Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Media composition on Asymbiotic Seed Culture of Vanda tessellata : An Approach to In vitro Conservation

For initiation of seed germination and protocorm growth in Vanda tessellata (Roxb.) Hook. ex G. Don different media, namely Knudson’s C basal medium, modified Knudson’s C basal medium, Murashige and Skoog basal medium, Vacin and Went basal medium and Lindeman basal medium either alone or supplemented with vitamin or 0.1% peptone (w/v) were used. Vitamin mixture was consisted of nicotinic acid, pyridoxine and thiamine HCl at 1 : 1 : 10, respectively. For the initiation of germination, all the treatments exhibited promising results without showing significant variation. But the rate of survival of the germinated seedlings was remarkably low in all the basal media. Maximum survival rate of germinated seedlings was recorded in MS + 0.1% peptone. Necrosis of protocorms was a common phenomenon in all the treatments and 100% necrosis was recorded in LM basal medium and LM + vitamin. Addition of vitamin mixture and peptone in the basal media increased the rate of survival as well as differentiation of the germinated protocorms. Maximum rooted plantlets were recorded in VW + 0.1% peptone Plant Tissue Cult. & Biotech. 30(2): 285-295, 2020 (December)
Japanese Discourse Relation Analysis: Task Definition, Connective Detection, and Corpus Annotation

uments, (2) automatically annotating discourse units and connectives, (3) designing a discourse relation tagset consisting of seven classes organized into a two-level hierarchy, and (4) annotating discourse relations through two types of annotators, namely experts and crowd workers. We report that there is signiﬁcant room for improvement in data annotation performed by crowd workers. Based on this corpus, we develop a Japanese discourse parser. Experimental results show that the proposed parser outperforms previously developed models. We also demonstrate that the automatic recognizer of discourse connectives can be used as a high-quality parser for explicit discourse relations. We implement a recognizer of discourse units and discourse connectives in KNP. We also make the corpus publicly available.
Boarding Schools as Colonizing and Oppressive Spaces: Towards Understanding Student Protest and Violence in Kenyan Secondary Schools

Goffman’s theory of total institutions and Fanon’s theory of violence were used to explain student protests and violence in Kenyan secondary schools. Youth violence around the world is not a new phenomenon. However, the persistence, frequency, and intensity of violence, and their consequences beg for logical explanations and remedies. This study was part of a three-year project facilitated through the Networked Improvement Community partnership for self-study and intervention. Although a holistic approach to research was applied, data for this study were gathered through narrative inquiry. Participants (teachers, principals, and members of the school community) were identified purposively using the snowball process. Data were analyzed through deductive and inductive reasoning. Findings indicate a preponderance of student protest and violence among students in boarding schools. Student violence was a response to the devaluing and oppressive environment in boarding schools which resembled total institutions, and students exercising democratic rights to protest. The paper argues that school authorities could mitigate violent protests by providing formal political means of representation and democratic decision-making; creating new spaces for negotiation and peaceful protest; listening to the voices of students; and engaging in dialogue to create a common vision and mission.
Institutional Quality and Health Outcomes in Sub-Saharan Africa

The objective of this research is to identify the institutional dimensions that are the most relevant to the improvement of health outcomes in sub-Saharan Africa. To this end, institutional quality measures are integrated into a health production model. This model is estimated by the Two-stage least squares method on a panel of 45 countries observed over the period 1996-2018. The data used are from the World Bank. The results show that the most relevant institutional dimensions that improve health outcomes in the region are by order: rule of law, control of corruption, government effectiveness, voice and accountability and political stability and absence of violence. For these reasons, African decision-makers who often have limited resources can focus on a few key components of these institutional qualities or their combinations to improve health outcomes in their countries.
Nanoscale Ordering in Oxygen Deficient Quintuple Perovskite Sm2-εBa3+εFe5O15-δ: Implication for Magnetism and Oxygen Stoichiometry

