Miracle-dz/UniFAR-FTUs huggingface dataset:
Green Infrastructure, Urbanization, and Ecosystem Services: The Main Challenges for Russia’s Largest Cities

Globally, the process of urbanization is transforming land use and, as a consequence, reducing the efficiency of ecosystem services (ESs), which ensure a healthy and comfortable urban environment. In cities, green infrastructure (GI) is a key source of urban ESs. Russia is a highly urbanized country: 70% of its population live in towns or cities. As cities continue to expand, they are swallowing unsealed lands that support ESs. In this paper, we present the results of an analysis of the current state and recent changes in urban GI in Russia’s 16 largest cities, including a biophysical evaluation of key urban ESs, using remote sensing data and freely available statistics. Our analysis identifies a weak correlation between GI area, ES volume, and favorable climate conditions as well as a stronger correlation between ESs and the increasing rate of urbanization. Considering Russia’s high level of urbanization, the key importance of ESs for the well-being of citizens, and ongoing reductions of urban GI, major revisions to urban planning policy are required. Indicators of urban biodiversity, GI, and ESs should be incorporated into decision-making processes. In particular, it is vital that the accounting and monitoring of GI and ESs are established in all of Russia’s larger cities.
A New Application of the Disturbance Index for Fire Severity in Coastal Dunes

Fires are a disturbance that can lead to short term dune destabilisation and have been suggested to be an initiation mechanism of a transgressive dune phase when paired with changing climatic conditions. Fire severity is one potential factor that could explain subsequent coastal dune destabilisations, but contemporary evidence of destabilisation following fire is lacking. In addition, the suitability of conventional satellite Earth Observation methods to detect the impacts of fire and the relative fire severity in coastal dune environments is in question. Widely applied satellite-derived burn indices (Normalised Burn Index and Normalised Difference Vegetation Index) have been suggested to underestimate the effects of fire in heterogenous landscapes or areas with sparse vegetation cover. This work assesses burn severity from high resolution aerial and Sentinel 2 satellite imagery following the 2019/2020 Black Summer fires on Kangaroo Island in South Australia, to assess the efficacy of commonly used satellite indices, and validate a new method for assessing fire severity in coastal dune systems. The results presented here show that the widely applied burn indices derived from NBR differentially assess vegetation loss and fire severity when compared in discrete soil groups across a landscape that experienced a very high severity fire. A new application of the Tasselled Cap Transformation (TCT) and Disturbance Index (DI) is presented. The differenced Disturbance Index (dDI) improves the estimation of burn severity, relative vegetation loss, and minimises the effects of differing soil conditions in the highly heterogenous landscape of Kangaroo Island. Results suggest that this new application of TCT is better suited to diverse environments like Mediterranean and semi-arid coastal regions than existing indices and can be used to better assess the effects of fire and potential remobilisation of coastal dune systems.
Association of Household Food Insecurity with Nutritional Status and Mental Health of Pregnant Women in Rural Bangladesh

Food insecurity may affect women’s health; however, pertinent research is scant among pregnant women. This study investigated the association of household food insecurity (HFI) with the nutritional status and mental health of 672 early-gestation (5–16 weeks) pregnant women with a singleton fetus, who participated in the screening activity of a community-based trial (NCT04868669) in Matlab, Bangladesh. Height (cm), weight (kg), body mass index (kg/m2), mid-upper arm circumference (MUAC) (cm), depression, anxiety, and stress were the outcomes studied. HFI was assessed using the Household Food Insecurity Access Scale. Women’s depression, anxiety, and stress were assessed using the Depression, Anxiety, and Stress Scales-21. Propensity score matching based weighted multivariable linear and logistic regression were used to evaluate the independent association of HFI with the outcomes. In adjusted models, pregnant women from food-insecure households in rural Matlab were on average 2.0 cm shorter (β = −2.0, 95% CI: −3.3, −0.7), 2.0 kg lighter (β = −2.0, 95% CI: −3.4, −0.7), and had 0.6 cm lower MUAC (β = −0.6, 95% CI: −1.1, −0.1) than their food-secure counterparts. HFI was associated with higher odds of depression (OR = 3.3, 95% CI: 1.8, 5.9), anxiety (OR = 6.1, 95% CI: 3.7, 10.0), and stress (OR = 4.8, 95% CI: 1.6, 14.2) among the women. Public health measures should focus on ensuring proper nutrition during the critical growth periods of life, pregnancy, and external environmental shocks, to mitigate the adverse effects of HFI on women’s health.
Students Academic Performance Analysis using Data Mining Techniques in Higher Education: A case study of college

