Miracle-dz/UniFAR-FTUs huggingface dataset:
Somatic Embryo (SE) Formation from Culturing Floral Explants of Rubber Tree (Hevea brasiliensis Muell. Arg.) and Assessment of Genetic Stability by RAPD and SSR Markers

Rubber tree is economically important rubber producing plant of Thailand. At present, a rubber tree plantation is susceptible to white root disease. Therefore, the use of rootstock from early introduce clone that proved to be resistant to white root disease could help sustain growing of rubber tree. Thus, the objectives of this research were to study the effects of plant growth regulators and different explants on somatic embryo (SE) induction of this rubber clone and assessment genetic stability. The results revealed that mix flower explant cultured on MS medium supplemented with 2.0 mg/L 6-benzyladenine (BA) and 1.5 mg/L 2,4-Dichlorophenoxyacetic acid (2,4-D) provided callus subsequent somatic embryo (SE) formation at the highest frequency of 39.84 % and number of cotyledonary embryos (CEs) at 3.25 embryos /callus after 3 passages of subculture in the same culture medium (4 weeks/passage). SEs germinated into embryonic axis at 50 % and further development into shoot at 25 % after transfer to 0.25 mg/L GA3 containing MS medium with the best concentrations of BA and 2,4-D for 4 weeks. The assessment gene stability by RAPD and SSR markers showed no variation between mother plant and in vitro plantlets. In this work, a novel explant source - the floral section of the rubber tree - was used for the first time in order to design an effective technique for in vitro somatic embryogenesis. HIGHLIGHTS The first report on plantlets regeneration using floral explant of rubber tree This mother plant is proved to be resistance to Phytopthora leaf fall and white root diseases Assessment genetic stability of regenerated plantlets by SSR and RAPD markers GRAPHICAL ABSTRACT
Application of Zebrafish as a Model for Anti-Cancer Activity Evaluation and Toxicity Testing of Natural Products

Developing natural product-based anti-cancer drugs/agents is a promising way to overcome the serious side effects and toxicity of traditional chemotherapeutics for cancer treatment. However, rapid assessment of the in vivo anti-cancer activities of natural products is a challenge. Alternatively, zebrafish are useful model organisms and perform well in addressing this challenging issue. Nowadays, a growing number of studies have utilized zebrafish models to evaluate the in vivo activities of natural compounds. Herein, we reviewed the application of zebrafish models for evaluating the anti-cancer activity and toxicity of natural products over the past years, summarized its process and benefits, and provided future outlooks for the development of natural product-based anti-cancer drugs.
“Komai Nisan Dare, Akwai Wani Online”: Social Media and the Emergence of Hausa Neoproverbs

This paper interrogates the changing paradigm in the evolution of traditional African proverbs in the postcolonial setting in which Hausa youth create proverbs centered around the power of both social media and their technologies. In this context, the notion of colonized subjects, cowering under the glare of English linguistic imperialism, is challenged by the Hausa youth through newly fabricated social media proverbs that acknowledge English terms, but use social media platforms to convey what I call ‘Hausa technofolk’ philosophy. This provides insight into how contemporary African youth force a new narrative in the notion of coloniality.
Hierarchical Control for Microgrids: A Survey on Classical and Machine Learning-Based Methods

Microgrids create conditions for efficient use of integrated energy systems containing renewable energy sources. One of the major challenges in the control and operation of microgrids is managing the fluctuating renewable energy generation, as well as sudden load changes that can affect system frequency and voltage stability. To solve the above problems, hierarchical control techniques have received wide attention. At present, although some progress has been made in hierarchical control systems using classical control, machine learning-based approaches have shown promising features and performance in the control and operation management of microgrids. This paper reviews not only the application of classical control in hierarchical control systems in the last five years of references, but also the application of machine learning techniques. The survey also provides a comprehensive description of the use of different machine learning algorithms at different control levels, with a comparative analysis for their control methods, advantages and disadvantages, and implementation methods from multiple perspectives. The paper also presents the structure of primary and secondary control applications utilizing machine learning technology. In conclusion, it is highlighted that machine learning in microgrid hierarchical control can enhance control accuracy and address system optimization concerns. However, challenges, such as computational intensity, the need for stability analysis, and experimental validation, remain to be addressed.
Row spacing and phosphorus use efficiency in no-tillage maize

