Miracle-dz/UniFAR-FTUs huggingface dataset:
Interplay Between KRAS and LZTR1 Protein Turnover, Controlled by CUL3/LZTR1 E3 Ubiquitin Ligase, is Disrupted by KRAS Mutations

KRAS is a proto-oncogene encoding a small GTPase. Mutations contribute up to 30% of human solid tumours including lung adenocarcinoma, pancreatic and colorectal carcinomas. Most KRAS activating mutations interfere with GTP hydrolysis, essential for its role as a molecular switch, leading to alterations in their molecular environment and oncogenic signalling. Here, APEX-2 proximity labelling was used to profile the molecular environment of wild type and G12D, G13D and Q61H activating mutants of KRAS under both, starvation and stimulation conditions. We demonstrate by quantitative proteomics the presence of known interactors of KRAS including a-RAF and LZTR1, which varied in abundance with wildtype and KRAS mutants. Notably, the KRAS mutations G12D, G13D and Q61H abrogate association with LZTR1. Wildtype KRAS and LZTR1, as part of the CUL3 ubiquitin E3 ligase complex, affect each other’s protein stability, revealing a direct feedback loop mechanism. KRAS mutations disconnect this regulatory circuit, thereby contributing to oncogenesis.
A method for measuring the permittivity without ambiguity using six-port reflectometer

Automatic network analyzers are used for the broadband measurement of permittivity in different experimental arrangements. In many of them ambiguity appears because permittivity is calculated by solving a transcendental equation. This makes automatic measurements difficult. A method of eliminating this ambiguity is shown, with no additional experimental data required, except for a manipulation of the existing data. Theory and experimental results for low-loss dielectrics are shown for the short-circuited waveguide method using a six-port reflectometer. Errors are analyzed and several samples with permittivities of up to 16 are measured with an accuracy on the order of 1%. >
Flexible ultra-wideband polarisation diversity antenna with band-notch function

A CPW-fed polarisation diversity monopole antenna on a flexible PET film for ultra-wideband (UWB) systems is proposed. The antenna consists of two heptagonal monopoles that are orthogonally and symmetrically aligned to have extended ground planes. The antenna is able to cover the entire UWB bandwidth from 3.1 to 10.6 GHz and shows a good isolation of less than 20 dB at each port over the entire UWB bandwidth. Also, it has a band-notch function to avoid overlap with the 5 GHz wireless local area network band. It can be easily mounted on a conformal shape, because it is fabricated on a PET film that is flexible enough to be mounted on a curved surface. Both the time-domain and frequency-domain characteristics of the antenna have been investigated by using the normalised antenna transfer function. From the results, it is observed that the proposed antenna can support polarisation diversity for UWB communications.
Analysis and design of optimum-amplitude nine-switch direct AC-AC converters

The maximum input-output transformer ratio, or output voltage ability, of direct AC-AC pulse-width-modulated converters is explored. An intrinsic limit, independent of the control algorithm, is found. A suitable novel converter control algorithm is discussed which achieves such maximum output amplitude ability and displays some interesting features. Finally, the opportunity to implement AC-AC converter control with the use of feedback techniques is considered, and a feedback-based control algorithm for the converter is proposed. >
The relative importance of individual attributes varies across preference elicitation

15 When choosing between different options, we tend to consider specific attribute qualities rather 16 than deliberating over some general sense of the options’ overall values. The importance of each 17 attribute together with its quality will determine our preference rankings over the available 18 alternatives. Here, we show that the relative importance of the latent attributes within food rewards 19 reliably differs when the items are evaluated in isolation compared to when binary choices are 20 made between them. Specifically, we used standard regression and sequential sampling models to 21 examine six datasets in which participants evaluated, and chose between, multi-attribute snack 22 foods. We show that models that assume that attribute importance remains constant across 23 individual evaluations and binary choices fail to reproduce fundamental patterns in the choice data 24 and provide quantitatively worse fits to the choice outcomes, response times, and confidence 25 reports compared to models that allow for attribute importance to vary across preference elicitation 26 methods. Our results provide important evidence that incorporating attribute-level information into 27 computational models helps us to better understand the cognitive processes involved in value28 based decision-making. 29 30
Disease resistance efficacy of macroalgae mediated silver nanoparticles and its prophylactic activity against Pseudomonas aeruginosa infection in Oreochromis mossambicus

