bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intraspecific variation of sex ratio and body size along latitude in the termite Reticulitermes speratus (Isoptera: Rhinotermitidae)
Authors: Morooka Fumiya , Maekawa Kiyoto , Kitade Osamu 
Published: May 2024

Abstract

The Japanese subterranean termite Reticulitermes speratus exhibits a female-biased alate sex ratio and a wide north-south distribution area. The possible causes of the biased sex ratio can be tested by examining alate sex ratios and their geographical variation. Considering the need for adaptation to the winter fasting period, a body size cline of alates may be present in this species. In this study, we examined variations in the sex ratio, head width, and dry weight of R. speratus alates in 157 colonies from 16 populations on the Japanese archipelago. The alate sex ratio was biased toward females; however, no colonies without males were found, thus contradicting the hypothesis that parthenogenetic colonies founded by two female alates bias the sex ratios. The sex ratio bias was more pronounced at lower temperatures (higher latitudes), which supports the hypothesis that asexual queen succession causes sex ratio bias. Interestingly, a distinct split sex ratio was observed at low-temperature sampling sites, indicating the existence of another factor causing disruptive selection. The head widths and dry weights of alates were larger at lower temperatures and higher latitudes. This is the first study of an intraspecific latitudinal body size cline in termites, which is common in a temperate ant species and many ectotherms.
Exploring Healthcare Provider Perspectives on Focused Trainings and Quality Improvement Initiatives in the Intensive Care Unit of the National Hospital in Tanzania
Authors: Strelzer Samantha , Julius Joseph , Anicet Niyo , Byabato Odillo , Chiwanga Faraja , Hassan Saria , Kayandabila Festo , Laizer Agness , Majuta Trustworthy , Murray Brittany , Said Tatu , Ndile Samson 
Published: May 2024

Abstract

Background
With high mortality rates and persisting constraints on resources, the question of how to implement quality care in a low-resource setting is imperative to answer to prevent excess deaths. In Tanzania, it was found that the mean average of knowledge in critical care settings was 38.6% in hospitals. Moreover, despite the Ministry of Health and Social Welfare implementing a Quality Improvement (QI) program, there have been continual obstacles to the success of patient outcomes, sparking high mortality rates. This research aims to understand the barriers and facilitators to implementing sustainable quality improvement and educational projects in Tanzania to transform quality care in a low resource setting.
Methods
After a needs assessment identifying local gaps in knowledge, a two-day site- and context-specific critical care training program was developed for providers working in the intensive care unit at the National Hospital. It included modules on Vital Signs Directed Therapy (VSDT), Cardiopulmonary and Brain Resuscitation (CPBR) knowledge and critical care concepts. Alongside medical knowledge topics, quality improvement measures and change management were also highlighted during the education. Qualitative semi-structured interviews were used to understand the experience of those involved in the training program. Utilizing rapid qualitative analysis, interview themes were extracted. A total of seven providers were interviewed.
Results
All providers recognized a positive impact of trainings and QI at their institution, noting that QI is institution-wide and engenders a culture shift. The themes that emerged included the following: A supportive team dynamic with identified advocates to champion QI practices has been a key factor. Moreover, the interviewees consistently identified barriers to providing quality care and to integrating QI at the National Hospital. Respondents perceived that change management has had an effect on their practice and the hospital culture.
Conclusion
Themes from interviews showed respondents appreciated the training and found change management concepts useful. This study suggests that combining Critical Care Training Program with QI concepts can impact a culture of change and may be of benefit to incorporate within a systematic approach to strengthening capacity of critical care delivery in limited resource settings, with implications for further innovation in other LMICs.
The NLRP1 inflammasome emerges as a promising therapeutic target and prognostic biomarker across multiple cancer types: A comprehensive pan-cancer analysis
Authors: Habibipour Leila , Sadeghi Mahboubeh , Raghibi Alireza , Khorasani Amirhossein Mohajeri , Mousavi Pegah , Sanadgol Nima 
Published: May 2024