Abstract Reduced row spacing has shown to increase maize (Zea mays L.) nitrogen (N) use efficiency, but little is known about it effects on phosphorous (P) use efficiency (PUE). The objective of this study was to evaluate the PUE of maize under reduced row spacing and varying N regimes. No till maize was grown in Balcarce, Argentina, during two growing seasons using three rows spacing (35, 52, and 70 cm) and three N rates (0, 90, and 180 kg N ha−1). Shoot dry matter (DM), grain yield, and accumulated P content were determined. At V6 and R6 growth stages, the P use efficiency (PUE = g aboveground DM or grain yield per g P available) and it components P utilization efficiency (PUTE = g aboveground DM or grain yield per g P uptake), and P uptake efficiency (PUPE = g P uptake/g P available) were determined. N rate and narrower rows increased total DM, grain yield, and accumulated P content. Phosphorous concentration, PUTE, PUPE and PUE were not affected by row spacing or N rate. The present study showed that row spacing did not affect P use efficiency in no till maize when the soil P availability was adequate.
The Impact of Green Credit Policies on Green Innovation in Heavily Polluting Firms: Evidence from China

Based on balanced panel data of listed companies from 2007-2017, this paper investigates the causal relationship between green credit policy and green innovation of heavily polluting enterprises. It finds that green credit policies can significantly promote green innovation among heavily polluting firms and that R&D investment mediates the relationship between the two, a finding that passes a series of robustness tests.
Fuzzy-set Method for Fast Edge Detection of Medical Image

In order to achieve simply and effectively the ideal edge of a medical image and thus perform an effective medical diagnose, a fast edge detection method based on the combination of fuzzy subsets is developed. We partition an image into two portions: the edge portion and the non-edge portion. Non-edge portion, consisting of the objects and its background, is removed from an image; the remainder is image's edge. Considering the fuzziness of image's edge, some fuzzy operations can be carried out. We firstly partition the gray-level histogram into several sub-regions and operate corresponding fuzzy subsets. Finally, image's edge is obtained. Experiment results show as compared with Sobel operator or Prewitt operator, that the described method is more excellent.
Hematopoietic Stem Cell: Regulation and Nutritional Intervention

Hematopoietic stem cells (HSCs) are crucial for the life maintenance of bio-organisms. However, the mechanism of HSC regulation is intricate. Studies have shown that there are various factors, either intrinsically or extrinsically, that shape the profile of HSCs. This review systematically summarizes the intrinsic factors (i.e., RNA-binding protein, modulators in epigenetics and enhancer–promotor-mediated transcription) that are reported to play a pivotal role in the function of HSCs, therapies for bone marrow transplantation, and the relationship between HSCs and autoimmune diseases. It also demonstrates the current studies on the effects of high-fat diets and nutrients (i.e., vitamins, amino acids, probiotics and prebiotics) on regulating HSCs, providing a deep insight into the future HSC research.
Identification of MicroRNA Expression Profiles Related to the Aggressiveness of Salivary Gland Adenoid Cystic Carcinomas

