bluuebunny/crossref_metadata_2025 huggingface dataset:
Improvidence, Precaution, and the Logical-Empirical Disconnect in UK Health Policy
Authors: Parsons Jordan A.
Published: December 2022

The last decade has seen significant developments in UK health policy, with are largely claimed to be evidence based. However, such a characterisation ought, in many cases, to be questioned. Policies can be broadly understood as based primarily on either a logical or empirical case. In the absence of relevant empirical evidence, policymakers understandably appeal to logical cases. Once such evidence is available, however, it can inform policy and enable the logical case to be set aside. Such a linear policy process is not always the reality, and logical cases often continue to guide policy decisions in direct opposition to empirical evidence. In this paper, I discuss two recent examples of this disconnect between logical and empirical cases in UK health policy. The first—organ donation—illustrates an example of a significant policy change being made in opposition to the evidence. I refer to this as the improvidence approach. The second—abortion—provides an example of policymakers not making a change that has extensive supporting data. I refer to this using the more recognisable language of the precautionary approach. Ultimately, I argue that both the improvidence and precautionary approaches are examples of problematic public policy where policymakers provide no explicit justification for going against the evidence.
Entrepreneurial networks, geographical proximity, and their relationship to firm growth: a study of 241 small high-tech firms
Authors: Löfsten Hans , Isaksson Anders , Rannikko Heikki
Published: December 2022

Start-up firms in high-tech sectors normally engage in networking to overcome their lack of resources, knowledge, and competence constraints. A newly established firm’s network can provide a source of social capital, which may enhance its growth prospects. In this study, 241 new technology-based firms (NTBFs) in Sweden are studied during their early formative years to investigate how entrepreneurial networks and the geographical proximity to actors in these networks affect the early performance of these firms in terms of growth. Three underlying factors are identified in the analysis: geographical proximity and professional and consultative networks. This study finds that professional networks have a positive and significant effect on NTBFs’ growth, which indicate that utilizing these networks benefit the growth of both young and growing firms. NTBFs in initial stages can acquire business opportunities by constructing professional networks. In addition, several formal links positively affect growth, such as regional business partners, incubator networks, and links to universities.
Conventional and emerging treatments of astrocytomas and oligodendrogliomas
Authors: Kessler Tobias , Ito Jakob , Wick Wolfgang , Wick Antje
Published: December 2022

Purpose

Astrocytomas and oligodendrogliomas are mainly diffuse primary brain tumors harboring a diagnostic and prognostically favorable isocitrate dehydrogenase mutation. They are still incurable besides growing molecular knowledge and therapy options. Circumscribed astrocytomas are also discussed here, although they represent a separate entity despite similarities in the nomenclature.

Methods

We reviewed clinical trials, preclinical approaches as well as guideline recommendations form the major scientific Neuro-Oncology organizations for astrocytomas and oligodendrogliomas according to PRISMA guidelines.

Results

After histopathological diagnosis and eventually a maximal safe resection, patients with good prognostic factors may be followed by magnetic resonance imaging (MRI). If further treatment is necessary, either after diagnosis or at progression, diffuse astrocytomas and oligodendrogliomas are mainly treated with combined radiochemotherapy or maximal safe resection followed by combined radiochemotherapy according to current guidelines based on randomized trials. Circumscribed gliomas like pilocytic astrocytomas, CNS WHO grade 1, or pleomorphic xanthoastrocytomas, CNS WHO grade 2, are often treated with surgery alone. Current approaches for therapy optimization include decision of the best chemotherapy regimen. The IDH mutation presents a rational target for small molecule inhibition and immune therapy in diffuse astrocytomas and oligodendrogliomas, while the BRAF pathway is frequently mutated and treatable in circumscribed gliomas.

Conclusion

Despite establishment of standard treatment approaches for gliomas that include resection, radio- and chemotherapy, there is a lack of effective treatments for progressive disease. Immune- and targeted therapies are currently investigated.
Analyse contrastive des textes de décisions judiciaires en la langue française, allemande et polonaise
Authors: Flöter-Durr Margarete , Nowak-Korcz Paulina
Published: December 2022

This article deals with the notion of jurisdictional discourse, which, as a specific type of complex discourse, always poses a real challenge to translators. The authors present a contrastive analysis of the texts of legal decisions in French, German and Polish in order to demonstrate the difficulties in translation and the consequences which they entail, and to suggest a strategy for overcoming them. Firstly, the authors briefly compare the texts of judicial decisions indicating their characteristics both in terms of the macrostructure of the text and in terms of syntactic and lexical units. Secondly, they explain the origin of the difficulties in translation resulting from the qualitative differences of the legal systems. Thirdly, the different types of difficulties are described and illustrated by practical examples, in order to make experienced translators and apprentice translators sensitive to them. The corpus used for the analysis consists of the integral and documented texts of the French, German and Polish judgments rendered in matters of civil law [37]. It should also be noted that the analyzed texts are comparable texts, which are a valuable tool for translators and allow them to acquire means of expression that are as natural as possible [40]. Regarding the methodology, the authors adopt for the analysis the contrastive method, borrowed from the theory of cultural transfer [15].
Coercion, voluntary exchange, and the Austrian School of Economics
Authors: Megger Dawid , Wysocki Igor
Published: December 2022

