bluuebunny/crossref_metadata_2025_split huggingface dataset:
NRAMP6 and NRAMP1 cooperatively regulate root growth and manganese translocation under manganese deficiency in Arabidopsis
Authors: Li Lun , Zhu Zongzheng , Liao Yonghui , Yang Changhong , Fan Ni , Zhang Jie , Yamaji Naoki , Dirick Léon , Ma Jian Feng , Curie Catherine , Huang Chao‐Feng 
Published: April 2022

SUMMARYThe essential micronutrient manganese (Mn) in plants regulates multiple biological processes including photosynthesis and oxidative stress. Some Natural Resistance‐Associated Macrophage Proteins (NRAMPs) have been reported to play critical roles in Mn uptake and reutilization in low Mn conditions. NRAMP6 was demonstrated to regulate cadmium tolerance and iron utilization in Arabidopsis. Nevertheless, it is unclear whether NRAMP6 plays a role in Mn nutrition. Here, we report that NRAMP6 cooperates with NRAMP1 in Mn utilization. Mutation of NRAMP6 in nramp1 but not in a wild‐type background reduces root growth and Mn translocation from the roots to shoots under Mn deficient conditions. Grafting experiments revealed that NRAMP6 expression in both the roots and shoots is required for root growth and Mn translocation under Mn deficiency. We also showed that NRAMP1 could replace NRAMP6 to sustain root growth under Mn deficiency, but not vice versa. Mn deficiency does not affect the transcript level of NRAMP6, but is able to increase and decrease the protein accumulation of NRAMP6 in roots and shoots, respectively. Furthermore, NRAMP6 can be localized to both the plasma membrane and endomembranes including the endoplasmic reticulum, and Mn deficiency enhances the localization of NRAMP6 to the plasma membrane in Arabidopsis plants. NRAMP6 could rescue the defective growth of the yeast mutant Δsmf2, which is deficient in endomembrane Mn transport. Our results reveal the important role of NRAMP6 in Mn nutrition and in the long‐distance signaling between the roots and shoots under Mn deficient conditions.
Quality of imported intermediates, innovation behaviour and markups: Firm‐level evidence from China
Authors: Huang Xianhai , Wang Yi , Zhu Zhujun , Song Xueyin 
Published: April 2022

AbstractThis paper examines whether higher quality imported intermediates can increase firms' markups. Based on the conceptual model, we first find that improving the quality of imported intermediates affects firms' decision‐making in terms of innovation and firm‐level markups through the price channel and the cost channel. We combine the annual survey data of Chinese industrial firms (ASIF), Chinese customs transactions and patent data to verify the theoretical propositions. The results report that: (1) there is a significantly positive correlation between the quality of imported intermediates and firms' markups; (2) innovation acts as a potential channel through which the quality of imported intermediates increases firms' markups; (3) by decomposing markups into the price channel and the cost channel, we find that the quality of imported intermediates affects firms' markups through the cost channel. Our results suggest that higher quality imported intermediates may improve firms' market power through innovation.
The effect of non‐absorbent hydrophobic sand litter on the urine protein‐to‐creatinine ratio in feline urine
Authors: Kennils Josh M. , Maunder Christina L. , Costa Marta T. 
Published: April 2022