Adenoid cystic carcinoma (ACC) has been reported as the second most common carcinoma of the salivary glands. Few studies have associated miRNA expression with ACC aggressiveness. In this study, we evaluated the miRNA profile of formalin-fixed, paraffin-embedded (FFPE) samples of salivary gland ACC patients using the NanoString platform. We studied the miRNA expression levels associated with the solid growth pattern, the more aggressive histologic feature of ACCs, compared with the tubular and cribriform growth patterns. Moreover, the perineural invasion status, a common clinicopathological feature of the disease that is frequently associated with the clinical progression of ACC, was investigated. The miRNAs showing significant differences between the study groups were selected for target prediction and functional enrichment, which included associations with the disease according to dedicated databases. We observed decreased expression of miR-181d, miR-23b, miR-455, miR-154-5p, and miR-409 in the solid growth pattern compared with tubular and cribriform growth patterns. In contrast, miR-29c, miR-140, miR-195, miR-24, miR-143, and miR-21 were overexpressed in patients with perineural invasion. Several target genes of the miRNAs identified have been associated with molecular processes involved in cell proliferation, apoptosis, and tumor progression. Together, these findings allowed the characterization of miRNAs potentially associated with aggressiveness in salivary gland adenoid cystic carcinoma. Our results highlight important new miRNA expression profiles involved in ACC carcinogenesis that could be associated with the aggressive behavior of this tumor type.
Why Do Employees Show Pro-Environmental Behaviors? A Perspective of Environment Social Responsibility

This research uses social identity theory to propose that environmental social responsibility perceptions influence green commitment, and then influence pro-environmental behaviors, which are moderated by institutional pressure. Data were collected from 100 employees of technology firms in Taiwan, and the results support all hypotheses. This research chose technology firms as empirical data because Taiwan’s technological level is known to the world, which can reduce sampling errors caused by the lack of environmental knowledge. Finally, this research not only advances the literature on sustainability issues in organizational management but also provides a paradigm to help firms implement pro-environmental behaviors to achieve competitive advantage and sustainable development goals.
Effects of Multimodal Physical and Cognitive Fitness Training on Sustaining Mental Health and Job Readiness in a Military Cohort

Drawing on the emerging area of workplace sustainability, this study sought to measure the effects of multimodal physical and cognitive fitness training on sustaining mental health and job readiness via impacts on subjective burnout, mental wellbeing, and resilience in a military cohort. Volunteer participants were block randomised into either a standard 4-week resilient mind program (RMP) intervention or an RMP combined with self-paced functional imagery practice (RMP+FI). Self-reported burnout, mental wellbeing, and resilience were measured at baseline and at the end of the 4-week intervention using the Maslach Burnout Inventory-General Survey (MBI-GS), Brief Resilience Scale (BRS), and the World Health Organization’s WHO-5 Well-Being Index (WHO-5), respectively. A total of 78 participants were enrolled in the study and 72 (92%) completed the program. Repeated measures ANOVAs showed significant effects of the RMP intervention, with both the RMP and RMP+FI groups reporting improved resilience (F(1, 70) = 13.08, p < 0.001, partial ω2 = 0.00086) and mental wellbeing (F(1, 70) = 41.86, p < 0.001, partial ω2 = 0.36). Both groups also reported improved burnout markers for professional efficacy (F(1, 70) = 6.25, p < 0.002, partial ω2 = 0.02), as well as reduced emotional exhaustion (F(1, 70) = 31.84, p < 0.001, partial ω2 = 0.02) and job cynicism (F(1, 70) = 8.80, p < 0.005, partial ω2 = 0.005). The FI practice produced no significant improvement in the RMP-only condition. Our results support the efficacy of RMP intervention in reducing burnout symptoms and improving self-reported mental wellbeing and resilience in a cohort of serving Navy aviators.
Universal Recommendations on Planning and Performing the Auditory Brainstem Responses (ABR) with a Focus on Mice and Rats

Translational audiology research aims to transfer basic research findings into practical clinical applications. While animal studies provide essential knowledge for translational research, there is an urgent need to improve the reproducibility of data derived from these studies. Sources of variability in animal research can be grouped into three areas: animal, equipment, and experimental. To increase standardization in animal research, we developed universal recommendations for designing and conducting studies using a standard audiological method: auditory brainstem response (ABR). The recommendations are domain-specific and are intended to guide the reader through the issues that are important when applying for ABR approval, preparing for, and conducting ABR experiments. Better experimental standardization, which is the goal of these guidelines, is expected to improve the understanding and interpretation of results, reduce the number of animals used in preclinical studies, and improve the translation of knowledge to the clinic.
Anomaly Detection for Hydraulic Power Units - A Case Study