According to National Knowledge Commission, Higher education in India refers to education beyond school (class 12). The medium term macro objective with regard to higher education would be to increase the gross enrolment ratio to at least 15% by 2015. In today’s competitive world improving & maintaining quality of education in society is challenging task for organizations. In modern times, the knowledge is a key ingredient to the development of the society. As the core competitive ability, the knowledge has become the most important factor to evaluate the quality of education. In many situations it will help to decision makers to better evaluate & enhance the higher educational organizations. To evaluation of such knowledge using mining techniques some interlinking between education domain & Data Mining is required. In this interlinking generally Data mining & Knowledge discovery both terms can be used as interchangeably because Data Mining is the key to KDD process. The effective interlinking between DM & higher education is very important to the sustainable development of the education. In this paper one case study is carried out for analyzing performance of first year (Bachelor of Computer Science) student & its dependency on their last year (Higher Secondary Education) performance. This analysis is done by statistical Data mining (DM) techniques. Using Hypothesis testing (DM) technique we will get patterns of students academic performance for predicate the profile of the students. This study is helpful to prediction of students profile for admitting them in the course. It is helpful to Decision Support Systems (DSS) are well suited technologies to provide decision support in the higher education environments.
Low cost, dual linearly polarised microstrip patch array

The design and experiments of a novel dual linearly polarised (LP) microstrip antenna array with a high isolation and low cross-polarisation levels are presented. The theoretical analysis is based on the finite-difference time-domain method and the multiport network model. The multifeed technique and the diagonal feeding are combined to realise the dual-polarised antenna elements. A single antenna element is designed and the experimental results show a good isolation between two polarisation ports. The dual LP elements are sequentially rotated to form the microstrip antenna array. A four-element dual LP array is also designed at 6.6 GHz and measured. Both theoretical and experimental results are presented and compared. The proposed array uses a single-layer structure so it is easy to fabricate and the cost is very low. It is also easy to extend the principle of present array to large-scale dual LP arrays and those of multilayered structures.
An analysis on the connections of factors in a public transport system by AHP-ISM

AbstractIn order to gain an overall view on all relevant connections of the elements in a public transportation system, a systematic approach is advisable to follow, which applies well-proven methodology. In case a structure contains both hierarchical and non-hierarchical connections, the formerly recommended methodologies are: ISM-AHP, ISM-ANP, ANP. This paper however proposes a different approach: AHP-ISM, which aims to keep the AHP hierarchy, but simul- taneously to amend that with the non-hierarchical types of linkages within the structure. By that, those connections that were verified in the AHP procedure can be considered dominant, but also weaker linkages might provide impor- tant additional information about the whole structure. The additional ISM procedure is suitable for two purposes: the most influential elements of the AHP structure can be selected, moreover also direct and indirect impacts of element improvement might be followed in the structure by considering both types of connections withi.
A novel V‐band antenna for nondestructive testing techniques

The original V‐band antenna design meant for precision near‐field measurements is presented. The evident antenna advantages are demonstrated by means of model experiments with the different artificial radio‐transparent dielectrics. It has been shown that the permittivity of local inhomogeneities embedded into the dielectric matrix can be determined with confidence. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 1732–1735, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22504
Mental Stress Classification Based on a Support Vector Machine and Naive Bayes Using Electrocardiogram Signals

