Miracle-dz/UniFAR-FTUs huggingface dataset:
14-Bit Fully Differential SAR ADC with PGA Used in Readout Circuit of CMOS Image Sensor

This paper proposes a 14-bit fully differential Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) with a programmable gain amplifier (PGA) used in the readout circuit of CMOS image sensor (CIS). SAR ADC adopts two-step scaled-reference voltages to realize 14-bit conversion, aimed at reducing the scale of capacitor array and avoiding using calibration to mitigate the impact of offset and mismatch. However, the reference voltage self-calibration algorithm is applied on the design to guarantee the precision of reference voltages, which affects the results of conversion. The three-way PGA provides three types of gains: 3x, 4x, and 6x, and samples at the same time to get three columns of pixel signal and increase the system speed. The pixel array of the mentioned CIS is 1026 × 1024 , and the pixel pitch is 12.5 μ m × 12.5 μ m . The prototype chip is fabricated in the 180 nm CMOS process, and both digital and analog voltages are 3.3 V. The total area of the chip is 6.25 × 18.38 mm2. At 150 kS/s sampling rate, the SNR of SAR ADC is 71.72 dB and the SFDR is 82.91 dB. What is more, the single SAR ADC consumes 477.2 uW with the 4.8 V PP differential input signal and the total power consumption of the CIS is about 613 mW.
On Tribonacci I -convergent sequence spaces

In this paper, we use the notion of ideal convergence ( I -convergence) to introduce Tribonacci I -convergent sequence spaces, that is, c I 0 ( T ) , c I ( T ) and l I ∞ ( T ) as a domain of regular Tribonacci matrix T = ( t jn ) (constructed by the Tribonacci sequence). We also present few inclusion relations and prove some topological and algebraic properties based results with respect to these spaces.
Perioperative Use of Flurbiprofen Axetil on Renal Function after Transurethral Prostatectomy: A Prospective Randomized Controlled Study

Objective. To explore the role of low-dose flurbiprofen axetil in perioperative renal protection. Methods. A total of 83 patients who underwent transurethral resection of the prostate (TURP) between August 2020 and November 2020 at the Third Xiangya Hospital of Central South University were selected, aged 60-85 years old, American Society of Anesthesia (ASA) physical status classes 1-3, BMI 18-30 kg/m2, randomly divided into the experimental group (group F, n = 42 ) and control group (group C, n = 41 ). 10 minutes before the operation, group F was injected with 100 mg (10 mL) flurbiprofen axetil, and group C was injected with 10 mL 0.9% saline, comparing the incidence of acute kidney injury (AKI) and changes in glomerular filtration rate (eGFR) between the two groups. Cystatin-C, Neutrophil Gelatinase-associated Lipocalin (NGAL), IL-6, and CRP were compared between the two groups at 4 time points (before surgery, 6 hours, 24 hours, and 48 hours after surgery). Results. A total of 80 cases were enrolled, 40 in group F and 40 in group C. There was no significant difference in baseline between the two groups ( P > 0.05 ). The NGAL of group F was significantly lower than group C at 6 hours after the operation ( 367.99 ± 311.83 vs. 243.02 ± 151.73 , P = 0.026 ), but there was no significant difference in NGAL and Cystatin-C at other time points ( P > 0.05 ). And there was no significant difference in the incidence of postoperative AKI between the two groups (0% vs. 2.5%, P = 0.314 ). Conclusion. 100 mg flurbiprofen axetil can reduce the NGAL at 6 hours after TURP, and it may have a protective effect on the kidney.
Different roles, different demands. A competency-based professional roles model for early career engineers, validated in industry and higher education