This article aims to present the real-world implementation of an anomaly detection system of a hydraulic power unit. Implementation involved the Internet of Things approach. A detailed description of the system architecture is provided. The complete path from sensors through PLC and the edge computer to the cloud is presented. Some technical information about hydraulic power units is also given. This article involves the description of several model-at-scale deployment techniques. In addition, the approach to the synthesis of anomaly and novelty detection models was described. Anomaly detection of data acquired from the hydraulic power unit was carried out using two approaches, statistical and black-box, involving the One Class SVM model. The costs of cloud resources and services that were generated in the project are presented. Since the article describes a commercial implementation, the results have been presented as far as the formal and business conditions allow.
THE VALIDITY AND RELIABILITY STUDY OF ELEMENTARY FOURTH GRADE NUMBER SENSE SCALE

In this study, it was aimed to develop a valid and reliable number sense scale for elementary school students. Construct validity studies were conducted with 299 elementary school 4th grade students studying in 2 public schools in Eskişehir province selected by cluster sampling method. Criterion validity studies were conducted with 312 elementary school 4th grade students studying in 4 public schools in Eskişehir. As a result of the literature review and expert opinions, it was decided that the theoretical structure of the scale would consist of 6 factors and 31 items, namely the meaning and size of numbers, decomposing and combining numbers, determining reference points, the effect of operations on numbers, the flexible use of numbers, and the sensibility of numbers. Item analysis studies were first conducted on the draft scale and it was decided to remove 6 items with low discrimination from the test. Following the item analysis studies, construct validity studies were conducted. Within the scope of construct validity, it was aimed to test the theoretical structure created by the researchers. In this context, confirmatory factor analysis (CFA) technique was thought to be more appropriate for the purpose. As a result of CFA, it was determined that the theoretical structure of the scale produced a high fit with its 6-factor 25-item structure. It was determined that the reliability coefficients of the whole scale and each factor were sufficient. Finally, within the scope of criterion validity, the relationship of the number sense scale with the problem solving achievement test developed by Ulu (2017) was examined. As a result, it was seen that all factors of the number sense scale had a moderately significant relationship with problem solving success, and this finding allowed us to see that the criterion validity of the number sense scale was sufficient.
Low-Profile Ultra-Wideband Dual-Polarized Omnidirectional Antenna for Indoor Base Station

A low-profile ultra-wideband omnidirectional antenna with dual polarizations for indoor mobile communication is presented. The horizontally polarized (HP) omnidirectional element is introduced by using 12 I-shaped slot antennas, which are arranged in a circle-shaped array and excited by a 1-to-12 power divider. The vertically polarized (VP) omnidirectional performance is introduced by using a dual-M-shaped monopole with a small ground plane. To enhance the impedance matching within an ultra-wide bandwidth, a top metal disk with four chunks, a bottom metal loop, and a ring slot embedded in the ground plane are employed for the design of the VP element. After replacing the metal disk of the VP element with the designed HP element, the omnidirectional antenna with dual polarizations is then simply achieved. By utilizing this new method, an ultra-wideband dual-polarized omnidirectional antenna for indoor mobile communications is designed, manufactured, and measured. It has an ultra-wide bandwidth of 117% (1.44–5.5 GHz), high isolation of 30 dB, and a low profile of $0.16\lambda _{\mathrm {L}}$ ( $\lambda _{\mathrm {L}}$ denotes the wavelength at the lowest frequency of the operating band). Good omnidirectional radiation performance with gain variation < 2.6 dBi is obtained for both HP and VP ports over the ultra-wide operating band.
‘Not everybody can do this job’: a qualitative inquiry into emotional labour from RCMP detachment services assistants

