Miracle-dz/UniFAR-FTUs huggingface dataset:
Precise Cell Injection and Extraction Control Based on Microscopic Visual Feedback

Nuclear transplantation is an effective method for processing, modifying, and reconstructing cells, which is widely used in biological experiments. Microinjections and extractions are key steps in nuclear transplantation. It is beneficial to the promotion and the application of nuclear transplantation by increasing the efficiency and improving the quality of microinjections. At present, little research has been implemented for the speed/volume control problem in the microinjection process. Motivated by this observation, this article designs an update-law-improved adaptive control scheme to implement precise injections and extractions. Specifically, a precise mathematical model of the overall system is established first, which takes the imaging, pneumatic pump, cell, and micropipette elements into full consideration. Since parameters in the model are difficult to calibrate or measure, an update-law-improved adaptive control algorithm, together with a trajectory planner, is constructed for the microinjection and extraction system, which shows great tolerance to parameter uncertainties, avoids overshoot of the system to ensure great protection for the manipulated cells, and demonstrates fast convergence rate. The stability of the designed control system is proved theoretically by LaSalle’s principle. Finally, the controller is tested by both numerical simulation and practical experiments, with the obtained data demonstrating satisfactory performances of the overall system.
Physical examination of the mammary gland and milk indicators of udder health in East Friesian Milk Sheep

Gegenstand: Es werden Untersuchungsergebnisse uber Zusammenhange zwischen Form- und Gesundheitsmerkmalen des Euters und deren Bedeutung fur Zucht, Rohmilchqualitat und Gesundheitsuberwachung beim Ostfriesischen Milchschaf dargestellt, wozu es in der Literatur wenig Angaben gibt. Material und Methoden: An 78 Schafen in zwei Herden wurden im Verlauf einer Laktationsperiode an acht Untersuchungsterminen Eutertyp (Kugeleuter, Hangeeuter), Euter- und Zitzenmase, Palpations- und Adspektionsbefunde (Euterhaut und -drusengewebe) sowie Zellgehalt, Zellbild, elektrische Leitfahigkeit, Laktosegehalt und bakteriologische Befunde in Vorgemelkproben aus Euterhalften oder in Einzelgemelkproben miteinander verglichen und Einflusse gepruft. Ergebnisse und klinische Relevanz: Mit steigender Laktationszahl verringert sich der Bodenabstand der Euter und die Aussackungen der Zisternen sowie die Euterasymmetrien nehmen zu. Hangeeuter und Asymmetrien sind vermehrt mit Befunden am Parenchym und in der Milch verbunden, die fur Infektionen und Entzundungen sprechen. Herde, Laktationsnummer, Termin der Probenentnahme und Anzahl gesaugter Lammer beeinflussen Milchbefunde und Euterformmerkmale deutlich.
Canonical Wnt signaling Is Involved in Anterior Regeneration of the Annelid Aeolosoma viride

Annelids are regenerative animals, but the underlying mechanisms await to be discovered. Because Wnt pathway is involved in animal regeneration to varying extents, we used Aeolosoma viride to interrogate whether and how this pathway plays a role in annelid anterior regeneration. We found that the expression of wnt4, β-catenin and nuclear-localized β-catenin protein were up-regulated during blastemal formation and down-regulated as anterior structures gradually reformed. Consistent with potential Wnt activities in the blastema, treatments with either Wnt pathway activator (azakenpaullone) or inhibitor (XAV939) inhibited head regeneration, which further supports a role of Wnt pathway during anterior regeneration. Detailed tissue-level examines demonstrated that wound closure and blastemal cell proliferation were impaired by over-activating the pathway, and that neuronal and musculature differentiation were affected under Wnt inhibition. Combined, gene expression and chemical inhibitor data suggest the presence of dynamic Wnt activities at different anterior regeneration stages: an initial low activity may be required for wound closure, and the following activation may signal blastemal formation and cell differentiation. In a nutshell, we propose that the canonical Wnt signaling regulates blastemal cellular responses during annelid regeneration.
Dynamic output nonfragile reliable control for nonlinear fractional-order glucose–insulin system

