challenges. Limitations arise in handling more intricate tasks, encountering difficulties in effective interaction with the environment, and facing constraints in the practical executability of machine control instructions directly generated by such models. In response to these challenges, this research advocates for the implementation of a multi-layer large language model to augment a robot’s proficiency in handling complex tasks. The proposed model facilitates a meticulous layer-by-layer decomposition of tasks through the integration of multiple large language models, with the overarching goal of enhancing the accuracy of task planning. Within the task decomposition process, a visual language model is introduced as a sensor for environment perception. The outcomes of this perception process are subsequently assimilated into the large language model, thereby amalgamating the task objectives with environmental information. This integration, in turn, results in the generation of robot motion planning tailored to the specific characteristics of the current environment. Furthermore, to enhance the executability of task planning outputs from the large language model, a semantic alignment method is introduced. This method aligns task planning descriptions with the functional requirements of robot motion, thereby refining the overall compatibility and coherence of the generated instructions. To validate the efficacy of the proposed approach, an experimental platform is established utilizing an intelligent unmanned vehicle. This platform serves as a means to empirically verify the proficiency of the multi-layer large language model in addressing the intricate challenges associated with both robot task planning and execution.
Passive Biotelemetric Detection of Tibial Debonding in Wireless Battery-Free Smart Knee Implants
Authors: Hall Thomas A. G. , Cegla Frederic , van Arkel Richard J.
Published: March 2024

Aseptic loosening is the dominant failure mechanism in contemporary knee replacement surgery, but diagnostic techniques are poorly sensitive to the early stages of loosening and poorly specific in delineating aseptic cases from infections. Smart implants have been proposed as a solution, but incorporating components for sensing, powering, processing, and communication increases device cost, size, and risk; hence, minimising onboard instrumentation is desirable. In this study, two wireless, battery-free smart implants were developed that used passive biotelemetry to measure fixation at the implant–cement interface of the tibial components. The sensing system comprised of a piezoelectric transducer and coil, with the transducer affixed to the superior surface of the tibial trays of both partial (PKR) and total knee replacement (TKR) systems. Fixation was measured via pulse-echo responses elicited via a three-coil inductive link. The instrumented systems could detect loss of fixation when the implants were partially debonded (+7.1% PKA, +32.6% TKA, both p < 0.001) and fully debonded in situ (+6.3% PKA, +32.5% TKA, both p < 0.001). Measurements were robust to variations in positioning of the external reader, soft tissue, and the femoral component. With low cost and small form factor, the smart implant concept could be adopted for clinical use, particularly for generating an understanding of uncertain aseptic loosening mechanisms.
Building Individual Player Performance Profiles According to Pre-Game Expectations and Goal Difference in Soccer
Authors: Skoki Arian , Gašparović Boris , Ivić Stefan , Lerga Jonatan , Štajduhar Ivan
Published: March 2024

Soccer player performance is influenced by multiple unpredictable factors. During a game, score changes and pre-game expectations affect the effort exerted by players. This study used GPS wearable sensors to track players’ energy expenditure in 5-min intervals, alongside recording the goal timings and the win and lose probabilities from betting sites. A mathematical model was developed that considers pre-game expectations (e.g., favorite, non-favorite), endurance, and goal difference (GD) dynamics on player effort. Particle Swarm and Nelder–Mead optimization methods were used to construct these models, both consistently converging to similar cost function values. The model outperformed baselines relying solely on mean and median power per GD. This improvement is underscored by the mean absolute error (MAE) of 396.87±61.42 and root mean squared error (RMSE) of 520.69±88.66 achieved by our model, as opposed to the B1 MAE of 429.04±84.87 and RMSE of 581.34±185.84, and B2 MAE of 421.57±95.96 and RMSE of 613.47±300.11 observed across all players in the dataset. This research offers an enhancement to the current approaches for assessing players’ responses to contextual factors, particularly GD. By utilizing wearable data and contextual factors, the proposed methods have the potential to improve decision-making and deepen the understanding of individual player characteristics.
Flying Target Detection Technology Based on GNSS Multipath Signals
Authors: Zhu Pengfei , Zhu Qinglin , Dong Xiang , Sun Mingchen
Published: March 2024

