bluuebunny/crossref_metadata_2025_split huggingface dataset:
Partitioning multi-layer edge network for neural network collaborative computing
Authors: Li Qiang , Zhou Ming-Tuo , Ren Tian-Feng , Jiang Cheng-Bin , Chen Yong 
Published: August 2023

AbstractThere is a trend to deploy neural network on edge devices in recent years. While the mainstream of research often concerns with single edge device processing and edge-cloud two-layer neural network collaborative computing, in this paper, we propose partitioning multi-layer edge network for neural network collaborative computing. With the proposed method, sub-models of neural network are deployed on multi-layer edge devices along the communication path from end users to cloud. Firstly, we propose an optimal path selection method to form a neural network collaborative computing path with lowest communication overhead. Secondly, we establish a time-delay optimization mathematical model to evaluate the effects of different partitioning solutions. To find the optimal partition solution, an ordered elitist genetic algorithm (OEGA) is proposed. The experimental results show that, compared with traditional cloud computing, single-device edge computing and edge-cloud collaborative computing, the proposed multi-layer edge network collaborative computing has a smaller runtime delay with limited bandwidth resources, and because of the pipeline computing characteristics, the proposed method has a better response speed when processing large number of requests. Meanwhile, the OEGA algorithm has better performance than conventional methods, and the optimized partitioning method outperforms other methods like random and evenly partition.
Blockchain based trusted execution environment architecture analysis for multi - source data fusion scenario
Authors: Yang Nan , Yang Li , Du Xingzhou , Guo Xunyi , Meng Fanke , Zhang Yuwen 
Published: August 2023

AbstractMulti-source data fusion techniques are widely applied in dynamic target detection scenarios, such as target situational awareness, radar signal resolution, and feature fusion labeling. Currently, techniques including clustering, neural networks, Bayesian analysis, and machine learning have been applied to improve the success rate of multi-source data fusion in terms of interference data noise reduction. The research on data tampering prevention of multiple data sources is mainly based on the data distributed authentication technology. The research on performing data fusion process in a trusted execution environment is mainly based on cryptography and codec technology. This paper focuses on the technical application architecture that can effectively improve the comprehensive efficiency of multi-source data fusion processing under the constraints of business scenarios. Accordingly, this paper proposes a trusted execution environment architecture based on blockchain technology for multi-source data fusion scenarios. It integrates the strategy of trusted data source data verification in blockchain smart contracts into the typical multi-source data fusion application architecture. After comparison tests in a simulation environment, the trusted execution environment architecture based on blockchain technology has shown considerable improvements in fusion success rate with limited performance cost.
Energy security of the European Union and corruption in Central Asia as the main challenges for the European sustainable energy future
Authors: Vasić Bojana , Pekić Ivan , Šimić Goran 
Published: August 2023

Abstract
Background
The main goal of the paper is to define, analyze and assess the basic security, development and institutional challenges faced by the Central Asian countries after 2022. Following the COVID-19 pandemic, and with the outbreak of the Ukrainian crisis, Europe faced problems in ensuring energy security, which were further complicated by its decision to stop importing natural gas from the Russian Federation. The Central Asian region is rich in energy resources, but at the same time, it is also a region of special geopolitical interest of often-conflicting parties, characterized by limited information and insufficient academic literature about development, various aspects of security, internal specificities and future challenges.

Methods
The research included qualitative and quantitative analyses carried out for Kazakhstan, the Kyrgyz Republic, Turkmenistan, Uzbekistan, Tajikistan and Germany. Data processing was performed based on 16 selected indicators in the fields of economy, energy, governance and climate change, for the time period 2011 to 2021. Data processing was performed using correlation and regression analysis (ANOVA).

Results
The results showed that corruption represents one of the biggest problems faced by the countries of Central Asia, with the biggest variations in the calculated Standardized Confidence level, which shows that this indicator trend, in relation to the 16 indicators used, is the least predictable. This represents a significant problem for all countries that are supplied with energy products from this region, or plan to do so. Energy security is positive only in the case of Turkmenistan. Regression analysis shows that Kazakhstan reported the best positive trend for most indicators. Data for Germany show consistent values over the observed period.

