bluuebunny/crossref_metadata_2025_split huggingface dataset:
One photon simultaneously excites two atoms in a ultrastrongly coupled light-matter system
Authors: Tomonaga Akiyoshi , Stassi Roberto , Mukai Hiroto , Nori Franco , Yoshihara Fumiki , Tsai Jaw-Shen 
Published: January 2024

Abstract
We experimentally investigate a superconducting circuit composed of two flux qubits ultrastrongly coupled to a common LC resonator. Owing to the large anharmonicity of the flux qubits, the system can be correctly described by a generalized Dicke Hamiltonian containing spin-spin interaction terms. In the experimentally measured spectrum, an avoided level crossing provides evidence of the exotic interaction that allows the simultaneous excitation of two artificial atoms by absorbing one photon from the resonator. This multi-atom ultrastrongly coupled system opens the door to studying nonlinear optics where the number of excitations is not conserved. This enables novel processes for quantum-information processing tasks on a chip.
Responses of Soil and Vegetation Properties to Chemical Fertilization in Restoring Coal Gangue Hills in an Alpine Mining Area
Authors: Jin Liqun , Li Xilai , Sun Huafang , Zhang Jing , Zhang Yufang , Gao Jay 
Published: January 2024

Abstract
During the coal mining operation, the accumulated soil in coal gangue hills often suffers from nutrient deficiencies, which can be overcome using fertilizer supplementation. The supplementation of exogenous nutrients has proven to be an effective means of enhancing physicochemical conditions of these soils and promoting vegetation reestablishment. This study aimed to investigate the characteristics of plant growth and soil properties in vegetation restoration to a coal gangue hill, focusing on artificially seeded grasslands in a high-altitude mining area as the research subject. Over a period of three consecutive years, varying gradients of nitrogen and phosphorus supplements were applied to the coal gangue hill. Furthermore, the interrelationships between plants and soil factors at different dosages of chemical fertilization were analyzed so as to determine the appropriate fertilization level conducive to the ecological system's restoration in the area. The results of this study revealed significant responses (P < 0.05) in vegetation height, coverage, and biomass to nitrogen and phosphorus dosage, leading to a significant increase in the availability of soil nutrients (P < 0.05). Apart from moss coverage, fertilizer dosage exhibited a significant positive correlation (P < 0.05) with various vegetation characteristics, as well as a highly significant positive correlation (P < 0.05) with soil nutrient availability. Notably, no significant differences (P > 0.05) were observed in soil physical properties with varying nitrogen and phosphorus amendments. In conclusion, nitrogen and phosphorus supplementation is beneficial for promoting vegetation growth and improving soil chemical properties in high-altitude mining areas with coal gangue hills. The recommended minimum dosage is 40g/m² of urea in combination with 30g/m² of diammonium phosphate. This supplement should be applied continuously. Considering the capacity of the mining area's ecosystem to self-repair and the costs of ecological restoration, it is advisable to utilize organic fertilizers and sheep manure in the next phase of restoration.
Routine Health Information Quality and Associated Factors Among Health Facilities in Eastern Zone of Tigray, Ethiopia, 2021: A Comparative Cross-Sectional Study
Authors: Nigusse Shimuye , Gebreegziabher Letekirstos , Gebretsadik Teklit 
Published: January 2024