Abstract

Aims: Nod-like receptor family pyrin domain containing 1 (NLRP1) serves as the central component of the inflammasome complex and has emerged as a potential contributor to cancer development. Despite accumulating evidence, a comprehensive assessment of NLRP1 across various cancer types has yet to be undertaken.
Main Methods: Several databases have evaluated NLRP1 expression across various cancer types in The Cancer Genome Atlas (TCGA). Additionally, studies have investigated the correlation between NLRP1 and various survival metrics, infiltration of cancer-associated fibroblasts, genetic alterations, drug sensitivity, and promoter methylation. Furthermore, research has explored the potential roles of NLRP1 and its interactions with other proteins.
Key Findings: Our analysis revealed decreased expression of NLRP1 in BLCA, BRCA, KICH, LUAD, LUSC, PRAD, and UCEC tumor tissues compared to normal tissues. We identified a significant correlation between NLRP1 expression and various cancer survival parameters, genetic mutations, and immune infiltration of cancer-associated fibroblasts. Furthermore, we observed that NLRP1 expression is regulated by promoter DNA methylation in ESCA. Abnormal expression of NLRP1 was associated with decreased sensitivity to multiple anti-tumor drugs and small compounds. NLRP1 was found to be involved in pathways associated with T cell receptors and chemokines.
Significance: Reduced NLRP1 expression contributes to cancer progression and holds potential as a crucial biomolecular marker for diagnostic, prognostic, and personalized therapeutic interventions across different malignancies.
Spam detection in IoT based on hybrid deep learning model and multi-objective optimization by NSGA II
Authors: Dehghani Samira , Ahmadinia Mohammad , Ghafoori Seyed Hamid 
Published: May 2024

Abstract

The Internet of Things (IoT) connects a range of things, including sensors, physical devices, controllers, and intelligent computer processors. Physical objects with the ability to organize and control independently are referred to as smart devices in the IoT architecture. The interconnected nature of devices within these networks makes them susceptible to various cyber threats, with spam posing a significant risk. Thus, the significance of effective spam detection in IoT networks, especially in the context of smart grids, lies in safeguarding the reliability, security, and optimal functionality of critical infrastructure systems essential for our modern way of life. Existing methods in IoT spam detection have often overlooked the critical aspects of extracting hidden dependencies and addressing the imbalanced nature inherent in spam data, limiting their effectiveness in ensuring comprehensive security measures. In this study, bidirectional gated recurrent unit (BiGRU) and Convolution neural network (CNN) are combined with the Non-dominated Sorting Genetic Algorithm- II (NSGA II) multi-objective optimization method to effectively detect spam in IoT. The novelty of this study combines deep learning models through multi-objective optimization to simultaneously capture spatial and temporal dependencies, addressing the challenge of imbalanced spam data in IoT. Our method excels over baseline and previous approaches in IoT spam detection, leveraging real data to adeptly capture hidden dependencies and effectively address the inherent imbalances in spam data, resulting in heightened accuracy and reliability of the detection system.
The effects of HIIT/MICT on the inhibition of fat accumulation during training and detraining
Authors: Liu Yu , Wang Qiqi , Zhang Lukai , Liu Hui , Zhu Xian’gui , Li Hong , Zhang Haifeng 
Published: May 2024

Abstract

Background:
HIIT had at least comparable effect on inhibiting the increase of fat compared with MICT. However, few studies have been conducted to examine their effects of detraining on body fat with high-fat diet rats. This study aimed to compare the effects of 10-week high-intensity interval training (HIIT) and moderate intensity continuous training (MICT) as well as 6-week detraining on body fat in high-fat diet rats.
Methods:
After 8-week high-fat feeding, fifty-four rats were randomly assigned to six groups: 1)CON-T(n = 9): sedentary for 10 weeks (T10); 2)MICT-T(n = 9): 10-week MICT; 3)HIIT-T(n = 9): 10-week HIIT; 4)CON-D(n = 9):sedentary for 16 weeks (T16); 5)MICT-D(n = 9): 10-week MICT and 6-week training cessation; 6)HIIT-D(n = 9): 10-week HIIT and 6-week training cessation. The training cession performed 5 days/week. The subcutaneous (inguinal; SCAT), visceral (periuterine; VAT) adipose tissue and serum lipid profiles were analyzed by histological staining. ATGL expression in VAT was assessed by Western Blot at T10 and T16.
Results:
Ten-week HIIT and MICT inhibited the increase of SCAT, VAT and serum lipid levels compared with CON. After 6-week detraining, HIIT continued to inhibit the increase of adipose tissue mass whereas MICT at least maintained this inhibition induced by the training compared with CON. The inhibition primarily resulted from the adipocyte hypertrophy prevention. HIIT showed the most significant expression of ATGL after training and detraining.
Conclusions:
HIIT which had a comparable effect to MICT in preventing fat mass increase during training showed superior sustainability to MICT after detraining.
Exploring Pediatric Neuroblastoma: A Comprehensive Analysis of Adrenal and Non-Adrenal Tumor Characteristics in the United States
Authors: Al-Wawi Gaith Emad , Refai Omar Al , Al-Wawi Zaki Emad , Qasim Asma , Hammami M Bakri 
Published: May 2024