Conclusions
The main conclusions of the paper indicate that the countries of Central Asia have certain specificities when it comes to sustainable development, where energy security, corruption and government efficiency can be considered the biggest problems. The European Union must find ways and mechanisms to overcome these and many other impediments if they decide to import energy products from the aforementioned region.
Investigation and evaluation methods of shallow geothermal energy considering the influences of fracture water flow
Authors: Deng Fengqiang , Pei Peng , Ren Yonglin , Luo Tingting , Chen Yixia 
Published: August 2023

AbstractThe energy replenishment and heat convection induced by fracture water flowing through the rock mass impact the shallow geothermal energy occurrence, transfer and storage mechanisms in it. In this article, a suitability evaluation and categorization system is proposed by including judgement indexes that are more closely aligned with the actual hydrogeological conditions in fracture developed regions; an assessment approach of regional shallow geothermal energy is proposed by coupling the influences of fracture water into the calculation methods of geothermal capacity, thermal balance and heat transfer rate. Finally, by taking two typical fracture aperture distributions as examples, the impacts of fracture water on the investigation and evaluation of shallow geothermal energy are quantitatively analyzed. Although the fracture apertures only share 1.68% and 0.98% of the total length of a borehole, respectively, in the two examples, the fracture water convection contributes up to 11.01% and 6.81% of the total heat transfer rate; and the energy replenishment potential brought by the fracture water is equivalent to the total heat extraction of 262 boreholes. A single wide aperture fracture can dominate the aforementioned impacts. The research results can support more accurate evaluation and efficient recovery of shallow geothermal energy in fracture developed regions.
Detecting heterogeneity parameters and hybrid models for precision farming
Authors: Ibidoja Olayemi Joshua , Shan Fam Pei , Sulaiman Jumat , Ali Majid Khan Majahar 
Published: August 2023

AbstractPrecision farming (PF) plays a crucial role in the field of agriculture to solve the challenges of food shortages in society. Heterogeneity, multicollinearity, and outliers are problems in PF because they can cause bias and lead to incorrect inferences. However, traditional methods typically assume it to be a homogenous model, and in machine learning, data scientists ignore heterogeneity. In this study, the aim is to identify the heterogeneity parameters and develop hybrid models before and after heterogeneity. Data on seaweed is collected using sensor smart farming technology attached to v-Groove Hybrid Solar Drier (v-GHSD). There are 29 drying parameters, and each parameter has 1914 observations. We considered the highest order up to the second order interaction, and the parameters increased to 435 parameters from 29 parameters. In high-dimensional data, the number of observations is less than the number of parameters. The authors proposed a method using the variance inflation factor to identify the heterogeneity parameters. Seven predictive models such as ridge, random forest, support vector machine, bagging, boosting, LASSO and elastic net are used to select the 15, 25, 35 and 45 significant drying parameters for the moisture content removal of the seaweed, and hybrid models are developed using robust statistical methods. For before heterogeneity, the hybrid model random forest M Hampel with 19 outliers is the best, because it performs better when compared to other models. For after heterogeneity, the hybrid model boosting M Hampel with 19 outliers is the best, because it performs better when compared to other models. These results are vital to seaweed precision farming. The study of heterogeneity will not only help us to comprehend the dynamics of the large number of the drying parameters, but also gives a way to leverage the data for efficient predictive modelling.
Ensemble size versus bias correction effects in subseasonal-to-seasonal (S2S) forecasts
Authors: Han Ji-Young , Kim Sang-Wook , Park Chang-Hyun , Son Seok-Woo 
Published: August 2023