AbstractBackgroundProteinuria can be quantified through the measurement of the urine protein‐to‐creatinine ratio (UPC). Voided urine samples in cats are often exposed to a non‐absorbable litter substrate prior to collection and urinalysis. Little is known about the effect exposure to such substrates has on pre‐analytical variability of UPC measurements.ObjectivesThe aim of this study was to assess agreement between UPC measurements from urine obtained by cystocentesis before and after exposure to non‐absorbent hydrophobic sand for 24 hours.MethodsUPCs were measured in 40 urine samples obtained by cystocentesis from 39 cats (baselineUPC). Urine was then exposed to non‐absorbent hydrophobic sand litter for 24 hours, recovered, and repeat UPCs were measured (litterUPC). Agreement between paired measurements and the presence of any bias or error was evaluated using Bland–Altman analysis Passing–Bablok regression analysis, respectively. Cohen's kappa was used to measure agreement for the International Renal Interest Society (IRIS) proteinuria classification of samples. Observed total error (TEobs) was calculated for the laboratory analyzer and compared against absolute percentage changes in paired UPC measurements.ResultsNeither proportional nor constant error was identified using Passing‐Bablok regression between baselineUPC and litterUPC. Visual inspection of the Bland–Altman plot revealed good agreement, with 95% of paired measures falling within the limits of agreement (LOA). Cohen's kappa demonstrated almost perfect agreement for the IRIS classification of proteinuria between baselineUPC and litterUPC. Absolute percentage changes of paired UPC measurements outside of the LOAs were lower than the inter‐assay TEobs.ConclusionsFeline urine exposed to non‐absorbent hydrophobic sand litter appears acceptable for UPC measurements.
GABAB‐ and GABAA‐receptor‐mediated regulation of Up and Down states across development
Authors: Kaplanian Ani , Vinos Michael , Skaliora Irini 
Published: April 2022

AbstractSlow oscillations, the hallmark of non‐REM sleep, and their cellular counterpart, Up and Down states (UDSs), are considered a signature of cortical dynamics that reflect the intrinsic network organization. Although previous studies have explored the role of inhibition in regulating UDSs, little is known about whether this role changes with maturation. This is surprising since both slow oscillations and UDSs exhibit significant age‐dependent alterations. To elucidate the developmental impact of GABAB and GABAA receptors on UDS activity, we conducted simultaneous local field potentials and intracellular recordings ex vivo, in brain slices of young and adult male mice, using selective blockers, CGP55845 and a non‐saturating concentration of gabazine, respectively. Blockade of both GABAB and GABAA signalling showed age‐differentiated functions. CGP55845 caused an increase in Down state duration in young animals, but a decrease in adults. Gabazine evoked spike and wave discharges in both ages; however, while young networks became completely epileptic, adults maintained the ability to generate UDSs. Furthermore, voltage clamp recordings of miniature inhibitory postsynaptic currents revealed that gabazine selectively blocks phasic currents, particularly involving postsynaptic mechanisms. The latter exhibit clear maturational changes, suggesting a different subunit composition of GABAA receptors in young vs. adult animals. Indeed, subsequent local field potential recordings under diazepam (nanomolar or micromolar concentrations) revealed that mechanisms engaging the drug's classical binding site, mediated by α1‐subunit‐containing GABAA receptors, make a bigger contribution to Up state initiation in young networks compared to adults. Taken together, these findings help clarify the mechanisms that underlie the maturation of cortical network activity and enhance our understanding regarding the emergence of neurodevelopmental disorders.Key points
Slow oscillations, the EEG hallmark of non‐REM sleep, and their cellular counterpart, Up and Down states (UDSs), are considered the default activity of the cerebral cortex and reflect the underlying neural connectivity.
GABAB‐ and GABAA‐receptor‐mediated inhibition play a major role in regulating UDS activity.
Although slow oscillations and UDSs exhibit significant alterations as a function of age, it is unknown how developmental changes in inhibition contribute to the developmental profile of this activity.
In this study, we reveal for the first time age‐dependent effects of GABAB and GABAA signalling on UDSs. We also document the differential subunit composition of postsynaptic GABAA receptors in young and adult animals, highlighting the α1‐subunit as a major component of the age‐differentiated regulation of UDSs.
These findings help clarify the mechanisms that underlie the maturation of cortical network activity, and enhance our understanding regarding the emergence of neurodevelopmental disorders.
Research on the performance of carbon film formed on thin stainless steel bipolar plates of PEMFC by laser irradiating
Authors: Huang Heping , Gao Chang , Yang Guogang , Huang Naibao 
Published: April 2022