Bacterial pathogens are major threat to the aquaculture industry and small scale aqua farming. The emergence of various virulence pathogens during the culturing period leads to mass mortality and influence the loss of aquaculture production. As a result it causes economic imbalance. This relies on the very importance position to serve the protein rich sources for human consumption. In order to improve the sustainable aquaculture production the biologically synthesized silver nanoparticles have been used as an alternative method for commercial antibiotics to control such pathogenic infection. Marine microalgae Caulerpa racemosa was used as a silver reducing agent in this study. This controls Pseudomonas aeruginosa infection in tilapia. The bioactive compounds present in the extracts showed potential antioxidant and antibacterial activities against P. aeruginosa infection. The formation of AgNPs was observed by the visualization of the colour change and further confirmed by the UV spectroscopy. It was characterised by Dynamic light scattering measurements (DLS). The antibacterial activity was tested against the fish pathogen. It was found to be effective.
Development Of Accurate UWB Dielectric Properties Dispersion At CST Simulation Tool For Modeling Microwave Interactions With Numerical Breast Phantoms

In this paper, a reformulation for the recently published dielectric properties dispersion models of the breast tissues is carried out to be used by CST simulation tool. The reformulation includes tabulation of the real and imaginary parts versus frequency on ultra-wideband (UWB) for these models by MATLAB programs. The tables are imported and fitted by CST simulation tool to 2 nd or 1 st order general equations. The results have shown good agreement between the original and the imported data. The MATLAB programs written in MATLAB code are included in the appendix.
P‐20: A Universal Circuit Model for Optical Response Simulation of Active‐Matrix Liquid Crystal Displays

We propose a behavioral circuit model to predict optical responses of an active‐matrix liquid crystal display (AMLCD). In order to verify our model's universality, we apply it to TN, PVA, and IPS AMLCDs. The simulation results of the transient optical responses show excellent matches with the measurement ones regardless of types of LCDs.
EXTRACTING THE OPINION THROUGH CUSTOMER FEEDBACK DATA FROM WEB RESOURCES

As the customer opens their views for the product and their services, so it is necessary that it is classifying and categorizing these views in feature manner. The job of analyzing such information is collectively called as customer product reviews, also called as opinion mining. Basically it consists of some steps, and different task achieved by applying different techniques. This paper basically explains such techniques that have been used for the implementation of task of opinion mining. On the basis of this analysis we provide an overall system design for the development of opinion mining approach.
S2049847021000583jra 1..18

We estimate how asset prices respond to a range of political shocks, including changes in a country’s economic stewardship, national elections, coup d’états, wars, and terrorist attacks. Using an event study approach and daily prices from the Buenos Aires exchange (Argentina) between 1967 and 2020, we find that stock-market volatility increases in the days immediately following major policy-shifting events. These results hold irrespective of whether returns are measured in nominal terms, in local consumption units, or in US dollars. The most significant increase in post-event risk is associated with irregular government turnovers. Volatility also increases in the days immediately following a defeat in an international war, national elections, and changes in the country’s economic stewardship. No changes in stock-market volatility occur, however, after terrorist attacks or when the date of a new administration’s inauguration is publicly known and determined sufficiently far in advance.
An evaluation of multicomponent absorption equilibria models

An investigation into the modelling of competitive adsorption equilibria data using the ideal adsorbed solution theory (IAST), the modified simplified competitive adsorption models (MSCAM), and the equivalent background compound (EBC) method is presented. The models were evaluated with the only competitive isotherms available which quantified both natural organic matter (NOM) and synthetic organic chemical (SOC) adsorption. The data used a mixture of 1,1,2-trichloroethane (TCEA) and NOM from river water measured as dissolved organic carbon (DOC). The IAST method was applied by representing the NOM in the river water as pseudocomponents. It was observed that the laborious and time-consuming regressions of only the TCEA isotherm data yield different sets of parameters, many of which do not describe the NOM data well. Simultaneous regression of TCEA and NOM isotherm data, like TCEA isotherm data regression, is highly dependent on the initial guesses of the parameters. MSCAM simulated the NOM adsorption very well but TCEA less so. TCEA simulation with the EBC method provided good results, but unrealistic EBC characteristics led to poor predictions. Model predictions of the experiment showed that the MSCAM model described the data better than the IAST method, but not perfectly. DOC-based MSCAM simulation does not offer any significant improvements over molar-based simulation.
Machine Learning for Solving Charging Infrastructure Planning Problems: A Comprehensive Review

As a result of environmental pollution and the ever-growing demand for energy, there has been a shift from conventional vehicles towards electric vehicles (EVs). Public acceptance of EVs and their large-scale deployment raises requires a fully operational charging infrastructure. Charging infrastructure planning is an intricate process involving various activities, such as charging station placement, charging demand prediction, and charging scheduling. This planning process involves interactions between power distribution and the road network. The advent of machine learning has made data-driven approaches a viable means for solving charging infrastructure planning problems. Consequently, researchers have started using machine learning techniques to solve the aforementioned problems associated with charging infrastructure planning. This work aims to provide a comprehensive review of the machine learning applications used to solve charging infrastructure planning problems. Furthermore, three case studies on charging station placement and charging demand prediction are presented. This paper is an extension of: Deb, S. (2021, June). Machine Learning for Solving Charging Infrastructure Planning: A Comprehensive Review. In the 2021 5th International Conference on Smart Grid and Smart Cities (ICSGSC) (pp. 16–22). IEEE. I would like to confirm that the paper has been extended by more than 50%.
CAD-integrated design for manufacturing and assembly in mechanical design

