Miracle-dz/UniFAR-FTUs huggingface dataset:
The ZAX Herbivory Trainer—Free software for training researchers to visually estimate leaf damage

Plants lose a remarkable amount of energy to herbivorous animals, and this damage has substantial impacts on plant fitness and species' distributions. There are many ways ecologists can measure leaf damage, with some methods being more time‐consuming than others. Due to a high variance in herbivory, accurate quantification of damage at the population level requires sampling of many leaves. A simple yet effective solution to this problem is to estimate leaf damage visually. Visually estimating leaf damage may be less accurate than scanning methods, but visual estimates of leaf damage are much faster than digital measurements. Using simulations, we show that gathering larger quantities of data at a slightly higher level of inaccuracy gives a more accurate estimate of a population's overall leaf damage than fewer, exact measurements. We then introduce the ZAX Herbivory Trainer, a free online application that teaches researchers to accurately visually estimate leaf damage. On average, users took ~9 min and 48 images to complete our trainer which significantly decreased their estimate inaccuracy from 13.2% to 6%. This low level of inaccuracy can be retained up to 3 months post‐training so researchers can use the ZAX Herbivory Trainer once prior to short fieldwork or every 3 months for extensive fieldwork. We also recommend a cut‐off point, whereby if a person has not completed the app in 17.5 min or 85 images (90th percentile), they may not be suitable to estimate herbivory for research purposes. The ZAX Herbivory Trainer will allow researchers of any experience level to assess herbivory quickly and accurately in a globally standardised way. International collaborators, students and citizen scientists can all find use in this app, no matter the scale of their projects. From this we can gather better data to address big picture questions in ecology such as patterns in herbivory relating to latitude or climate change.
Minding the Cultural Gaps between Different Countries - A Real Challenge for the International Managers

The managers that intend to develop their businesses at the global scale are frequently confronted with situations which require skills related to effective communication in diverse cross-cultural contexts. The paper’s aim was to answer the following question: “How can a Cultural Intelligence web platform provide the support for international managers in their search of a specific business culture’s peculiarities? ” In this way, we conducted a qualitative research by using the web platform Country Navigator, in order to compare Romania’s cultural profile from business point of view with two representative E.U. countries’ profiles, France, respectively Germany. The main findings of our study outline significant gaps between Romania and Germany and moderate differences between Romania and France. The in-depth analysis of the cultural dimensions also reflects interesting aspects which must be taken into account by the managers. The paper concludes with several recommendations for the managers concerning practical ways to “bridge the gaps” between the cultural profiles of the countries taken into consideration in the study.
QUALITY AND GROWTH DEVELOPMENT OF ROSELLE GROWN ON BRIS SOIL IN RELATION TO REGULATED DEFICIT IRRIGATION

A greenhouse experiment was conducted to evaluate the effects of different irrigation schedules on postharvest quality and growth of roselle and also to determine a significant amount of water to be applied. Thirty-two roselle plants were grown on Beach Ridges Interspersed with Swales (BRIS) soil and treated with four different regimes namely control (100% full irrigation, I), 20% regulated deficit irrigation (RDI) (80% irrigation), 40% RDI (60% irrigation) and 60% RDI (40% irrigation). All the irrigation treatments were replicate quadrice and each replicate comprised two experimental units. RDI imposed for 91 days on roselle plants did not significantly influence plant growth (plant height, stem diameter and number of branches), postharvest quality (titratable acidity, firmness and total anthocyanins concentration) and cumulative number of roselle calyx. However, in general, water deficit treatments applied showed a significant effect only in fresh weight and soluble solid concentration (SSC) of roselle calyx. The treatment of 20% RDI increased yield (calyx fresh weight) compared to the control. In conclusion, 20% RDI (80% irrigation) tends to increase roselle yield and maintain plant growth development without adversely affecting calyx quality. Besides, 20% RDI saved water by 20% and increased irrigation use efficiency of roselle planted on BRIS soil.
CALCULATION OF THE AIRGAP FLUX DENSITY OF PM SYNCHRONOUS MOTORS WITH BURIED MAGNETS INCLUDING AXIAL LEAKAGE AND TEETH SATURATION

It has been shown earlier that the airgap flux density of unsaturated PM motors with buried magnets can be calculated analytically, with a satisfactory result, compared to 2D-FEM calculations. By taking axial leakage flux, and stator and rotor teeth saturation into account an improved expression for the airgap flux density, showing better agreement with experiments, is obtained.
Reliability of microsystems based on a failure mechanism approach

