bluuebunny/crossref_metadata_2025_split huggingface dataset:
Independence and upper extremity functioning after spinal cord injury: a cross-sectional study
Authors: Lili Lamprini , Sunnerhagen Katharina S. , Rekand Tiina , Alt Murphy Margit 
Published: February 2023

AbstractUpper extremity functioning is important for achieving independence in activities of daily living (ADL). A better understanding of relationships between different aspects of independence in ADL after spinal cord injury (SCI) and upper extremity functioning is required to guide rehabilitation practices. To determine which aspects of independence in ADL are correlated with upper extremity functioning in individuals with cervical or thoracic SCI. A total of 25 adults (mean age 58.4 years, 72% men) with established cervical or thoracic SCI were recruited. Independence in ADL was assessed by Spinal Cord Independence Measure (SCIM-III) and upper extremity functioning by kinematic measures (movement time, smoothness, and wrist angle during drinking task), grip strength, Upper Extremity Motor and Sensory Score, Box and Block Test (BBT), Action Research Arm Test (ARAT), and Upper Extremity Basic Data Set (ISCI-Hand and ISCI-Shoulder). Spearman correlation coefficients were used for data analyses. The SCIM-self-care subscale, particularly the feeding and dressing items, correlated moderately (r ≥ 0.5) with movement time and smoothness, grip strength, ARAT, BBT, and ISCI-Hand. The SCIM-respiration/sphincter subscale and the SCIM-mobility showed very low and low correlations with upper extremity assessments. However, at item level, respiration and bed/wheelchair mobility showed moderate correlations. Independence in self-care as domain and feeding/dressing, respiration and bed/wheelchair mobility as separate items were dependent on upper extremity functioning in individuals with cervical or thoracic SCI. Movement time and smoothness along with BBT, grip strength, ARAT, and ISCI-Hand can be used as indicators of independence in ADL. These findings can provide guidance to clinical practice in selection of upper extremity assessments in the context for ADL in individuals with SCI.
Estimation of rocks’ failure parameters from drilling data by using artificial neural network
Authors: Siddig Osama , Ibrahim Ahmed Farid , Elkatatny Salaheldin 
Published: February 2023

AbstractComprehensive and precise knowledge about rocks' mechanical properties facilitate the drilling performance optimization, and hydraulic fracturing design and reduces the risk of wellbore-related problems. This paper is concerned with the failure parameters, namely, cohesion and friction angle which are conventionally estimated using Mohr's cycles that are drawn using compressional tests on rock samples. The availability, continuity and representability, and cost of acquiring those samples are major concerns. The objective of this paper is to investigate an alternative technique to estimate these parameters from the drilling data. In this work, more than 2200 data points were used to develop and test the correlations built by the artificial neural network. Each data point comprises the failure parameters and five drilling records that are available instantaneously in drilling rigs such as rate of penetration, weight on bit, and torque. The data were grouped into three datasets, training, testing, and validation with a corresponding percentage of 60/20/20, the former two sets were utilized in the models' building while the last one was hidden as a final check afterward. The models were optimized and evaluated using the correlation coefficient (R) and average absolute percentage error (AAPE). In general, the two models yielded good fits with the actual values. The friction angle model yielded R values around 0.86 and AAPE values around 4% for the three datasets. While the model for cohesion resulted in R values around 0.89 and APPE values around 6%. The equation and the parameters of those models are reported in the paper. These results show the ability of in-situ and instantaneous rock mechanical properties estimation with good reliability and at no additional costs.
Assessing brain state and anesthesia level with two-photon calcium signals
Authors: Tort-Colet Núria , Resta Francesco , Montagni Elena , Pavone Francesco , Allegra Mascaro Anna Letizia , Destexhe Alain 
Published: February 2023