ABSTRACT This study contributes to the current research in career and professional identity development in that it developed a validated competency-based framework to enhance professional and self-awareness of future engineers. Through a mixed-method design, key competencies were identified for three professional roles for early career engineers. Ninety-six engineers and HR experts from different fields were involved. This resulted in three portraits of early career engineers in practice (engineers in a role focusing on radical innovation, on process optimisation and/or on customised solutions) and what it requires to be successful in these roles. For example, perseverance and creativity were deemed essential for engineers in an innovative role, whereas positive critical attitude and stress resistance were indicated essential for engineers focusing on optimisation. The competency profiles with an aspiration to career perspectives can be a valuable instrument in creating more diversity in engineering. Implications for education, industry, and future research are discussed.
Computed tomography measurement of 3D combustion chemiluminescence using single camera

Instantaneous measurement of flame spatial structure has been long desired for complicated combustion condition (gas turbine, ramjet et.). Three dimensional computed tomography of chemiluminescence (3D-CTC) is a potential testing technology for its simplicity, low cost, high temporal and spatial resolution. In most former studies, multi-lens and multi-CCD are used to capture projects from different view angles. In order to improve adaptability, only one CCD was utilized to build 3D-CTC system combined with customized fiber-based endoscopes (FBEs). It makes this technique more economic and simple. Validate experiments were made using 10 small CH4 diffusion flame arranging in a ring structure. Based on one instantaneous image, computed tomography can be conducted using Algebraic Reconstruction Technique (ART) algorithm. The reconstructed results, including the flame number, ring shape of the flames, the inner and outer diameter of ring, all well match the physical structure. It indicates that 3D combustion chemiluminescence could be well reconstructed using single camera.
Data-driven molecular design for discovery and synthesis of novel ligands: a case study on SARS-CoV-2

Bridging systems biology and drug design, we propose a deep learning framework for de novo discovery of molecules tailored to bind with given protein targets. Our methodology is exemplified by the task of designing antiviral candidates to target SARS-CoV-2 related proteins. Crucially, our framework does not require fine-tuning for specific proteins but is demonstrated to generalize in proposing ligands with high predicted binding affinities against unseen targets. Coupling our framework with the automatic retrosynthesis prediction of IBM RXN for Chemistry, we demonstrate the feasibility of swift chemical synthesis of molecules with potential antiviral properties that were designed against a specific protein target. In particular, we synthesize an antiviral candidate designed against the host protein angiotensin converting enzyme 2 (ACE2); a surface receptor on human respiratory epithelial cells that facilitates SARS-CoV-2 cell entry through its spike glycoprotein. This is achieved as follows. First, we train a multimodal ligand–protein binding affinity model on predicting affinities of bioactive compounds to target proteins and couple this model with pharmacological toxicity predictors. Exploiting this multi-objective as a reward function of a conditional molecular generator that consists of two variational autoencoders (VAE), our framework steers the generation toward regions of the chemical space with high-reward molecules. Specifically, we explore a challenging setting of generating ligands against unseen protein targets by performing a leave-one-out-cross-validation on 41 SARS-CoV-2-related target proteins. Using deep reinforcement learning, it is demonstrated that in 35 out of 41 cases, the generation is biased towards sampling binding ligands, with an average increase of 83% comparing to an unbiased VAE. The generated molecules exhibit favorable properties in terms of target binding affinity, selectivity and drug-likeness. We use molecular retrosynthetic models to provide a synthetic accessibility assessment of the best generated hit molecules. Finally, with this end-to-end framework, we synthesize 3-Bromobenzylamine, a potential inhibitor of the host ACE2 protein, solely based on the recommendations of a molecular retrosynthesis model and a synthesis protocol prediction model. We hope that our framework can contribute towards swift discovery of de novo molecules with desired pharmacological properties.
Treatment of organosolv and steam explosion lignins with molecular hydrogen iodide: A structural probe