In this paper we analyse the concept of coerced exchange (and partly of voluntary exchange inasmuch as the absence of coercion is its necessary condition), which is of utmost importance to economic theory in general and to the Austrian School of Economics in particular. The subject matter literature normally assumes that a coerced action occurs under threat. Threats in turn can be studied from the perspective of speech act theory, which is concerned with the speaker’s intentions. Ultimately, our goal is to provide a descriptive (i.e. non-moralized) definitions of threat and coercion, based on the analysis of the coercer’s intentions. If successful, we would be in a position to present such an account of coerced and voluntary exchanges that is compatible with both speech act theory and the Austrian methodology. Although we focus on the Austrian School of Economics, we believe that our investigations might impact on economic theory in general. We also criticize a rights-based account of coercion employed in the research practice of some neo-Austrians and based on the libertarian ethic of property rights.
A Note on the Connection Between Trek Rules and Separable Nonlinear Least Squares in Linear Structural Equation Models
Authors: Ernst Maximilian S. , Peikert Aaron , Brandmaier Andreas M. , Rosseel Yves
Published: December 2022

We show that separable nonlinear least squares (SNLLS) estimation is applicable to all linear structural equation models (SEMs) that can be specified in RAM notation. SNLLS is an estimation technique that has successfully been applied to a wide range of models, for example neural networks and dynamic systems, often leading to improvements in convergence and computation time. It is applicable to models of a special form, where a subset of parameters enters the objective linearly. Recently, Kreiberg et al. (Struct Equ Model Multidiscip J 28(5):725–739, 2021. https://doi.org/10.1080/10705511.2020.1835484) have shown that this is also the case for factor analysis models. We generalize this result to all linear SEMs. To that end, we show that undirected effects (variances and covariances) and mean parameters enter the objective linearly, and therefore, in the least squares estimation of structural equation models, only the directed effects have to be obtained iteratively. For model classes without unknown directed effects, SNLLS can be used to analytically compute least squares estimates. To provide deeper insight into the nature of this result, we employ trek rules that link graphical representations of structural equation models to their covariance parametrization. We further give an efficient expression for the gradient, which is crucial to make a fast implementation possible. Results from our simulation indicate that SNLLS leads to improved convergence rates and a reduced number of iterations.
Establishment and validation of a prediction model for the first recurrence of Budd–Chiari syndrome after endovascular treatment: a large sample size, single-center retrospective study
Authors: Wang Zhongkai , Wang Ziwei , Zhang Zhiyuan , Li Jiandong , Pan Zhiyang , Liu Ang , Lu Jian , Guo Jinhe , Zu Maoheng , Xu Hao
Published: December 2022

Objective

To investigate the independent risk factors for the first recurrence after endovascular management in patients with Budd–Chiari syndrome (BCS), and to establish a prediction model for predicting recurrence in target patients.

Methods

BCS patients who underwent endovascular treatment in the Affiliated Hospital of Xuzhou Medical University from January 2010 to December 2015 were retrospectively examined, with their clinical, laboratory test, and imaging data collected and analyzed. Independent risk factors for recurrence were identified, and a prediction model was established and validated.

Results

A total of 450 patients met the filtering criteria, and 102 recurred during the follow-up. The median follow-up time was 87 months, ranging from 1 to 137 months. The 1-, 3-, 5- and 10-year cumulative recurrence rate was 9.11% (6.41–11.73%), 17.35% (13.77–20.78%), 20.10% (16.30–23.72%), and 23.06% (18.86–27.04%), respectively. Liver cirrhosis, ascites, thrombosis, and all the main intrahepatic drainage veins obstructed (obstructed HV + AHV) are independent risk factors, while age is an independent protective factor. The prediction model was named MRBET. Based on the model, the risk score of each patient equals (−0.385981 * Age/10) + (0.0404184 * PT) + (0.0943423 * CRE/10) + (0.0157053 * LDH/10) + (0.592179 * LC) + (0.896034 * Ascites) + (0.691346 * Thrombosis) + (0.886741 * obstructed HV + AHV), and those in the high-risk group (risk score ≥ 1.57) were more likely to recur than those in the low-risk group (HR = 6.911, p < 0.001). The MRBET model is also available as a web tool at https://mrbet.shinyapps.io/dynnomapp.