The investigation of the system Sm–Ba–Fe-O in air has allowed an oxygen deficient perovskite Sm2-eBa3+eFe5O15-δ (δ = 0.75, e = 0.125) to be synthesized. In contrast to the XRPD pattern which gives a cubic symmetry (ap = 3.934 A), the combined HREM/EELS study shows that this phase is nanoscale ordered with a quintuple tetragonal cell, “ap × ap × 5ap”. The nanodomains exhibit a unique stacking sequence of the A-site cationic layers along the crystallographic c-axis, namely “Sm–Ba–Ba/Sm–Ba/Sm–Ba–Sm”, and are chemically twinned in the three crystallographic directions. The nanoscale ordering of this perovskite explains its peculiar magnetic properties on the basis of antiferromagnetic interactions with spin blockade at the boundary between the nanodomains. The variation of electrical conductivity and oxygen content of this oxide versus temperature suggest potential SOFC applications. They may be related to the particular distribution of oxygen vacancies in the lattice and to the 3d5L configuration of iron.
Determinants of Market Participation of Smallholder Sorghum Farmers and Strategies for Improving Their Participation; the Case of Moretna Jiru District, Ethiopia

The purpose of this study is to identify market participation of smallholder’s Sorghum producers in Moretna jiru district, central Ethiopia. Primary data was collected from 355 randomly selected smallholder farm households from three randomly selected kebeles in the district. The survey data was analyzed using descriptive statistics and econometrics model with probit and Tobit censored model. Results of the probit model analysis showed that output, farm size, extension contact and ownership of transport positive and significant role in households’ decision to participate in sorghum output sales at 1% level of significance; whereas, household income, off-farm income, access to credit and lack of information negatively at 1% and 10% level of significance. Results of Tobit censored analysis showed; extension contact, farm size, output and membership of farmer group have positive and significant role in the value of sorghum at 1% level of significance; while access to credit was found to have negative significant role at 5% level of significance. Farm size, output, extension contact and membership of farmer group was found to affect both households’ decisions to participate and intensity of participation in sorghum sales at 1% level of significance. Based on the findings there is a need to enhance the interaction between extension export and farmers and distribute trained extension exports in all kebeles by giving different trainings. ; and help the farmers improve land productivity, where possible, by intensifying farm practices through provision of sustainable and timely availability of inputs and management practices so as to generate surplus sorghum output and boost sales.
Leadership in Excellent School: A Qualitative Study

The main school activities are learning activities. Learning is a reflection of school performance. For the learning activities carried out by the teacher to achieve the goals, it requires a school commitment to support learning activities. Learning leadership is leadership behavior that seeks to develop better learning over time. Therefore, the principal’s learning leadership is the key to the success of excellent schools. This research aims to describe learning leadership in excellent schools. This research was conducted with a qualitative approach. The informants for data collection were school principals, teachers, and staff. The data were analyzed using the following processes: (1) data reduction; (2) presenting data; and (3) verification. The conclusion of this study is that the leadership of the principal has an important role in the process of developing excellent schools.
Incorporate Online Hard Example Mining and Multi-Part Combination Into Automatic Safety Helmet Wearing Detection

Automatic detection of workers wearing safety helmets at the construction site is essential for safe production. Aiming at the problem of low recognition rate caused by factors such as background and light in the automatic detection of safety helmets using traditional machine learning methods, this paper proposes an object detection framework that combines Online Hard Example Mining (OHEM) and multi-part combination. In our framework, we first use the multi-scale training and the increasing anchors strategies to enhance the robustness of the original Faster RCNN algorithm to detect different scales and small object. Then, the OHEM is to optimize the model to prevent the imbalance of positive and negative samples. Finally, the person wearing the helmet and its parts (helmet and person) are detected by improved Faster RCNN. The multi-part combination method uses the geometric information of the detection objects to determine if a worker is wearing a helmet. Experiments show that compared with the original Faster RCNN, the detection accuracy is increased by 7%. It also has better detection performance for partial occlusion and different-size objects, showing good generalization and robustness.
A method for the synthesis of neural regulators for linear objects