Compactness, complexity of the interconnections and specific packaging, which are characteristics of Microsystems (MEMS), rule out the use of statistical procedure to assess reliability in space applications. Predictable reliability is the method recommended in this paper that uses a similar approach as CALCE already did for hybrid and microelectronic circuits. This method based on a failure mechanism approach is recalled at first and an example to illustrate this procedure based on the evolution of material crystal properties under radiation is presented.
Impact of Intelligent Transportation Systems on Vehicle Fuel Consumption and Emission Modeling: An Overview

Climate change due to greenhouse gas emissions has led to new vehicle emissions standards which in turn have led to a call for vehicle technologies to meet these standards. Modeling of vehicle fuel consumption and emissions emerged as an effective tool to help in developing and assessing such technologies, to help in predicting aggregate vehicle fuel consumption and emissions, and to complement traffic simulation models. The paper identifies the current state of the art on vehicle fuel consumption and emissions modeling and its utilization to test the environmental impact of the Intelligent Transportation Systems (ITS)' measures and to evaluate transportation network improvements. The study presents the relevant models to ITS in the key classifications of models in this research area. It demonstrates that the trends of vehicle fuel consumption and emissions provided by current models generally do satisfactorily replicate field data trends. It shows as well that microscopic modeling is the most accurate type of vehicle fuel consumption and emissions modeling and macroscopic modeling is most helpful in estimating aggregate emissions inventories. In addition, the paper demonstrates that mesoscopic models and empirical models strike a balance between accuracy and simplicity so that they are highly suitable for evaluating the environmental impact of the ITS' measures and transportation network improvements. The study indicates that there is a significant impact of ITS measures on vehicle fuel consumption and emissions rates. It identifies as well the relation among transportation models, cold start excess emission modeling subcategories, and hot-stabilized emission models. The study concludes that no one model as yet fully meets the needs of ITS applications.
Parents’ and teachers’ perceptions of emotional and behavioural problems of school-going adolescents

Self-reported studies alone cannot be used to deduce the significance of adolescent problems. Therefore, the current study focuses on parents’ and class teachers’ perspectives of school-going adolescents’ emotional and behavioural problems. The objectives are to apprehend the prevalence of adolescent problems, comparisons on gender, school-area; and its association with socio-demographic details. A cross-sectional questionnaire-based study was conducted among 19 schools from government-private and rural-urban schools across Kollam District, Kerala. Malayalam/English version of the Strength and Difficulties Questionnaire (SDQ) was administered among a sample of 600 parents and 60 class teachers of school-going adolescents. Gender correlation with parents’ report found emotional problems (P<0.01), conduct problems (P<0.01), hyperactivity (P<0.001), peer problems (P<0.001) whereas in teachers’ report found relationship with emotional problems (P<0.05) and hyperactivity (P<0.001). Multivariate test results reveal that there is a statistically significant difference in emotional and behavioural problems of school-going adolescents based on school area (government-urban, government-rural, private-urban and private-rural). Multiple linear regression analysis on parents reports is significantly predicted with gender (P<0.01), urban-rural settings (P<0.001) and socioeconomic status (P<0.01). Teachers’ report has significantly been predicted with urban-rural settings (P<0.01) and socioeconomic status (P<0.001). Parents’ reports revealed a less overall prevalence of emotional and behavioural problems than teachers’ reports. Female adolescents tend to have more emotional problems and males were found to be more hyperactive. A significant difference was found with the school-area settings and significant association with socio-demographic details of adolescents. More attention is needed for the protection of adolescents’ mental health and fills mental health gaps in services.
Spamalytics: An Empirical Analysis of Spam Marketing

The “conversion rate” of spam—the probability that an unsolicited email will ultimately elicit a “sale”—underlies the entire spam value proposition. However, our understanding of this critical behavior is quite limited, and the literature lacks any quantitative study concerning its true value. In this paper we present a methodology for measuring the conversion rate of spam. Using a parasitic infiltration of an existing botnet’s infrastructure, we analyze two spam campaigns: one designed to propagate a malware Trojan, the other marketing online pharmaceuticals. For nearly a half billion spam emails we identify the number that are successfully delivered, the number that pass through popular antispam filters, the number that elicit user visits to the advertised sites, and the number of “sales” and “infections” produced.
REVITALIZING INDONESIAN ISLAMIC BANKING PERFORMANCE: A STAKEHOLDER ANALYSIS