Conclusion

Liver cirrhosis, ascites, thrombosis, and obstructed HV + AHV are independent risk factors for the first recurrence; age is an independent protective factor. The prediction model can effectively and conveniently predict the risk of recurrence and screen out patients at a high recurrence risk.
Evidence-based capacity of natural cytochrome enzyme inhibitors to increase the effectivity of antineoplastic drugs
Authors: Manthalkar Laxmi , Ajazuddin  , Bhattacharya Sankha
Published: December 2022

Cytochrome (CYP) enzymes catalyze the metabolism of numerous exogenous and endogenous substrates in cancer therapy leading to significant drug interactions due to their metabolizing effect. CYP enzymes play an important role in the metabolism of essential anticancer medications. They are shown to be overexpressed in tumor cells at numerous locations in the body. This overexpression could be a result of lifestyle factors, presence of hereditary variants of CYP (Bio individuality) and multi-drug resistance. This finding has sparked an interest in using CYP inhibitors to lower their metabolizing activity as a result facilitating anti-cancer medications to have a therapeutic impact. As a result of the cytotoxic nature of synthetic enzyme inhibitors and the increased prevalence of herbal medication, natural CYP inhibitors have been identified as an excellent way to inhibit overexpression sighting their tendency to show less cytotoxicity, lesser adverse drug reactions and enhanced bioavailability. Nonetheless, their effect of lowering the hindrance caused in chemotherapy due to CYP enzymes remains unexploited to its fullest. It has been observed that there is a substantial decrease in first pass metabolism and increase in intestinal absorption of chemotherapeutic drugs like paclitaxel when administered along with flavonoids which help suppress certain specific cytochrome enzymes which play a role in paclitaxel metabolism. This review elaborates on the role and scope of phytochemicals in primary, secondary and tertiary care and how targeted prevention of cancer could be a breakthrough in the field of chemotherapy and oncology. This opens up a whole new area of research for delivery of these natural inhibitors along with anticancer drugs with the help of liposomes, micelles, nanoparticles, the usage of liquid biopsy analysis, artificial intelligence in medicine, risk assessment tools, multi-omics and multi-parametric analysis. Further, the site of action, mechanisms, metabolites involved, experimental models, doses and observations of two natural compounds, quercetin & thymoquinone, and two plant extracts, liquorice & garlic on CYP enzymes have been summarized.

Graphical Abstract
Fabrication of an erbium–ytterbium-doped waveguide amplifier at communication wavelengths for integrated optics applications
Authors: Mirhosseini Shaghayegh , Kazemikhah Payman , Aghababa Hossein , Kolahdouz Mohammadreza
Published: December 2022

Erbium–ytterbium-doped waveguide amplifiers provide a considerable gain at telecom wavelengths, low noise, nonlinearity, and compatibility with optical networks, making it an outstanding amplification module for telecommunication systems. This study reports on the fabrication of an optical waveguide amplifier for integrated optics. The signal can be amplified by using rare-earth dopings such as erbium (Er), which works at telecommunication wavelengths, i.e., 1.55 μm. Er-doped phosphate glass waveguides can be deposited using the sol–gel method, which is convenient for preparing active films on several substrates. The Er concentration was 1–2 × 1020/cm3. The confinement and the gain of the waveguide can be increased by reducing the width of the waveguide to 0.5 μm. In such a case, more than 1dB net gain can be achieved without additional pump power. The other material used as a dopant in optical amplifiers is ytterbium (Yb). For Er energy levels, a more significant pump intensity is necessary for inversion due to the limited absorption cross-section. This issue is solved by including a substance with a large absorption cross-section that transfers energy to Er. The Ag–Na ion exchange process is then used to fabricate the buried waveguide. In such a process, ions trade between the core material and the molten salt. Then, the waveguide is immersed in the molten salt. The fabricated waveguide has low loss, and a net gain of around 2 dB at a wavelength of approximately 1.55 μm in Er:Yb:Al: phospho silicate glass is achieved. The focus of the research is on the fabrication procedure (materials and methods) of the waveguide.
A Hybrid Picture Fuzzy Similarity Measure and Improved VIKOR Method
Authors: Li Linyu , Chen Zichun , Jiang Xiaowei
Published: December 2022

Picture fuzzy set (PFS) can intuitively express the answers of “yes”, “neutral”, “no” and “reject”, which have strong advantages in solving uncertain information. The similarity measure is an effective tool to determine the relationship between two picture fuzzy sets (PFSs). In this paper, we propose a hybrid picture fuzzy (PF) similarity measure which combines the Hamming distance and the transformed tetrahedral centroid distance and verifies that it satisfies the four properties of the similarity measure. The proposed and existing picture fuzzy similarity measures are compared and investigated through numerical examples and some applications of pattern recognition. The results show that the proposed similarity measure not only produces no unreasonable results, but also overcomes the shortcomings of the existing similarity measures. Furthermore, we investigate an improved VIKOR method based on the proposed similarity measure of PFS. Finally, through an example, several multi-attribute decision-making (MADM) methods are compared and analyzed to illustrate the effectiveness and practicability of the improved VIKOR method.
Research on the Recognition Method of the Axle End Mark of a Train Wheelset Based on Machine Vision
Authors: He Yuchun , Liu Dezhi , Zeng Yong , Lu Qian , Yao Suheng , Yuan Yuxin
Published: December 2022