In this study, a passive radar system that detects flying targets is developed in order to solve the problems associated with traditional flying target detection systems (i.e., their large size, high power consumption, complex systems, and poor battlefield survivability). On the basis of target detection, the system uses the multipath signal (which is usually eliminated as an error term in navigation and positioning), enhances it by supporting information, and utilizes the multi-source characteristics of ordinary omnidirectional global navigation satellite system (GNSS) signals. The results of a validation experiment showed that the system is able to locate a passenger airplane and obtain its flight trajectory using only one GNSS receiving antenna. The system is characterized by its light weight (less than 5 kg), low power consumption, simple system, good portability, low cost, and 24/7 and all-weather work. It can be installed in large quantities and has good prospects for development.
Analysis of the Impacts of Small-Scale LNG Projects for Energy Supply of the North Region of Brazil: The Case of Roraima
Authors: Passos Gabriela Pantoja , de Medeiros Costa Hirdan Katarina , dos Santos Edmilson
Published: March 2024

Natural gas is a fossil resource less polluting compared to oil and coal. Despite the large volumes of proven reserves in Brazil, exploration and production are low because of several factors like the lack of infrastructure along several regions of the country, the regulatory model in the consolidation phase, and legal impasses regarding tariffs. In the Brazilian north region, the expansion of the natural gas market is even more complex due to regional specificities both in relation to natural characteristics and the existence of conflicts of interest that impact regional development. However, natural gas has been gaining notoriety over the years, with the existence of large projects that foster the gas market in some states in the region. This article aimed to discuss the impacts of increasing the participation of natural gas in the regional energy matrix through small-scale LNG projects, analyzing the case of the state of Roraima and the impacts of the Azulão-Jaguatirica II Project on this state. As a result, this research presented an evaluation of the existent regulation in Brazilian’s northern states, a bibliometric analysis of natural gas in the Brazilian Amazon which demonstrated how little the topic is covered, and a SWOT matrix about the impacts of natural gas in regional energy supply in order to help future decision-making on the subject.
Improvement of Saline Soil Properties and Brassica rapa L. Growth Using Biofertilizers
Authors: Li Rui , Sun Bo , Song Manjiao , Yan Gaojun , Hu Qing , Bai Zhihui , Wang Jiancheng , Zhuang Xuliang
Published: March 2024

The decline in agricultural productivity because of soil salinization has become a global problem in recent years. Biofertilizers show great potential for soil improvement as a sustainable strategy; however, their effectiveness in improving saline soils and enhancing plant growth under saline stress is poorly understood. We assessed the effectiveness of biofertilizers in improving saline soils and enhancing crop growth under saline stress and investigated the related potential mechanisms. Changes in soil physicochemical properties, plant physiological parameters, and soil microbial communities were analyzed using pot experiments. The results showed that biofertilizer application reduced total soluble salts in the soil by 30.8% and increased Brassica rapa L. biomass by 8.4 times. Biofertilizer application increased soil organic matter, total nitrogen, and available phosphorus by 56.1%, 57.0%, and 290%, respectively. Simultaneously, superoxide dismutase, catalase, chlorophyll a, chlorophyll b, total soluble sugar, and proline levels also increased by 89.5%, 140%, 110%, 190%, and 130%, respectively. Biofertilizers increased the abundance of Bacillus and Planococcus and decreased the abundance of Mortierella and Aspergillus, which could potentially be the underlying reason for the promotion of plant growth. Overall, the results of this study demonstrate the efficacy of biofertilizers in improving saline soils and that the application of biofertilizer could greatly promote agricultural production.
Valorisation of Sugarcane Bagasse for the Sustainable Production of Polyhydroxyalkanoates
Authors: Hassan Soulayma , Ngo Tien , Ball Andrew S.
Published: March 2024