Examining mental health is crucial for preventing mental illnesses such as depression. This study presents a method for classifying electrocardiogram (ECG) data into four emotional states according to the stress levels using one-against-all and naive Bayes algorithms of a support vector machine. The stress classification criteria were determined by calculating the average values of the R-S peak, R-R interval, and Q-T interval of the ECG data to improve the stress classification accuracy. For the performance evaluation of the stress classification model, confusion matrix, receiver operating characteristic (ROC) curve, and minimum classification error were used. The average accuracy of the stress classification was 97.6%. The proposed model improved the accuracy by 8.7% compared to the previous stress classification algorithm. Quantifying the stress signals experienced by people can facilitate a more effective management of their mental state.
Making local economic development strategies: a trainer's manual

Making Local Economic Development Strategies: A Trainer's Manual consists of six separate but complimentary sections that together form a comprehensive teaching tool for local economic development (LED) strategic planning. The Trainer's Guide outlines the core trainer competencies, approach and requirements necessary to successfully deliver the training program. The five teaching modules that comprise the training course provide a step-by-step approach reflecting the five stage approach to LED strategic planning. This introduction outlines the structure of the Trainer's Guide and the Trainer's Manual, and provides a brief description of each of the teaching modules that comprise the Manual.
Social Support and Connective Affordances: Examining Responses to Early Covid-19 Patient Support Seeking on Microblogs

ABSTRACT Focusing on the new Super-Topics Platform (STP) of Weibo, this study examined microblog users’ responses to the support seeking of early Covid-19 patients suffering the first outbreak in China. A total of 853 patients’ support-seeking messages, along with 81,000 comments to 270 patients’ help-requests, were crawled and analyzed. Results showed that content characteristics influenced endorsing, sharing, and commenting by users. Furthermore, the study identified three types of social support present in Weibo viewers’ comments: emotional, informational, and diffusional supports. These social support types were inherently linked to the connective affordances, which are more inclusive than paralinguistic digital affordances, of microblogs.
Impact of a Cold Environment on the Performance of Professional Cyclists: A Pilot Study

The practice of physical activity in a variable climate during the same competition is becoming more and more common due to climate change and increasingly frequent climate disturbances. The main aim of this pilot study was to understand the impact of cold ambient temperature on performance factors during a professional cycling race. Six professional athletes (age = 27 ± 2.7 years; height = 180.86 ± 5.81 cm; weight = 74.09 ± 9.11 kg; % fat mass = 8.01 ± 2.47%; maximum aerobic power (MAP) = 473 ± 26.28 W, undertook ~20 h training each week at the time of the study) participated in the Tour de la Provence under cold environmental conditions (the ambient temperature was 15.6 ± 1.4 °C with a relative humidity of 41 ± 8.5% and the normalized ambient temperature (Tawc) was 7.77 ± 2.04 °C). Body core temperature (Tco) was measured with an ingestible capsule. Heart rate (HR), power, speed, cadence and the elevation gradient were read from the cyclists’ onboard performance monitors. The interaction (multivariate analysis of variance) of the Tawc and the elevation gradient has a significant impact (F(1.5) = 32.2; p < 0.001) on the variables (cadence, power, velocity, core temperature, heart rate) and on each individual. Thus, this pilot study shows that in cold environmental conditions, the athlete’s performance was limited by weather parameters (ambient temperature associated with air velocity) and race characteristics. The interaction of Tawc and elevation gradient significantly influences thermal (Tco), physiological (HR) and performance (power, speed and cadence) factors. Therefore, it is advisable to develop warm-up, hydration and clothing strategies for competitive cycling under cold ambient conditions and to acclimatize to the cold by training in the same conditions to those that may be encountered in competition.
Design of Non Linear Controller for a Satellite Attitude Control Simulator