AbstractBrain states, such as wake, sleep, or different depths of anesthesia are usually assessed using electrophysiological techniques, such as the local field potential (LFP) or the electroencephalogram (EEG), which are ideal signals for detecting activity patterns such as asynchronous or oscillatory activities. However, it is technically challenging to have these types of measures during calcium imaging recordings such as two-photon or wide-field techniques. Here, using simultaneous two-photon and LFP measurements, we demonstrate that despite the slower dynamics of the calcium signal, there is a high correlation between the LFP and two-photon signals taken from the neuropil outside neuronal somata. Moreover, we find the calcium signal to be systematically delayed from the LFP signal, and we use a model to show that the delay between the two signals is due to the physical distance between the recording sites. These results suggest that calcium signals alone can be used to detect activity patterns such as slow oscillations and ultimately assess the brain state and level of anesthesia.
Development of a chub mackerel with less-aggressive fry stage by genome editing of arginine vasotocin receptor V1a2
Authors: Ohga Hirofumi , Shibata Koki , Sakanoue Ryo , Ogawa Takuma , Kitano Hajime , Kai Satoshi , Ohta Kohei , Nagano Naoki , Nagasako Tomoya , Uchida Seiichi , Sakuma Tetsushi , Yamamoto Takashi , Kim Sangwan , Tashiro Kosuke , Kuhara Satoru , Gen Koichiro , Fujiwara Atushi , Kazeto Yukinori , Kobayashi Takanori , Matsuyama Michiya 
Published: February 2023

AbstractGenome editing is a technology that can remarkably accelerate crop and animal breeding via artificial induction of desired traits with high accuracy. This study aimed to develop a chub mackerel variety with reduced aggression using an experimental system that enables efficient egg collection and genome editing. Sexual maturation and control of spawning season and time were technologically facilitated by controlling the photoperiod and water temperature of the rearing tank. In addition, appropriate low-temperature treatment conditions for delaying cleavage, shape of the glass capillary, and injection site were examined in detail in order to develop an efficient and robust microinjection system for the study. An arginine vasotocin receptor V1a2 (V1a2) knockout (KO) strain of chub mackerel was developed in order to reduce the frequency of cannibalistic behavior at the fry stage. Video data analysis using bioimage informatics quantified the frequency of aggressive behavior, indicating a significant 46% reduction (P = 0.0229) in the frequency of cannibalistic behavior than in wild type. Furthermore, in the V1a2 KO strain, the frequency of collisions with the wall and oxygen consumption also decreased. Overall, the manageable and calm phenotype reported here can potentially contribute to the development of a stable and sustainable marine product.
The tumor biological significance of RNF43 and LRP1B in gastric cancer is complex and context-dependent
Authors: Holm Bente , Barsuhn Stephan , Behrens Hans-Michael , Krüger Sandra , Röcken Christoph 
Published: February 2023

AbstractGastric cancer (GC) is the fifth most common cancer in the world with a poor prognosis. Both RNF43 and LRP1B function as tumor suppressors in the Wnt signaling pathway and have been described to be frequently mutated in GC. In this study of a large and well characterized cohort of 446 GCs we explored the significance of expression of RNF43 and LRP1B and their correlations with clinicopathological patient characteristics. Immunostaining of whole mount tissue sections was documented with the histoscore. Dichotomized at the median, we separated the cohort into a low/negative and a high/positive group of RNF43 and LRP1B expression, respectively. Apart from the entire cohort, we also examined the intestinal and diffuse type GCs separately. Regarding the entire cohort, the expression of RNF43 and LRP1B correlated significantly with the Lauren phenotype and with each other. Interestingly, differences were noted regarding RNF43 between the intestinal and diffuse type GCs. Survival analysis of the intestinal type GCs showed that RNF43 low/negative GCs tended to have a better outcome compared with RNF43 high/positive GCs [24.5 months overall survival (OS) and 25.0 months tumor-specific survival (TSS) vs. 14.1 months OS and 17.9 months TSS, respectively]. To the contrary, diffuse type GCs with RNF43 low/negative had a worse outcome compared with RNF43 high/positive GCs (12.9 months OS and 18.2 months TSS vs. 17.1 months OS and 21.5 months TSS, respectively). On multivariate analysis, RNF43 low/negative versus high/positive was an independent prognosticator of survival in diffuse type GC (hazard ratio 2.393 for OS and 2.398 for TSS). These data support the contention that the expression and biological effect of RNF43 and LRP1B in GC is context-dependent.
Modelling individual head‐related transfer function (HRTF) based on anthropometric parameters and generic HRTF amplitudes
Authors: Zhang Rui , Meng Ruijie , Sang Jinqiu , Hu Yi , Li Xiaodong , Zheng Chengshi 
Published: February 2023