Abstract Many police organisations employ and rely on public servants to complete specialised tasks with their organisations. The Royal Canadian Mounted Police (RCMP) regularly hires public servants known as Detachment Services Assistants (DSAs) to take on various support roles. As part of DSAs’ many clerical and administrative responsibilities, these workers must often perform emotional labour across different job tasks, which in turn, can be a personal yet occupationally mandated source of stress and strain. In the current study, we draw from semi-structured interviews with DSAs (n = 54) to investigate the different situations in which DSAs undertake emotional labour, the various styles of emotional labour DSAs perform, and the negative toll emotional labour places on DSAs in their workplace. Our research aims to contribute to the broader emotional labour literature on policing and the niche police literature on public servants, a form of civilian staff, employed by the RCMP.
Regulation of Vicia faba L. Response and Its Effect on Megoura crassicauda Reproduction under Zinc Stress

The heavy metal zinc (Zn) is known to be transmitted in the food chain; however, the effect of Zn stress on beans and herbivorous insects is largely unclear. This study aimed to investigate the resistance of broad bean plants to Zn stress and the consequent changes in their physiological and biochemical metabolism by simulating heavy metal pollution in soil. Simultaneously, the effects of aphid progeny treated with different Zn concentrations on the expression of carbohydrate and related genes were analyzed. The results showed that Zn had no effect on the germination rate of broad beans, but other effects mainly manifested as follows. (1) Chlorophyll content decreased. (2) The total soluble sugar and Zn content in stems and leaves increased with increasing Zn content. (3) The proline content first increased and then decreased with increasing Zn content. (4) The height of the seedlings indicates that low concentrations promote growth and high concentrations inhibit growth. In addition, only the first-generation fecundity decreased significantly when aphids fed on heavy metal broad beans. Continuous high Zn levels increase the trehalose content of aphid F1 and F2, while F3 decreases. These results can not only provide a theoretical basis for exploring the impact of soil heavy metal pollution on ecosystems but also preliminarily evaluate the possibility of broad beans as a means of pollution remediation.
Labelled Indoor Point Cloud Dataset for BIM Related Applications

BIM (building information modelling) has gained wider acceptance in the AEC (architecture, engineering, and construction) industry. Conversion from 3D point cloud data to vector BIM data remains a challenging and labour-intensive process, but particularly relevant during various stages of a project lifecycle. While the challenges associated with processing very large 3D point cloud datasets are widely known, there is a pressing need for intelligent geometric feature extraction and reconstruction algorithms for automated point cloud processing. Compared to outdoor scene reconstruction, indoor scenes are challenging since they usually contain high amounts of clutter. This dataset comprises the indoor point cloud obtained by scanning four different rooms (including a hallway): two office workspaces, a workshop, and a laboratory including a water tank. The scanned space is located at the Electrical and Computer Engineering department of the Faculty of Engineering of the University of Porto. The dataset is fully labelled, containing major structural elements like walls, floor, ceiling, windows, and doors, as well as furniture, movable objects, clutter, and scanning noise. The dataset also contains an as-built BIM that can be used as a reference, making it suitable for being used in Scan-to-BIM and Scan-vs-BIM applications. For demonstration purposes, a Scan-vs-BIM change detection application is described, detailing each of the main data processing steps.
A systematic review of prediction accuracy as an evaluation measure for determining machine learning model performance in healthcare systems.

Focus on predictive algorithm and its performance evaluation is extensively covered in most research studies. Best predictive models offer Optimum prediction solutions in the form of prediction accuracy scores, precision, recall etc. Prediction accuracy score from performance evaluation have been used as a determining factor for appropriate model recommendations use. It is one of the most widely used metric for identifying optimal prediction solutions irrespective of context or nature of dataset, size and output class distributions between the minority and majority variables. The key research question however is the impact of using prediction accuracy as compared to balanced accuracy in the determination of model performance in healthcare and other real-world application systems. Answering this question requires an appraisal of current state of knowledge in both prediction accuracy and balanced accuracy use in real-world applications including a search for related works that highlight appropriate machine learning methodologies and techniques.