Abstract

Background
The quality of healthcare relies on evidence-based decisions backed by high-quality routine health information (RHI). Evaluating RHI quality and factors associated with it is crucial for advancing healthcare information systems and improving overall healthcare quality. This study assesses RHI quality and its influencing factors in health facilities, specifically in primary healthcare facilities in Eastern Tigray, Ethiopia.
Methods
A comparative cross-sectional study was conducted in selected health facilities in Eastern Tigray, supported by the Mekelle University Capacity Building and Monitoring program. Simple random sampling was used to select the woredas, with 224 departments assessed. Data was collected through questionnaires, observation checklists, and registry review. Descriptive statistics and ordinal logistic regression were used to analyze the routine health information quality and associated factors. The significance level was set at p-value < 0.05 with a 95% confidence interval.
Result
Only 13.39% of health facility departments meet the acceptable limit for routine health information quality (85% completeness, timeliness on 23–25 of the month, and accuracy of 90–110% verification factor). Being supported by the project is significantly associated with quality (Pearson X2 = 14.703, P = 0.001). Factors such as training on health information systems (2.173, 95% CI: 1.018, 4.638), display of targets (2.853, 95% CI: 1.10, 7.752), feedback (2.836, 95% CI: 1.267, 6.345), and perception of the importance of routine health information (5.330, 95% CI: 1.403, 20.254) are associated with quality in facilities not supported by the Capacity Building program. Supervision is a factor associated with quality in facilities supported by the program (adjusted proportional odds ratio and 95% confidence interval: 3.806, 1.66-12.427).
Conclusion
The data quality was below national expectations. Health centers had lower RHI quality compared to hospitals. Support from projects and training, supervision, and feedback improved data quality. Scaling up training, monitoring, and written feedback at various health system levels is recommended.
Emotion perception through the nose: How olfactory emotional cues modulate the perception of neutral facial expressions in affective disorders
Authors: Bò Elisa Dal , Cecchetto Cinzia , Callara Alejandro , Greco Alberto , Mura Francesca , Vanello Nicola , Francesco Fabio Di , Scilingo Enzo , Gentili Claudio 
Published: January 2024

Abstract

Human body odors are an effective modality of social communication. Individuals exposed to emotional body odors report a partial reproduction of the affective state of the sender. The present study aimed to explore how body odors collected in happiness and fearful conditions modulate the subjective ratings, the psychophysiological response and the neural processing of neutral faces in individuals with depressive symptoms, social anxiety symptoms, and healthy controls (N = 22 per group). To this aim, electrocardiogram (ECG) and HD-EEG were recorded continuously. For subjective ratings, individuals with depressive symptoms rated the neutral faces as more arousing when presented with the fear odor compared to the clean air condition. The heart rate variability (HRV) results showed a main effect of odor: HRV increased during the fear and happiness body odors compared to clean air, suggesting that at a peripheral level the two emotional body odors seem to increase the vagal tone. Lastly, event-related potentials (ERPs) and event-related spectral perturbations (ERPSs) extracted from the EEG were analysed. For ERPs data, mixed ANOVA analyses did not show any significant effects. However, the ERPSs analyses revealed that the emotional body odors modulated the processing of the neutral faces both at an early and a late stage of stimulus processing, regardless of the presence of depressive or social anxiety symptoms. The current research offers new insights, demonstrating that emotional chemosignals serve as potent environmental cues. This represents a substantial advancement in comprehending the impact of emotional chemosignals in both individuals with and without affective disorders.
A retrospective study for diagnostic value of chromosomal microarray analysis in fetuses with high-risk prenatal indications
Authors: Xiao Hui. , xiao junfang , Huang Shuhui , Zou Yongyi , Lu Qing , Yuan Huizhen , Yang Bicheng , Liu Yanqiu 
Published: January 2024