AbstractThe head‐related transfer function (HRTF) plays a vital role in immersive virtual reality and augmented reality technologies, especially in spatial audio synthesis for binaural reproduction. This article proposes a deep learning method with generic HRTF amplitudes and anthropometric parameters as input features for individual HRTF generation. By designing fully convolutional neural networks, the key anthropometric parameters and the generic HRTF amplitudes were used to predict each individual HRTF amplitude spectrum in the full‐space directions, and the interaural time delay (ITD) was predicted by the transformer module. In the amplitude prediction model, the attention mechanism was adopted to better capture the relationship of HRTF amplitude spectra at two distinctive directions with large angle differences in space. Finally, with the minimum phase model, the predicted amplitude spectrum and ITDs were used to obtain a set of individual head‐related impulse responses. Besides the separate training of the HRTF amplitude and ITD generation models, their joint training was also considered and evaluated. The root‐mean‐square error and the log‐spectral distortion were selected as objective measurement metrics to evaluate the performance. Subjective experiments further showed that the auditory source localisation performance of the proposed method was better than other methods in most cases.
Complexity‐reduced maximum‐likelihood hybrid detection for MIMO systems
Authors: Chang Ming‐Xian , Su Szu‐Lin 
Published: February 2023

AbstractFor wireless communications, the multiple‐input multiple‐output (MIMO) system efficiently makes use of the spectrum and enhances the transmission throughput. In this work, the maximum‐likelihood (ML) detection for the MIMO system is studied, and two ML detection algorithms are first considered for the MIMO system, including the sphere decoding (SD) algorithm and an algorithm based on differential metrics (DMs). Each of the two algorithms has its advantages and disadvantages. The two algorithms are first modified such that they are based on the same signal model. Then, a new ML detection algorithm is proposed for the MIMO system based on the hybrid operation of the two modified algorithms on the tree search process, in which both the branch‐and‐bound principle and indicative functions are applied to remove unnecessary searches. The proposed algorithm can attain the ML detection with lower average complexity over low and high ranges of signal‐to‐noise ratio (SNR), as the authors verify by simulations. The proposed ML detection can also generate soft output, and anti‐phase sequences are exploited to further reduce the complexity.
Maximizing the network outage rate for fast fluid antenna multiple access systems
Authors: Wong Kai‐Kit , Tong Kin‐Fai , Chen Yu , Zhang Yangyang 
Published: February 2023

AbstractUsing reconfigurable fluid antennas, it is possible to have a software‐controlled position‐tuneable antenna to realize spatial diversity and multiplexing gains that are previously only possible using multiple antennas. Recent results illustrated that fast fluid antenna multiple access (f‐FAMA) which always tunes the antenna to the position for maximum signal‐to‐interference ratio (SIR) on a symbol‐by‐symbol basis, could support hundreds of users on the same radio channel, all by a single fluid antenna at each user without complex coordination and optimization. The network outage rate, nevertheless, depends on the SIR threshold chosen for each user. Motivated by this, this paper adopts a first‐order approximation to obtain the outage probability expression from which a closed‐form solution is derived for optimizing the SIR threshold in maximizing the network outage rate. Moreover, a closed‐form expression is provided to estimate the number of users in the f‐FAMA network in which the outage rate begins to plateau. Numerical results show that the proposed SIR threshold achieves near‐maximal outage rate performance.
Decentralized energy management system for smart microgrids using reinforcement learning
Authors: Darshi Razieh , Shamaghdari Saeed , Jalali Aliakbar , Arasteh Hamidreza 
Published: February 2023