Whether the wheelset of a high-speed train has defects such as cracks is very important to the safety of high-speed trains. Hence, the wheelset must be regularly inspected for flaws. For flaw detection of a wheelset, it is necessary to record the axle end information of the wheelset to correlate with the flaw detection results. To quickly and accurately identify the axle end mark of the wheelset, an automatic identification method based on machine vision is proposed. Our method identifies seven types of marks on the axle end, including the smelting number, steel grade number, unit number, sequence number, year and month, axle type mark, and the azimuth mark. Using the established automatic identification method of axle end marks, based on Retinex theory, an improved dual-core Laplacian combined with Gaussian filtering operation is proposed to solve the problem of the low contrast of the wheelset axle end image. An improved image tilt correction algorithm based on the combination of Hough circle detection and bilinear interpolation is proposed, which solves the angle tilt problem of the target character area of the axis end image. To handle the various types of axis end markers and the small amount of data, a retraining method to improve recognition accuracy is proposed. This method first uses Chi_Sim as the basic font for training and then retrains based on the trained font. Finally, Tesseract-OCR is used to improve the accuracy of the recognition results. Experiments are carried out by developing an automatic recognition program for axle end marks. The results show that the proposed method can effectively identify and classify seven-character types, and the recognition accuracy reaches 96.88% while the recognition time of each image is 5.88 s.
Modeling Perennial Bioenergy Crops in the E3SM Land Model (ELMv2)
Authors: Sinha Eva , Calvin Katherine V. , Bond‐Lamberty Ben , Drewniak Beth A. , Ricciuto Daniel M. , Sargsyan Khachik , Cheng Yanyan , Bernacchi Carl , Moore Caitlin E.
Published: December 2022

Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties of the terrestrial ecosystem. Few Earth System Models (ESMs) represent such crops, however. In this study, we expand the Energy Exascale Earth System Land Model to include perennial bioenergy crops with a high potential for mitigating climate change. We focus on high‐productivity miscanthus and switchgrass, estimating various parameters associated with their different growth stages and performing a global sensitivity analysis to identify and optimize these parameters. The sensitivity analysis identifies five parameters associated with phenology, carbon/nitrogen allocation, stomatal conductance, and maintenance respiration as the most sensitive parameters for carbon and energy fluxes. We calibrated and validated the model against observations and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The validated model represents the latent heat flux fairly well, but sensible heat flux for miscanthus is not well captured. Finally, we validated the model against observed leaf area index (LAI) and harvest amount and found modeled LAI captured observed seasonality, although the model underestimates LAI and harvest amount. This work provides a foundation for future ESM analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger Earth system, and sets the stage for studying the impact of future biofuel expansion on climate and terrestrial systems.
Machine learning and hypothesis driven optimization of bull semen cryopreservation media
Authors: Tu Frankie , Bhat Maajid , Blondin Patrick , Vincent Patrick , Sharafi Mohsen , Benson James D.
Published: December 2022

Cryopreservation provides a critical tool for dairy herd genetics management. Due to widely varying inter- and within-bull post thaw fertility, recent research on cryoprotectant extender medium has not dramatically improved suboptimal post-thaw recovery in industry. This progress is stymied by the interactions between samples and the many components of extender media and is often compounded by industry irrelevant sample sizes. To address these challenges, here we demonstrate blank-slate optimization of bull sperm cryopreservation media by supervised machine learning. We considered two supervised learning models: artificial neural networks and Gaussian process regression (GPR). Eleven media components and initial concentrations were identified from publications in bull semen cryopreservation, and an initial 200 extender-post-thaw motility pairs were used to train and 32 extender-post-thaw motility pairs to test the machine learning algorithms. The median post-thaw motility after coupling differential evolution with GPR the increased from 52.6 ± 6.9% to 68.3 ± 6.0% at generations 7 and 17 respectively, with several media performing dramatically better than control media counterparts. This is the first study in which machine learning was used to determine the best combination of constituents to optimize bull sperm cryopreservation media, and provides a template for optimization in other cell types.
Effects of different applied voltages of irreversible electroporation on prostate cancer in a mouse model
Authors: Kim Hong Bae , Zeng Chu Hui , Kim Yunlim , Jeong Seung , Kim Song Hee , Kang Jeon Min , Park Yubeen , Won Dong-Sung , Kim Ji Won , Ryu Dae Sung , Lim Bumjin , Park Jung-Hoon
Published: December 2022

