Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuously Energy Consumption Measure Approach Using a DMA Double-Buffering Technique

Measuring the consumption of electronic devices is a difficult and sensitive task. Data AcQuisition (DAQ) systems are often used to determine such consumption. In theory, measuring energy consumption is straightforward, just by acquiring current and voltage signals we can determine the consumption. However, a number of issues arise when a ne analysis is required. The main problem is that sampling frequencies have to be high enough to detect variations in the assessed signals over time. In that regard, some popular DAQ systems are based on RISC ARM processors for microcontrollers combined with Analog-Digital Converters (ADC) to meet the frequency acquisition requirements. The efficient use of the Direct Memory Access (DMA) modules combined with pipelined processing in the microcontroller allows to improve the sample rate overcoming the processing time and the internal communication protocol limitations. This paper presents a novel approach for high frequency energy measurement composed of a DMA rate improvement (data acquisition logic), a data processing logic and a low-cost hardware. The contribution of the paper is the combination of a double buffered signal acquisition mechanism and an algorithm that computes the device's energy consumption using parallel data processing. The combination of these elements enables a high-frequency (continuous) energy consumption measurement of an electronic device, improving the accuracy and reducing the cost of existing systems. We have validated our approach by measuring the energy consumed by basic circuits and Wireless Sensors Networks (WSNs) motes. The results indicate that the energy measurement error is less than 5%, and that the proposed method is suitable to measure WSN motes even during sleep cycles, enabling a better characterization of their consumption prole.
Apatinib Suppresses Gastric Cancer Stem Cells Properties by Inhibiting Sonic Hedgehog Pathway

Wanshuang Cao Nanjing Medical University Yuan Li Nanjing Drum Tower Hospital: Nanjing University Medical School A liated Nanjing Drum Tower Hospital Hongliang Sun Taikang Xianlin Drump Tower Hospital Jianyun Zhu Suzhou Municipal Hospital Chunfeng Xie Nanjing Medical University Xiaoting Li Nanjing Medical University Jieshu Wu Nanjing Medical University Shanshan Geng Nanjing Medical University Lu Wang Jiangsu Hengrui Medicine Co Ltd Liangfei Sun Jiangsu Hengrui Medicine Co Ltd Guozhu Geng Jiangsu Hengrui Medicine Co Ltd Hongyu Han Sun Yat-sen University Cancer Center Caiyun Zhong (  cyzhong@njmu.edu.cn ) Nanjing Medical University https://orcid.org/0000-0002-5402-3713
Estimation of Separation Factor for Analogues in CCC Using UNIFAC

Abstract Separation factor is an important index for judging the eluotropic sequence of solutes in countercurrent chromatography (CCC). This paper has proven that the contribution of the common basic agglomerate can be eliminated when calculating the separation factor for analogues and introduced a computational equation based on UNIFAC. According to the equation, the estimation of separation factors needs only a few different groups of analogues. Eleven kinds of analogues, such as phytosterol, chlorinated s‐triazines, flavonoids, theaflavins, anthocyanins, sporaviridins, etc., have been tested with the method. Though the solvent systems used are different from each other, the estimated eluotropic sequences are all consisted well with the literatures except for two chlorinated s‐triazines.
The influence of thermal after-treatment on the adhesion of 3D prints on textile fabrics

3D printing belongs to the emerging technologies of our time. While it enables producing new structures and makes individualized products affordable, 3D printed objects still suffer from low production speed and often insufficient mechanical properties. Both these problems can be tackled by combining 3D printing with substrates prepared by conventional technologies, e.g. textile fabrics. In this case, the adhesion between both partners is most challenging and defines for which possible applications such composites are suitable. Here, we report on a new approach to increase the adhesion between 3D printed materials and warp knitted fabrics, showing that in some cases a thermal after-treatment, in the simplest case performed by ironing, is able to significantly increase the adhesion between both materials.
Exposing the Revolving Door in Executive Branch Agencies

We develop the first comprehensive mapping of the revolving door phenomenon in the U.S. by examining the work experience in executive branch agencies of 1,910,150 individuals covering top corporate positions in 373,011 unique firms. We document that the phenomenon is prevalent, with one out of every 15 firms, and one out of every three publicly traded firms, having at least one top employee with prior work experience in U.S. executive branch agencies. On average, former regulators are hired in response to or concomitant with increases in regulation as well as concomitant with more aggressive regulator behavior in the form of a higher incidence of fines. Firms headquartered in more corrupt states, firms seemingly more corruption-prone, and established violators receive benefits in the form of a reduction in the incidence of fines after hiring former regulators from fine-imposing agencies. In contrast, we do not observe other firms receiving benefits on average.
Problems and Practice of Management on Menstruation by Adolescents Girls of Basic Schools of Chitwan, Nepal