AbstractThis paper presents a novel fully decentralized and intelligent energy management system (EMS) for a smart microgrid based on reinforcement learning (RL) strategy. The purpose of the proposed EMS is to maximize the benefit of all microgrid entities comprising customers and distributed energy resources (DERs). Due to unpredictable features of renewable energy sources and variability of consumers’ demands, designing the microgrid EMS is a complicated task. To overcome this issue, the multi‐agent hour‐ahead energy management problem is modelled as a finite Markov decision process. The microgrid entities are considered as intelligent agents. The optimal policy of agents is obtained through a newly developed framework of the model‐free Q‐learning algorithm to maximize the benefit of all renewable and non‐renewable energy resources and battery energy storage system. The degradation model of the battery is considered to reduce the number of battery replacements. To ensure customers’ comfort, customers’ expenses are decreased without demand curtailment via introducing two types of load shifting techniques. The microgrid operation is analysed under four scenarios comprising no‐learning, generator‐learning, customer‐learning, and whole‐learning. the performance of the proposed algorithm is compared to the Monte Carlo method and simulation results on the real power‐grid dataset show the superiority of the algorithm.
Comprehensive analysis and design of a switched‐inductor type low inductance‐requirement DC‐DC buck‐boost converter for low power applications
Authors: Hamood‐Ur‐Rehman  , Ahmed Nisar , Sher Hadeed Ahmed , Al‐Durra Ahmed , Hasanien Hany M 
Published: February 2023

AbstractThis paper aims to comprehensively analyze, critically discuss, and provide a step‐by‐step design guideline for a previously proposed Modified Switched‐Inductor type Buck‐Boost (MSIBB) converter which is based on a boost converter. The MSIBB converter is originally based on switched‐inductor phenomena whereby two inductors are switched in a proper sequence to ensure appreciable buck as well as boost characteristics. Appreciable buck and boost characteristics are desirable specifically in low power applications. In regulated low power applications, DC‐DC switching power converters undergo frequent mode‐shift from buck to boost, and vice versa. At the overlap between input/output voltage, the converters efficiency does not suffer significantly, but the wide input‐voltage operating area compels the regulated converters to operate at extreme values of the duty cycle, that is, close to 0 and 1, which causes lower efficiency. A high‐efficiency switching converter is required specifically for low‐power applications that can ensure voltage step‐up and step‐down without resorting to operating at extreme values of the duty‐cycle. In this perspective, switched‐inductors based converter, termed as MSIBB converter, was previously proposed. The MSIBB converter exhibits appreciable voltage‐gain, and experiences lesser current/voltage stress on the semiconductor components. In particular, it has comparable Maximum Switch Stress Factor that generally translates to alleviated switch conduction and switching losses. Besides, the inductors minimum peak stored energy is comparatively lower, reflecting reduced physical size of the inductors as well as reduced onboard losses, and therefore better caters to low power applications. Detailed analysis of the converter and step‐by‐step approach for design example, and comparative analysis are carried out, besides providing some experimental results from the previously proposed converter.
Development of ECRH-based methods for assisted discharge burn-through: Experiment and simulation
Authors: Ricci D. , Stober J. , Dux R. , Figini L. , Wauters T. , Lerche E. , Granucci G. ,   the ASDEX Upgrade Team,   Eurofusion WPTE Team
Published: February 2023

Electron Cyclotron (EC) waves will be routinely used in future reactors not only for plasma heating and/or non-inductive current drive during the flat top but also to assist the plasma start-up phase in large tokamaks with superconductive coils. In ITER, for example, EC start-up is foreseen since first plasma operation. To limit the level of stray radiation, ECRH can be used after ohmic breakdown, as a robust solution to successfully sustain the plasma burn-through in the presence of pre-filling gas and impurity influx from the wall.
On ASDEX Upgrade (AUG), a series of dedicated experiments have been performed using EC heating (X2) with a controlled Ne impurity injection in the prefill phase, to mimic non-favourable burn-through conditions such as would be expected in a discharge following a disruption event. The time for EC heating onset has been optimised to assist the early burn-through and a scan of the Ne concentration has been performed to find the threshold for successful burn-through conditions for two ECH power levels (0.7 and 1.4 MW). The toroidal magnetic field flexibility has been also documented, with the cold resonance position being shifted up to 13% in major radius to match the ITER condition. These experiments showed that optimised settings of ECH power (onset and duration of the pulse) have a key role in making feasible the early Ne burn-through (with Ne concentration up to 14% and EC power of 1.4 MW). Successful pulses will be extended to study stationarity and clean up properties.
For an efficient and robust use of such a technique, it is essential to develop appropriate models capable of describing present experiments and of extrapolating (or predicting) to future scenarios. In this work, the predictive 0D model for the burn-though phase BKD0 [1] has been used to reproduce experimental results and estimate the power required for a successful burn-through as a function of the impurity concentration, finding that ECH power of 1.4 MW is required to sustain burn-through with more than 20% of Ne. The scalability of the model has been also tested on TCV [2] and its implication for ITER will be discussed.
Comparison of Fatigue Level, Musculoskeletal Disorders and Physical
Activity Level in Aircraft Engineers Working in the Morning Shift and Night
Shift
Authors: Sharan Shikshita , Sheereen Fauzia Javed , Chahal Aksh , Alshehri Mohammed M , Najmi Ayat Abdullah Ahmad , Alajam Ramzi Abdu , Shaphe Mohammad Abu 
Published: February 2023