As a non-thermal ablation method, irreversible electroporation (IRE) has been widely investigated in the treatment of prostate cancer. However, no consensus has been achieved on the optimal parameters of IRE for prostate cancer. Since high voltage is known to carry risks of muscle contraction and patient discomfort, it is crucial to identify the minimum but effective and safer applied voltage to inhibit tumor growth. In this study, the effect of different applied voltages of IRE on prostate cancer was evaluated in BALB/c nude mice. Mathematical simulation and measurement of the actual ablation area revealed a larger ablation area at a higher voltage. In in vivo experiment, except for the three different voltages applied, all groups received identical electrical conditions: pulse number, 180 (20 groups × 9 pulses/group); pulse width, 100 µs; pulse interval, 2 ms; distance between the electrodes, 5 mm; and electrode exposure length, 15 mm. Whilst the tumor volume initially decreased in the 500 V (1000 V/cm) and 700 V (1400 V/cm) groups and subsequently increased, only a transient increase followed by a continuous decrease until the sacrifice was observed in the 900 V (1800 V/cm) group. This result demonstrated a lasting effect of a higher applied voltage on tumor growth inhibition. The histological, immunohistochemical, and western blot findings all confirmed IRE-induced apoptosis in the treatment groups. Taken together, 900 V seemed to be the minimum applied voltage required to reduce tumor growth, though subsequent studies are anticipated to further narrow the voltage intervals and lower the minimum voltage required for tumor inhibition.
Observation and simulation of atmospheric gravity waves exciting subsequent tsunami along the coastline of Japan after Tonga explosion event
Authors: Nishikawa Yasuhiro , Yamamoto Masa-yuki , Nakajima Kensuke , Hamama Islam , Saito Hiroaki , Kakinami Yoshihiro , Yamada Masumi , Ho Tung-Cheng
Published: December 2022

Tsunamis are commonly generated by earthquakes beneath the ocean floor, volcanic eruptions, and landslides. The tsunami following the Tonga eruption of 2022 is believed to have been excited by atmospheric pressure fluctuations generated by the explosion of the volcano. The first, fast-traveling tsunami was excited by Lamb waves; however, it has not been clarified observationally or theoretically which type of atmospheric fluctuations excited more prominent tsunami which followd. In this study, we investigate atmospheric gravity waves that possibly excited the aforementioned subsequent tsunami based on observations and atmosphere-ocean coupling simulations. The atmospheric fluctuations are classified as Lamb waves, acoustic waves, or gravity waves. The arrival time of the gravity wave and the simulation shows that the gravity wave propagated at a phase speed of 215 m/s, coinciding with the tsunami velocity in the Pacific Ocean, and suggesting that the gravity wave resonantly excited the tsunami (Proudman resonance). These observations and theoretical calculations provide an essential basis for investigations of volcano-induced meteotsunamis, including the Tonga event.
Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing
Authors: Khan Sulaiman , Khan Habib Ullah , Nazir Shah
Published: December 2022

Big data has revolutionized the world by providing tremendous opportunities for a variety of applications. It contains a gigantic amount of data, especially a plethora of data types that has been significantly useful in diverse research domains. In healthcare domain, the researchers use computational devices to extract enriched relevant information from this data and develop smart applications to solve real-life problems in a timely fashion. Electronic health (eHealth) and mobile health (mHealth) facilities alongwith the availability of new computational models have enabled the doctors and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. Digital transformation of healthcare systems by using of information system, medical technology, handheld and smart wearable devices has posed many challenges to researchers and caretakers in the form of storage, minimizing treatment cost, and processing time (to extract enriched information, and minimize error rates to make optimum decisions). In this research work, the existing literature is analysed and assessed, to identify gaps that result in affecting the overall performance of the available healthcare applications. Also, it aims to suggest enhanced solutions to address these gaps. In this comprehensive systematic research work, the existing literature reported during 2011 to 2021, is thoroughly analysed for identifying the efforts made to facilitate the doctors and practitioners for diagnosing diseases using healthcare big data analytics. A set of rresearch questions are formulated to analyse the relevant articles for identifying the key features and optimum management solutions, and laterally use these analyses to achieve effective outcomes. The results of this systematic mapping conclude that despite of hard efforts made in the domains of healthcare big data analytics, the newer hybrid machine learning based systems and cloud computing-based models should be adapted to reduce treatment cost, simulation time and achieve improved quality of care. This systematic mapping will also result in enhancing the capabilities of doctors, practitioners, researchers, and policymakers to use this study as evidence for future research.
Search and rescue system-of-systems influence degree evaluation of aviation equipment based on simulation
Authors: Gao Yan , Liu Hu , Niu Fu , Tian Yongliang , Wang Jin , Cheng Wangchi
Published: December 2022

Search and rescue (SAR) is an important part of joint operations, and also one of the key supports for ensuring combat effectiveness. Aviation equipment is a major component of SAR action. Therefore, the SAR capability of aviation equipment has become the key to affecting the overall SAR action. This paper proposes the concept of the system of systems influence degree (SoSID) and conducts a scientific quantitative evaluation to quantitatively measure the effect of aviation equipment used in SAR. First, according to the characteristics of SAR action in threat environments, the SAR capability of aviation equipment is analyzed, and an indicator decomposition hierarchy model based on this SAR capability is proposed. Second, based on the above model, the DECIDE (destroy, execute, cost, implement, defend, evade) SoSID evaluation model is proposed. Third, a comparative test is designed and a sensitivity analysis is conducted based on the sobol power sensitivity (SPS) analysis method to obtain the index sensitivity of the SAR capability. The sensitivity is then ranked to obtain key indicators. Finally, we build a simulation test environment to obtain multiple test plans for comparison and verify the rationality of the index decomposition hierarchy model and the SoSID evaluation model as well as the effectiveness of the SPS analysis method through analysis of the simulation results.
Incidental nodal irradiation in patients with esophageal cancer undergoing (chemo)radiation with 3D-CRT or VMAT
Authors: Peschel David Paul , Düsberg Mathias , Peeken Jan C. , Kaiser Jan Christian , Borm Kai Joachim , Sommer Katharina , Combs Stephanie E. , Münch Stefan
Published: December 2022