In order to improve the anti-corrosion performance of thin stainless steel bipolar plates of proton exchange membrane fuel cell (PEMFC), the carbon film (of about 0.82-[Formula: see text]m thickness) was fabricated on the thin stainless steel by laser direct writing technology irradiating the formed dense polydopamine (PDA) film. The results indicated that the PDA film has partially transformed into nanocrystalline graphite. Laser power and scanning speed had great effect on the anti-corrosion performance of the final obtained film in simulated PEMFC environment. When the laser power is 3.5 W and the scanning speed is 10 mm/s, the film obtained on the thin stainless steel has the best electrochemical performance in simulated PEMFC environment. Its corrosion current densities were [Formula: see text]A [Formula: see text] cm[Formula: see text]@ −0.1 V (versus SCE) and [Formula: see text]A [Formula: see text] cm [Formula: see text]@ 0.6 V (versus SCE) in simulated anode and cathode environments, respectively. Compared with the bare thin stainless steel, the corresponding corrosion current densities decreased by 45% and 62%. The results obtained in this text provide a novel strategy for modifyingPEMFC thin metal bipolar plates.
Low power residue number system using lookup table decomposition and finite state machine based post computation
Authors: Morasa Balaji , Nimmagadda Padmaja 
Published: April 2022

In this paper, memory optimization and architectural level modifications are introduced for realizing the low power <span lang="EN-US">residue number system (RNS) with improved flexibility for electroencephalograph (EEG) signal classification. The proposed RNS framework is intended to maximize the reconfigurability of RNS for high-performance finite impulse response (FIR) filter design. By replacing the existing power-hungry RAM-based reverse conversion model with a highly decomposed lookup table (LUT) model which can produce the results without using any post accumulation process. The reverse conversion block is modified with an appropriate functional unit to accommodate FIR convolution results. The proposed approach is established to develop and execute pre-calculated inverters for various module sets. Therefore, the proposed LUT-decomposition with RNS multiplication-based post-accumulation technology provides a high-performance FIR filter architecture that allows different frequency response configuration elements. Experimental results shows the superior performance of decomposing LUT-based direct reverse conversion over other existing reverse conversion techniques adopted for energy-efficient RNS FIR implementations. When compared with the conventional RNS FIR design with the proposed FSM based decomposed RNS FIR, the logic elements (LEs) were reduced by 4.57%, the frequency component is increased by 31.79%, number of LUTs is reduced by 42.85%, and the power dissipation was reduced by 13.83%.</span>
Electronic datasheet parameter extractor and verifier system for printed circuit board development
Authors: Cuntapay Ma. Chalina S. , Enojas Mark Joseph B. , Bongao Hohn Lois C. 
Published: April 2022

Library components are composed of devices, symbols, and footprints which are the fundamental parts to design and develop printed circuit boards (PCB). <span lang="EN-US">In archiving PCB libraries, the creation and checking of the component’s parameters are very important. The checking of footprints and pin configurations from datasheets are manually done which causes delays and downtime when the components do not fit the developed PCB. It was found in a survey that 61.5% of errors come from footprints dimensions. These cause delays in the production and development of PCBs. In this study, a parameter extractor and verifier system were developed to mitigate the error of manual process of archiving library parameters from datasheets. Text recognition and pattern matching algorithms were used for the processing of images from datasheets. The 10-trial tests conducted for each footprint for the extraction of text from the cropped images for standard operating procedures (SOP) series and heat sink thin shrink small outline package (HTSSOP) series were found successful without any error. The checking of footprints and pin configuration was reduced from 45 minutes to 25 minutes. The developed system was evaluated based on user perception by 10 PCB library users which resulted to agree that the system is functional, efficient, and convenient to use.</span>
Efficient carry select 16-bit square root adder with complementary metal-oxide semiconductor implementation
Authors: Sathyanarayan Pavitha Uppinakere , Mohan Mamtha , Kakde Sandeep , Karthik Annam 
Published: April 2022