The technique of mild depolymerization of lignin with hydrogen iodide, developed earlier for isolated preparations, was applied to organosolv lignins (ALPULP, spruce, aspen, sugarcane; ALCELL, mixed hardwood, wheat straw, palm oil bunches), organosolv pulps (ALPULP, spruce, aspen) and lignocellulosic materials, after steam explosion and enzymatic hydrolysis of Douglas fir. The yields and composition of the chloroform-soluble monomeric lignin depolymerization products, 1,3-diiodo-1-(4-hydroxyaryl)propanes, originated from guaiacyl (G), syringyl (S) and 4-hydroxyphenyl (H) units, were assessed on a semi-quantitative basis. ALPULP lignins were found to be more resistant to depolymerization than the respective lignins of the original lignocellulosic materials (17-21% yields). ALCELL lignin demonstrated similar properties, yet at lower (9-13%) yields. The degree of condensation is apparently higher in the residual lignin in pulp than in the dissolved lignins of the ALPULP process. Lignocellulosic materials produced by steam explosion did not demonstrate any significant depolymerization with hydrogen iodide. For steam-exploded Douglas-fir, the yield of guaiacyl monomer was below 1%, and no noticeable effect of the subsequent enzymatic hydrolysis was evident. The same behavior was observed for the alkali-soluble fraction of the steam explosion softwood lignin. SO 2 -Catalyzed steam explosion of softwood seems to change the α-reactive centers in lignin, thus making both residual and soluble lignins resistant to reductive cleavage by hydrogen iodide.
Integrating MODIS and Landsat Data for Land Cover Classification by Multilevel Decision Rule

In some cloudy and rainy regions, the cloud cover is high in moderate-high resolution remote sensing images collected by satellites with a low revisit cycle, such as Landsat. This presents an obstacle for classifying land cover in cloud-covered parts of the image. A decision fusion scheme is proposed for improving land cover classification accuracy by integrating the complementary information of MODIS (Moderate-resolution Imaging Spectroradiometer) time series data with Landsat moderate-high spatial resolution data. The multilevel decision fusion method includes two processes. First, MODIS and Landsat data are pre-classified by fuzzy classifiers. Second, the pre-classified results are assembled according to their assessed performance. Thus, better pre-classified results are retained and worse pre-classified results are restrained. For the purpose of solving the resolution difference between MODIS and Landsat data, the proposed fusion scheme employs an object-oriented weight assignment method. A decision rule based on a compromise operator is applied to assemble pre-classified results. Three levels of data containing different types of information are combined, namely the MODIS pixel-level and object-level data, and the Landsat pixel-level data. The multilevel decision fusion scheme was tested on a site in northeast Thailand. The fusion results were compared with the single data source classification results, showing that the multilevel decision fusion results had a higher overall accuracy. The overall accuracy is improved by more than 5 percent. The method was also compared to the two-level combination results and a weighted sum decision rule-based approach. A comparison experiment showed that the multilevel decision fusion rule had a higher overall accuracy than the weighted sum decision rule-based approach and the low-level combination approach. A major limitation of the method is that the accuracy of some of the land covers, where areas are small, are not as improved as the overall accuracy.
Microplastics in commercial bivalves harvested from intertidal seagrasses and sandbanks in the Ria Formosa lagoon, Portugal

Through seafood consumption, microplastic (MP) pollution is potentially threatening human health. Commercial bivalves in particular are a cause of major concern because their filter-feeding activity directly exposes them to MP in the water column and they are then ingested by humans. Here, we provide a quantitative and qualitative baseline data on MP content in the soft tissues of three commercially important bivalves (Ruditapes decussatus, Cerastoderma spp. and Polititapes spp.) collected in Ria Formosa lagoon, southern Portugal. The abundance of MPs (items per soft tissue weight) did not significantly differ among species. On average, R. decussatus exhibited the highest MP abundance (on average, 18.4±21.9 MP items g–1 WW), followed by Cerastoderma spp. (11.9±5.5 MP items g–1 WW) and Polititapes spp. (10.4±10.4 MP items g–1 WW). Overall, 88% of the MPs found were synthetic fibres, the majority of which were blue (52%). Size categories >0.1–1mm and >1–5mm were the most common (60% and 34% respectively). The most represented polymers were polyethylene (PE) and polystyrene (PS). The unexpectedly high number of MPs recorded in the three commercially exploited species suggests that this semi-closed lagoon system is experiencing a higher anthropogenic pressure than are open coastal systems.
Towards Intangible Freshwater Cultural Ecosystem Services: Informing Sustainable Water Resources Management