The extent of elective nodal irradiation (ENI) in patients undergoing definitive chemoradiotherapy (dCRT) for esophageal squamous cell carcinoma (ESCC) remains unclear. The aim of this dosimetric study was to evaluate the extent of incidental nodal irradiation using modern radiation techniques. A planning target volume (PTV) was generated for 30 patients with node-negative esophageal carcinoma (13 cervical/upper third, 7 middle third, 10 lower third/abdomen). Thereby, no elective nodal irradiation (ENI) was intended. Both three-dimensional conformal radiotherapy (3D-CRT) and volumetric-modulated arc therapy (VMAT) treatment plans (50 Gy in 25 fractions) were calculated for all patients. Fifteen nodal stations were contoured according to the definitions of the AJCC and investigated in regard to dosimetric parameters. Compared to 3D-CRT, VMAT was associated with lower dose distribution to the organs at risk (lower Dmean, V20 and V30 for the lungs and lower Dmean and V30 for the heart). For both techniques, the median Dmean surpassed 40 Gy in 12 of 15 (80%) nodal stations. However, VMAT resulted in significantly lower Dmeans and equivalent uniform doses (EUD) compared to 3D-CRT for eight nodal stations (1L, 2L, 2R, 4L, 7, 8L, 10L, 15), while differences did not reach significance for seven nodal station (1R, 4R, 8U, 8M, 10R, 16). For dCRT of ESCC, the use of VMAT was associated with significantly lower median (incidental) doses to eight of 15 regional lymph node areas compared to 3D-CRT. However, given the small absolute differences, these differences probably do not impair (regional) tumor control rates.
Evaluation of center of mass estimation for obese using statically equivalent serial chain
Authors: Chebel Elie , Tunc Burcu
Published: December 2022

The complex structure of the human body makes its center of mass (CoM) estimation very challenging. The typically used estimation methods usually suffer from large estimation errors when applied to bodies with structural differences. Thus, a reliable estimation method is of utmost importance. In this paper, we present a detailed evaluation of a subject-specific CoM estimation technique named Statically Equivalent Serial Chain (SESC) by investigating its estimation ability over two different groups of subjects (Fit and Obese) in comparison to the segmental analysis method. For this study, we used an IMU-based motion capture system and a force platform to record the joint angles and corresponding center of pressure (CoP) values of twenty-five participants while performing a series of static postures. The root-mean-square errors (RMSE) of SESC’s estimation for both groups showed close and lower mean values, whereas the segmental analysis method showed significantly larger RMSE values in comparison to SESC (p < 0.05). In addition, we used the Bland–Altman analysis to evaluate the agreement between the two techniques and the ground truth CoP, which showed the accuracy, precision, and reliability of SESC over both groups. In contrast, the segmental analysis method did not present neither accurate nor precise estimations, as our analysis revealed considerable fixed and proportional biases.
The prevalence of ocular Demodex folliculorum in 2253 young males
Authors: Ye Qian , Yan Weiming , Wang Yunpeng , Chen Meizhu
Published: December 2022

To investigate the prevalence and influencing factors of Demodex folliculorum (DF) in the eyelashes of healthy young males. An epidemiological cross-sectional prevalence study was conducted. We conducted visual acuity, eye-related examination, eyelash microscopic examination and DF count of recruits in Fujian Province in 2019. The presence of DF was analyzed according to age, keratorefractive surgery, annual household income, educational level, long-term residence, sleep time, time of using electronic products, smoking and drinking habit. A total of 2253 healthy young males (aged 17–24 years) were studied for the presence of DF within eyelash follicles. The total prevalence of DF was 20.73% in our study. Subjects with history of keratorefractive surgery had a statistically significant increase in the prevalence of DF (P < 0.001). The prevalence of DF was higher in subjects with ocular symptoms than in those without symptoms (P < 0.05). Factors such as the educational level and so on we analyzed had no significant correlation with the prevalence of DF (all P > 0.05). According to the multivariate logistic regression analysis, the history of keratorefractive surgery was the risk factors of DF infection (P < 0.001), and the risk of infection was 1.437 times higher in the population with the history of keratorefractive surgery than in the population without. There was no correlation between ocular discomfort and DF infection (P > 0.05). The prevalence of DF in eyelash follicles in healthy young males was relatively high. The history of keratorefractive surgery was an important risk factor for the infection.
Performance evaluation and financial viability analysis of grid associated 10 MWP solar photovoltaic power plant at UP India
Authors: Singh Shailendra , Alharthi Majed , Anand Abhishek , Shukla Amritanshu , Sharma Atul , Panchal Hitesh
Published: December 2022