The main intention of this paper is to scrutinize the problem of internal model-based dynamic output feedback nonfragile reliable control problem for fractional-order glucose–insulin system. Specifically, a robust control law that represents the insulin injection rate is designed in order to regulate the level of glucose in diabetes treatment in the existence of meal disturbance or external glucose infusion due to improper diet. By the construction of suitable Lyapunov functional, a novel set of sufficient conditions is derived with the aid of linear matrix inequalities for obtaining the required dynamic output feedback control law. In particular, the designed controller ensures the robust stability and disturbance attenuation performance against meal disturbance of the glucose–insulin system. Numerical simulation results are performed to verify the advantage of the developed design technique. Specifically, the irregular blood glucose level can be brought down to normal level by injecting suitable rate of insulin to the patient. The result exposes that the level of blood glucose is sustained in the identified ranges via the proposed dynamic output feedback control law.
Oligodontia Management in Patients with Ectodermal Dysplasia Syndrome

Background and aim: A relatively common sex- linked dermatitis characterized by a congenital dysplasia of one or more ectodermal structures is Ectodermal dysplasia (ED). Common signs include fragile skin and nails, defective teeth and salivary glands, frontal bossing with prominent supra orbital ridges, nasal bridge depression and protuberant lips. There are often a few conical teeth existing (hypodontia or Oligodontia) that results in generalized spacing. Deciduous and/or the permanent dentition may fail to form (anodontia), and, consequently, hypoplasia of jaws may happen in both cases. This article reports a case of ED and shows how to handle it. Case report: A 5 years old girl with HED visited SBMU, school of dentistry. Clinical examination showed hypotrichosis following the missing of eyelashes and eyebrows, dry skin, saddle nose and pigmentation on the legs which are characteristics of ED. Partial denture for lower jaw and composite restoration for upper jaw was used as the treatment plan. Conclusion: Preventive treatments are very crucial to save present teeth in ED patients. One treatment option is to use removable dentures as a cost-benefit and desired intermediate treatment to restore both function and esthetics and improve patient’s psychological status in Oligodontia cases.
Analysis on current flow style for vehicle alternator fault prediction

Vehicle alternator is only seen as fragment piece in vehicle. This project will analyse the vehicle alternator current output flow style. A study on charging rate onto battery can be made based on this analyst. From this a prediction can be made on the vehicle alternator health and may prevent it from affecting other charging system component. Features extracted from the raw sample data are root mean square (RMS), waveform length (WL) and autoregressive (AR). These features will then go through normality test to find the sample is normally distributed or not. The normality test used in this experiment is Jarque-Bera (JB) test. After go through the normality test, it shows that need to continue with non-parametric test. Because JB test shows that p-value is less than 0.05 confidence level. Kruskal-Wallis is used as non-parametric data validation. In this test, the hypothesized value is the value is the median instead of the mean as in Analysis if Variance (ANOVA). The Kruskal-Wallis test evaluates for any significance difference in the population medians on a dependent variable across all levels of a factor. For classification K-Nearest Neighbour (KNN) is used to find the number of K to differentiate between classes. After that the K value is use in Holdout method for training and testing. Final result shows that the accuracy of this machine learning tools is 94%. This number is a good percentage to be able to called as vehicle alternator fault prediction.
Effect of Training Program for nursing leader regarding Evidence-based Practice: pathway to Evidence-based management