Abstract

Background and Purpose Neuroblastoma (NB) is an aggressive malignant tumor arising from a primitive neural crest origin. While the significance of tumor location in survival outcomes is recognized, it remains inadequately explored. This study provides a comprehensive analysis of the survival, and characteristics of pediatric adrenal and non-adrenal NB in the United States (US).Methods Retrospective analysis of pediatric primary NB between 1975 and 2016 was conducted using the Surveillance, Epidemiology and End Results (SEER) database. Univariate and multivariate regression analysis were used to determine prognostic variables.Results A total of 4554 patients were included, 52% Males (n = 2385) and 79.2% Caucasians (n = 3569). Median age was 1 year old [Range 0–19]. 44.4% (n = 1996) had adrenal NB and 55.6% (n = 2496) non-adrenal. Adrenal NB was significantly more prevalent among males and those presenting at a younger age (p < 0.001). Adrenal NB was more likely to have a higher grade and distant metastasis at diagnosis (p < 0.001). Non-adrenal NB, female sex, surgical resection, and later year of diagnosis were associated with improved survival (p < 0.001).Conclusion This study highlights important risk factors that are helpful for prognostication of NB patients in the US. Tailored approaches considering tumor site are crucial for effective management of NB.
A discrete element model for multi-field numerical analysis of the CO 2 transport in fractured rock matrix
Authors: Zhang Liwei , Liu Chun , Liu Hui , Chen Longlong 
Published: May 2024

Abstract

In order to investigate fluid flow in fractured porous media, this study presents a multi-field fracture-pore seepage model based on the discrete element method. The fluid transport, heat conduction and convection in pore system and fractures are considered in the model. The numerical model is validated using seepage tests to ensure correctness and accuracy. Besides, the established model is analyzed for two scenarios: isotropic micro-fractures and anisotropic micro-fractures with different numbers of micro-fractures. The relationship between the macro permeability and micro permeability is investigated, which is further used to determine different micro-fracture distributions based on the model and field conditions. Furthermore, the proposed model is applied to a field CO2 sequestration experiment to simulate the CO2 injection process, as well as the temperature, and pressure variations. The results indicate that the proposed model can provide insight into fracture distribution by combining macro-micro permeability relationship and field conditions. The results also help predict the fluid flow, facilitating the simulation of field engineering applications and investigation of fluid migration characteristics.
Carotid Body Tumor: Characteristics and Surgical Outcome
Authors: Kakamad Fahmi Hussein , Mustafa Mihr Naif , Yasin Shara Wahdaldeen , Xalid Shanga Sherzad , Mohammed Ayoob A. , Othman Snur , Hiwa Dilan S. , Abdullah Hiwa O. , Abdalla Berun A. , Nasralla Hawkar A. , Ahmed Sasan M. , Mustafa Ayman M. , Hassan Shko H. , Hussein Bushra O. 
Published: May 2024