The main aim of this simulation work is to assess the financial possibility analysis of 10 MWP grid-associated solar photovoltaic (PV) power plants in seven cities i.e. Lucknow, Agra, Meerut, Gorakhpur, Kanpur, Allahabad, and Varanasi of Uttar Pradesh (UP) state of India with the RETScreen Software. The presented research work demonstrates the method of selection of profitable locations for solar PV power plants according to financial viability indicators. It is found that Allahabad city is the most profitable site with values of 16,686 MWh of electricity exported to the grid (EEG), US$20,896.30/year of electricity export revenue (EER), 9.4 years of simple payback period (SPP), 7.7 years of equity payback period (EPP), 19545.9 tCO2/year of GHG emission reduction, US$3492.82/year of the annual life cycle savings (ALCS), 1.5 benefit-cost (B-C) ratio, US$27394.59 of net present value (NPV), 16.5% internal rate of return on equity (IRR-equity), 12.3% modified internal rate of return on equity (MIRR-equity), 5.4% internal rate of return on assets (IRR-assets), and 7% modified internal rate of return on assets (MIRR-assets). The second most profitable site is found in Gorakhpur city and Varanasi city is found the least profitable site. The other two cities, Agra and Kanpur are not found suitable because of the negative values of NPV and ALCS.
Diarylation of thiazolopyrimidines by laccase and their in vitro evaluation as antitumor agents
Authors: Shahedi Mansour , Shahani Rojina , Habibi Zohreh , Yousefi Maryam , Brask Jesper , Minaei-Tehrani Arash , Samadi Fatemeh Yazdi , Mohammadi Mehdi
Published: December 2022

A mild and efficient method was developed for the synthesis of new derivatives of thiazolo[3,2-a] pyrimidin-3(2H)-ones from available starting materials based on the oxidation of catechols to ortho-quinone by Myceliophthora thermophila laccase (Novozym 51,003) and 1,4-addition of active methylene carbon to these in situ generated intermediates in moderate to good yields (35–93%). The structure of the products was confirmed through 1H NMR, 13C NMR, HMBC, HSQC, DEPT-135, and mass spectroscopy techniques. These novel compounds were evaluated as active antitumor agents against human colorectal adenocarcinoma and liver adenocarcinoma cell lines. All compounds displayed potent inhibition activities against the HT-29 cell line with IC50 values of 9.8–35.9 µM, superior to the positive control doxorubicin, and most showed potent anticancer activities against the HepG2 cell line.
Hybrid fuzzy deep neural network toward temporal-spatial-frequency features learning of motor imagery signals
Authors: Sorkhi Maryam , Jahed-Motlagh Mohammad Reza , Minaei-Bidgoli Behrouz , Daliri Mohammad Reza
Published: December 2022

Achieving an efficient and reliable method is essential to interpret a user’s brain wave and deliver an accurate response in biomedical signal processing. However, EEG patterns exhibit high variability across time and uncertainty due to noise and it is a significant problem to be addressed in mental task as motor imagery. Therefore, fuzzy components may help to enable a higher tolerance to noisy conditions. With the advent of Deep Learning and its considerable contributions to Artificial intelligence and data analysis, numerous efforts have been made to evaluate and analyze brain signals. In this study, to make use of neural activity phenomena, the feature extraction preprocessing is applied based on Multi-scale filter bank CSP. In the following, the hybrid series architecture named EEG-CLFCNet is proposed which extract the frequency and spatial features by Compact-CNN and the temporal features by the LSTM network. However, the classification results are evaluated by merging the fully connected network and fuzzy neural block. Here, the proposed method is further validated by the BCI competition IV-2a dataset and compare with two hyperparameter tuning methods, Coordinate-descent and Bayesian optimization algorithm. The proposed architecture that used fuzzy neural block and Bayesian optimization as tuning approach, results in better classification accuracy compared with the state-of-the-art literatures. As results shown, the remarkable performance of the proposed model, EEG-CLFCNet, and the general integration of fuzzy units to other classifiers would pave the way for enhanced MI-based BCI systems.
Fabrication and characterization of polycaprolactone/cellulose acetate blended nanofiber mats containing sericin and fibroin for biomedical application
Authors: Barnthip Naris , Teeka Jantima , Kantha Puripat , Teepoo Siriwan , Damjuti Watchara
Published: December 2022