Nurseleader play an important role which promoting evidence-based practice (EBP) on clinical units within hospitals. They have to use evidence skillfully to use in both in practice and leadership. Aim of the study:This study aimed to assess the effect of nursing leader training program regarding evidence-based practice (EBP) at AL-Menshawy Hospital. Research design: A quasi experimental design was used in this study. Studysetting:The study was conducted in inpatients units of Medical ,Surgical departments and Intensive Care units at EL-Menshawy Hospital affiliated of Ministry of Health, the total number of the studied units were(3)units. The study sample was all the available nurse leader(n=40). Tools for data collection: One toolwasused: Evidence-based Practice Questioners, this tool has six subscales of EBP, attitudes towards EBP, and Knowledge/Skills associated with EBP, Leadership roles towards developing EBP, leadership responsibilities for changing the cultures of EBPandbarriers toadopting Evidence-based Practice Questioner. The results showed that, there was a highly statistical significant improvement in nurses leader perception of using research knowledge to build up the evidence-based practice.Also, there was a highly statistical significant difference improvement in nurses leader level (80%) post program compared to preprogram (32,5%) regarding to perceptions of effect of training program of EBP.Also, the most of nurses leader reported that the common barriers, lack of access of internet at work, lack of resources, lack of time lack of knowledge and lack of cooperation with doctors. Thestudyconcluded that there was appositive attitude towards EBP and the training had helped nurse leaders to understand that decision can be justified with research knowledge, which strengthened the leaders responsibility to develop EBP. The study recommendedthat Evidence-based practice should be included in the curricula of students nursing education of. In-services training for nurses leader and nurses for EBP to reduce barriers for using research evidence in clinical practice.
A Comparison Between Support Vector Machine (SVM) and Convolutional Neural Network (CNN) Models For Hyperspectral Image Classification

This study presents a methodology model for the spectral classification of hyperspectral images. The applied methodology, first extracts neighbouring spatial regions via a suitable statistical support vector machine (SVM-Linear) architecture, support vector machine radial basis function (SVM-RBF) and Deep Learning (DL) architecture that comprises principal component analysis (PCA) and convolutional neural networks (CNN) and then applies a soft max classifier. PCA is introduced to reduce the high spectral dimensionality, noise, and redundant information of the input image. The SVM-Linear, SVM-RBF and CNN model is used to extract useful high-level features automatically given that it provides results comparable with each other, including hyperspectral image classification. However, because the CNN, SVM models alone may fail to extract features with different scales and to tolerate the large-scale variance of image objects, the presented methodology uses PCA optimization for spatial regions to construct features that can be then used by the SVM and CNN model to classify hyperspectral images. Experimental results obtained in the classification of the Hyperspec-VNIR Chikusei datasets show that the performance of the presented model is competitive with that of other DL and traditional machine-learning methods. The best overall accuracy of the presented methodology for the Hyperspec-VNIR Chikusei datasets is 98.84 % in SVM-RBF model.
Physiotherapy and Mental Health

Physiotherapy in mental health care and psychiatry is recognized by the World Confederation for Physical Therapy (WCPT) as a specialty within physiotherapy. Physiotherapy in mental health offers a wide range of interventions in regard of body functions, physical activity, exercises, sensory, body and movement awareness, stress and tense regulation and pain management, based on clinical and scientific evidence-based literature. Additionally, the promotion of a healthy lifestyle and “physio-education” (i.e. the process of providing education and information regarding specific physiotherapy related topics to patients and their family members) should be a responsibility of the physiotherapist. This paper gives a short overview of the interventions in the field of mental health to offer appropriate care to a specific vulnerable but growing group in our society.
PROFESSIONAL INSERTION OF MASTER AND DOCTORATE STUDENTS IN THE FIELDS OF COMMUNICATION