The cost and error of theSatellite Attitude Control System design can be minimize by using ground test simulator. However, it construction difficulties are associated with creating zero gravity and no friction environments. Air bearing simulator provides the environment for investigation of satellite attitude dynamics and control problems. Large angle manoeuvre usually present highly non-linear plant and if the system parameters are not well determined the plant can also present some kind of uncertainty. As a result, controller designed by linear control technique can have its performance and robustness degraded. This paper presents the application of the StateDependent Riccati Equation (SDRE) method to design and test an attitude control algorithm for 3-D satellite simulator. The simulator model is general since it is inertia moment dependent. The matlab/simulink simulator model is similar to 3-D INPE simulator which allows testing satellite hardware and software. The control strategy is based on gas jets and reaction wheel torques to perform three axes large angle manoeuvre. Simulation has investigated that SDRE controller performance and robustness for angular velocity reduction associated with stringent pointing requirement. This work served to validate the numerical simulator model and to verify the functionality of the control algorithm designed.
Linear cyclic correlation approaches for blind identification of FIR channels

Blind fractionally spaced equalizers rely on output only samples taken at a rate higher than the symbol rate in order to estimate the channel taps. Simple methods for mixed phase FIR channel identification are developed by solving a linear system of equations formed by sample cyclic correlations of the received oversampled data sequence. In addition to computational simplicity over existing multivariate alternatives, the resulting linear algorithm is easily modified to yield asymptotically minimum variance weighted least squares channel estimators. A "deterministic" approach is also developed which requires only persistently exciting inputs and leads to closed form data based solutions. Comparisons and tools for performance analysis are also described. <<ETX>>
Finite element analysis of total knee replacement considering gait cycle load and malalignment

This work or any part thereof has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgments, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person.
Pb103 Regulates Zygote/Ookinete Development in Plasmodium berghei via Double Zinc Finger Domains

Sexual reproduction of Plasmodium parasites takes place in anopheline mosquitoes, where male and female gametes fuse to form zygotes and then ookinetes. These processes are orchestrated by stage-specific protein expression, which is mediated in part by translational repression. Accumulating evidence shows that RNA binding proteins (RBPs) play crucial roles in these processes. Here, we report the characterization of P. berghei 103 (Pb103), which encodes a protein possessing double zinc finger domains (ZFs), an RBP. Reporter parasites expressing azami green fluorescent protein (AGFP) under the endogenous Pb103 gene promoter (Pb103-AGFP reporter) showed that the AGFP fluorescent signal was detected from gametes to ookinetes, while AGFP mRNA was translationally repressed in female gametocytes. The Pb103-disrupted parasites (Pb103(−)) grew and produced gametocytes with similar efficiencies to those of wild-type parasites. However, no oocysts were formed in mosquitoes fed Pb103(−). An in vitro fertilization assay showed abortion at the zygote stage in Pb103(−), suggesting that Pb103 plays a critical role in zygote/ookinete development. Cross-fertilization assays with Pb103(−) and male- or female-sterile parasites revealed that Pb103 was essential exclusively for female gametes. To identify the domains critical for zygote/ookinete development, transgenic parasites expressing partially deleted Pb103 were generated and assayed for ookinete maturation. As a result, deleting either of two ZFs but not the C-terminal region abolished zygote/ookinete development, highlighting the indispensable roles of ZFs in parasite sexual development, most likely via translational repression.
Monthly river flow forecasting by an adaptive neuro‐fuzzy inference system

In this study, the applicability of an adaptive neuro‐fuzzy inference system (ANFIS) to forecast for monthly river flows is investigated. For this, the Göksu river in the Seyhan catchment located in southern Turkey was chosen as a case study. The river flow forecasting models having various input structures are trained and tested by the ANFIS method. The results of ANFIS models for both training and testing are evaluated and the best‐fit forecasting model is determined. The best‐fit model is also trained and tested by feed forward neural networks (FFNN) and traditional autoregressive (AR) methods, and the performances of the models are compared. Moreover, ANFIS and FFNN models are verified by a validation data set including river flow data records during the time period 1997–2000. The results demonstrate that ANFIS can be applied successfully and provides high accuracy and reliability for monthly river flow forecasting.
Research On Android Intelligent Phones Controlling the Car to Run