AbstractThis study explores the ensemble size effect on subseasonal-to-seasonal (S2S) forecasts of the European Center for Medium-Range Weather Forecasts (ECMWF) model. The ensemble forecast skill and its sensitivity to the ensemble size are assessed for the troposphere and stratosphere, and compared with theoretical estimates under the perfect model assumption. The degree of skill improvement in ensemble-mean forecasts with increasing ensemble size agrees well with theoretical estimates in the troposphere. However, in the stratosphere, increasing the ensemble size does not yield as much of the skill improvement as expected. Decomposition of the mean square skill score reveals that the weak ensemble size effect in the stratosphere is primarily caused by a large unconditional bias, which exhibits no apparent decrease with increasing ensemble size. Removing such bias significantly improves the S2S forecast skill and ensemble size effect, suggesting that bias correction is crucial for S2S forecasts, especially in the stratosphere.
Crushed, uncooked egg in the oropharynx: a café coronary?
Authors: Mgbehoma A. I. , Soyemi S. S. , Obafunwa J. O. 
Published: August 2023

Abstract
Background
Obstruction of the upper respiratory airway can terminate in fatal asphyxia. Autopsy findings in asphyxial deaths as described in literature are not necessarily pathognomonic. A complete autopsy with ancillary studies is necessary to establish the cause, time, and manner of death.

Case presentation
The authors present a 44-year-old male who was found dead in his car. He had been remanded in prison for drug trafficking 1 year prior to his death. No other history or death scene findings were provided by the police. Autopsy revealed a crushed, uncooked egg in his oropharynx. Postmortem radiology and toxicology were not done due to nonavailability of the required facilities. Death was ascribed to asphyxia due to a crushed, uncooked egg in the oropharynx.
The manner of death could not be ascertained because pertinent information regarding the deceased’s medical records, locus report, and other ancillary investigations was not available.

Conclusions
This report presents an unusual cause of mechanical upper airway obstruction that has never been documented and discusses some of the deficiencies of autopsy practice in resource-limited countries.
Comparison of analgesic efficacy of perineural dexamethasone in rectus sheath block and intravenous dexamethasone with levobupivacaine in bilateral rectus sheath block for patients undergoing midline abdominal surgery: a randomized controlled trial
Authors: Singariya Geeta , Saini Pradeep Kumar , Choudhary Usha , Kamal Manoj , Bihani Pooja , Choudhary Kusum , Khatri Chanda 
Published: August 2023

Abstract
Background
Dexamethasone is used in regional analgesia to prolong the duration of analgesia and anaesthesia. The perineural and intravenous (IV) dexamethasone in fascial plane block have conflicting results. The study aimed to compare analgesic efficacy of perineurally and intravenously dexamethasone in rectus sheath block (RSB). This prospective, double-blinded, randomized control study was conducted in 105 patients, equally divided in three groups. All the patients received ultrasound-guided RSB block with 20 ml of 0.25% levobupivacaine on each side. Additionally, in group A, 1-ml normal saline (NS) on each side in RSB block and 2-ml NS IV; in group B, 4-mg dexamethasone on each side in RSB block and 2-ml NS IV; and in group C, 1-ml NS on each side in RSB block and 8-mg dexamethasone IV.
The primary objective of the study was the duration of analgesia, and secondary objectives were total morphine consumption in the first 24 h, numeric rating scale (NRS) scores at rest and on cough, complications and patient’s satisfaction score.

Results
The duration of analgesia was maximum in group B (935.91 ± 121.82 min) and then in group C (730.31 ± 129.64 min) and group A (418.34 ± 29.22 min) (P < 0.0001). The morphine consumption and mean NRS score (at rest and cough) were lowest in group B and then group C and group A (P < 0.0001).

Conclusions
The perineural dexamethasone as an adjuvant to levobupivacaine prolongs the duration of analgesia with decreased analgesic requirements compared to intravenous dexamethasone in bilateral RSB in patients undergoing midline laparotomy surgery.
A quantum particle swarm optimization-based optimal LQR-PID controller for load frequency control of an isolated power system
Authors: Rene Ebunle Akupan , Fokui Willy Stephen Tounsi 
Published: August 2023