Managing menstruation in a hygienic way is a challenge in most of the low and middleincome countries (LMIC) including Nepal, where normal and natural physiological process of menstruation is considered as girls’ problem which is viewed as sinful, unholy and matter of shame. This paper explores the current practice and existing difficulties that adolescents girls encounter hygienic management of menstruation (MHM) especially during school days. The study was conducted on five purposively selected community schools of Chitwan district. The study adopted Participatory Action Research (PAR) as an approach, that is encapsulated with mixed method research design. For qualitative information observation, focus group discussions (FGD) and field notes were used, whereas for quantitative data self-administrative questionnaires were used. Quantitative information was collected from 205 girls students who were present at schools on the day of data collection. The finding shows that majority of the girls (93.7%) who encounter hygienic management of menstruation were of 10-14 years old age, whereas nearly one third of them were (29%) from grade eight. Similarly, among the total 205 girls, only 79 girls have already started their menstruation; among those who have started menstruation majority (78%) had heard about menstruation form their mothers. Likewise, 35% girls used homemade cotton pads and 40.5% of them changed pad three times a day. During FGD, adolescents girls shared that lack of water and soap in toilets, stress and lack of concentration during menstruation are the major difficulties which they encounter during days of menstruation. They suggested the concerned authorities to manage pad bank, make soap and water available, and develop skills for proper disposing of used sanitary pads for MHM at schools.
Maternal Mediation of Retail Food Promotions Directed at Children

Abstract The present study seeks to identify whether mothers perceive the effect of in-store food promotional strategies on food shopping behavior of children and mediate this impact by using feeding practices. Data have been collected from 473 mothers of children in the age category 4–11 years from Punjab (India). The mothers are found to use multiple feeding practices because they recognize that the use of in-store food promotional strategies have negative effects on the health of children. They use “teaching about nutrition” and “food as a reward” practices because they find rampant use of in-store food promotional strategies.
Measurement of Inter-Individual Variability in Assessing the Quality of Life in Respondents with Celiac Disease

Quality of life of Celiac Disease (CD) patients is affected by constraints in their physical, social and emotional behaviour. Our objective is to assess differences in two relevant dimensions of the Celiac Quality of Life (CQoL) scale, Limitations due to the disease and Dysphoria (i.e., feelings of depression and discomfort), in relation to the perceived social support and some individual and disease-related characteristics. The paper exploits suitable unidimensional Item Response Theory (IRT) models to individually analyse the two mentioned dimensions of the CQoL and Multidimensional Latent Class IRT models for ordinal polytomous items in order to detect sub-populations of CD patients that are homogenous with respect to the perceived CQoL. The latter methods allow to address patients with similar characteristics to the same treatment, performing at the same time a more tailored overture to health promotion programmes. The analysis extracts the relevant patterns and relations among CD patients, disentangling respondents receiving CD diagnosis in adolescence or adult age rather than in childhood (the first perceive high levels of Limitations and Dysphoria), patients with high perceived social support, a factor influencing in a positive way motivation to engage in management of CD-related distress and psychological well-being, and participants who are married or cohabiting. The latter report higher latent trait levels.
Direct measurement of petiole sap nitrate in potato to determine crop nitrogen status.

Abstract Rapid determination of crop nitrogen (N) status in the field would facilitate the use of plant tissue testing as a tool for ? management in potato (Solarium tuberosum L.). The Cardy portable nitrate (NO3) meter may provide the means for on‐site determination of petiole sap NO3 (PSN) concentration. Our objective was to establish the relationship between Cardy meter readings of PSN and laboratory measures of petiole dry matter NO3 (PDMN). In a two‐year replicated field study in western Montana, ‘Russet Burbank1 potatoes were grown under a line‐source sprinkler irrigation system with ? fertilization treatments of 0 ? or a rate of 270 kg N/ha applied in four different timing schemes. This created a wide range in crop ? and water status. Petiole samples were collected at five or six dates each year. Subsamples were analyzed for PSN in expressed sap using the Cardy NO3‐specific electrode or for PDMN with a benchtop NO3‐specific electrode after extraction with a solution of aluminum sulfate [A12(SO4)3].
Spectral Imaging in a Programmable Array Microscope by Hadamard Transform Fluorescence Spectroscopy