The system finished the android smart mobile phone to control the intelligent car to avoid the obstacles wirelessly based on the bluetooth communication protocol. The android system is popular. But researches on applying it in the wireless sensors are very few. This paper allowed the bluetooth-enabled android phones to communicate with sensors wirelessly through our designed software. The software is installed simplely on the phones.The operator can run the software and touch the screen on the intelligent phones to drive the car. When he/she presses the front / the back/the left/the right on the LCD screen of the phones, the car can move forward / backward / the left or / the right. In addition, the gravity sensing of the smart telephone can also control the motion of the car wirelessly in the same way. The car itself can avoid the obstacle intelligently. The ultrasonic sensor can finish the rotation of the 180 degrees to detect the obstacle with the help of the steering gear. And the system also designed the PCB and made the hardware by ourself. The system has advantages of low-cost, convenience and feasibility. DOI: http://dx.doi. org/10.11591/telkomnika.v11i12. 3743 Full Text: PDF
Manganese-Doped N-Hydroxyphthalimide-Derived Carbon Dots—Theranostics Applications in Experimental Breast Cancer Models

Background: Theranostics, a novel concept in medicine, is based on the use of an agent for simultaneous diagnosis and treatment. Nanomaterials provide promising novel approaches to theranostics. Carbon Dots have been shown to exhibit anti-tumoral properties in various cancer models. The aim of the present study is to develop gadolinium, Fe3+, and Mn2+-doped N-hydroxyphthalimide-derived Carbon Dots. The resulted doped Carbon Dots should preserve the anti-tumoral properties while gaining magnetic resonance imaging properties. Methods: Normal and cancer cell lines have been treated with doped Carbon Dots, and the cell viability has been measured. The doped Carbon Dots that exhibited the most prominent anti-tumoral effect accompanied by the lowest toxicity have been further in vivo tested. Magnetic resonance imaging evaluates both in vitro and in vivo the possibility of using doped Carbon Dots as a contrast agent. Results: According to the results obtained from both the in vitro and in vivo experimental models used in our study, Mn2+-doped Carbon Dots (Mn-CDs-NHF) exhibit anti-tumoral properties, do not significantly impair the cell viability of normal cells, and reduce lung metastasis and the volume of mammary primary tumors while allowing magnetic resonance imaging. Conclusions: Our findings prove that Mn-CDs-NHF can be used as theranostics agents in pre-clinical models.
Silage Fermentation: A Potential Microbial Approach for the Forage Utilization of Cyperus esculentus L. By-Product

Cyperus esculentus L. leaves (CLL) are agricultural by-products produced from Cyperus esculentus L. harvesting, and can be used as livestock feed despite their low economic value for human consumption. This study aims to develop a favorable approach to processing Cyperus esculentus L. by-product as coarse fodder. The chopped CLL was pretreated by (1) mixing with canola straw at a 4:1 ratio, or (2) wilting it for 8 h, then it ensiling with or without compounded lactic acid bacteria (LAB) additives for 60 days. Our results demonstrated that compounded LAB additives: improved CLL silage fermentation quality by increasing acetic acid and lactic acid contents and decreasing ethanol and ammonia-N contents; preserved nutrients by raising the level of crude protein and water soluble carbohydrates; modified the bacterial community by increasing the relative abundance of Lactobacillus while decreasing the relative abundance of undesirable Enterococcus; and also might improve animal health by increasing the relative concentrations of antioxidant substances (such as 7-galloylcatechin) and antibacterial compounds (such as ferulic acid). This study provides strong evidence that Cyperus esculentus L. by-product can be a potential livestock feed after being ensiled with compounded LAB additives.