The article proposes a method for the synthesis of a neural controller for closed-loop systems with linear objects. The scientific novelty of the proposed method lies in the fact that the neural controller, to the input of which the object state vector is fed, must be trained to stabilize in one of the possible desired values, and to ensure regulation in other desired values. For objects with an inaccessible state vector, it is possible to use the estimation vector of the object state vector. It is proposed to proportionally decrease/increase the signal of the state vector and increase/decrease the control signal formed by the neural regulator. Also, other advantages of the proposed method include: 1) the absence of the need for training on several desired values, which greatly simplifies and accelerates the training of the neural network, and also eliminates control errors in the range of values for which the neural controller was not trained; 2) the possibility of learning from an initially unstable state of a closed-loop system. The proposed method for the synthesis of a neural controller for a closed-loop system with a linear object was tested on the example of the synthesis of a controller for an object 1/s 3, which is unstable. A neural network is used as a regulator, which is proposed to be trained using one of the reinforcement learning methods (in the article, the Deterministic Policy Gradient method allowed us to obtain the best results). The resulting graphs of transient processes allow us to conclude about its successful application. The article ends with conclusions and considerations about further lines of research, which include the quality of the transient process and the possibility of adjusting it by changing the reward function, which will allow setting the graphs of transient processes.
Can Gamma Glutamyle Transferase Predict Unhealthy Metabolic Phenotype in Healthcare Workers in Azar Cohort Study?

Background: There is a close connection between serum gamma-glutamyltransferase (GGT), insulin resistance, and the increased number of the components of the metabolic syndrome (MetS). However, there are no studies evaluating the correlation between GGT and cardiometabolic phenotype. Thus, the main objective of the current study is to evaluate the relationship between GGT and cardiometabolic phenotypes among healthcare workers in Azar Cohort Study.Method: In this cross-sectional study, anthropometric measurements, fasting blood sugar (FBS), triglyceride (TG), cholesterol, high lipoprotein density (HDL), GGT, and blood pressure of 1458 healthcare workers were evaluated. MetS was determined according to the report by the National Cholesterol Education Program Adult Treatment Panel III (ATP III). We classified participants into four cardiometabolic phenotypes. These phenotypes consist of metabolically-healthy lean (MHL) (no MetS and BMI < 25 kg/m2), metabolically-unhealthy lean (MUHL) (MetS present and BMI < 25 kg/m2), metabolically-healthy obese (MHO) (no MetS and BMI ≥25 kg/m2), and metabolically-unhealthy obese (MUHO) (MetS present and BMI ≥ 25 kg/m2). Results: The first and third GGT tertiles have the highest prevalence of MHL (31%) and MHO (65.1%), respectively, which is statistically significant (P-value ≤ 0.001). In comparison with the lowest GGT tertile, the odds of MHO and MUHO increased by 2.84 (95% CI 2.01-4.01) and 9.12 (95%CI 5.54-15), respectively. However, the correlation between MUHL and GGT tertile does not show a similar trend. According to the ROC curve, the cutoff value of 18.5 U/l for GGT allowed us to distinguish between MHO and MUHO.Conclusions: Based on the findings of the study, the GGT can be used as a biomarker to reveal the risk of MetS, and we believe that the GGT level can be used for the early detection of MHO at risk of MetS and for administering proper interventions.
Hotspot Detection Method in Large Capacity Photovoltaic (PV) Farm