With the world shifting towards renewable and sustainable resources, polyhydroxyalkanoates (PHAs) have attracted significant interest as an alternative to synthetic plastics. While possessing promising properties suitable for various applications, the production of PHAs has not yet reached a global commercial scale. The main reason is the high cost of production, which represents a major limitation. Sugarcane bagasse (SCB) is an abundant lignocellulosic waste around the world. Its use to produce PHA enhances the feasibility of producing PHAs at commercial scale. However, SCB requires pretreatment and hydrolysis steps to release the sugars prior to the microbial fermentation. The cost associated with these steps poses additional challenges for large-scale production. Another challenge is the release of inhibitors during the pretreatment process which can result in a low PHA yield. The development of a low cost, co-culture strategy for the bioconversion of SCB into PHAs, can represent a pivotal step towards the large-scale production of bioplastics. This review highlights the advancements made in recent years on the microbial production of PHA using SCB as potential feedstock, with a proposed biological strategy and circular economy model.
Molecular-Memory-Induced Counter-Intuitive Noise Attenuator in Protein Polymerization
Authors: Bai Xiaojun , Wang Sizhe , Zhang Xin , Wang Haohua
Published: March 2024

Gene expression comprises many asymmetric and complex processes. Transcriptional details revealed by the whole genome indicate that genes resort to transcriptional bursting and accumulate molecular memory. However, it is still unclear how the interplay of transcriptional bursting and memory regulates robustness and expression noise. Here, we consider a model of multiple coupled processes of protein polymerization to focus on decoding the effect of molecular memory. Using non-Markovian transformation technology, we first define the memory index to measure the correlation window of expression to decipher the mechanism of regulation. The results indicate that memory from synthesis can amplify expression noise, while memory originating from polymerization can reduce the lower bound of the noise of gene products; that is, the memory from different sources plays distinct regulatory roles to induce non-symmetry. Moreover, it is counterintuitive that the dual regulation from memory and bursting expression can directly suppress system noise, violating the principle that transcriptional bursting enhances noise. Our results not only provide a theoretical framework for investigating the function of memory but also imply that expression noise is not part of a half-power relationship with, nor mediated by, memory.
Original methods of reflexotherapy combined with pharmacopuncture in rehabilitation of patients with cerebral palsy
Authors:   Federal State Budgetary Educational Institution of Higher Education «Saint Petersburg State Pediatric Medical University» of the Ministry of Health of Russia, St. Petersburg, Russia, Rostacheva E. A. , Suslova G. A. ,   Federal State Budgetary Educational Institution of Higher Education «Saint Petersburg State Pediatric Medical University» of the Ministry of Health of Russia, St. Petersburg, Russia, Rostacheva A. A. ,   Federal State Budgetary Educational Institution of Higher Education «Saint Petersburg State Pediatric Medical University» of the Ministry of Health of Russia, St. Petersburg, Russia, Suslov V. M. ,   Federal State Budgetary Educational Institution of Higher Education «Saint Petersburg State Pediatric Medical University» of the Ministry of Health of Russia, St. Petersburg, Russia, Bulina O. V. ,   Federal State Budgetary Educational Institution of Higher Education «Saint Petersburg State Pediatric Medical University» of the Ministry of Health of Russia, St. Petersburg, Russia
Published: March 2024

The article is devoted to the current problem of rehabilitation of patients with cerebral palsy. The purpose of the article is to summarize new material on the use of combined reflexology, which can complement many treatment methods, including pharmacological ones. The article analyzes traditional and modern concepts in the selection of active exposure points and channels, as well as the selection of drugs for pharmacopuncture.The author proposes a method for the introduction of a point injection of drugs with a double effect on the body: stimulation of the active point and pharmacotherapy. The main content of the study is the analysis of three reflexotherapy techniques: acupuncture, pharmacopuncture, and exposure with a combination of pharmacopuncture and acupuncture. Based on the analysis and the objectification of research, it has been found that the combined method is the most effective. To sum up, conclusions about the efficacy of combined reflexotherapy are drawn, and the prospects for further study of this method as a means of rehabilitation are confirmed, which justifies wider inclusion of reflexotherapy in the standards of treatment of patients with cerebral palsy.
Visiones del Futuro Urbano: El Paradigma Teórico de las Smart Cities
Authors: Cárdenas Villavicencio Oscar Efrén , Zea Ordoñez Mariuxi Paola , Honores Tapia Joofre Antonio , Lamar Peña Freddy Stalin
Published: March 2024