Abstract

Background
Carotid body tumors are uncommon neuroendocrine growths near the carotid bifurcation. While some advocate preoperative embolization to minimize bleeding, others avoid it due to complications. This study shares the experience of a single center in managing patients with carotid body tumors without practicing preoperative embolization
Methods
This was a cross-sectional study of patients with carotid body tumors managed between 2020 and 2024. Data were collected from the hospital’s registry. Routine blood tests, neck ultrasonography, and computed tomography scans, when necessary, were conducted. The tumors were categorized according to Shamblin classification. The average duration of follow-up was 20 months.
Results
The study involved 25 patients, with 22 (88%) females and 3 (12%) males. Their ages ranged from 27 to 85 years old. Twenty (80%) cases presented with neck swelling, and six (24%) had positive medical history. Tumors were mainly on the right side (52%), with 20 (80%) showing ill-defined neck masses. Tumor sizes ranged from 1.5 to 7 cm, with Shamblin type II tumor being discovered in the majority of cases (72%). Types of tumors were significantly associated with the tumor size (p-value < 0.05). Blood transfusion was required in five cases (20%); three from type III and two from type II, with none from type I (p-value = 0.001). Temporary neurological deficits occurred in 3 cases (12%). No functional impairment or mortality was recorded.
Conclusions
Carotid body tumors are rare tumors with an unknown etiology. Operation without practicing preoperative embolization may be a feasible management with an acceptable outcome.
Investigating Geogenic Sources of Selenium in Shallow Groundwaters of Las Vegas Valley, USA
Authors: Ehsani Sahar , James David , Hodge Vernon , Zhou Xiaoping , Buck Brenda , Karakouzian Moses , Ahmad Izrar 
Published: May 2024

Abstract

Selenium concentrations above Environmental Protection Agency safe levels are of potential concern in various parts of the Las Vegas Valley in both water and sediment media. Previous studies suggest that the source of elevated selenium in the Valley is possibly resurfacing groundwater. Shallow groundwater flows into Las Vegas Wash wetlands and therefore has important environmental implications for surface water quality and aquatic life. The objective of this study was to identify the source of selenium in the shallow groundwater of the Las Vegas Valley through a detailed geochemical analysis. A comparison of major anions and cations concentrations and the 4 trace oxyanions (Se, B, As, and Mo) in the Quaternary alluvium (Qa) zone versus Quaternary to Tertiary (QTs) zone wells show that Qa wells consistently exhibit higher concentrations of all the mentioned parameters than QTs wells. The mean Qa concentrations of the major ions and trace oxyanions ranged between 130–728% higher than the mean QTs concentrations. Study results suggest that selenium concentrations in the shallow groundwater in the Qa zone were highly correlated (p < 0.01) with the major ions: Na+ (r = 0.88), K+ (r = 0.87), SO42− (r = 0.86), NO3−-N (r = 0.74), and TDS (r = 0.84), and EC (r = 0.87) indicating a common source genesis. However, in the QTs zone, correlations among Se and the mentioned parameters were not significant. Principal component analysis performed on the major ions, EC, TDS, and Se of Qa and QTs showed that Se was one of the influencing parameters in the first principal component of Qa; however, in QTs, Se did not contribute to the variations of the first principal component. Pearson correlations further corroborated that salinity is associated with Se, B, and As in the Qa zone and only associated with B in the QTs zone. Overall, many more significant associations of Se with water quality parameters were determined in the Qa than in the older QTs formations, indicating that geological processes and formations’ mineralogy have influenced the mentioned associations.
QSAR study of anti -leishmania activity of quinolines, A DFT calculation
Authors: Hosseini Sharieh , tootonphoroosh Zahra mashhadi ali 
Published: May 2024