Polycaprolactone/cellulose acetate blended nanofiber mats containing sericin and fibroin were fabricated by electrospinning process to study the effect of sericin and fibroin on the physical and structural properties, wettability, degradability, elastic modulus, cell adhesion, and cell cytotoxicity of the electrospun nanofibers. Polycaprolactone/cellulose acetate solution was prepared with different percentage ratio of sericin and fibroin to be the running solution. Nanofibers were spun at fixed solution flow rate, flying distance, and operating voltage. The diameter of the obtained nanofibers linearly increases with the increasing of the sericin ratio. The derivative structures of polycaprolactone, cellulose acetate, sericin, and fibroin of the obtained nanofibers were confirmed by FTIR analysis. All acquired nanofibers show superhydrophilicity with adequate time of degradation for L-929 cell adhesion and growth. More elasticity is gained when the sericin ratio decreases. Moreover, all fibers containing sericin/fibroin reveal more elasticity, cell adhesion, and cell growth than that with only polycaprolactone/cellulose acetate. Greater cell adhesion and growth develop when the sericin ratio is lower. All the fabricated nanofibers are low toxic to the cells. Fibers with a mixture of sericin and fibroin at 2.5:2.5 (% w/v) are the most promising and suitable for further clinical development due to their good results in each examination. The novelty found in this study is not only making more value of the sericin, silk industrial waste, and the fibroin, but also getting the preferable biomaterials, scaffold prototype, with much greater mechanical property and slower degradation, which are required and appropriate for cell attachment and proliferation of cell generation process, compared to that obtaining from polycaprolactone/cellulose acetate or sericin/fibroin nanofibers.
Abandonment of ancient cities near the Salawusu River valley, China, triggered by stream capture
Authors: Wang Wei , Li Baosheng , Wen Xiaohao , Xu Liubing , Huang Rihui , Feng Jing , Qiu Mingkun
Published: December 2022

Several cities in the Salawusu River basin in the western Mu Su Desert of China were abandoned after the Yuan Dynasty (1271 to 1368 CE). Incisions of rivers caused by earth uplift coupled with a drier climate after the Yuan Dynasty have previously been attributed to such irreversible abandonments. Here we use geomorphological analyses, coupled with hydrological reconstructions to investigate the ancient stream patterns in the period leading up to the abandonments. We find that the abandonment of wells, the thermoluminescence age of which is about 640 years before present, in these cities coincided with a stream capture event that led to rapid river valley incision of up to 95 mm/year. We suggest that this stream piracy event lowered the water table in the area and triggered the abandonment of settlements, rather than a change to a drier climate as previously believed. We conclude that when considering environmental influences on archaeological records, geographic events must be considered in addition to climatic change.
Thermo- and photo-induced electron transfer in a series of [Fe2Co2] capsules
Authors: Meng Lingyi , Deng Yi-Fei , Holmes Stephen M. , Zhang Yuan-Zhu
Published: December 2022

A series of [Fe2Co2] squares encapsulated by different alkyldiamines are reported, which exhibit incomplete thermo-induced electron transfer and photo-responsive behaviors.
In situ growth of Prussian blue analogue-derived Fe-doped NiS on Ni(OH)2 for efficient hydrogen evolution reaction
Authors: Ding Xinyao , Zhang Mingyi , Chang Xin , Zhou Xuejiao
Published: December 2022

Prussian blue analogue-derived Fe-doped NiS on Ni(OH)2 exhibited both enhanced electrocatalytic activity and excellent long-term stability for HER.
Overview and prospect of information and communication technology development in virtual power plants
Authors: Li Bin , Wang JingJu , Bai XueFeng , Tang TianYue , Zhao JianLi , Liu Chuan , Hou ZhanSheng , Banimenia Izzeddin , Ali Rashid
Published: December 2022

As a new energy‐supply service solution to address massive, distributed energy access to the power system, a virtual power plant has higher transmission reliability and real‐time communication requirements. To achieve collaborative optimisation, distributed load and energy resources must be aggregated using new information and communication technology. This study analyses underlying communication technologies for virtual power plant interaction from the perspective of standardisation, efficiency, reliability, and security, summarises the application of blockchain, cloud‐edge collaboration, machine learning, and other new information and communication technologies in virtual power plant energy trading, interaction, and scheduling, and proposes ideas for addressing shortcomings in interaction. To improve virtual power plant interaction, performance parameter mapping between communication and business technology, and multilevel virtual power plant interaction technology are proposed.
Anomaly detection and clustering‐based identification method for consumer–transformer relationship and associated phase in low‐voltage distribution systems
Authors: Chu Zhenyue , Cui Xueyuan , Zhai Xingli , Liu Shengyuan , Qiu Weiqiang , Waseem Muhammad , Aziz Tarique , Wang Qin , Lin Zhenzhi
Published: December 2022

The identification accuracy of low‐voltage distribution consumer–transformer relationship and phase are crucial to three‐phase unbalanced regulation and error correction in consumer–transformer relationships. However, owing to the rapid increase in the number of consumers and the upgrade of the feed lines for low‐voltage distribution systems, the timely update of the consumer‐transformer relationship and phase information of consumers is challenging. This influences the accuracy of the basic information of the power grid. Thus, this study proposes a low‐voltage distribution network consumer–transformer relationship and phase identification method based on anomaly detection and the clustering algorithm. First, the improved fast dynamic time warping distance based on the filter search between voltage sequences is used to measure the similarity between voltage curves. Subsequently, an abnormal consumer detection method based on the local outlier factor is used to identify consumers with mismatched consumer‐transformer relationships by determining the local outlier factor scores of voltage curves. Furthermore, the phase information of normal consumers is identified through clustering by fast search and find of density peaks. Finally, the proposed method is validated using case studies of practical low‐voltage distribution systems in China. The proposed method can effectively improve phase identification accuracy and maintain high adaptability in various data environments.