This investigation is part of an academic innovation project within the framework of the Complutense University of Madrid (UCM) Quality Strategic Plan 2015-2019. With the experience of having participated in several innovation and teaching projects, we proposed the beginning of a new project in the field of postgraduate, official masters and doctoral programs’ training. This project allows students to improve their learning experience by conducting their research work of Master and Doctoral Theses within the framework of the professional reality. This experience shows the best academic training for professional insertion of master and doctorate students, in the fields of research applied to communication, especially in relation to the management of public institutions and non-profit organizations. This project aimed graduate, masters and doctorate students carrying out their work to Master's and Doctoral Theses in collaboration with public utilities. Thus, students are offered the opportunity to realize their academic work as an exercise of professional practice in real cases, in the real context of working activity of the present moment, achieving their training goals. For its part, the partner organizations provide necessary information and tools for the development of the mentioned works, while they see their interests satisfied to receive the results of the academic work done by students. In turn, the development of the mentioned works of master's and Doctoral Theses have the accurate guidance of tutors and teachers who are involved in the good work of their students and that once the work is completed, will facilitate the transfer of results not only to the collaborating entity, but also to all the scientific community. To carry out all these graduate work, as mentioned, students have the invaluable support of the Director of the Library of the School of Information Sciences, as well as all staff of it. The results can serve as indicators of the quality of master's and doctorate’s programs from the School of Information Sciences at the Complutense University of Madrid, and as a reference for the implementation of similar projects to other graduate degrees from different universities, both in Spain and abroad. On the other hand, it offers tutors the ability to link their teaching to professional practice, raising the direction of the work of their students as exhaustive case studies. Innova-Docencia Group number 281 is formed by the academics: María Teresa García Nieto, Graciela Padilla Castillo, Dimitrina Jivkova Semova, Nuria Villagra García, Cristóbal Fernández Muñoz, David Caldevilla Domínguez, Cristina Fuertes Planas, María Soledad Martínez Chillón, Ana Isabel Segovia Alonso, Roxana Popelka Sosa Sánchez, María José Cavadas Gormaz, Belén Casas Mas, Rafael Barberá González, Francisco Cabezuelo Lorenzo y Mónica Viñarás Abad; and several master's and doctoral students.
GDP is Well-Being! Results in the USA and China

This article quality assures GDP and then links it to well-being in the world’s two largest economies. Despite the global plethora of national indexes, there has been little quality assurance of the unidimensionality of their component indicators. Unidimensional index theory constructs a weighted composite from a 2-level principal components analysis of its several indicators. This weighted composite evaluates its unweighted counterpart, and informs governments about the allocation of resources over its composite indicators. Two axioms predict that weighted and unweighted indexes are perfectly correlated over successive yearly populations in the USA and China. Under these axioms, fractional polynomial regressions of any criterion on these weighted and unweighted indexes perfectly predict this criterion. We confirm the unidimensionality of American and Chinese GDP indexes and their near-perfect prediction of the United Nation’s Human Development Index (HDI). This application discovers that HDI computation can be carried out from a nation’s GDP alone, i.e., without survey sampling, questionnaire interrogation, probabilistic inference, significance testing, or even HDI data.
Should Glaciers Be Considered Permafrost?

This commentary critically evaluates concepts of extending the term permafrost to any parts of an active glacier. The whole mass of any glacier is at zero centigrade or below (cryotic), except for non-ice inclusions at the glacier surface. Therefore, if glacial ice is considered a monomineral rock, then any glacier constitutes a perennially cryotic ground (i.e., permafrost), according to the purely thermal definition. However, extending the term permafrost to active glaciers introduces misconceptions, rather than a clarification of important geological terms.
Histological and ultrastructural studies on the effect of amoxicillin on the liver of mice foetuses