We report the use of a thin-film transistor (TFT) twisted nematic liquid crystal spatial light modulator (SLM) for Hadamard transform two-dimensional spectral imaging in a fluorescence microscope. The liquid crystal SLM placed in the primary image plane of the microscope generates a set of spatial encoding masks defined by a cyclic S-matrix. The light passing through the mask is relayed by anamorphic optics to the entrance of an imaging spectrograph and detected with a charge-coupled device (CCD) camera. The SLM allows for the convenient generation of arbitrary masks without moving parts. The Hadamard transform approach transmits up to 50% of the light from the image field for multichannel detection, but is subject to transmission losses in the SLM. The system allows the convenient acquisition of two-dimensional spectral images. We characterized and tested many of the parameters controlling both spatial and spectral resolution, and demonstrated the system in the analysis of both naturally fluorescing and stained biological samples.
Review of the Application of Big Data and Artificial Intelligence in Geology

Big data and artificial intelligence (AI) have provided new methods and opportunities for many applications in geology. Nevertheless, big data and AI-based geoscience applications are still in their infancy, and the methods and objectives are still scattered, lacking a unified theoretical and application framework. This study reviews the application of big data and AI in geology and analyzes and summarizes the current status, development trends and existing problems of ongoing studies from the perspectives of geology. This study can provide a reference for the future research and development of the application of big data and AI in the field of geology.
Barriers and drivers to the uptake of innovative, affordable, and zero-energy dwellings in Belgium and Ireland

Despite efforts to promote and accelerate the adoption of innovative, affordable, and zero-energy dwelling solutions, the number of dwellings complying with standards such as the EPBD remains relatively low as we reach year 2020. Studies have already explored potential challenges and opportunities to the uptake of such designs. However, despite previous findings and recommendations, the market’s response remains slow. Building on existing knowledge and as part of the Housing 4.0 Energy project, this study investigates current financial, cultural, legislative and technical barriers and drivers to the implementation and uptake of small, innovative, affordable, zero-energy dwellings in small towns in Belgium and Ireland. Focus groups gathering housing providers, decision makers, stakeholders, and contractors were conducted in Leuven and Kilkenny. Outcomes revealed that participants’ general perceptions around barriers and drivers are similar between the two countries and are validated by previous research findings. However, a closer look at context specific barriers reveals considerable differences. The identification of these contextual differences enables a better apprehension of the current situation in every location leading to the formulation of context specific recommendations and a better allocation of precedence. Thus, this paper demonstrates the importance of context specific investigations not only in the identification of challenges to energy efficiency innovations but also in establishing more effective implementations.
Utilization of Evolutionary Plant Breeding Increases Stability and Adaptation of Winter Wheat Across Diverse Precipitation Zones

Evolutionary plant breeding (EPB) is a breeding method that was used to create wheat (Triticum aestivum L.)-evolving populations (EP), bi-parental and composite-cross populations (BPPs and CCPs), by using natural selection and bulking of seed to select the most adaptable, diverse population in an environment by increasing the frequency of favorable alleles in a heterogeneous population. This study used seven EPs to evaluate EPB in its ability to increase the performance of agronomic, quality, and disease resistance traits and adaptability across different precipitation zones. The populations were tested in field trials in three diverse locations over 2 years. Least significant differences showed the EPs performance was dependent on their pedigree and were statistically similar and even out-performed some of their respective parents in regards to grain yield, grain protein concentration, and disease resistance. Stability models including Eberhart and Russel’s deviation from Regression (S2di), Shukla’s Stability Variance (σi2), Wricke’s Ecovalance (Wi), and the multivariate Additive Main Effects and Multiplicative Interaction (AMMI) model were used to evaluate the adaptability of the EPs and their parents. The BPPs and CCPs demonstrated significantly greater stability over the parents across precipitation zones, confirming the capacity of genetically diverse EP populations to adapt to different environments.
A new red wine prediction framework using machine learning

Red wine has become an integral part of people’s lives and culture. Modeling the red wine quality is crucial. We propose a new framework to predict the red wine quality ratings. MF-DCCA was utilized to quantitatively investigate the cross-correlation between quality and physicochemical data. The long-range correlations importance was ranked. We compared two machine learning algorithms with other common algorithms implemented on the red wine data set, which was taken from UC Irvine Machine Learning Repository to ensure the reliability and performance. These data sets contain 1599 instances for red wine with 11 features of physicochemical data. Our model has better performance than other results.
Food web models reveal potential ecosystem effects of seagrass recovery in the northern Wadden Sea

