Miracle-dz/UniFAR-FTUs huggingface dataset:
Response to Treatment with Recombinant Human Growth Hormone (rhGH) of Short Stature Children Born Too Small for Gestational Age (SGA) in Selected Centres in Poland

Short stature resulting from SGA is an obligatory indication for treatment with rhGH. The aim of the study was to assess the response to rhGH treatment in patients treated in the years 2016–2020 in six clinical centers in Poland. During the analysis, auxological data were collected, and anthropometrical parameters (Ht, SDS Ht, HV and ΔHV) were reassessed. Subgroups of patients with dysmorphic features (DYSM), fetal alcohol syndrome (FAS) and Silver-Russel syndrome (SRS) were selected. The study group consisted of 235 children (137 boys). The medium initial age was 9.08 years, and 190 patients were in the prepubertal stage. The poor response to treatment was defined as ΔHt SDS < 0.3 and/or ΔHV < 3 cm/year. Seventeen per cent of all patients after the first year and 44% after the second year met the ΔHt SDS < 0.3 criterion, and 56% during the first and 73% during the second year met the ΔHV < 3 cm/year criterion. Our data suggest that patients with SRS may show the best response to treatment, which was sustained throughout the follow-up period. The best response in all subgroups was observed during the first 12 months of therapy. Although the proportion of patients meeting the poor response criteria was high, only a few patients exceeded the 97th percentile for IGF-1 concentration during the first year of treatment. This might suggest that increasing the dose of rhGH in the second treatment year in order to sustain accelerated HV would be safe in these patients.
Arm proprioception in lateral epicondylalgia; a cross-sectional study

Introduction: Lateral epicondylalgia is one of the most common injuries due to overuse with inflammation of the elbow on the lateral epicondyle. Although the clinical features of this disorder are well defined, few therapeutic intervention has been effective. Objectives: This study aimed to investigate the proprioception in the upper limb of patients with lateral epicondylalgia, using the sense of joint position and of force reproduction tests. Participants and Methods: Twenty patients with unilateral lateral epicondylalgia and 20 healthy subjects participated in this study. The evaluation of position sense of shoulder, elbow and wrist, and force reproduction sense of shoulder abductor, elbow flexor and wrist extensor were conducted. The proprioceptive performance was determined, using absolute, constant and variable error values. Results: Significant differences were found for the sense of the position of the elbow and wrist between the lateral epicondylalgia and control groups for the variables of absolute error (P=0.003 and P=0.02, respectively) and constant error (P=0.001, P=0.03, respectively). A significant difference was also observed for the sense of force of the elbow flexor and wrist extensor between the two groups for the variables of absolute error (P=0.02 and P=0.02, respectively) and constant error (P=0.016 and P=0.001, respectively). No statistical difference was found for variable errors neither in sense of position nor sense of force (P>0.05). Conclusion: The data confirmed the hypothesis of proprioception deficits in subjects with lateral epicondylalgia, compared to the healthy subjects during the evaluation of the sense of force and position.
The relationships between environmental parameters in livestock pen and physiological parameters of Holstein dairy cows

There has been an increase in temperature and the incidence of extreme weather events, such as heat wave, due to global warming, which has promoted the incidence of livestock diseases. Therefore, it is important to examine the effect of changes in environmental parameters on livestock performance. The aim of this study was to examine the relationship between ambient environmental conditions in livestock pen and the physiological parameters of Holstein dairy cows. The results showed that there was a decrease in the red blood cell counts, hemoglobin concentrations, and mean corpuscular hemoglobin concentration of the cows with increasing pen temperature, wet bulb globe temperature (WBGT), and temperature humidity index (THI). Additionally, high daily variation in temperature caused a decrease in the serum albumin levels of the cows. Moreover, the lowest serum calcium, inorganic phosphorus, and magnesium concentrations were observed in November, and were negatively correlated with the 24-hr temperature, WBGT, and THI range of the pen prior to sampling. Multiple regression analysis showed a positive correlation between serum cortisol concentration and 24-hr WBGT range of the pen prior to samplings and packed cell volume. However, serum cortisol and total protein concentrations were negatively correlated. Overall, the findings of the study suggest that large variation in temperature induced stress in the cows, which could be overcome by increased water consumption and improved protein digestion and absorption by the animals, and the addition of minerals, such as calcium to the diet.
Prediction of Diabetes Using ML Classifiers