ABSTRACT Design for Manufacturing and Assembly (DfMA) is a consolidated engineering activity that suffers a real integration with 3D CAD systems. DfMA principles are currently applied downstream of the 3D modelling, by following the well-known rules available from the literature and company’s know-how. The paper provides a method to acquire, elaborate and represent DfMA rules sets to aid designers and engineers in developing mechanical products. This research work wants to define a general method able to couple DfMA design guidelines (knowledge-based design) with geometrical product features available by the investigation of the 3D model. The analysis of the 3D CAD model allows to anticipate manufacturing issues and to control manufacturing cost during product design. Moreover, a framework to embed this approach within a 3D CAD system is presented for future development in a software tool. Two case studies, a simple casing made of six parts and a centrifugal pump made of sixty-eight parts, highlight how the proposed method allows easy deployment of this approach in DfMA projects. Several benefits are recognized: (i) anticipation of manufacturing and assembly issues, (ii) reduction of manufacturing and assembly cost and, (iii) reduction of effort and time required by designers during the product development process.
Multidimensional sentiment recognition of film and television scene images

Abstract. Identifying and analyzing the sentiment information of an image is a complicated task in content understanding with nondeterministic features. To establish an effective model for multidimensional emotion recognition of film and television scene images and explore the relationship between the inputs and prediction results, we chose eight feature selection schemes based on principal component analysis, least absolute shrinkage operator (Lasso) regression, Pearson correlation, and the importance of random forest (RF) to establish the input vectors and the relevant model of machining learning. After the test on the data set with fixed combination of dimension reduction of 19 emotional descriptors, the fuse of Lasso regression and the RF importance extraction were proved to have the best performance on accuracy with the regression models. The experimental results showed that our algorithm performed well on the regression task of multidimensional affective dataset, which was convenient and time-saving. The extracted features and relevant dimension reduction methods also achieved good results on the cross-dataset classification tasks.
A Modern Concept of Blind Hiring: Its Importance and Benefits

Blind hiring is an HR practice that aims at reducing biases during the hiring process. The idea is to promote talent acquisition based on a transparent method and hire eligible candidates regardless of their name, gender,mother tongue, religion and socio economic background. The focus instead is on skills, talents and abilities and these are evaluated as objectively as possible. Rather than submit resumes for position openings, interested candidates will instead complete batteries of assessments work samples and such on.
The China Syndrome in US: Import Competition, Crime, and Government Transfer

In this paper, we exploit the exogenous rise of Chinese imports in US to investigate the effect of import competition on crime at county level. Our results indicate that counties with high exposure to Chinese import competition are with high crime rates while the exposure effect on property crime is much larger than that for violent crime: one standard deviation increase of exposure will increase 2.1 more violent crimes in the county while such increase of exposure will cause 26.5 more property crimes. Interestingly, we find that the crime impact of exposure to Chinese import competition disappears in counties with high government transfer.
Genetic Diversity and Population Structure of Moroccan Isolates Belong to Alternaria spp. Causing Black Rot and Brown Spot in Citrus

Alternaria alternata is one of the most important fungi causing various diseases on citrus worldwide. In Morocco, Alternaria black rot (ABR) and Alternaria brown spot (ABS) are two major diseases causing serious losses in commercial cultivars of citrus. The aim of the present work was to study the genetic diversity and the population structure of isolates belonging to sect. Alternaria obtained from infected citrus fruits, collected from seven provinces at different locations in Morocco (markets, packinghouses, and orchards). Forty-five isolates were analyzed by sequence-related amplified polymorphism (SRAP) markers, and cluster analysis of DNA fragments was performed using UPGMA method and Jaccard coefficient. Cluster analysis revealed that isolates were classified in four distinct groups. AMOVA revealed also a large extent of variation within sect. Alternaria isolates (99%). The results demonstrate that no correlation was found among SRAP pattern, host, and geographical origin of these isolates. Population structure analyses showed that the Alternaria isolates from the same collection origin had almost a similar level of admixture.
Characteristics of single-ended resonant-type inverter for HID lamps