Rivers provide a range of Cultural Ecosystem Services (CES) such as aesthetic values, sense of place and inspiration, which remain insufficiently studied due to challenges associated with the assessment of their subjective and intangible attributes. However, the understanding of CES remains important as they are strongly linked to human wellbeing. This study utilizes a questionnaire-based survey to capture views from two villages along the mainstream of the Beas River in India, to identify the CES it provides, to assess how local communities appreciate their importance and how they relate to river flows. In total, 62 respondents were interviewed. Findings show that the Beas River provides several CES but among these, spiritual/religious ceremonies and rituals, aesthetic values and inspiration benefits were indicated as absolutely essential to the local communities. Results also demonstrate that people’s perception of the quality of CES is sometimes linked to river flows. It can be concluded that the Beas River is crucial in the functioning and livelihoods of local communities as it lies within the core of their cultural, religious and spiritual practices. This study reinforces the need to consider the full suite of ecosystem service categories in sustainable water resources development, planning and decision making.
Quantitative Performance Review of Wheeled Mobile Robot Path Planning Algorithms

Path planning evaluates and identifies an obstacle free path for a wheeled mobile robot (WMR) to traverse within its workspace. It emphasizes metric like, start and goal coordinate, static or dynamic workspace, static or dynamic obstacles, computational time and local minimum problem. Path planning play a significant role toward WMR effective traverse within it workspace like industrial, military, hospital, school and office. In this workspace, path planning is an optimal method to increase the productivity of WMR to achieve it specific task. Hence, in this paper, we present a review of path planning algorithms (classical algorithms, heuristics and intelligent algorithms, and machine learning algorithm) for mobile robot using statistical method. Regarding our objective, we use this statistical method to evaluate the success of these algorithms base on the following metrics: architecture (hybrid or standalone), algorithm sub-category (global or local or combine), workspace (static or dynamic), obstacle type (static or dynamic), number of obstacle (≤ 2, ≤ 5, > 5) and test workspace (virtual or real-world). Research materials are sourced from recognized databases where relevant research articles are obtained and analyzed. Result shows hybrid of machine learning approach with heuristic and intelligent algorithm has superior performance where they are applied compare to other hybrid. Also, in complex workspace Q-learning algorithm outperforms other algorithms. To conclude future research is discussed to provide reference for hybrid of Q-learning algorithm with Cuckoo Search, Shuffled Frog Leaping and Artificial Bee Colony algorithm to improve its performance in complex workspace.
Satellite Formaldehyde to Support Model Evaluation

Formaldehyde (HCHO), a known carcinogen classified as a hazardous pollutant by the United States Environmental Protection Agency (U.S. EPA), is measured through monitoring networks across the U.S. Since these data are limited in spatial and temporal extent, model simulations from the U.S. EPA Community Multiscale Air Quality (CMAQ) model are used to estimate ambient HCHO exposure for the EPA National Air Toxics Assessment (NATA). Here, we employ satellite HCHO retrievals from the Ozone Monitoring Instrument (OMI)—the NASA retrieval developed by the Smithsonian Astrophysical Observatory (SAO), and the European Union Quality Assurance for Essential Climate Variables (QA4ECV) retrieval—to evaluate three CMAQ configurations, spanning the summers of 2011 and 2016, with differing biogenic emissions inputs and chemical mechanisms. These CMAQ configurations capture the general spatial and temporal behavior of both satellite retrievals, but underestimate column HCHO, particularly in the western U.S. In the southeastern U.S., the comparison with OMI HCHO highlights differences in modeled meteorology and biogenic emissions even with differences in satellite retrievals. All CMAQ configurations show low daily correlations with OMI HCHO (r = 0.26–0.38), however, we find higher monthly correlations (r = 0.52–0.73), and the models correlate best with the OMI‐QA4ECV product. Compared to surface observations, we find improved agreement over a 24‐h period compared to afternoon‐only, suggesting daily HCHO amounts are captured with more accuracy than afternoon amounts. This work highlights the potential for synergistic improvements in modeling and satellite retrievals to support near‐surface HCHO estimates for the NATA and other applications.
Comparison of three cooking methods of rabbit meat