In the medical organization, many of the intriguing and relevant uses of machine learning can be seen. The concept of machine learning has quickly gained traction in the health-care industry. Diabetes is a chronic sickness; it is also a collection of metabolic illnesses caused by a persistently high blood sugar level. If a precise early prediction is achievable, the unpredictability and severity of this prolonged sickness can be considerably decreased. When diabetes is discovered early, it is possible to not only slow but also even stop the progression of the disease. Treatment of frank hyperglycemia and diabetic complications is substantially more expensive than disease prevention. Thus, early prediction is the key in diabetes. A framework for diabetes prediction is proposed using machine learning classifiers, such as K-NN, Naive Bayes, Decision Tree, Random Forest, AdaBoost, and XGBoost. The accuracy for this system is checked using the ROC and some performance metrics.
A Comparative Study on the Efficacy of Coenzyme Q10 and Amitriptyline in the Prophylactic Treatment of Migraine Headaches in Children: A Randomized Controlled Trial

Background: Migraine, one of the most common headaches in children, has a significant impact on children and their family's quality of life (QoL). There are two approaches for controlling migraine headaches preventative and controlling acute attacks. Several drugs have been used for this purpose, and tricyclic antidepressants were at the top. Amitriptyline has shown not only a desirable effect on controlling the headaches but also some adverse side effects. Recently, finding effective drugs with fewer side effects, become more critical. Among them, nutraceuticals were one of the promising ones. Materials and Methods: In this randomized clinical trial on 72 patients aged 5–15 years old with diagnosis of migraine based on the International Headache Society criteria, we compare the effectiveness of coenzyme Qten on frequency, duration, and severity of childhood migraine. For comparing the QoL, we used the International PedMIDAS questionnaire. Results: Coenzyme Qten showed good therapeutic effects in children, especially in long-term use; however, amitriptyline showed more rapid response. After 3 months of treatment, clinical outcomes in the two groups did not significantly differ from each other. Similarly, Children's QoL increased in the same way. There are more reported side effects in children using amitriptyline compared to coenzyme Qten. Conclusions: According to results, Co-enzyme Q10, with fewer side effects and comparable therapeutic effects, especially in the long term, could be a good drug for prophylactic treatment of migraine headaches.
A Wasserstein Distributionally Robust Planning Model for Renewable Sources and Energy Storage Systems Under Multiple Uncertainties

Nowadays, electricity markets and carbon trading mechanisms can promote investment in renewable sources but also generate new uncertainties in decision-making. In this paper, a two-stage Wasserstein distributionally robust optimization (WDRO) model is presented to determine the optimal planning strategy for renewable energy generators (REGs) and energy storage systems (ESSs) in the distribution network. This model considers supply-side and demand-side uncertainties in the distribution network and the interaction uncertainty from the main grid which are depicted by the ambiguity sets based on the Wasserstein metric and historical data. Meanwhile, both 1-norm and ∞-norm Wasserstein metric constraints are considered to satisfy the decision-maker's different preference. Furthermore, to solve this WDRO model, a systematic solution method with a three-step process is developed. Numerical results from a modified IEEE 33-node system and a 130-node system in the real world demonstrate the advantages of the two-stage WDRO model and the effectiveness of the solution method.
Synthesis of PWM Converters From Conversion Ratios Using Flux- or Charge-Balance Equations