This paper examines views of Islamic banks’ stakeholders, which can be used as bases for measuring and improving bank performance. Taking Indonesia as a case study, we compile information and data from both internal and external stakeholders through in-depth interview and FGD, code them using N-Vivo, and finally apply the stakeholder management framework for data analysis. The results we obtain suggest that the Internal stakeholder's view on IIB performance is relatively positive. Meanwhile, the external stakeholders tend to have varied views on Islamic banking performance. This research finds that the religious values ​​promoted by Islamic banks can increase the company's value but at the same time it can also reduce the interest in Islamic banking. Based on these findings, it is necessary to investigate further how to strategize the religious values for the promotion of Islamic banking.
TraceRank: Abnormal service localization with dis‐aggregated end‐to‐end tracing data in cloud native systems

Modern cloud native applications are generally built with a microservice architecture. To tackle various performance problems among a large number of services and machines, an end‐to‐end tracing tool is always equipped in these systems to track the execution path of every single request. However, it is nontrivial to conduct root cause analysis of anomalies with such a large volume of tracing data. This paper proposes a novel system named TraceRank to identify and locate abnormal services causing performance problems with dis‐aggregated end‐to‐end traces. TraceRank mainly includes an anomaly detection module and a root cause analysis module. The root cause analysis procedure is triggered when an anomaly is detected. To fully leverage the information provided by the tracing data, both the spectrum analysis and the PageRank‐based random walk methods are introduced to pinpoint abnormal services. The experiments in TrainTicket and Bookinfo microservice benchmarks and a real‐world system show that TraceRank can locate root causes with 90% in Precision and 86% in Recall. TraceRank has up to 10% improvement compared with several state‐of‐the‐art approaches in both Precision and Recall. Finally, TraceRank has good scalability and a low overhead to adapt to large‐scale microservice systems.
Fabrication of dual damascene BEOL structures using a multilevel multiple exposure (MLME) scheme, part 1: lithographic patterning

In this work, the conventional via-first dual damascene (DD) patterning scheme is replaced by a cost-efficient Multi-Level Multiple Exposure (MLME) patterning and etching approach. A two-layer positive-tone photoresist stack is sequentially imaged using 193 nm dry lithography, to produce a DD resist structure that is subsequently transferred into an auxiliary dual organic underlayer stack, and then further into a dielectric layer. This novel integration approach eliminates inter-tool wafer exchange sequences as performed in a conventional litho-etch-litho-etch process flow, while simultaneously being applicable to all back-end-of-the-line (BEOL) levels, ensuring throughput increase. The top and bottom resist layers are chemically designed in such a way that they feature differential solubility in organic solvents making it possible to coat the top photoresist onto the bottom resist layer without intermixing to enable a strict litholitho- etch processing sequence. Independent registration of the via and trench structures in the bottom and top resist layers is achieved by selective photospeed decoupling of the respective layers, so that the bottom resist is largely insensitive at nominal resist exposure dose for the top resist. Imaging performance evaluation of the newly introduced MLME technology includes the resist materials selection process and their required properties (solvent compatibility, adhesion, photospeed, defectivity and correction of via dose bias due to trench exposure) as well as metrology work. Image transfer of the patterned DD resist structure into an underlying transfer layer stack and then further into a dielectric layer using Reactive Ion Etching (RIE) followed by electroplating, polishing and electrical testing was also thoroughly investigated and is described in detail in an accompanying paper.
Cardiac Organoids and Gastruloids to Study Physio-Pathological Heart Development

Ethical issues restrict research on human embryos, therefore calling for in vitro models to study human embryonic development including the formation of the first functional organ, the heart. For the last five years, two major models have been under development, namely the human gastruloids and the cardiac organoids. While the first one mainly recapitulates the gastrulation and is still limited to investigate cardiac development, the second one is becoming more and more helpful to mimic a functional beating heart. The review reports and discusses seminal works in the fields of human gastruloids and cardiac organoids. It further describes technologies which improve the formation of cardiac organoids. Finally, we propose some lines of research towards the building of beating mini-hearts in vitro for more relevant functional studies.
Waveguide E-Plane All-Metal Inserted Diplexer

This paper presents the procedure for designing a waveguide E-plane diplexer for Ku band with inserted metal septa. The diplexer is designed with fil- ters of the fifth order and with T-junction in E-plane for the purpose of easier in- tegration with microwave transceiver. The aim of this work is to master the design of a diplexer that should obtain 60 dB insulation between receiver and transmitter of a radio link and that will not need to be adjusted in serial production.
Bouncing mode electrostatically actuated scanning micromirror for video applications