Abstract
Background Shift work is a system in which different groups of workers
work at different times of the day and night. It may affect the physiological
health of an individual and hence fatigue, musculoskeletal disorder and changes
in physical activity may arise.
Objective To compare the fatigue level, musculoskeletal disorders (MSDs)
and physical activity level in aircraft engineers working in morning shift and
night shift.
Method The study consisted of 100 aircraft engineers working at Indira
Gandhi International Airport, Terminal 1. 50 aircraft engineers working in
morning shift and 50 aircraft engineers working in night shift participated in
the study. Self-administered questionnaire i. e., Chalder Fatigue Scale,
Nordic Musculoskeletal Questionnaire and International Physical Activity
Questionnaire were used to access the fatigue level, the number of MSDs, and
physical activity level, respectively.
Results The results showed significant difference in fatigue level, and
the level of physical activity morning shift versus night shift workers
(p<0.001). The mean value of fatigue level in morning shift was 4.9 and
in night shift was 14.6. The average mean value of physical activity level in
morning shift was 1972.61 MET min a week and in night shift was 1277.83 MET min
a week. MSDs were more common in night shift workers as compared to morning
shift workers.
Conclusion The findings of the study suggested an increased in the level
of fatigue and decrease in the physical activity level among aircraft engineers
working night shift compared to those working morning shift. There are more MSDs
in aircraft engineers working night shift as compared to those working morning
shift.
Development and Validation of HPLC Method for Quantification of
Plumbagin in Plumbago Zeylanica L. Roots
Authors: Shukla Babita , Kushwaha Poonam 
Published: February 2023

Abstract
Background An RP-HPLC (Reverse Phase-High-performance liquid
chromatography) method for the quantitative estimation and validation of the
plumbagin in the methanolic fraction of Plumbago zeylanica L. was
developed.
Method For achieving good separation, the RP-HPLC method was carried out
with reverse phase C18 column, using methanol and water as mobile phase in the
ratio of 65:35 (v/v), at the flow rate of 1 mL/min. The
detection wavelength was set at 265 nm.
Results The retention time of plumbagin was found at
7.5±0.2 min. The coefficient of determination of plumbagin was
found to be (r2) 0.9985 and equation Y=23148x+4327.
The LOD and LOQ were found to be 34.06 and 113 ng/mL,
respectively.
Conclusion The developed method was accurate, specific, precise, and
reproducible. This RP-HPLC may be useful for quantitative estimation of the
chemical constituents present in the plant extract as well as the quality
assessment of the herbal product.
Histopathologische Veränderungen bei kornealen Ektasien
Authors: Bulirsch Louisa M. , Löffler Karin U. , Holz Frank G. , Herwig-Carl Martina C. 
Published: February 2023

ZusammenfassungDen kornealen Ektasien werden der Keratokonus, der Keratoglobus, die pelluzide marginale Degeneration sowie iatrogene Keratektasien zugeordnet. Bei allen Formen der kornealen Ektasie kommt
es zu einer Verdünnung der Hornhaut, die mit einer kornealen Aufsteilung sowie einem irregulären Astigmatismus einhergeht. Nachfolgend wird ein Überblick über histopathologische
Veränderungen der verschiedenen kornealen Ektasien gegeben. Ebenso werden histologische Veränderungen nach operativen Verfahren, die im Zusammenhang mit Ektasien durchgeführt werden, wie das
korneale Crosslinking und die perforierende Keratoplastik (pKPL) sowie nach refraktiven chirurgischen Verfahren, die potenziell zu einer Ektasie führen können, dargestellt. Neben einer
Literaturrecherche erfolgte auch die Aufarbeitung und Untersuchung von histopathologischem Archivmaterial zur exemplarischen Darstellung der spezifischen histologischen Veränderungen.