Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing Teacher Evaluation Systems: New Guidance from the Measures of Effective Teaching Project

Designing Teacher Evaluation Systems is a collection of sixteen articles analyzing data produced by the Measures of Effective Teaching project, an initiative of the Bill and Melinda Gates Foundation. The research was conducted with three thousand pre-collegiate teachers working in urban districts. The results and the articles forming the book itself are divided among three themes: using data for feedback and evaluation, connecting evaluation measures with student learning, and the properties of evaluation systems. In short, the book takes on the challenge of what classroom observations and standardized test scores can tell us about good teaching. The core audience for the book seems to be those responsible for educational policy and leadership in primary and secondary schools.
Unraveling Plant Cell Death during Phytophthora Infection

Oomycetes form a distinct phylogenetic lineage of fungus-like eukaryotic microorganisms, of which several hundred organisms are considered among the most devastating plant pathogens—especially members of the genus Phytophthora. Phytophthora spp. have a large repertoire of effectors that aid in eliciting a susceptible response in host plants. What is of increasing interest is the involvement of Phytophthora effectors in regulating programed cell death (PCD)—in particular, the hypersensitive response. There have been numerous functional characterization studies, which demonstrate Phytophthora effectors either inducing or suppressing host cell death, which may play a crucial role in Phytophthora’s ability to regulate their hemi-biotrophic lifestyle. Despite several advances in techniques used to identify and characterize Phytophthora effectors, knowledge is still lacking for some important species, including Phytophthora cinnamomi. This review discusses what the term PCD means and the gap in knowledge between pathogenic and developmental forms of PCD in plants. We also discuss the role cell death plays in the virulence of Phytophthora spp. and the effectors that have so far been identified as playing a role in cell death manipulation. Finally, we touch on the different techniques available to study effector functions, such as cell death induction/suppression.
Be Nice to Thy Neighbors: Spatial Impact of Foreign Direct Investment on Poverty in Africa

This study examines the spatial impact of FDI on the poverty of 44 African countries. In achieving this, the study uses the Driscoll–Kraay fixed effect instrumental variable regression, the instrumental variable generalized method of moments estimator (IV-GMM), and the spatial Durbin model. The empirical investigation of this study yielded four significant findings: (1) neighboring countries’ FDIs have a positive and significant impact on the incidence and intensity of the host country’s poverty, (2) improved institutional quality in neighboring countries has a significant impact on the FDI–poverty reduction nexus of the host country, (3) the empirical results lend support for a significant spatial spillover of poverty in the region, (4) the marginal effect results indicate that countries within the region are no longer in isolation or independent, i.e., the level of poverty in a particular country is influenced by its determinants in the neighboring country. This result is robust to the alternative proximity matrix, which is the inverse distance. Since there is spatial interdependence among African countries, we recommend that African governments, through the African Union (AU), should not only champion the institutional reform in the region, but also establish a binding mechanism to ensure reform implementation.
Automatic Classification for Sagittal Craniofacial Patterns Based on Different Convolutional Neural Networks

(1) Background: The present study aims to evaluate and compare the model performances of different convolutional neural networks (CNNs) used for classifying sagittal skeletal patterns. (2) Methods: A total of 2432 lateral cephalometric radiographs were collected. They were labeled as Class I, Class II, and Class III patterns, according to their ANB angles and Wits values. The radiographs were randomly divided into the training, validation, and test sets in the ratio of 70%:15%:15%. Four different CNNs, namely VGG16, GoogLeNet, ResNet152, and DenseNet161, were trained, and their model performances were compared. (3) Results: The accuracy of the four CNNs was ranked as follows: DenseNet161 > ResNet152 > VGG16 > GoogLeNet. DenseNet161 had the highest accuracy, while GoogLeNet possessed the smallest model size and fastest inference speed. The CNNs showed better capabilities for identifying Class III patterns, followed by Classes II and I. Most of the samples that were misclassified by the CNNs were boundary cases. The activation area confirmed the CNNs without overfitting and indicated that artificial intelligence could recognize the compensatory dental features in the anterior region of the jaws and lips. (4) Conclusions: CNNs can quickly and effectively assist orthodontists in the diagnosis of sagittal skeletal classification patterns.
Evaluation of the Putative Duplicity Effect of Novel Nutraceuticals Using Physico-Chemical and Biological In Vitro Models