Abstract

Leishmaniasis is a parasitic disease caused by infection with Leishmania parasites, which are spread by the bite of phlebotomine sand flies. Quinoline derivatives have shown potential as antileishmanial agents. However, it is important to note that quinoline derivatives are still in the research phase, and their clinical use for leishmaniasis treatment is not yet established. This study aimed to conduct QSAR modeling of quinoline derivatives and develop new drugs with anti leishmania properties. A total of 52 compounds were carefully chosen for this study. The optimized compounds and quantum descriptors were obtained using Gaussian software and the DFT/B3LYP computational method with a 6-31G (d) basis set. Other descriptors were determined using Dragon software. To analyze the relationship between these descriptors and the activity of the compounds, the MLR linear correlation method was employed. As a result, a QSAR equation with an R2 = 0.74 and R=0.86 was derived. The model's acceptability was further confirmed by the values of RMSE (0.48), and Q2 (0.62). The obtained equation indicates that the negative coefficients of MATS1v, GATS6m and HATS7u influence the activity of these compounds. This implies that as these descriptors' values increase, the compounds' activity decreases. Conversely, the activity of these compounds is influenced by the positive coefficients of HATS8e, R5u+, and G2u. In other words, as these descriptor values increase, the activity of the compounds also increases. This correlation between the experimental and predicted activity values demonstrates a strong relationship.
AG-Net: Category-level 6D Pose Estimation Network Based on Attention Mechanism and Global Enhancement
Authors: Bowen Shi , Jinlong Shi , Suqin Bai , Qiang Qian , Zhen Ou , Dan Xu , Ruixue Gong 
Published: May 2024

Abstract

How to effectively enhance feature extraction is a challenge faced by current 6D pose estimation methods. To address this issue, we propose a novel 6D pose estimation network based on VI-Net, shortened as AG-Net, which uses ECA block and Global enhancev module to enhance feature extraction: ECA block embeds a channel attention mechanism into the convolutional layers, replacing the fully connected layers with 1×1Conv to capture relationships between different channels and improves the performance of feature extraction. The Global enhancev module further processes the received information and enhances feature extraction by fusing global features, effectively balancing performance and speed, and better estimating the translation and size of objects. We applied the proposed AG-Net to category-level 6D pose estimation tasks and tested it on the REAL275 and CAMER25 datasets using IOU 3D intersection and n◦mcm evaluation metrics. The results showed that AG-Net outperformed current state-of-the-art methods. Our code and models are available at https://github.com/AFESDTTM/AG-Net
Correlation-Based Feature Selection of Single Cell Transcriptomics Data from Multiple Sources
Authors: Mitić Nenad S. , Malkov Saša N. , Ružičić Mirjana M. Maljković , Veljković Aleksandar N. , Čukić Ivan Lj. , Lin Xin , Lyu Minjie , Brusić² Vladimir 
Published: May 2024

Abstract

When using data mining or machine learning techniques on large and diverse datasets, it is often necessary to construct descriptive and predictive models. Descriptive models are used for discovering relationships among the attributes of the data while predictive models identify the characteristics of the data that will be collected in future. Bioinformatics data are high-dimensional, making it practically impossible to apply the majority of "classic" algorithms for classification and clustering. Even when the algorithms are useful, the training with large multidimensional data significantly increases the processing time. The algorithms specialized for working with high-dimensional data often cannot process data that contains large data sets that have several thousand dimensions (features). Dimension reduction methods (such as PCA) do not provide satisfactory results, and in addition, they obscure the meaning of the initial attributes in the data. For the constructed models to be usable, they must meet the requirement of scalability due to the large increase in the amount of bioinformatics data collected daily. Furthemore, the significance of the individual data features can also differ from source to source. This work describes an attribute selection method to efficiently classify high-dimensional (30,698) transcriptomics data collected from multiple sources. The proposed method was tested using 22 classification algorithms. The classification results for the selected sets of attributes are comparable to the results for the complete set of attributes.
Analyzing the effect of oceanic turbulence on spreading properties of the Whittaker-Gaussian laser beam
Authors: Nossir N. , Dalil-Essakali L. , Belafhal A. 
Published: May 2024

Abstract

This paper explores the spreading feature of the Whittaker-Gaussian light beam (WG) propagating through turbulent oceanic environments by utilizing the diffraction integral formula and under the Rytov approximation theory. From the analytical formula, some numerical simulations are derived and analyzed to examine the evolution of the axial intensity of the corresponding beam propagating through oceanic turbulence. The outcomes that were achieved show that the development of the variation of the intensity of the WG beam depends strongly on its starting parameters and oceanic variables including the wavelength, the beam waist, the dissipation rate of mean-square temperature, the ratio of temperature to salinity fluctuation and the dissipation rate of turbulent kinetic energy per unit mass of ocean. The outcomes acquired by our simulations have significant applications in the fields of subsea optical communication and imaging technologies.