Three different methods of cooking rabbit meat were compared: boiling in water bath at 100°C, frying at 175°C, roasting at 200°C. The meat was considered cooked when its core temperature reached 80°C. Checking temperature every minute we verified that the meat was cooked after 3, 8 and 15 min, respectively, for frying, boiling and roasting. The cooking method significantly modified some traits of the meat: cooking and moisture loss, water holding capacity, shear force, chromatic parameters.
VD-PQ; A Velocity-Dependent Viscous Damping Model for Wave-Structure Interaction Analysis

For the analysis and design of coastal and offshore structures, viscous loads represent one of the most influential parameters that dominate their response. Very commonly, the potential flow theory is used for identifying the excitation wave loads, while the viscous damping loads are taken into consideration as distributed drag type loads and/or as linear and quadratic damping loads approximated with the use of motion decay curves of the structure in specific degrees of freedom. In the present paper, is developed and proposed a numerical analysis method for addressing wave-structure interaction effects through a velocity-dependent viscous damping model. Results derived by a computational fluid dynamics model are coupled with a model that uses the boundary element method for the estimation of the viscous damping loads iteratively in every time-step of the analysis. The computational fluid dynamics model solves the Navier–Stokes equations considering incompressible flow, while the second model solves the modified Cummins Equation of motion of the structure in the time domain. Details about the development of the coupling method and the velocity-dependent viscous damping (VD-PQ) are presented. The coupling between the different models is realized through a dynamic-link library. The proposed coupling method is applied for the case of a wave energy converter. Results derived with the use of the developed numerical analysis method are compared against experimental data and relevant numerical analysis predictions. The importance of considering the instantaneous velocity of the structure in estimating the viscous damping loads is demonstrated. The proposed numerical analysis method for estimating the viscous damping loads provides good accuracy compared to experimental data and, at the same time, low computational cost.
VALUES AND PSYCHOLOGICAL WELLBEING OF YOUTH: A SUSTAINABLE INTERCONNECTION

Values play the most influential role in the well-being of individuals with a particular focus on youth and their development. Psychological well-being refers to how people evaluate their lives. The purpose of this study was to determine the impact of values on the psychological well-being of adolescents. Using a quantitative research method, a sample of 300 adolescents aged 18 to 21 years was selected. The Personal Values Questionnaire by Sherry and Verma, the Psychological Well-Being Scale by Sisodia and Choudhary and the General Information Schedule were provided to them. The results showed that the dimensions of personal values have a significant positive correlation with the dimensions of adolescent psychological well-being. All dimensions of psychological well-being are shown to be positively predicted by values.
Vegetation classification for the management of large mammalian herbivores: a case study at Mushingashi Conservancy, Central Province, Zambia

The vegetation of Mushingashi Conservancy in central Zambia was classified and mapped to provide a template for wildlife management. Putative vegetation types were delineated using Landsat 8 imagery, then sampled with 73 plots for vegetation composition and structure, and topo-edaphic properties. Classification followed a four-stage process. Valley dambo and floodplain grasslands were first separated as landscape units from wooded plots. Hierarchical cluster analysis was then used to identify 13 vegetation types based on woody composition and structure. Convex hull plots on a principal component analysis biplot successfully delineated the topo-edaphic environment and woody structure of each type. Linear discriminant analysis confirmed differences in topo-edaphic environment among types. The main environmental gradient was from vertic clays, supporting open Acacia woodland, to sandy soils, supporting miombo woodland, but other gradients were also important. Of a total of 193 woody species recorded, 25 occurred only on large termitaria. An influence of environmental gradients independent of plant-available moisture and nutrients is emphasised. Total woody cover decreased conspicuously on clay-rich soils with increased water availability. A functional vegetation classification of this nature is considered an essential first step towards the informed management of rangeland for large herbivores. Potential applications for management are discussed.