AbstractOne of the characteristics of a robust power grid is minimal variations in its frequency to load change or loss in generating unit(s). From the perspective of optimal control theory, the issue of load frequency control in the context of the interconnected functioning of power systems is investigated in this work, and a novel load frequency controller is proposed for a single area isolated power network. This novelty incorporates all the primary characteristics of the solutions that are based on a mixture of optimal controller designs by establishing a linear quadratic regulator optimized with quantum particle swarm optimization to design a proportional integral derivative (PID) controller unlike the conventional PID controller designs that are based on a combined Ziegler-Nichols and root locus (ZN-RL) method and manual tuning. The simulation results of the proposed controller using MATLAB show its efficacy in not only ensuring that there is no steady-state error in terms of the system frequency with load changes but also in achieving smoother transients. Following these landmark achievements, a transfer function model of the resulting power grid is constructed. The outcome of the model reveals that the system transients have been improved while keeping the intended steady-state characteristics. Furthermore, it is observed that the proposed load frequency controller has the best performance when compared with the combined ZN-RL method and the manual PID designs. This, therefore, demonstrates the superiority of the proposed design for load frequency control in power systems.
Effect of Roxadustat on Thyroid Function in Patients With Renal Anemia
Authors: Haraguchi Takuya , Hamamoto Yoshiyuki , Kuwata Hitoshi , Yamazaki Yuji , Nakatani Susumu , Hyo Takanori , Yamada Yuichiro , Yabe Daisuke , Seino Yutaka 
Published: August 2023

Abstract

Context
Roxadustat, a hypoxia-inducible factor prolyl hydroxylase (HIF-PH) inhibitor, a recently developed class of drugs for treatment of anemia in chronic kidney disease (CKD), is reported to have a structure unlike that of other HIF-PH inhibitors but similar to that of triiodothyronine and bind to the thyroid hormone receptor in vitro. However, reports on the effects of roxadustat on thyroid function are limited and not detailed, and it remains unknown whether other HIF-PH inhibitors also affect thyroid function.

Objective
To compare the effect of roxadustat with daprodustat, another HIF-PH inhibitor, on thyroid function in patients with renal anemia in CKD.

Methods
This retrospective observational study included a total of 26 patients with anemia in CKD who were treated with roxadustat or daprodustat; thyroid-stimulating hormone (TSH) and free thyroxine (FT4) were measured before and after treatment with the drugs.

Results
After initiation of roxadustat, TSH showed a significant decrease (2.4732 [1.7858-4.9016] μIU/mL before treatment and 0.659 [0.112-2.005] μIU/mL after treatment, P &lt; .05); FT4 showed a significant decrease (0.93 [0.84-1.05] ng/dL before treatment and 0.70 [0.53-0.85] ng/dL after treatment, P &lt; .01). After daprodustat initiation, neither TSH nor FT4 showed a significant change (TSH: 3.044 [1.853-4.171] μIU/mL before treatment and 2.893 [1.866-4.894] μIU/mL after treatment, P = .635; FT4 was 0.93 [0.81-1.00] ng/dL before treatment and 0.97 [0.87-1.05] ng/dL after treatment, P = .328).

Conclusion
Roxadustat decreases TSH and FT4 levels while daprodustat does not.
The Mineralocorticoid Receptor Plays a Crucial Role in Macrophage Development and Function
Authors: Faught Erin , Schaaf Marcel J M 
Published: August 2023