This paper presents a novel type of solid state ballast and ignitor for HID (high intensity discharge) lamps. This ballast is composed of a single-ended resonant-type inverter, which can supply high frequency (100 kHz) power to a 70 W metal-halide lamp, one of the HID lamps, without an acoustic resonance. The proposed ignitor is composed of a magnetic pulse compression (MPC) circuit, which can generate sufficiently high voltage pulses for the instantaneous restarting of the HID lamp. The characteristics of this proposed inverter and ignitor circuits for HID lamps are described in this paper. Based on the results obtained from experiments, the proposed circuits are more useful than the conventional one.
Does the Requirement of Readability Testing Improve Package Leaflets? Evaluation of the 100 Most Frequently Prescribed Drugs in Germany Marketed before 2005 and First Time in 2007 or After

Objectives: Based on the “Action Plan 2008/2009 for Improving Drug Therapy Safety” issued by the German Federal Ministry of Health, the Federal Institute for Drugs and Medical Devices (BfArM) has launched a study on the effect of readability user tests on the quality of Package Leaflets (PLs). Methods: Based on recommendations from the EU Readability Guideline, a criteria catalogue for the analysis of PLs has been set up, serving as surrogate parameters for readability of statements within the PL. 100 of the most frequently prescribed medicinal products in Germany were selected and their readability analyzed. The study was blinded. Results: This study shows that merely 44% of the 100 most frequently prescribed medicinal products in Germany have PLs with a “normal” or better readability. PLs on the market since 2007 show a trend towards improvement when compared with products marketed before 2005. This effect was even more pronounced with the 23 PLs tested as required. Conclusions: The new European legislation in force by the end of 2005 induced a trend towards better usable PLs. On the average, however, this effect is barely recognisable. Only new products on the market need to be tested in regard to readability. Simultaneously, the text extent increased – a considerable effect against the intended improvement. Practice Implications: Apart from text required to be short as possible, of short sentences, simple and clearly written, other legal requirements influence the length of PLs: These conflicts cannot be resolved as long as the entire SmPC needs to be mentioned in the PL due to Medicinal Product Act and liability provisions Nowadays, other (technical) solutions should be legally confirmed to present the content of a PL with a good design in different ways according to the need of each of different user groups.
What determines commute time choices? A structural equation modelling approach

Abstract Many researchers have been attracted by the phenomenon of constant travel time, and the time spent on travel has been an important indicator of understanding travellers’ behaviours. This paper is based on a survey conducted in a university in London which includes both objective and subjective variables in relation to commute time and some demographic characteristics. Two conceptual structural models are examined in order to explore the factors determining travellers’ choices. Results of the analysis reveal some interesting relationships: (1) a positive relationship between age and commute time; (2) females are more likely to read or listen to music during their journeys, and their ideal commute time (ICT) and current commute time (CCT) generally tend to be longer; (3) academic staff tend to have the habit of working during their commute, administrative staff tend to commute longer while students tend to spend a shorter time commuting; (4) normally, a habit while travelling is significantly associated with CCT; those with a habit of reading or working during their commute journey tend to have longer commute times and (5) the relationship between CCT and commuters’ ICT and tolerable commute time is positive; both hypothesised causal relationships are significant so that a loop is formed between subjective and objective variables, and thus a dynamic modelling process could be envisaged as temporal sequences of those variables.
Choose Appropriate Subproblems for Collaborative Modeling in Expensive Multiobjective Optimization

In dealing with the expensive multiobjective optimization problem, some algorithms convert it into a number of single-objective subproblems for optimization. At each iteration, these algorithms conduct surrogate-assisted optimization on one or multiple subproblems. However, these subproblems may be unnecessary or resolved. Operating on such subproblems can cause server inefficiencies, especially in the case of expensive optimization. To overcome this shortcoming, we propose an adaptive subproblem selection (ASS) strategy to identify the most promising subproblems for further modeling. To better leverage the cross information between the subproblems, we use the collaborative multioutput Gaussian process surrogate to model them jointly. Moreover, the commonly used acquisition functions (also known as infill criteria) are investigated in this article. Our analysis reveals that these acquisition functions may cause severe imbalances between exploitation and exploration in multiobjective optimization scenarios. Consequently, we develop a new acquisition function, namely, adaptive lower confidence bound (ALCB), to cope with it. The experimental results on three different sets of benchmark problems indicate that our proposed algorithm is competitive. Beyond that, we also quantitatively validate the effectiveness of the ASS strategy, the CoMOGP model, and the ALCB acquisition function.
A Wideband Linear FM Ramp Generator for the Long-Range Imaging RADAR

This paper describes the linear FM ramp generator that provides the wideband transmitted signal and correlation receiver reference for the long-term imaging RADAR (LRIR) developed and operated by the M.I. T. Lincoln Laboratory. The signal generated has a bandwidth of 1000 MHz and a duration of 250 mu s. Because of its large time-bandwidth product, the signal is generated actively by sweeping a voltage-controlled oscillator. Special attention is given to the means for achieving linearity, reproducibility, and coherence of the generated ramps.