Abstract
Objective
The aim of this study was to determine the diagnostic value of prenatal chromosomal microarray analysis (CMA) for fetuses with high risk for various conditions on chromosomal abnormalities.
Methods
8560 clinical samples were collected from pregnant women between Feb 2018 and June 2022, including 75 villus, 7642 amniotic fluid, and 843 umbilical cord blood samples. This retrospective analysis included pregnancies with high-risk indications for invasive prenatal diagnosis, mainly including ultrasound anomalies, high-risk for maternal serum screening(MMS), high-risk for non-invasive prenatal tests (NIPT), family history of genetic disorders or birth defects, and advanced maternal age (AMA). All samples were evaluated by both CMA and karyotyping. The rate of clinically significant genomic imbalances between the different groups was compared.
Results
The success rate of CMA was 99.95% (8556/8560). A total of 1037 samples (12.11%, 1037/8560) presented with chromosomal abnormalities by using CMA, whereas 803 samples (9.38%, 803/8560) presented with chromosomal abnormalities by using karyotyping. The overall prenatal diagnostic yield was 1040 (12.14%) of 8560 pregnancies. Clinically significant genomic aberrations were identified in 153 (6.21%) of 2463 patients with non-structural ultrasound anomalies, 79(6.38%) of 1238 with structural ultrasound anomalies, 37 (4.26%) of 868 at high-risk for MSS, 395(42.29%) of 934 at high-risk for NIPT, 16 (2.94%) of 544 with a family history, 7 (1.89%) of 369 with AMA, 1 (1.56%) of 64 with history of adverse exposure, 10 (4.46%) of 224 with parental chromosome anomalies and 9 (2.99%) of 301 with other indications.
Conclusion
CMA has a better diagnostic value for screening chromosomal abnormalities, especially for pregnant women with normal karyotypes. The diagnostic yields of CMA for pregnancies with different indications greatly varied. CMA could serve as a first-tier test for structural anomalies, especially multiple anomalies, hydrops fetalis, cystic hygroma and thickened nuchal translucency or nuchal fold.
Biodegradation of polyethylene (PE), polypropylene (PP), and polystyrene (PS) microplastics by floc-forming bacteria, Bacillus cereus strain SHBF2 isolated from a commercial aquafarm
Authors: Hossain Shahadat , Shukri Zuhayra Nasrin Ahmad , Waiho Khor , Ibrahim Yusof Shuaib , Kamaruzzan Amyra Suryatie , Rahim Ahmad Ideris Abdul , Draman Ahmad Shuhaimi , Wahab Wahidah , Khatoon Helena , Kasan Nor Azman 
Published: January 2024

Abstract

The ubiquitous proximity of the commonly used microplastic (MP) particles particularly polyethylene (PE), polypropylene (PP), and polystyrene (PS) poses a serious threat to the environment, and human health globally. Biological treatment as an environment-friendly approach to counter MPs pollution has recent interest when the bio-agent has beneficial functions in their ecosystem. This study aimed to utilize beneficial floc-forming bacteria B. cereus SHBF2 isolated from an aquaculture farm in reducing the MPs particles (PE, PP, and PS) from their environment. The bacteria were inoculated for 60 days in a media containing MPs particles as a sole carbon source. On different days of incubation (DOI), the bacterial growth analysis was monitored and the MPs particles were harvested to examine their weight loss, surface changes, and alterations in chemical properties. After 60 DOI, the highest weight loss was recorded for PE, 6.87 ± 0.92%, which was further evaluated to daily reduction rate (k), 0.00118 gday− 1, and half-life (t1/2), 605.08 ± 138.52 days. The OD value (1.74 ± 0.008 Abs.) indicated the higher efficiency of bacteria for PP utilization, and so for the colony formation per define volume (1.04 × 1011 CFU/mL). Biofilm formation, erosions, cracks, and fragments were evident during the observation of the tested MPs using the scanning electron microscope (SEM). The formation of carbonyl and alcohol group due to the oxidation and hydrolysis by SHBF2 strain were confirmed using the Fourier transform infrared spectroscopic (FTIR) analysis. Additionally, the alterations of pH and CO2 evolution from each of the MPs type ensures the bacterial activity and mineralization of the MPs particles. The findings of this study have confirmed and indicated a higher degree of biodegradation for all of the selected MPs particles. B. cereus SHBF2, the floc-forming bacteria used in aquaculture, has demonstrated a great potential for use as an efficient MPs degrading bacterium in the biofloc farming system in the near future to guarantee a sustainable green aquaculture production.
Tripartite motif-containing protein 26 promotes colorectal cancer growth by inactivating p53
Authors: Lu Hua , Tan Zhihui , Ko Hyunmin , Naji Parnia , Zhu Rong , Wang Jieqiong , Huang Shibo , Zhang Yi-Wei , Zeng Shelya 
Published: January 2024