The adder is the maximum usually used mathematics block in programs inclusive of <span lang="EN-US">central processing unit (CPU) and virtual sign processing. As a result, it is important to expand a space-saving, low-strength, high-overall performance adder circuit. The hassle is diagnosed to layout mathematics sub structures with minimized strength dissipation, low area, and minimal time postpone of common-sense circuits. In conventional <a name="_Hlk95894088"></a>carry select adder (CSA), the time required to generate the sum output is less than other basic adder circuits but the principal difficulty is the location because the variety of transistors used to put in force the CSA circuit is fairly more. So, the area increases because of which the overall power consumption of the circuit will be more. If it's far viable to lessen the variety of transistors used withinside the structure of CSA adder, then, the strength intake of the circuit may be decreased or even the reaction time will improve. By lowering the area of the adder circuit, the suggested solution intends to reduce power consumption and latency.</span>
Magnetic resonance coupling wireless power transfer for green technologies
Authors: Nafiaa Reem Emad , Yonis Aws Zuheer 
Published: April 2022

Wireless <span>power transfer (WPT) is a technology that is considered the focus of scientists' attention for its development and creation to be compatible with many devices that are used today and also consider one of the green technology apps which means any technology can reduce the effect of people on the environment which is today grow continuously. In this paper, a wireless power transfer for a mobile charger had been discussed to get a maximum power and efficiency power transfer. WPT is considered as a reliable technology, efficient, fast, not using wires, and can be used for short and long-range. There are three methods for WPT, electromagnetic induction, magnetic resonance coupling, and radio waves which are classified by the distance that sends the power. Magnetic resonance coupling is the method that has been focused on in this paper because of compatibility with short or medium distances as battery chargers which depend on the magnetic field to transfer power without wires that can protect devices from damages and heating. As result the effect of distance on efficiency has been discussed with reached to nearer distance can improve efficiency however by using magnetic resonance technique, acceptable efficiency can be obtained with appropriate distance.</span>
A heuristic approach to minimize three criteria using efficient solutions
Authors: Hassan Dara Ali , Amiri Nezam Mehdavi , Ramadan Ayad Mohammed 
Published: April 2022

In <span>optimization, scheduling problems is concerning allocations of some resources which are usually limited. These allocations are done in order to fulfil some criterion by performing some tasks or jobs to optimize one or more objective functions. Simultaneous multi-criteria scheduling problem is known as np-hard optimization problem. Here, we consider three criteria for scheduling a number of jobs on a single machine. The problem is to minimize the sum of total completion time, maximum earliness and maximum tardiness. Every job is to be processed without interruption and becomes available for processing at time zero. The aim is to find a processing order of the jobs to minimize three-objective functions simultaneously. We present a new heuristic approach to find a best overall solution (accepted) of the problem using efficient solutions of one of the other related criteria. We establish a result to restrict the range of the optimal solution, and the lower bound depends on the decomposition of the problem into three subproblems. The approach is tested on a set of problems of different number of jobs. Computational results demonstrate the efficiency of the proposed approach.</span>
Improvised convolutional auto encoder for thyroid nodule image enhancement and segmentation
Authors: Gunjali Drakshaveni , Hansavath Prasad Naik 
Published: April 2022

Thyroid <span>ultrasonography and thermography are a widely used clinical technique for nodule diagnosis in thyroid regions. However, it remains difficult to detect and recognize the nodules due to low contrast, high noise, and diverse appearance of nodules. To alleviate doctors’ tremendous labor in the diagnosis procedure, we advocate a machine learning approach to the detection and recognition tasks in this paper. Moreover, this research mainly focuses on segmenting the image and finding the probable region. In this research work an improvised convolutional auto encoder (ICAE) is introduced for segmenting the image and finding the probable region of thyroid gland and it enhances image. ICAE comprises various layer and mechanism, each having their own task. Apart from the traditional approach, skip connection is applied for the image enhancement and dual frame is introduced for better feature extraction. Further optimization technique is used for increasing the learning rate. ICAE is evaluated considering digital database thyroid image (DDTI) dataset with performance metrics like accuracy, true positive rate, false positive rate, dice coefficient and similarity index (SI); also, comparative analysis is carried out with various existing model and proposed model simply outperforms the existing model.</span>
Transformer based multi-head attention network for aspect-based sentiment classification
Authors: Shirahatti Abhinandan , Rajpurohit Vijay , Sannakki Sanjeev 
Published: April 2022