The obligation to use low carbon emissions power plants encourages the increased utilization of renewable energy generation. Among the whole renewable energy plants, photovoltaic (PV) is a modular plant that is easy to implement, which the utilization reaches 100GW in the year 2017. By the increasing use of PV globally, the health of PV modules needs to be a concern because, during the operation, PV modules can experience various faults. Almost 50% of the overall fault is the hotspot which is very hard to detect on a wide area PV farm. For example, a 30 MW PV generation with an area of 60 hectares and composed of 126000 modules (consists of millions of cell), the existing hotspot detection methods takes up to 210 days. The long time and not continuous detection lets the hotspot to degrade and burn the modules. To prevent catastrophic failure due to hotspot, a detection method that can detect the fault quickly is needed. The proposed method, thermal imaging using a fish-eye lens could be used in this case as it has a very wide angle of view, which allows monitoring all of the PV modules in one detection period.
Mathematical description of water flow quantity for microhydroelectric station

The main methods of regulating water flow and power of a microhydroelectric power plant are considered. New technical solutions are proposed for screw jet hydraulic turbines adapted to low heads and water flow rates. Preliminary calculations carried out by the authors show that the power of a micro-hydroelectric power plant depends on the individual factors of the area.As the speed of the water flow increases, the speed of the water wheel also increases, and in turn, the electric power of the micro-hydroelectric power plant is increased.
Macroeconomic Policies and Social Inclusion in the Developing World

Many in the developing world face social exclusion and discrimination, preventing them from actively participating in society itself. Sound macroeconomic policies with a focus on stabilizing the price level and social outcomes can help to achieve social justice for marginalized people. This study empirically examines the impact of macroeconomic policies on social inclusion, considering specifically the coordination among them in promoting that social inclusion. It deals primarily with pure non-income dimensions of social inclusion such as education, and health, etc. Using annual panel data of 51 developing countries for the period 1995-2017 this study employs state-of-the-art panel data estimation methods – pooled estimation, fixed-effect, and random-effect models. To check for robustness and to handle the problem of endogeneity, the 2SLS technique has also been used. This study argues that a well-designed macroeconomic policy framework can do much more than just achieve economic goals. Results suggest that fiscal and monetary policy, through resource mobilization, can play a significant and positive role in promoting social inclusion. However, these fiscal and monetary policy actions are not independent; thus, a policy mix is required to achieve the target of an inclusive society.
Osteoarthritis of the Knee: Recent Advances and Management During COVID-19 Era

Osteoarthritis is a debilitating joint disorder that causes progressive weakening of the articular cartilage and the synovium leading to a stiff joint. It is a very common inflammatory disorder that has been closely related to aging, obesity, genetics, mechanical stress, medications, and injury. Osteoarthritis has a multifactorial etiology including constitutional and mechanical factors, biochemical processes, cellular processes, mechanical forces, local inflammation, genetic predisposition, and joint integrity. Older and newer therapies are continuously under investigation, and some have shown promising preliminary results in many studies. This review aims to give an overview of the current knowledge of therapies available for knee osteoarthritis with a focus on non-surgical intervention, especially in the COVID-19 era. COVID-19 has imposed a challenge to the usage of traditional methods and techniques for providing proper patient management. Thus, it is crucial to provide guidelines for patients with knee osteoarthritis during the COVID-19 pandemic.
Comparative Study of Deep Learning Models for Automatic Coronary Stenosis Detection in X-ray Angiography

The article explores the application of machine learning approach to detect both single-vessel and multivessel coronary artery disease from X-ray angiography. Since the interpretation of coronary angiography images requires interventional cardiologists to have considerable training, our study is aimed at analysing, training, and assessing the potential of the existing object detectors for classifying and detecting coronary artery stenosis using angiographic imaging series. 100 patients who underwent coronary angiography at the Research Institute for Complex Issues of Cardiovascular Diseases were retrospectively enrolled in the study. To automate the medical data analysis, we examined and compared three models (SSD MobileNet V1, Faster-RCNN ResNet-50 V1, FasterRCNN NASNet) with various architecture, network complexity, and a number of weights. To compare developed deep learning models, we used the mean Average Precision (mAP) metric, training time, and inference time. Testing results show that the training/inference time is directly proportional to the model complexity. Thus, Faster-RCNN NASNet demonstrates the slowest inference time. Its mean inference time per one image made up 880 ms. In terms of accuracy, FasterRCNN ResNet-50 V1 demonstrates the highest prediction accuracy. This model has reached the mAP metric of 0.92 on the validation dataset. SSD MobileNet V1 has demonstrated the best inference time with the inference rate of 23 frames per second.
RISCO PSÍQUICO E DESENVOLVIMENTO INFANTIL: IMPORTÂNCIA DA DETECÇÃO PRECOCE NA PUERICULTURA