Abstract

Tripartite motif-containing protein 26 (TRIM26) is an E3 ubiquitin ligase that exhibits divergent roles in various cancer types (oncogenic and anti-oncogenic). This study investigates the interaction of TRIM26 with the tumor suppressor protein p53 in colorectal cancer (CRC) cells by performing a comprehensive set of biochemical, cell-based assays, and xenograft experiments. As a result, we found that overexpression of TRIM26 significantly enhances CRC cell proliferation and colony formation, while knockdown of TRIM26 suppresses these processes. Xenograft experiments further validated the tumor-promoting role of TRIM26 in CRC. Supporting this is that TRIM26 is highly expressed in human CRC tissues as revealed by our analysis of the TCGA database. Biochemically, TRIM26 directly bound to the C-terminus of p53 and facilitated its ubiquitination, resulting in proteolytic degradation and attenuated p53 activity independently of MDM2. Also, TRIM26 increased the MDM2-mediated ubiquitination of p53 by binding to MDM2’s C-terminus. This study uncovers the oncogenic potential of TRIM26 in CRC by inhibiting p53 function. Through its ubiquitin ligase activity, TRIM26 destabilizes p53, consequently promoting CRC cell proliferation and tumor growth. These findings shed light on the complex involvement of TRIM26 in cancer and identify this ubiquitin ligase as a potential therapeutic target for future development of CRC treatment.
The Incidence of Sports-Related Concussion in Children and Adolescents: A Systematic Review and Meta-Analysis
Authors: Ingram Veronica , Fielding Megan , Dunne Laura A M , Piantella Stefan , Weakley Jonathon , Johnston Rich D , McGuckian Thomas Baxter 
Published: January 2024

Abstract
Background
Sport-related concussions (SRC) are a concern for young athletes due to the potential for long-term health problems. This systematic review and meta-analysis aimed to provide a comprehensive overview of the literature exploring SRC incidence in youth sports to understand the associated risks.
Methods
Medline, Embase, SportDiscus, PsycInfo, and Web of Science databases were searched without language restrictions until March 2023. Studies were included if they i) reported data for calculation of SRC incidence, ii) were a prospective cohort study, and iii) included a sample aged ≤ 18 years. Studies that reported Athlete Exposure (AE) or Player Hours (PH) as SRC incidence data measures were included in a multi-level random-effects meta-analysis. Additional analysis explored SRC incidence based on age, gender, country, year of data collection, setting, and level of contact.
Results
Of the 5833 studies reviewed for eligibility, 109 studies were accepted for a systematic review and 93 in the meta-analysis. The pooled incidence rate of SRC per 1,000 AE was found to be 1.41 across 21 sports, and 4.16 per 1,000 PH across 7 sports. The highest incidence per 1,000 AE were in taekwondo, rugby union, and ice hockey, and the highest incidence per 1,000 PH were in rugby 7’s, rugby league, and rugby union.
Conclusions
This systematic review and meta-analysis can serve as an updated baseline for risk of concussion among youth athletes across various sports. Registration: This systematic review was registered on OSF registries (https://osf.io/v298s).
A Lightweight Convolutional Neural Network based network intrusion detection and classification method for Social Internet of Things
Authors: G Murugesan , Maheswaravenkatesh P. 
Published: January 2024

Abstract
The Internet of Things (IoT) and social networking principles have been combined to create the so-called Social Internet of Things paradigm, which holds that devices can build social connections with their owners on their own. In this scenario, "things" engage with their peers in order to find the services they require.If the IoT is not handled properly, assaults and issues could overshadow any advantages.The quantity and methods of attacks have, however, expanded due to the extraordinary improvement of this technology. The complexity of maintaining data privacy as a result makes it even more challenging to offer top-notch services and complete security.The development of intrusion detection systems (IDS), which can quickly and accurately identify and categorise intrusions at various levels of networks, has made substantial use of deep learning techniques. In this work, a network intrusion detection model based on convolutional neural networks that has five convolutional layers is proposed. This model is tested using the CICIDS2018 dataset, a publicly accessible dataset with 80 statistical features, for both binary and multi-class classification. Data transformation and numerical standardisation procedures are used to pre-process the dataset.Experiments are conducted to assess the performance of the proposed system, and the results of the study demonstrate that the proposed CNN outperforms existing intrusion detection techniques in terms of multi-class categorization detection, with average values for accuracy, precision, recall, and F1-score of 99.65%, 99.16%, 98.70% and 99.09%, respectively.
Comparative study of different machine learning methods to forecast cucurbit fruit fly, Zeugodacus cucurbitae (Coquillett) occurrence in Eastern plain zone of Uttar Pradesh, India
Authors: Deb Dibyendu , HALDER JAYDEEP , RAI A. B. 
Published: January 2024