Aspect-based <span>sentiment classification is vital in helping manufacturers identify the pros and cons of their products and features. In the latest days, there has been a tremendous surge of interest in aspect-based sentiment classification (ABSC). Since it predicts an aspect term sentiment polarity in a sentence rather than the whole sentence. Most of the existing methods have used recurrent neural networks and attention mechanisms which fail to capture global dependencies of the input sequence and it leads to some information loss and some of the existing methods used sequence models for this task, but training these models is a bit tedious. Here, we propose the multi-head attention transformation (MHAT) network the MHAT utilizes a transformer encoder in order to minimize training time for ABSC tasks. First, we used a pre-trained Global vectors for word representation (GloVe) for word and aspect term embeddings. Second, part-of-speech (POS) features are fused with MHAT to extract grammatical aspects of an input sentence. Whereas most of the existing methods have neglected this. Using the SemEval 2014 dataset, the proposed model consistently outperforms the state-of-the-art methods on aspect-based sentiment classification tasks.</span>
Optimizing random forest classifier with Jenesis-index on an imbalanced dataset
Authors: Zeffora Joylin , Shobarani Shobarani 
Published: April 2022

Random <span>forest is an ensemble algorithm for machine learning. In decision trees, the splitting criteria is built on the prediction of the nodal points and formation of rules by Gini index and Information Gain. Gini index is a measure of inequality. Gini index does not take into consideration the structural changes in the dataset, and inaccurate data can distort the validity of the gini-coefficient. For data with the same feature but different outcomes, the gini-coefficient remained the same. The proposed method for attribute selection measure takes into consideration that there may be structural changes in the dataset overtime and it adapts to such expected changes and maintain the accuracy of the algorithm avoiding under-fitting and over-fitting. A dataset on myocardial infarctions was taken for the study and the results were promising.</span>
Vector support machine algorithm applied to the improvement of satisfaction levels in the acquisition of professional skills
Authors: Chamorro-Atalaya Omar , Ortega-Galicio Orlando , Morales-Romero Guillermo , Villar-Valenzuela Darío , Meza-Chaupis Yeferzon , León-Velarde César , Quevedo-Sánchez Lourdes 
Published: April 2022

<span lang="EN-US">The study <span>carried out identifies the metricss of the predictive model obtained through the support vector machine (VSM) algorithm, which will be applied in the satisfaction of the acquisition of professional skills of the students of the Professional Engineering Career. As part of the development, the statistical classification tool is used, during the development of the research, it was identified that the predictive model presents as general metrics an accuracy of 82.1%, a precision of 70.72%, a sensitivity of 91.06% and a specificity of 87.60%. Through this model, it contributes significantly to decision-making in relation to improving satisfaction related to the acquisition of professional skills in engineering students, since decision-making by university authorities will have a scientific basis, to take early and timely actions in relation to the predictive elements.</span></span>
Delay-power efficient VLSI architecture design for robust proportionate adaptive filter
Authors: Lakshmaiah Gangadharaiah Soralamavu , Narayanappa Chikkajala Krishnappa , Narasimhaiah Divya Muddenahalli , Nagabhushanam Munivenkatappa , Venkatesh Nuthan Prasad , Shobhavathi Bhanu Darshan Srinivas 
Published: April 2022

This paper proposes <span lang="EN-US">the robust proportionate adaptive filtering algorithms and their respective efficient very large-scale integration (VLSI) architectures for sparse system identification under impulsive noise, several types of algorithms are combined to obtain optimum results. Here, we rendered a relative analysis on these algorithms and the algorithms are mapped on to the hardware to show that the improvement is obtained with respect to convergence rate and hardware complexity of VLSI architectures and has negligible hardware overhead with improved robustness. Good performance and convergence rate is obtained by combining the delayed μ-law proportionate (DMP) and least mean logarithmic square (LMLS) algorithms i.e. delayed µ-law proportionate least mean logarithmic square (DMP LMLS). Robust proportionate adaptive filter is coded in system verilog and synthesized using cadence genus compiler with 90 nm technology library.</span>