En el siglo XXI, el rápido surgimiento de las urbanizaciones ha dado lugar a desafíos significativos en la gestión de recursos, la sostenibilidad ambiental y la calidad de vida en las ciudades. El objetivo de la investigación fue identificar las visiones del futuro urbano con base a las publicaciones en respuesta a las Smart Cities que han surgido como una solución prometedora respaldada por avances tecnológicos. Esta revisión sistemática de la literatura se basó en el uso del método PRISMA 2020 que permite una mejor estructura de los artículos científicos publicados entre 2019 y 2023, en inglés y español, utilizando criterios de calidad y relevancia. Los resultados de la revisión sistemática de literatura, permitió identificar un crecimiento constante en el interés académico sobre ciudades inteligentes, con un aumento notable en las publicaciones desde 2019 hasta 2021, determinando que Europa lidera en la producción de literatura sobre el tema, seguida de América Latina y Asia, lo que refleja un interés global en el desarrollo de ciudades inteligentes. Los enfoques temáticos identificados en los estudios incluyen el Desarrollo Sostenible y Medio Ambiente como el tema predominante, destacando la importancia de equilibrar la eficiencia y la calidad de vida con la protección ambiental. La Tecnología e Innovación son fundamentales para mejorar la eficiencia urbana, mientras que la participación ciudadana, la planificación urbana efectiva y la educación son esenciales para fomentar una mayor conciencia ambiental.
Evaluación comparativa de herramientas tecnológicas basadas en Inteligencia Artificial para el monitoreo de enfermedades
Authors: Cárdenas Villavicencio Oscar Efrén , Valarezo Pardo Milton Rafael , Jumbo Castillo Freddy Aníbal , Jaramillo Barreiro Juan Andrés
Published: March 2024

La atención médica está experimentando una revolución sin precedentes gracias a los avances en informática, inteligencia artificial (IA) y telemedicina. En este contexto, los chatbots se han convertido en herramientas innovadoras que transforman las prácticas médicas tradicionales al ofrecer atención personalizada y orientación instantánea. Esto desafía el enfoque convencional de seguimiento de enfermedades, que solía depender históricamente de visitas médicas programadas y recopilación manual de datos. Este estudio se enfoca en evaluar comparativamente las herramientas tecnológicas basadas en IA diseñadas para el monitoreo de enfermedades. Adoptando el método PRISMA 2020, se llevó a cabo una revisión exhaustiva de la literatura y estudios pertinentes. Este enfoque metodológico permitió un análisis preciso de la eficacia, exactitud y viabilidad de chatbots específicos como GYANT, Babylon Health, EDAChatbot, Med-PaLM, Symptomate y Buoy Health. Los resultados obtenidos revelan el impacto positivo que estas tecnologías tienen en la mejora de la atención médica. Además, ofrecen una guía sólida para su desarrollo y adopción futura. Es fundamental destacar que la implementación de estas tecnologías debe llevarse a cabo sin descuidar principios éticos fundamentales, como la protección de la privacidad y la autonomía del paciente. En cuanto a los hallazgos específicos, se encontró que los chatbots EDAChatbot, Buoy Health y Symptomate sobresalen en varios aspectos críticos. Estos incluyen: respuestas rápidas e instantáneas, interfaz amigable y sencilla, adaptabilidad Lingüística, integración con Registros Médicos Electrónicos (EMR) y seguridad de Datos, garantizando la confidencialidad y protección de la información del paciente.
Processo de criação de máquina extrusora para criação de filamentos de impressão 3d, através de resíduos sólidos recicláveis de polímeros termoplásticos
Authors: Ferreira Gabriel de Lima , Santos Sostenes Fernandes dos , Oliveira Iuri Kauã Simão de , Mamede Filho Marcos Cordeiro , Noberto Emerson Medeiros
Published: March 2024