Abstract
Insect pests damage a large amount of agricultural produce every year. This damage can be mitigated to a large extent if it is predicted in advance. Machine Learning (ML) models can be a game-changer in terms of pest management policy planning due to their high prediction accuracy. To forecast the occurrence of the cucurbit fruit fly (Zeugodacus cucurbitae), a polyphagous pest in the vegetable ecosystem, different machine learning algorithms such as multiple linear regression, artificial neural networks, support vector machines, decision tree, random forests, and XGBoost were compared. During the years 2013-2019, adults of cucurbit fruit flies were trapped using bottle traps (ethanol, insecticide (Spinosad / Malathion / DDVP) and culture (6:1:2) covered in wooden blocks) at a rate of 25-30 traps per hectare at weekly intervals. The meteorological observatory recorded several weather data such as daily maximum temperature (oC), daily lowest temperature (oC), average daily temperature (oC), average day relative humidity at 7.00 am and 2.00 pm, bright sun shine hour, evaporation, rainfall, and wind velocity. XGBoost has the highest R2, 0.89, out of the six machine learning models tested, followed by the decision tree model (R2= 0.87). As a result, the best fit model for forecasting this cucurbit fruit fly under the vegetable environment might be these two machine learning methods.
Communication breakdown! Signal modality drives the effect of information loss on the behavioral responses of the threatened Great-Billed Seed-Finch, Sporophila maximiliani (Thraupidae: Passeriformes)
Authors: Santos Gabriela Sales dos , Leal Lara Louredo , Nomura Fausto 
Published: January 2024

Abstract

Communication is a central process in animals' interactions and the transmission of information depends on the signal quality. As signals degrade, the resulting loss of information has the potential to increase the ambiguity about the sender’s motivation and status. Thus, the information loss can generate in the receptor a state of motivational conflict and increases the aggressiveness as a coping strategy. We tested whether the information loss affects the behavioral response of Sporophila maximilianiusing (i) a playback experiment, to simulate an acoustic signal, and (ii) a mirror experiment, to simulate a visual signal. We found that a greater degradation of the acoustic signal induced in males’ calls a modulation from lower to higher frequencies, indicating a fear state. Conversely, the degradation of visual signal resulted in an equally high emission of displacement activity in relation to total visual information context, showing no effect of the signal interference. Also, we detected that an increase in the background noise, more than the loss of information, resulted in an increase of the emission of displacement activities and calls of lower frequency, indicating stressful and aggressive states, respectively. So, the response of S. maximiliani to information interference was modulated by the signal modality. The great interference in acoustic signals results in a fear state due to the ambiguity of the interaction context, suggesting that a partially comprehensible signal is more harmful than a totally degraded one. The emission of maintenance behaviors as displacement activities is an indicator of the higher stress endured by the individuals exposed to visual signals, independent of interferences on signal quality. Furthermore, the negative effect of artificial environmental noise can be high, suggesting some level of neophobia in S. maximiliani.
The Agent-based Model's Role in Assessing Paratransit Performance in a Data-Scarcity Context.
Authors: Elgohary Mohamed 
Published: January 2024

Abstract
The study of informal mobility, particularly Paratransit, faces significant challenges in academic research and urban planning practices. This difficulty stems from a lack of information and resources coupled with an organized, complex nature of the Paratransit in developing countries. Making a comprehensive study on Paratransit is a resource-consuming process. This paper addresses these challenges by complementing the recent studies on paratransit modeling by proposing a pipeline to model the Paratransit corridors with multiple stops in Alexandria, Egypt. The proposed methodology aims to integrate the Paratransit into a multi-agent-based Simulation model. The process includes collecting GPS data through minibus users, constructing an Origin-Destination Matrix, and constructing, mapping, and ground-truth the Paratransit routes for an agent-based business-as-usual model. The findings highlight the variable demand for paratransit services under different mobility conditions. Ultimately, the Model was tested to make the Paratransit more accessible. The result shows a gradual change in the boarding behavior at the start and end line, while the demand fluctuated in the middle of the route. These results can support an evidence-based urban mobility policy that places a Paratransit line along the Minibus corridor. The process is based on open access data with a small sample of crowdsourcing data, enabling replicating the methods in similar data-scarcity contexts.