Miracle-dz/UniFAR-FTUs huggingface dataset:
Tree species mixing reduces biomass but increases length of absorptive fine roots in European forests

Mixed‐species forests often enhance the provision of ecosystem functions, both above‐ and below‐ground. Several of these effects are mediated by the amount and spatial distribution of tree tissues. However, previous studies on tree diversity effects on fine‐root biomass (FRB) have returned inconsistent results and did not distinguish between absorptive and transport fine roots. Furthermore, owing to the lack of species‐specific data, it is not well understood whether complementarity or selection effects contribute more to these mixing effects. Here, we analysed tree species mixing effects on fine‐root traits while considering the respective tree species contributions and root functional types. Specifically, we tested whether tree species mixing increases FRB and root length density (RLD) and results in vertical root stratification. We quantified FRB and RLD in 30‐cm deep soil profiles for 13 tree species in mixed and pure stands across four widespread European forest types. The differentiation of different fine‐root species in mixtures allowed us to disentangle complementarity and selection effects. Across all sites, mixtures supported on average less FRB than pure stands, which was reflected in negative complementarity and selection effects. RLD of absorptive fine roots did not change across the soil profile and even increased in the topsoil, which was associated with positive complementarity effects. There was no evidence for vertical root stratification. Conifer proportion, which was mainly associated with selection effects, dampened net diversity effects. Root functional type further influenced tree species mixing effects. Synthesis. Despite the underyielding of FRB in mixtures, overall soil occupation by absorptive fine roots (RLD) did not decrease in mixtures, pointing to morphological root trait adaptations associated with higher resource‐use efficiency. Increased RLD in the most nutrient‐rich layer in mixtures further indicates complementary interactions among species and a greater resource uptake capacity. This work illustrates that considering only one aspect of trait‐functioning relationships, for example, root biomass, may not capture the full effect of plant diversity on ecosystem functioning. The integration of a larger range of relevant traits is required. Moreover, traditional classification of fine roots based on the 2‐mm diameter cut‐off may obscure responses of roots to environmental changes.
THE EFFECT OF FINANCIAL PERFORMANCE AND DIVIDEND POLICY ON CUMULATIVE ABNORMAL RETURN

The purpose of this study was to determine the effect of financial performance and dividend policy on Cumulative Abnormal Return for company shares in Jakarta Islamic Index. The population was all company stocks listed on The Jakarta Islamic Index from 2009 to 2018. The samples were selected by purposive sampling with the criteria the companies were consistently included in JII (not delisted and relisted) during the 2009-2018 period and those that met the criteria were five companies. Financial performance was proxies by Earning per Share, Price Earnings Ratio, Current Ratio, and Return on Equity. Meanwhile, dividend policy was proxies by the Dividend Payout Ratio. This research type was quantitative by using the panel data regression method. The results showed that Earning per Share effect on Cumulative Abnormal Return, while the Price Earnings Ratio, Current Ratio, Return On Equity and Dividend Payout Ratio variables had no effect on Cumulative Abnormal Return. The implications of this research for other parties consists of scientific development, especially in the field of financial management, and can be an input for investors in investing in shares on the Indonesia Stock Exchange (IDX) so that it can have a positive impact in the form of dividends or capital gains to investors. And can be used as a reference for further researchers by adding other variables that are not included in this study.
Strategies employed by EFL doctoral candidates in dissertation writing completion

This research study aimed at revealing the strategies employed by successful English as a Foreign Language (EFL) doctoral candidates in accomplishing their dissertation writing and their perspectives in association with the stages of research report writing. This is a narrative qualitative inquiry, and the data were collected through an in-depth interview with ten successful EFL fresh graduates who had completed their dissertation writing within six and seven semesters. Using a retrospective technique, the respondents were asked to recall their experiences and activities during the process of writing their dissertation. The results reveal that the successful doctoral candidates used four main strategies of dissertation writing: cognitive, metacognitive, affective, and social strategies. In completing each of the dissertation stages, the doctoral candidates spent much time reading a huge collection of research articles, writing their dissertation on a daily basis, and having intensive consultation with their advisors. This study would be useful for EFL doctoral students to avoid delay in completing their studies and to meet their academic timeline so that they can face their challenging dissertation writing to complete their study on time.
Role of sonomammography and its diagnostic accuracy for evaluating benign and malignant breast lesions