Este trabalho descreve o desenvolvimento de uma extrusora de baixo custo para a produção de filamentos de impressão 3D a partir de garrafas PET recicladas. A iniciativa surgiu com o objetivo de criar uma solução acessível para escolas públicas, institutos e laboratórios Maker em todo o Brasil, permitindo a fabricação de filamentos sustentáveis e a promoção da educação ambiental. A pesquisa foi embasada em estudos anteriores que destacam o potencial do PET reciclado para uso em impressão 3D. O processo envolveu várias etapas, começando pelo filetamento das garrafas PET para obter uma fita de 1 cm de largura, conforme sugerido por estudos durante a revisão bibliográfica. Em seguida, a fita de PET foi direcionada para uma matriz aquecida, parte fundamental da extrusora, onde foi derretida e remodelada para a forma cilíndrica, com diâmetro de 2 mm, adequada para impressoras 3D. A extrusora utilizou um bico de 2 mm de diâmetro, e o filamento resultante foi tracionado por um motor de passo com engrenagens controlado por um potenciômetro, garantindo um diâmetro final de 1,75 mm, compatível com impressoras 3D convencionais. O processo foi realizado a uma temperatura de 240°C, garantindo a fusão adequada do PET. Um aspecto importante deste trabalho foi a investigação da pigmentação do filamento. Foram realizados testes com diferentes pigmentos, incluindo tinta de pincel permanente nas cores preta e vermelha, bem como tintas de canetas esferográficas e de quadro branco. Apenas a tinta de pincel permanente vermelha demonstrou aderência homogênea ao material, permitindo a impressão 3D sem problemas. A pesquisa se alinhou com estudos sobre pigmentação de polímeros, proporcionando impressões com uma espessura de camada de 0,2 mm perfeitamente. Os resultados obtidos foram extremamente promissores, evidenciando a viabilidade técnica da produção de filamentos PET reciclados para uso em impressão 3D. Durante o desenvolvimento do projeto, a extrusora foi montada e testada com sucesso no Laboratório Sertão Maker do IFPB Campus Patos. O impacto foi notável, com várias escolas públicas e particulares expressando interesse em replicar a iniciativa em suas instituições. Além disso, o trabalho foi apresentado em eventos acadêmicos, como a SCNT em João Pessoa e a EXPOTEC 2023, com destaque para a contribuição do IFPB Campus Patos. Isso demonstra o potencial de disseminação dessa tecnologia e de nossa pesquisa. Como resultado adicional, foi aprovada uma segunda pesquisa, com foco na produção de vergalhões de alta resistência a partir de polímeros termoplásticos derivados de resíduos sólidos, como o PET, com a aplicação de grafeno e outros compostos na construção civil. Essa pesquisa busca ampliar o conhecimento sobre as propriedades do PET e suas possíveis aplicações.
Examining the factors affecting technology continuance and its role in economic growth of emerging economies
Authors: Shahid Muhammad Khalid , Khin Aye Aye , Seong Lim Chee , Alkharabsheh Omar Hamdan Mohammad , Arfat Yasser
Published: March 2024