Nutraceuticals are experiencing a high-rise use nowadays, which is incomparable to a few years ago, due to a shift in consumers’ peculiarity tendencies regarding the selection of alternatives to Western medicine, potential immunity boosters, or gut-health promoters. Nutraceuticals’ compositions and actual effects should be proportional to their sought-after status, as they are perceived to be the middle ground between pharma rigor and naturally occurring actives. Therefore, the health benefits via nutrition, safe use, and reduction of potential harm should be the main focus for manufacturers. In this light, this study assess the nutritional profile (proteins, fats, fibers, caloric value, minerals) of a novel formulated nutraceutical, its physico-chemical properties, FTIR spectra, antioxidant activity, anthocyanins content, and potential hazards (heavy metals and microbiological contaminants), as well as its cytotoxicity, adherence, and invasion of bacteria on HT-29 cells, as well as its evaluation of beneficial effect, potential prebiotic value, and duplicity effect on gut microbiota in correlation with Regulation (EC) No 1924/2006. The results obtained indicate the growth stimulation of Lb. rhamnosus and the inhibitory effects of E.coli, Ent. Faecalis and Lc. lactis. The interaction between active compounds suggested a modulator effect of the intestinal microbiota by reducing the number of bacteria that adhere to epithelial cells or by inhibiting their growth.
# 1042-1319 A Publication of the Association of Management ROLE OF HUMAN RESOURCE IN INFORMATION TECHNOLOGY ALIGNMENT IN ORGANIZATIONS : A METRIC BASED STRATEGIC ASSESSMENT FRAMEWORK HAREKRISHNA MISRA INSTITUTE OF RURAL MANAGEMENT

Information technology (IT) is increasingly becoming an important factor and fundamental to support business processes in organizations. IT acquisitions are quite productive in supporting transactions and in aiding coordination mechanism provided the organizational resources and business processes are properly aligned with the IT. However, many IT acquisition projects fail due to improper alignment of the business process with IT. Role of human resource (HR) is quite critical to such alignment process. It is important that acquiring organizations display HR capability to support alignment process especially in the pre-acquisition stage to minimize the post acquisition shocks. In this paper role of HR in IT alignment process is discussed through some metrics during pre-acquisition stage. A framework is developed and causal relationships among metrics are discussed. This framework is then tested for its fitness and applied to a case for appreciation.
Research on Marketing Strategy of Railway Passenger Travel Behaviour Analysis in Competitive Section

The deep mining of passengers’ travel data can identify competitive segments and gain insights into passengers’ characteristics and differentiated demands. This can not only effectively support precise marketing strategy adjustment of railway transport but also improve its competitiveness in the passenger transportation market. In this paper, hidden railway travel behaviour is introduced and integrated with railway travel behaviour to create a complete passenger travel chain, based on existing distance-based competitive segment recognition methods. The loyalty index values of passengers are calculated using this travel chain to identify competitive segments. Furthermore, passenger classification and grouping currently ignore social relationships as well as personal travel characteristics. Therefore, a novel passenger grouping method is proposed; it integrates individuals’ travel characteristics and social relations. Individual travel labels are created for travellers based on their travel data. Social relation topologies, such as ticketing relation, the relation of travelling together, and benefit relation via point redemption, can be extracted using these labels. Social relation traits can be retrieved using graph attention networks and multigraph fusion. Finally, travellers are categorised based on their individual travel characteristics. As an example, and a case study, the grouping of Guangzhou–Shanghai passengers in 2020 is taken which shows that the suggested method has the potential to improve both the precision and the feasibility of grouping railway passengers. As a result, new ideas for passenger grouping in railway marketing might be offered.
Determinants of financial inclusion in Latin America and the Caribbean

ABSTRACT Financial inclusion is an important determinant of local economic development. Lack of adequate access to formal financial services can have detrimental effects on households, such as hampering liquidity levels. The benefits of financial inclusion could be especially important in Latin America and Caribbean, a region with modest and volatile economic growth, savings, and investment levels. The objective of this paper was to examine the determinants of financial inclusion in Latin America and the Caribbean region. Overall, our results indicate that greater income and education levels are associated with higher probability of financial inclusion.
An image watermark removal method for secure internet of things applications based on federated learning

Watermark adding is one of the important means for image security and privacy protection in Internet of things (IOT) applications based on federated learning. It is often inseparable from adversarial training with watermark removal algorithms. The effect of watermark removal algorithms will directly affect the final result of watermark addition. However, the existing watermark removal algorithms have drawbacks such as incomplete image watermark removal, poor image quality after watermark removal, large demand for training data, and incorrect filling, which seriously affects the development of image information security and privacy protection in IOT applications based on federated learning. To solve the above problems, this paper proposes an improved image watermark removal convolutional network model based on deep image prior. First, we improve the U‐Net network model, using six downsamping layers and six deconvolution layers combined with deep image prior method to reduce the loss of details and perceive high‐level features, thereby improving the ability of the network to extract high‐level features of the image. In addition, we design a new type of loss function which is called stair loss, and add L1 loss and perception loss to establish new constraints. In order to verify the effectiveness of our method, a comprehensive experimental comparison was conducted on the public dataset PASCAL VOC 2012 in the same experimental environment with CGAN and the deep prior method. The experimental results show that the improved model combined with the deep image prior method can extract the high‐level feature information and can directly remove the watermark from the picture without pretraining the network, the L1 loss and perceptual loss can better retain the image structure information and speed up the watermark removal of the model, the stair loss corrects the final output more accurately by correcting the output of each layer; our method improves the learning ability of the model, and under the condition of the same training time, the image quality after watermark removal is higher, and the final watermark removal result is better, which is more suitable for distributed structure of IoT application based on federated learning.
Apology Cost Is More Strongly Associated With Perceived Sincerity Than Forgiveness