Background: Mammography and ultrasound are the best-known techniques used for screening and diagnosis of breast cancer. This study evaluated the accuracy of sonomammography in diagnosing breast lesions, both benign and malignant separately and confirmation of the findings by histopathology. Methods: A prospective study was conducted for 18 months in women aged above 15 years with breast lesions or symptoms of breast diseases. The diagnosis protocol consisted of clinical breast examination, mammography, ultrasound and histopathological examination. Mammograms were interpreted according to the breast imaging reporting and data system (BI-RADS) diagnostic categories on a five-point scale. This was followed by ultrasound imaging of the breast and axilla with ultrasound-guided fine needle aspiration cytology (sonomammography-FNAC) from the breast lump. Results: Among the 52 patients, three patients were divorced, 40 were married and nine were unmarried. Eight had a history of oral contraceptive pills (OCP) use and one patient had a family history of breast lesions. The mammography report revealed 31 patients suspected to be malignant and 21 patients to be benign. According to the sonomammography report, 32 patients were suspected to be malignant while 20 patients were suspected to be benign. Correlation between mammography report, sonomammography report and grade versus histopathological finding also showed significance with p<0.0001. Conclusions: Sonomammography reveals good sensitivity and specificity for detecting all breast lesions. Hence it can be considered as a suitable means of investigation than mammography especially in patients less than 40 years of age.
Red pasta: What is the technological impact of the enrichment of beet ingredient in fresh pasta?

The objective of this study was to evaluate the partial replacement of wheat flour by beet flour (BF) in fresh pasta production, analyzing its chemical, technological, and sensorial characteristics. BF showed good water (4.2 g water/g flour) and oil absorption (2.2 g oil/g flour), water solubility (67.3%), and emulsifying properties (30.0%). The incorporation of BF in fresh pasta formulations improved the nutritional value of the pasta, increased the ash (1.65 to 2.16 g/100 g) and fiber contents (1.31 to 12.29 g/100 g) of the fresh pasta, and decreased the lipid contents (50.0% reduction), thereby causing changes in its cooking properties. The antioxidant capacity (0.5 to 4.76%) and the content of total phenolics (69.1 to 70.5 mg/100 g) and betalains (0.04 to 0.16 mg/100g) also increased with the addition of BF, improving the functional profile of the pasta. In the sensory profile, the pasta formulated with the highest concentrations of BF demonstrated the highest intensities for the sensory attributes among fresh pasta evaluated. In general, it was shown that BF represents a promising ingredient to produce new fresh pasta with functional characteristics.
An evaluation of public policy student placements: outcomes of a Malta-based study

PurposeThe purpose of this paper is to evaluate short-term, unpaid placements offered to students reading for a degree in public policy. They provide added value to their tertiary education experience. Elective placements were offered in 2012 and became a mandatory requirement for students reading for a three-year bachelor of commerce degree in public policy in 2018. To date, no research has been carried out on these placements and this may serve as a model for a post-evaluation assessment.Design/methodology/approachData were collected from students who undertook placements, embedded in the public policy undergraduate programme. A document analysis of selected student and placement provider's reports was carried out to complement the students' responses to an online questionnaire.FindingsPlacements are of value to students as they served as an introduction to the working world. They enable students to establish connections with the course content and carry out research. They were exposed to real-life situations, developing their knowledge, acquiring soft skills and learning new tools, sought after by employers. These placements were valued as a route to graduate employment tailor-made to the degree's requirements. Students were able to embark on a soul-searching, introspective discovery and journey which made them mature and shed light in the direction of future work prospects.Research limitations/implicationsPlacements give students the opportunity to gain insights into real-work environments and are able to link theories learnt in the class-room with real-life situations. Placements have positive implications on students adjusting to their work life easily after graduation. The limitations are that the sample size was small and that the reflective reports which were randomly selected may not have necessarily been representative of the full complement.Practical implicationsThe practical implications are that the placements system and process can easily be implemented and replicated in other academic disciplines and universities as a compulsory component of their studies.Social implicationsPlacements gave students the opportunity to reflect on their learning, develop non-technical skills and enhance their confidence levels. They were also able to network and communicate with different employees.Originality/valuePlacements provided exposure to relevant organisations and personal enrichment in terms of acquiring skills, autonomy and independence. Students with placement experience are also more likely to secure future employment, relevant to their undergraduate degree.
Railway Vehicle Wheel Flat Detection with Multiple Records Using Spectral Kurtosis Analysis

The gradual deterioration of train wheels can increase the risk of failure and lead to a higher rate of track deterioration, resulting in less reliable railway systems with higher maintenance costs. Early detection of potential wheel damages allows railway infrastructure managers to control railway operators, leading to lower infrastructure maintenance costs. This study focuses on identifying the type of sensors that can be adopted in a wayside monitoring system for wheel flat detection, as well as their optimal position. The study relies on a 3D numerical simulation of the train-track dynamic response to the presence of wheel flats. The shear and acceleration measurement points were defined in order to examine the sensitivity of the layout schemes not only to the type of sensors (strain gauge and accelerometer) but also to the position where they are installed. By considering the shear and accelerations evaluated in 19 positions of the track as inputs, the wheel flat was identified by the envelope spectrum approach using spectral kurtosis analysis. The influence of the type of sensors and their location on the accuracy of the wheel flat detection system is analyzed. Two types of trains were considered, namely the Alfa Pendular passenger vehicle and a freight wagon.
Real‐time model‐free resilient control for discrete nonlinear systems