Introduction: In spite of the beneficial role of the beta-lactam antibiotics in the treatment of many cases of urinary tract infections, acute otitis media, and pneumonia, yet some medical reports incriminating it in producing certain adverse consequences following its use. Antibiotics remain important in pregnancy and may be second to only iron and food supplement.Aim of Work: Hence, the present investigation was carried out to evaluate the effect of two doses of the beta-lactam antibiotic amoxicillin on the liver of maternally treated foetuses.Materials and Methods: The pregnant female mice were allocated into three groups. The pregnant mothers of the first group served as control group (injected intra peritoneally with the drug solvent) and those of the other two groups were injected intra peritoneally for 8 days from day 7 till day14 during gestation with the low dose (205 mg/ kg body weight) and high dose (820 mg/ kg body weight) of the beta-lactam antibiotics amoxicillin.Results: The histological examination of the foetal liver sections of amoxicillin-treated groups showed vacuolar and fatty degenerations in the cytoplasm of the hepatocytes, as well as inflammatory cell infiltration. At the ultrastructure level, the hepatocytes of maternally treated foetuses revealed conspicuous alternations, represented by devastations of mitochondria that displayed loss of their cristae and their internal matrices materials. Fragmentation of the cisternae of rough endoplasmic reticulum into smaller stacks was also observed.Conclusion: The use of such doses of the beta-lactam antibiotic amoxicillin induces morphological alterations in fotal liver of mice subjected to this antibiotic during the period of gestation
Word Representations for Neural Network Based Myanmar Text-to-Speech System

: The main objective of this paper is to improve the naturalness of Myanmar Text-to-Speech (TTS) system without using time-consuming and expensive annotation of training corpus. Recently, word embedding, which has the advantage of training directly from a large amount of raw text data, has been used as the additional input features with the conventional input features or as the replacement of that conventional input features on the acoustic modelling of TTS systems. In this paper, the effectiveness of applying word vectors as the additional input features are investigated for Myanmar speech synthesis on the three acoustic modelling techniques, Deep Neural Network (DNN), Long Short-Term Memory Recurrent Neural Network (LSTM-RNN), and a hybrid of DNN and LSTM-RNN (Hybrid-LSTM-RNN). For the purpose of achieving better TTS performance, we built our own word vectors for Myanmar language. We further explore the best modelling method and vector dimension of word embedding for Myanmar TTS systems. Both objective and subjective evaluations are done on DNN, LSTM-RNN and Hybrid-LSTM-RNN based Myanmar TTS systems with and without additional input features such as Part-of-Speech (POS) and word vectors. According to the subjective results, applying additional input features in DNN, LSTM-RNN, and Hybrid-LSTM-RNN based Myanmar TTS systems can improve the naturalness of the synthesized speeches though objective results cannot lead to the significant improvement in LSTM-RNN and Hybrid-LSTM-RNN based systems. To the best of our knowledge, this is the first attempt to apply word vector features in neural network based Myanmar TTS systems.
Super Resolution of Videos using SRGAN

: The primary objective of our project is to generate the Super resolved images. To enhance the quality of images we are using SRGAN techniques. There are various methods of image transformation where the computing system receives some input and transforms it in output image. Previous techniques of up scaling were based on minimizing the mean squares reconstructed error. Generative Adversarial Networks are the deep neural network architectures comprised of two networks Generator and Discriminator. GANs are about creating, like drawing a portrait or composing a symphony. SRGAN provides several benefits over other techniques it proposes a perceptual loss function which consists of adversarial loss and content loss. The two main blocks are Generator and Discriminator. The Discriminator discriminates between real HR images from generated super resolved images. The Generator function is to train a propagating model. Adversarial loss function uses discriminator network which is already trained to discriminate between the two images. The content loss function uses perceptual similarity instead of pixel space similarity. One of the best things about SRGANs is that they generate data that is similar to real data. SRGANs learn the internal representations of data to generate the upscale images. The neural network is successful in recovering the photo realistic textures from downgraded images. The SRGAN techniques lack high peak to signal noise ratio but provides high efficiency and visual perception. Combining the perceptual and adversarial loss will generate a high quality super resolved image. During training phase perceptual losses measure image similarities more robustly than per-pixel losses. Perceptual loss functions measures the high level perceptual and semantic differences between the images. Our method uses semantic content losses which has a VGG network and an edge promoting adversarial losses for edges.