This study aimed at replicating a previously reported pattern: costly apologies are perceived as more sincere than non-costly apologies even when the transgression was unintentional, while costly apologies do not foster forgiveness more than non-costly apologies when the transgression was unintentional. We conducted a vignette study with a 2 (apology cost: costly vs. non-costly) × 3 (intention: no vs. ambiguous vs. malicious intention) between-participants factorial design. We failed to replicate the aforementioned pattern. Instead, we found that costly apologies promote not only perceived sincerity but also forgiveness in all three intention conditions. In addition, there were two notable patterns. First, the effect of apology cost was stronger for perceived sincerity than for forgiveness in all three intention conditions. Second, both perceived sincerity and forgiveness decreased as the intentional nature of the transgression was described more clearly.
The power of knowledge management: how top management team bricolage boosts ambidexterity and performance

Purpose This paper aims to explore the relationship between top management team bricolage and performance and also examines unit ambidexterity's mediating role. More essentially, to understand the black box of organizational knowledge dynamism, a multilevel moderated mediating model is established by exploring the effects of two firm-level moderators, namely, potential absorptive capacity and realized absorptive capacity. Design/methodology/approach To test the cross-level moderated mediation model, this study used multisource data from 90 R&D units in 45 Taiwanese manufacturing firms through two-wave surveys and retrieving the archival data for assessing unit performance. Findings This study’s evidence revealed that unit-level ambidexterity mediates the effect between firm-level top management teams’ (TMT) bricolage and unit-level performance. This study also found that firm-level potential absorptive capacity positively moderates the effect between firm-level TMT bricolage and unit-level ambidexterity. Moreover, firm-level realized absorptive capacity strengthens the indirect relationships between firm-level TMT bricolage and unit-level performance via unit-level ambidexterity. The findings shed light on how and why TMT bricolage influences unit ambidexterity and performance in knowledge-intensive sectors. Originality/value This paper adds to the existing knowledge-based theory literature by disentangling the association between top management team bricolage and unit performance and identifying the pivotal role of absorptive capacity at both the firm and unit levels.
Resting-State Neuronal Activity and Functional Connectivity Changes in the Visual Cortex after High Altitude Exposure: A Longitudinal Study

Damage to the visual cortex structures after high altitude exposure has been well clarified. However, changes in the neuronal activity and functional connectivity (FC) of the visual cortex after hypoxia/reoxygenation remain unclear. Twenty-three sea-level college students, who took part in 30 days of teaching at high altitude (4300 m), underwent routine blood tests, visual behavior tests, and magnetic resonance imaging scans before they went to high altitude (Test 1), 7 days after they returned to sea level (Test 2), as well as 3 months (Test 3) after they returned to sea level. In this study, we investigated the hematological parameters, behavioral data, and spontaneous brain activity. There were significant differences among the tests in hematological parameters and spontaneous brain activity. The hematocrit, hemoglobin concentration, and red blood cell count were significantly increased in Test 2 as compared with Tests 1 and 3. As compared with Test 1, Test 3 increased amplitudes of low-frequency fluctuations (ALFF) in the right calcarine gyrus; Tests 2 and 3 increased ALFF in the right supplementary motor cortex, increased regional homogeneity (ReHo) in the left lingual gyrus, increased the voxel-mirrored homotopic connectivity (VMHC) value in the motor cortex, and decreased FC between the left lingual gyrus and left postcentral gyrus. The color accuracy in the visual task was positively correlated with ALFF and ReHo in Test 2. Hypoxia/reoxygenation increased functional connection between the neurons within the visual cortex and the motor cortex but decreased connection between the visual cortex and motor cortex.
A Reactive Power Compensated Control Scheme for Solar-Assisted EV Fast-Charging Applications