O objetivo deste estudo foi realizar uma reflexao sobre desafios e caminhos para a puericultura a partir dos resultados vivenciados no seguimento de bebes nascidos a termo e prematuros tardios em uma unidade basica de saude, no qual se pode analisar o desenvolvimento infantil do ponto de vista do psiquismo, linguagem e motricidade. Os resultados apontam para a necessidade de se repensar os profissionais e os espacos para insercao da puericultura, tendo em vista as limitacoes do SUS relacionadas a inexistencia de uma carreira nacional de saude que impacta na organizacao hierarquica dos niveis de atencao, a ausencia ou limitacao na insercao de tematicas como psiquismo e linguagem na formacao dos profissionais da puericultura, e as limitacoes educacionais familiares. Sugere-se que uma visao intersetorial e menos medico-centrada podera ampliar possibilidades no acompanhamento do desenvolvimento infantil.
Adsorption behaviours of lysozyme onto poly-hydroxyethyl methacrylate cryogels containing methacryloyl antipyrine-Ce(III)

ABSTRACT In this study, Ce3+-based cryogel with methacryloyl antipyrine (MAAP) and 2-hydroxyethyl methacrylic acid (HEMA) [p(HEMA-MAAP-Ce3+] was prepared. MAAP-Ce3+ complex was characterized by UV–near infrared and energy-dispersive X-ray spectroscopy. Cryogel was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and swelling test. Pore size of the cryogel was found to be about 30–50 µm. The effects of flow rate, pH, temperature, and initial enzyme concentration have been investigated. Maximum adsorption capacity was found to be 57.84 mg g−1 cryogel at pH 6.0. After seven times of adsorption–desorption cycles of same cryogel, it was observed that there is negligible decrease in the adsorption capacity. GRAPHICAL ABSTRACT
Incidencia estacional de mareas rojas en la bahía de Santa Marta y sectores adyacentes, Caribe colombiano

In order to describe the environmental and climatic conditions associated with the occurrence of six red tide events between 2010 and 2017, in Santa Marta (Colombian Caribbean), biological and physicochemical information during these events was collected. Additionally, precipitation data and the Oceanic Niño Index (ONI) between 2010 and 2017 were consulted. The results showed that the dinoflagellate Cochlodinium sp. was responsible for three events that occurred in October 2010, October 2011 and November 2015, reaching a maximum densities of 5 × 10 cells L. These events were associated with an increase in rainfalls and seawater surface temperature (29.7 oC) and a decrease in salinity (< 35.5). The Mesodinium cf. rubrum ciliate was responsible for three other events (January 2015, January 2017 and March 2017), recording maximum concentrations of 9.2 × 10 cells L. During these last events, there was no rainfall and high concentrations of nutrients, increases in salinity (> 36.6) and sea temperatures below 26 oC were evident. Associating the occurrences of red tide events and the ONI index, it was evidenced that Cochlodinium sp. blooms occurred during years influenced by moderate-strong climatic (thermal) events (ONI > ±1 oC) whereas the blooms of M. cf. rubrum occurred during neutral years (ONI between 0.5 and -0.5 oC). The red tides presented a temporal pattern of occurrence in the Magdalena region, influenced by the climatic and environmental variability of each period, without representing a risk to human health until now. KEYwoRDS: red tides, algae blooms, climatic variability, Colombian Caribbean Boletín de Investigaciones Marinas y Costeras • Vol. 49 (2) • 2020