Motivated by the increasing complexity of systems to be controlled and different system components that cause uncertainties, threats, and disturbances, among other system stressing phenomena. Resilient control is an important design paradigm that has attracted attention from academics, practitioners, and the industrial sector. Therefore, this paper proposes the design of a model‐free resilient control for unknown discrete‐time nonlinear systems based on a recurrent high order neural network trained with an on‐line extended Kalman filter‐based algorithm for output trajectory tracking in the presence of uncertainties, disturbances, and unmodeled dynamics. This paper also includes the stability proof of the entire proposed scheme; its applicability is shown via simulation and experimental results including a comparative analysis of the proposed controller against well‐known controllers for a three‐phase induction motor.
Financial incentive strategy for weight loss and maintenance of weight loss

Summary Introduction The aim of this study was to investigate the effect of financial incentives on weight loss, maintain in obese women and biochemical factors. Methods This quasi-experimental study was conducted on 103 women with body mass index (BMI) ≥ 30 kg/m2. The participants were assessed over a 12-month follow-up in eight phases. Money payment for losing weight was incentive intervention in this study. The participants were given diet and physical activity. Results Mean of BMI was 34.78 ± 4.29 kg/m2 in baseline, that reduced to 32.41 ± 3.51 kg/m2 in the sixth phase, and 31.64 ± 3.71 kg/m2 in the final phase (P < 0.001). At baseline, mean of percentage of body fat (PBF) was 40.77 ± 2.81 that reduced to 37.34±4.02 at the end of the study (P < 0.001). Waist to hip ratio (WHR) and lean body mass (LBM) decreased significantly over the 12-month (P < 0.001). At the end of each phase, the mean of BMI reduction of 0.39 units was observed in the subjects, and 9 units of change were achieved by the end of the study compared to the baseline. The mean of triglyceride in the first, fourth and seventh phases were 128.57 ± 13.33, 101.43 ± 57.99 and 87.40 ± 57.59 mg/dl, respectively (P = 0.003). The mean of serum glutamic oxaloacetic transaminase (SGOT) and serum glutamate-pyruvate transaminase (SGPT) decreased significantly over the 12-month, P = 0.052 and P = 0.005, respectively. Conclusions Financial incentives can effectively help to weight loss and maintenance of weight, and improve lipid profiles; blood sugar and liver enzymes. The use of motivational factors with proper training (diet and physical activity) will have a better result.
A proposal to minimize the cost of processing big geospatial data in public cloud providers

Spatial data represent abstractions of real‐world entities and can be obtained in various ways. They have properties that differentiate them from other types of data, such as a complex structure and dynamism. In recent years with the increasing volume of spatial data, referred to as “big geospatial data,” some tools have been developed to process such data efficiently, such as SpatialHadoop. The use of appropriate data indices based on the data set to be processed, as well as queries and operations to be performed, is essential for the optimal performance of these applications. In particular, since public cloud providers’ charges are based on the resources used, it is imperative to optimize application execution in order to avoid unnecessary expense. This article proposes the use of six conditions that seek to minimize the cost of processing big geospatial data in public cloud providers. The tests performed demonstrate that the use of these conditions and the choice of the lowest‐cost provider can reduce the total processing cost by up to 41%.
Humanoid robot adoption and labour productivity: a perspective on ambidextrous product innovation routines

Abstract The increasing presence of humanoid robot adoption has generated a change in explorative and exploitative routines. If the explorative routines provoke creativity and critical thinking which are delivered by humans, exploitative routines induce repetitive actions and mimic activities which are executed by humanoids. This has raised the need for a better balance between both routines involving an ambidextrous dynamic process. Here, product innovations play a relevant role in enhancing such balance and labour productivity. If, from the conceptual standpoint, this phenomenon has already been explored, there is still the need to empirically analyse it. We thus offer a meso-analysis of twenty-four countries located in Europe through the lens of the Service Robot Deployment (SRD) Model and the conceptual lens of organizational ambidexterity. By a regression methodology, the results show that humanoid robot adoption is still not affecting labour productivity which, by contrast, is positively and significantly connected with both radically new and marginally modified/unchanged production of innovative routines. Our original contribution, which falls in the field of Human Resources Management and Artificial Intelligence, is that humanoids are not directly impacting labour productivity but indirectly through the generation of both new and marginally modified (or unchanged) routines. This situation persuades senior leaders to achieve a balance between exploitative and explorative product innovation routines. Supplemental data for this article is available online at https://doi.org/10.1080/09585192.2021. 1897643 .
Impact of Community Service Arrangements on Volunteer Intention, Responsibility, and Satisfaction among Hong Kong Adolescents