AbstractStress and the attendant rise in glucocorticoids (GCs) results in a potent suppression of the immune system. To date, the anti-inflammatory role of GCs, via activation of the glucocorticoid receptor, has been well-characterized. However, cortisol, the primary GC in both fish and humans, also signals through the high-affinity mineralocorticoid receptor (MR), of which the immunomodulatory role is poorly understood. Here, we tested the hypothesis that MR is a key modulator of leukocyte function during inflammation. Using transgenic MR knockout zebrafish with fluorescently labelled leukocytes, we show that a loss of MR results in a global reduction in macrophage number during key development stages. This reduction was associated with impaired macrophage proliferation and responsivity to developmental distribution signals, as well as increased susceptibility to cell death. Using a tail fin amputation in zebrafish larvae as a model for localized inflammation, we further showed that MR knockout larvae display a reduced ability to produce more macrophages under periods of inflammation (emergency myelopoiesis). Finally, we treated wild-type larvae with an MR antagonist (eplerenone) during definitive hematopoiesis, when the macrophages had differentiated normally throughout the larvae. This pharmacological blockade of MR reduced the migration of macrophages toward a wound, which was associated with reduced macrophage Ccr2 signalling. Eplerenone treatment also abolished the cortisol-induced inhibition of macrophage migration, suggesting a role for MR in cortisol-mediated anti-inflammatory action. Taken together, our work reveals that MR is a key modulator of the innate immune response to inflammation under both basal and stressed conditions.
The impact of CBCT-head tilting on 3D condylar segmentation reproducibility
Authors: El Bachaoui Samy , Verhelst Pieter-Jan , de Faria Vasconcelos Karla , Shaheen Eman , Coucke Wim , Swennen Gwen , Jacobs Reinhilde , Politis Constantinus 
Published: August 2023

Objectives: To investigate whether variations in head positioning may influence the reproducibility of cone-beam CT (CBCT) three-dimensional (3D) segmented models of the mandibular condyle. Methods: Five fresh frozen cadaver heads were scanned in four different positions: reference position (RP) and a set of three tilted alternative head positions (AP) in anteroposterior direction (AP1: 2 cm anterior translation, AP2: 5° pitch rotation, AP3: 10° pitch rotation). Surface models of mandibular condyles were constructed and compared with the condylar reference position using voxel-based registration. Descriptive statistics and a linear mixed-effects model were performed to compare condylar volumetric differences and root mean square (RMS) distance between surfaces of AP vs RP. Results: The mean differences in condylar volumes of AP vs RP were 14.1 mm³ (95% CI [−79.3, 107.4]) for AP1, 1.0 mm³ (95% CI [−87.2, 89.2]) for AP2 and 0.1 mm³ (95% CI [−88.3, 88.4]) for AP3. Mean and absolute volumetric differences did not exceed earlier reported intraoperator differences of 30 mm³. The RMS distance values obtained per group were 0.12 mm (95% CI [0.05,0.20]) for AP1, 0.17 mm (95% CI [0.10, 0.22]) for AP2 and 0.17 mm for AP3 (95% CI [0.10,0.22]). The confidence intervals (CI) for RMS distance remained far below the threshold for clinical acceptability (0.5 mm). Conclusions: Within the limits of the present study, it is suggested that tilted head positions may affect the reproducibility of 3D condylar segmentation, thereby influencing outcome in repeated CBCT scanning. Nevertheless, observed differences are unlikely to have a meaningful impact on clinical patient diagnosis and management.
Risk factors of colorectal cancer – literature review
Authors: Urbańczyk Agnieszka , Rutkowska Julia , Skorek Klaudia , Babiak Rafał , Rzęsa-Tokarczyk Żaneta , Bajak Karolina , Gawęda Agnieszka , Grabek Agata , Czuchryta Paulina , Domańska Anastazja 
Published: August 2023

Introduction and purpose: Colorectal cancer is one of the most common cancers in the world. It is very important to expand knowledge about this disease because it affects millions of people. Better understanding of the disease will help develop better prevention and treatment strategies. The aim of our work is to classify, analyze and describe colorectal cancer risk factors. This article was written based on articles found in the PubMed database.
State of knowledge: Colorectal cancer risk factors can be divided into two groups: modifiable and unmodifiable. Modifiable factors include: diet, low physical activity, smoking, alcohol, overweight and obesity. Unmodifiable factors include: age, sex, inflammatory bowel diseases, genetic factors, family history of colorectal cancer. Each of them increases the risk of developing the disease, the risk is the greater the more factors are present simultaneously. Modifiable factors seem to play a greater role in the development of the disease than unmodifable factors.
Summary: Studies of colorectal cancer risk factors may help in the development of prevention. It can also facilitate the personalization of preventive examinations and treatment. By influencing modifiable factors, we can reduce the risk of developing the disease, because following the principles of a healthy lifestyle can minimize the risk associated with genetic factors for the development of colorectal cancer.