In contrast to the global trend, seagrass beds have recovered in size and density in the northern part of the European Wadden Sea, but ecosystem effects of seagrass recovery and the impacts to ecosystem services are largely unknown. We used temporal‐dynamic food web modeling Ecopath with Ecosim to assess potential ecosystem effects of seagrass recovery in the semi‐enclosed Sylt‐Rømø Bight at the German‐Danish border. In addition to changes in the system's structure and functioning over time, the model predicted changes in biomass of seagrass‐associated species. For seagrass consumers, we projected an increase in biomass as a result of an increase in food supply. Likewise, the model predicted an increase in biomass of seagrass meadow inhabitants from decreased predation pressure. Correspondingly, the main predators of these inhabitants decreased in biomass according to model results. Proxies representing ecosystem services predicted an increase of tourism appeal of the site with increasing seagrass meadows. Indirect mediation effects of seagrass severely influenced the model output and are thus crucial to forecast potential effects of the recovery of habitat‐forming species. Our study illustrates that holistic approaches such as food web models could provide a suitable basis for predicting ecosystem effects of changes in the biomass of habitat‐forming species such as seagrasses.
Epidemiology and Antimicrobial Susceptibility Pattern of Uropathogens in Patients with the Community- and Hospital-Acquired Urinary Tract Infections at a Tertiary Hospital in Somalia

Background: Urinary tract infections (UTIs) are the most common infections in the community and in hospitalized patients. Objectives: To investigate the epidemiology and antimicrobial susceptibility pattern of uropathogens and determine the appropriate empirical antibiotics to treat UTIs in the community and hospitalized patients. Methods: A total of 2,485 urine cultures were performed at Mogadishu Somali Turkish Training and Research Hospital. Through the standard Kirby-Bauer disk diffusion method and commercial disks, antimicrobial sensitivity and resistance were studied based on the Clinical and Laboratory Standards Institute (CLSI) system using Mueller-Hinton agar. The identification of the microorganisms was done using eosin methylene blue agar and blood agar. Results: Escherichia coli was the most predominant pathogen (63.4%) in all age groups, both genders, and in the community and hospital-acquired UTIs, followed by Klebsiella pneumonia (13.3%). Ceftriaxone, trimethoprim/sulfamethoxazole, ampicillin, cefuroxime, and cefixime revealed the highest resistance level (82-100%) against uropathogens. Ciprofloxacin (67.7%) and levofloxacin (54.2%) showed increasing resistance rates against uropathogens. Tigecycline, colimycin, vancomycin, and teicoplanin exhibited the most powerful sensitivity rate (100%). Moreover, fosfomycin, nitrofurantoin, and amikacin manifested a significant sensitivity rate ranging from 86% - 95%. Acinetobacter baumannii was the most prevalent pathogen that belonged to multidrug- and extensively drug-resistant patterns in 69.1% of the samples. Escherichia coli and K. pneumonia showed similar multidrug-resistant patterns in 35.2% of the cases. Conclusions: The results indicated increased trends of antimicrobial resistance rate in trimethoprim/sulfamethoxazole (85.1%) and fluoroquinolones (61%) against E. coli that was higher than the recommended local resistance rate for empirical therapy (< 20% and < 10%, respectively). According to the results, using fosfomycin and nitrofurantoin are suggested for UTI empiric treatment, and other antibiotics should be prescribed carefully.
Vehicle speed preview control with road curvature information for safety and comfort promotion

Vehicle lateral acceleration is a critical state and index for vehicle safety and ride comfort. To limit it in high speed cornering situation, a vehicle speed preview controller is proposed with the information of future road curvature, just as a human driver behavior. The future road curvature can be obtained from high definition map in intelligent vehicle control, and to implement it, model predictive control method (MPC) is implemented taking advantage of its preview nature. In this preview speed control framework, a novel kinematics model with vehicle location, speed and track curvature is established for vehicle states prediction. The control performance index of MPC is constructed with vehicle road following index and lateral acceleration index with the aiming of promoting safety and ride comfort. The controller is evaluated during cornering with different road trajectory, initial speed, preview time and road adhesion coefficient in a hardware-in-the-loop simulation platform. It is testified that vehicle slows down before cornering as human driver does to decrease lateral acceleration and steering angle with the benefit of promoting comfort and safety.
Subnational governance strategies at the extractive frontier: collaboration and conflict in Peru

ABSTRACT The past decade has witnessed profound transformations in subnational territories engendered by a dramatic increase in natural resource extraction. Research to date has concentrated largely on why the transfer of extractive revenues often reinforces a ‘local resource curse’; however, little work has been done on subnational governments’ attempts to maximize the benefits and minimize the costs of mining expansion. Drawing on the literature on subnational governance in the context of resource extraction and neoliberal reforms, this study analyses the strategies – confrontational or collaborative – subnational political leaders pursue and the reasons why they pursue them. The findings are based on in-depth field research in two Peruvian subnational regions that are highly dependent on mineral extraction. More specifically, we examine the collaborative strategy pursued in one region and compare it with a confrontational strategy in another. Our analysis indicates that an interplay between institutional capacity and supporting coalitions affects whether subnational leaders undertake a collaborative or a confrontational approach. Based on our findings, we consider the likely effects of these strategies for regional development. By shifting the focus to the agency of subnational leaders, we make an essential contribution to debates about subnational governance in the realm of resource extraction.