We present a design and operation concept of a scanning device based on an electrostatic torsional micromirror that is aimed to fulfil the requirements of motion linearity, high operational frequency and low actuation voltages imposed by laser display applications. The operational mode incorporates a contact event between the mirror and an elastic constraint followed by a bouncing and an inversion of motion. A triangular response signal is obtained by the application of an actuation voltage which is piecewise constant in time. The tuning of the resonant frequency through the control of the applied voltage permits the synchronization of the response of the microfabricated device with a video signal.
Ultrasonic Guided Wave Tomography for Damage Detection in Harsh Environment

Guided wave tomography is an attractive tool for the detection and monitoring of the critical area in a structure. Using signal difference coefficient (SDC) as the tomographic feature, RAPID (Reconstruction Algorithm for the Probabilistic Inspection of Damage) is an effective and flexible tomography algorithm. In this algorithm, signal changes are exclusively attributed to the structural variation. However, external environment factors like water loading or oil loading also change signals significantly. The presence of anti-symmetric mode with a predominant out of plane displacement makes it very sensitive to these interferences and leads to false alarms. In this paper, Lamb wave is excited in the low-frequency domain, where only the fundamental modes A0 and S0 exist. The significant difference in group velocity between the two modes makes it possible to separate them in time domain. A new method is proposed to extract pure S0 mode signal as valid measurement data to improve the algorithm in addressing false alarm caused by water loading. The results of the experiment demonstrate that the improved algorithm has the capability of providing accurate identification of damage in the presence of water loading.
On the performances of two algorithms in phaseless antenna measurements

Antenna diagnostics techniques from phaseless measurements of the near field are receiving more and more attention, because they are the only viable methods at millimeter and submillimeter frequencies for the testing of antennas, with a diameter of some thousands of wavelengths and with low sidelobe levels. Two techniques for predicting the radiation pattern of the antenna from intensity measurements of the near field are currently under consideration. The first one is the Gabor holography which employs the interference intensity distribution between the antenna under test and a known reference source. However, such a technique presents some drawbacks concerning the measurement procedure. The second technique is phase retrieval, which requires a knowledge of the amplitude information of the near field over two scanning surfaces. Since the reference wave is not required, such a method is not affected by stability problems and the achievable accuracy is limited only by the low intensity drift. However, the phase retrieval method requires a knowledge of the intensity distributions over two scanning surfaces; this can be overcome when enhanced holographic techniques, which require three measurements of intensity distributions over a single surface, are employed. In any case, for the phase retrieval method the problem of the determination of a complex function, i.e. the near field, from amplitude data arises. The performance of the two approaches are compared with respect to the local minima problem by investigating the different mathematical properties.
Strategic orientations and mass customisation capability: the moderating effect of product life cycle

This study examines the influence of three strategic orientations (customer, competitor and innovation) on mass customisation (MC) capability via the organisational learning process known as customisation knowledge utilisation (CKU). The moderating effect of product life cycle (PLC) is also investigated. Using data collected from 204 manufacturers, we show that all three strategic orientations positively contribute to MC capability, both directly and indirectly through CKU. Further, our empirical findings suggest that the effects of customer, competitor and innovation orientation on MC capability are contingent on PLC. The effects of customer orientation on CKU and the effects of competitor orientation on CKU and MC capability are stronger when a product is in the maturity stage of its life cycle, whereas the effect of innovation orientation on CKU and MC capability are stronger in the growth stage. These findings suggest that to effectively improve MC capability, managers need to leverage external and internal orientations at different stages of the PLC.
Twitter Arabic Sentiment Analysis to Detect Depression Using Machine Learning

: Depression has been a major global concern for a long time, with the disease affecting aspects of many people’s daily lives, such as their moods, eating habits, and social interactions. In Arabic culture, there is a lack of awareness regarding the importance of facing and curing mental health diseases. However, people all over the world, including Arab citizens, tend to express their feelings openly on social media, especially Twitter, as it is a platform designed to enable the expression of emotions through short texts, pictures, or videos. Users are inclined to treat their Twitter accounts as diaries because the platform affords them anonymity. Many published studies have detected the occurrence of depression among Twitter users on the basis of data on tweets posted in English, but research on Arabic tweets is lacking. The aim of the present work was to develop a model for analyzing Arabic users’ tweets and detecting depression among Arabic Twitter users. And expand the diversity of user tweets, by adding a new label (“neutral”) so the dataset include three classes (“depressed”, “non-depressed”, “neutral”). The model was created using machine learning classifiers and natural language processing techniques, such as Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), K-nearest Neighbors (KNN), AdaBoost, and Naïve Bayes (NB). The results showed that the RF classifier outperformed the others, registering an accuracy of 82.39%.