Abstract This study examines the effect of community service arrangements on secondary school students in Hong Kong under the Other Learning Experiences (OLE) component of the New Senior Secondary (NSS) Curriculum. Previous literature has indicated the importance of arrangements and modes of volunteer services on the positive experiences of individual volunteers. A total of 1,046 secondary school students from seven schools in Hong Kong were recruited to participate in a self-administered survey; they were split into two groups – students from schools providing relatively structured service programs, and students from schools providing relatively unstructured service programs. The results of bivariate analyses showed that students from the schools that provided structured service programs tended to score higher in their future volunteering intention, sense of responsibility, and satisfaction with volunteering. The multivariate analyses showed that after controlling for age, gender, and class of the students, previous volunteer experience was positively correlated to volunteer satisfaction, level of responsibility, and intention to volunteer in future. On the other hand, friends’ modeling was positively correlated to both volunteer satisfaction and level of responsibility. The type of volunteer service was not correlated to either of the dependent variables. Those making service arrangements for school personnel, volunteer managers, and social workers are thus advised to take note of the advantage of ensuring the retention of volunteers and their service sustainability for the enhancement of their satisfaction, sense of responsibility, and volunteering intention, as well as the role of peers in facilitating volunteers in becoming more productive from volunteering.
Imputations for High Missing Rate Data in Covariates Via Semi-supervised Learning Approach

Abstract Advancements in data collection techniques and the heterogeneity of data resources can yield high percentages of missing observations on variables, such as block-wise missing data. Under missing-data scenarios, traditional methods such as the simple average, k-nearest neighbor, multiple, and regression imputations may lead to results that are unstable or unable be computed. Motivated by the concept of semi-supervised learning, we propose a novel approach with which to fill in missing values in covariates that have high missing rates. Specifically, we consider the missing and nonmissing subjects in any covariate as the unlabeled and labeled target outputs, respectively, and treat their corresponding responses as the unlabeled and labeled inputs. This innovative setting allows us to impute a large number of missing data without imposing any model assumptions. In addition, the resulting imputation has a closed form for continuous covariates, and it can be calculated efficiently. An analogous procedure is applicable for discrete covariates. We further employ the nonparametric techniques to show the theoretical properties of imputed covariates. Simulation studies and an online consumer finance example are presented to illustrate the usefulness of the proposed method.
Primitive Chain Network Simulation of Elongational Flows of Entangled Linear Chains: Role of Finite Chain Extensibility

For entangled linear monodisperse polymers, uniaxial elongational flow behavior was examined with the primitive chain network (PCN) simulation, which was originally formulated for a network of Gaussian chains bound by sliplinks but was modified in this study to properly take into account the finite extensibility of actual chains. On an increase of the elongational rate e from the terminal relaxation frequency 1/τd (at equilibrium) to the Rouse relaxation frequency 1/τR, the original and modified simulations gave an indistinguishable steady state elongational viscosity ηE that almost scaled as e–1/2. On a further increase of e > 1/τR, ηE obtained from the original PCN simulation diverged to infinity (as noted also for the unentangled Rouse chains). In contrast, ηE deduced from the modified simulation increased but did not diverge with increasing e > 1/τR (similarly to the behavior of FENE dumbbells). This feature of the modified PCN simulation, i.e., hardening to a finite (nondiverging) level, mimicked.
The Heterogeneous Impact of Financialisation on Economic Growth in the Long Run

Financialisation, i.e., the process by which financial markets and their participants gain more influence over the functioning of enterprises/companies and the framework of the financial system, changes the functioning of the economic system, both at the macro- and microeconomic level. There is no doubt that financialisation impacts economic growth. Still, research does not substantiate the heterogeneity of financialisation effects and does not provide a comprehensive analysis of the sources of heterogeneity. In most cases, researchers provide only theoretical insights into what may lead to different effects of financialisation on economic growth. This study empirically examines whether institutional quality and economic development intermediate the relationship between financialisation and economic growth using a panel of 96 countries over the period of 1996–2017 and least squares dummy variables (LSDV) estimator. We found that the impact of financialisation on economic growth differs across countries and that institutional quality and economic development are the sources of the heterogeneous impact of financialisation on economic growth.