Technological developments have been thought to portray a pivotal role in promoting economic growth, particularly within the financial sector in developing economies which has been reported significantly influenced by users' perceptions of technology usability, which are shaped by their technology usage experiences. This study integrates antecedents of the UTAUT model with the Innovation Diffusion Theory to empirically assess the perceived usability of Internet banking and its role for economic growth. Post-experience data were collected from 315 banking clients in Lahore, Pakistan. After validating the sample's reliability, validity, adequacy, and sphericity, a structural equation model (SEM) was employed to test the study's hypotheses. The findings revealed that the perceived usability of bank clients was positively influenced by perceived ease of use and perceived usefulness, which in turn impact their intention to continue the use of Internet banking. Mediating role of perceived usability did not support by the results. However, the presence of ease of use and usefulness exhibited a positive moderating effect of financial risk on users' intention to continue using Internet banking. These findings provide valuable insights for academics seeking to comprehend users’ experience and usability about the use of technology. Additionally, the results steer policymakers to formulate effective policies that maintain users’ engagement in Internet banking, thus contributing to economic growth through effective use of technology. Notably, this study contributes new perspectives based on data collected from functioning Internet banking users in developing economies.
Relationship of Early Maladaptive Schemas and Emotional Cognitive Regulation with the Mental Health of Operating Room Technologists
Authors: Khalilpour Abbas , Hanani Sedigheh , Hosseinzadeh Fatemeh , Sheikhi Siamak , Rasouli Mahboobeh
Published: March 2024

Background: The mental health of individuals is an effective factor in having harmonious communication with others and changing and improving personal and social environments. This study aimed to investigate the relationship between primary incompatible patterns, cognitiveemotional regulation, and the mental health of operating room technologists in educational therapeutic centers in West Azerbaijan province, Iran. Methods: This cross-sectional descriptive-analytical study consisted of all operating room technologists working in educational centers in West Azerbaijan province. The inclusion criteria were technologists who had no history of mental illness diagnosed by a psychiatrist. The sample consisted of 123 people who were selected by simple random sampling. The data were collected using several demographic data forms, including the Early Maladaptive Schema Questionnaire, the Cognitive-Emotional Regulation Questionnaire (CERQ), and the Mental Health Questionnaire. The obtained data were analyzed by descriptive and inferential statistical tests, including the Kolmogorov-Smirnov test and Spearman correlation in SPSS 20 software. Results: The results showed a direct relationship between early maladaptive schemas and mental health (r=0.37, P<0.05), as well as between emotional cognitive regulation and mental health (r=0.30, P<0.05). A significant difference was found between emotional cognitive adjustment with age (r=0.12, P<0.05) and work experience (r=0.14, P<0.05), as well as between mental health and employment status (r=0.07, P<0.05). There was a direct and significant relationship. Conclusion: Based on the results, a direct and significant relationship was observed between early maladaptive schemas, emotional cognitive regulation, and the mental health of operating room technologists.
An Overview of the Application of Green Nature Deep Lung Support, a Natural Product With Herbal Source in Medicine
Authors: Fakharian Atefeh , Mirenayat Maryam Sadat , Babazadeh Modjtaba , Zahiri Reyhaneh , Mirtajani Seyed Bashir , Jamaati Hamidreza
Published: March 2024

Background: The use of natural resources, especially medicinal plants, for treating and improving the quality of life has roots as far back as human history. The extensive abilities of plants and the ease of access have led to the use of these huge natural resources in modern medicine. The present study focused on reviewing the component properties of the Green Nature Deep Lung Support as one of the medicinal products with a natural source. Furthermore, while examining some plants’ effects on viral respiratory infections, the scientific bases supporting these claims were discussed as well. Methods: Data were collected by searching keywords such as "drug development", "herbal medicine", "infectious disease", "natural product", and "SARS-CoV-2" in Medline, Embase, and Web of Science databases. The main texts of all related articles were reviewed after reviewing the titles of the articles and their abstracts. Results: The use of herbal medicines for the treatment and control of viral respiratory infections has been of interest in the past. The effects and benefits of a wide variety of antiviral herbs have been discussed. Green Nature Deep Lung Support product with the extract of plants such as Eriobotrya japonica, Fritillaria cirrhosa, Taraxacum Officinale, Andrographis paniculata, and Echinacea purpurea can be effective in improving respiratory and inflammatory symptoms of various diseases. Conclusion: The herbal extracts used in Green Nature Deep Lung Support product have antiinflammatory and immune-modulating properties and can be influential as a potential treatment in diseases such as COVID-19 that are affected by a cytokine storm.