The main objective of this work is to develop an efficient reactive power compensated control technique for a fast-charging scheme for electric vehicle(s) (i.e., level-3 charging). The developed charging technique has the four-quadrant power flow operation with the simultaneous assurance of the compensated reactive power control. The developed charging infrastructure scheme involves a solar panel and 3-phase grid to charge the E-mobility. A DC-DC boost converter is used to achieve maximum power tracking (MPPT) of a solar PV array, and a 3-phase grid-tied bidirectional voltage source converter (VSC) is utilized to provide the bulk of power to charge the EV. The 3-phase VSC has multiple functionalities including grid side power quality (PQ) improvement with reactive power compensation, seamless flow of power from the grid to EV, and solar to grid or battery to grid (V2G) operation. This scheme also facilitates tariffs earned by discharging solar energy to the grid with additional benefits of reactive power compensation. An arrangement is also made to tackle grid failure conditions during battery discharging mode by connecting a load for ancillary purposes. The effectiveness of this charging scheme is first examined in MATLAB/Simulink environment and then validated on developed hardware.
A TPACK Course for Developing Pre-Service Teachers’ Technology Integration Competencies: From Design and Application to Evaluation

Technological Pedagogical Content Knowledge (TPACK) is one of the technology integration models that focuses on effective technology integration related to teacher competencies. This model is based on the interaction and combination of teachers’ technology, pedagogy, and content knowledge. A new course was created using a TPACK model of education. In this context, the trainer takes responsibility of being a role model and the use of new technology-based applications for educational purposes appropriately updated. Additionally, integrating the TPACK model of education could make important contributions to technology integration in teacher training if the information is concretized with concept maps, if students are made creative in their own fields with digital storytelling
Integrated microRNA–mRNA Expression Profiling Identifies Novel Targets and Networks Associated with Autism

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, with mutations in hundreds of genes contributing to its risk. Herein, we studied lymphoblastoid cell lines (LCLs) from children diagnosed with autistic disorder (n = 10) and controls (n = 7) using RNA and miRNA sequencing profiles. The sequencing analysis identified 1700 genes and 102 miRNAs differentially expressed between the ASD and control LCLs (p ≤ 0.05). The top upregulated genes were GABRA4, AUTS2, and IL27, and the top upregulated miRNAs were hsa-miR-6813-3p, hsa-miR-221-5p, and hsa-miR-21-5p. The RT-qPCR analysis confirmed the sequencing results for randomly selected candidates: AUTS2, FMR1, PTEN, hsa-miR-15a-5p, hsa-miR-92a-3p, and hsa-miR-125b-5p. The functional enrichment analysis showed pathways involved in ASD control proliferation of neuronal cells, cell death of immune cells, epilepsy or neurodevelopmental disorders, WNT and PTEN signaling, apoptosis, and cancer. The integration of mRNA and miRNA sequencing profiles by miRWalk2.0 identified correlated changes in miRNAs and their targets’ expression. The integration analysis found significantly dysregulated miRNA–gene pairs in ASD. Overall, these findings suggest that mRNA and miRNA expression profiles in ASD are greatly altered in LCLs and reveal numerous miRNA–gene interactions that regulate critical pathways involved in the proliferation of neuronal cells, cell death of immune cells, and neuronal development.
Cooperative localization and control of multiple heterogeneous robots using a string formation

This paper is on cooperative localization and control of multiple heterogeneous robots utilizing a string formation. This formation is preferred, since robots can move along a narrow passage utilizing this formation. Dead reckoning localization based on inertial measurement units leads to accumulated localization error. To avoid the error accumulation in dead reckoning localization, this paper introduces the last‐move strategy for multiple heterogeneous robots. In the last‐move strategy, a single robot is selected for maneuvering, and it turns on its bearing‐range sensors for a short amount of time, in order to locate itself. While the selected robot moves, all other robots stop moving and perform as static landmarks for the moving robot. A robot may not maintain its desired course, in the case where environmental disturbance is severe. We thus develop a control strategy for avoiding obstacles while estimating the disturbance direction at a robot's location. To the best of our knowledge, this paper is novel in localization and control of a team of heterogeneous robots, considering the case where environmental disturbance is severe. The proposed localization process is energy‐efficient, thus is suitable for practical applications. The performance of the proposed schemes is demonstrated utilizing MATLAB simulations.
Promoting evidence-based nursing through journal clubs: an integrative review

Background The journal club has been proposed as a tool to fill the gap between theory and practice. Aim The present research is an integrative review of studies focussing on journal clubs. Methods An integrative review. We searched the databases during 2010–2019 to find papers using the keywords journal club, nursing, evidence-based practice. The modified version of Cooper’s five-stage integrative review was applied. Results The results are presented in two sections – the benefits and challenges of nursing journal clubs and an outline of presentation guidelines. We also discuss the effectiveness of journal clubs in the promotion of evidence-based nursing. Conclusions The purpose of the nursing journal club is to review existing literature, discuss the latest information and evidence and identify practical changes required to ultimately improve patient outcomes. Further studies are needed to evaluate the effectiveness of journal clubs in patient care.