To cater to the heterogeneity in emerging applications, researchers have constantly been driven to invent novel dc–dc converter topologies. A review of prior art in dc–dc converter synthesis methods shows that many converter choices are available for a given input and output specification. This article quantifies the number of these choices using the flux balance equation (FBE). As the number of state variables that can be used to derive the FBE is limited, it is possible to find out the total number of possible FBEs available for a given voltage conversion ratio. Once the FBEs are known, synthesizing a converter is carried out as an inverse problem. Three different strategies to solve this inverse problem of converter synthesis and some critical synthesis results are summarized in this article. The dual synthesis of current-fed topologies with given current conversion ratios based on the charge balance equation (CBE) is also demonstrated. Four novel topologies were synthesized to illustrate the effectiveness of the CBE-based synthesis method. The mathematical formulation of the CBE-based inverse problem and the quantification of complexities in solving it are also reported.
Education and training for the energy industry

The Energy Institute runs an enormous range of training courses and accredits many more from external organisations. There is a strong tradition of courses in energy management and sustainability from the old Institute ofEnergy - these now lie alongside a substantial programme of courses with roots in the old Institute of Petroleum, covering everything from the fundamentals of the oil and gas industry to price risk management. Here, Sarah Beacock discusses some recent developments.
A Model for Highly Fluctuating Spatio-Temporal Infection Data, with Applications to the COVID Epidemic

Spatio-temporal models need to address specific features of spatio-temporal infection data, such as periods of stable infection levels (endemicity), followed by epidemic phases, as well as infection spread from neighbouring areas. In this paper, we consider a mixture-link model for infection counts that allows alternation between epidemic phases (possibly multiple) and stable endemicity, with higher AR1 coefficients in epidemic phases. This is a form of regime-switching, allowing for non-stationarity in infection levels. We adopt a generalised Poisson model appropriate to the infection count data and avoid transformations (e.g., differencing) to alternative metrics, which have been adopted in many studies. We allow for neighbourhood spillover in infection, which is also governed by adaptive regime-switching. Compared to existing models, the observational (in-sample) model is expected to better reflect the balance between epidemic and endemic tendencies, and short-term extrapolations are likely to be improved. Two case study applications involve COVID area-time data, one for 32 London boroughs (and 96 weeks) since the start of the COVID epidemic, the other for a shorter time span focusing on the epidemic phase in 144 areas of Southeast England associated with the Alpha variant. In both applications, the proposed methods produce a better in-sample fit and out-of-sample short term predictions. The spatial dynamic implications are highlighted in the case studies.
Integrative taxonomy supports two new species of Chimarra Stephens, 1829 from Brazil (Trichoptera: Philopotamidae)

Chimarra Stephens, 1829 is the largest genus of the Philopotamidae with about 930 species and cosmopolitan distribution. Recent taxonomic revisions have subdivided the genus into four subgenera: Chimarra, Curgia Walker, 1860, Chimarrita Blahnik, 1997, and Otarrha Blahnik, 2002, the last three restricted to the New World. In this paper, we describe and illustrate two new species of Chimarra from Brazil, C. (Otarrha) paraodontasp. nov. from Rio de Janeiro State and C. (Chimarrita) truncatasp. nov. from Amazonas and Pará states. Partial sequences of cytochrome oxidase subunit I (COI, DNA barcodes) were generated and integrated with morphological evidence to delimit the new species and evaluate their phylogenetic relationships within the genus. A maximum likelihood analysis of 48 COI sequences representing 19 species of Chimarra corroborated their subgeneric assignment based on morphology and highlighted their putative sister species. Both new species showed high K2P divergences when compared to their sister species: Chimarra (O.) paraodontasp. nov. and C. (O.) odonta (17.4–21.3%) and Chimarra (C.) truncatasp. nov. and C. (C.) simpliciforma (20.0–21.3%). These distances are comparable to the range of interspecific distances calculated for the whole genus (13.6–22.7%), adding support to their description as new species. This analysis was especially important because of the high morphological similarity of C. paraodontasp. nov. and C. odonta. Finally, analysis of the sequences of Chimarra odonta suggests that the nominal species may represent a complex of cryptic species with high intraspecific divergences (up to 18.1%), with at least two of those lineages co-occurring with C. paraodontasp. nov. at Parque Nacional do Itatiaia.
An investigation into multi-dimensional prediction models to estimate the pose error of a quadcopter in a CSP plant setting

The Solar Thermal Energy Research Group (STERG) is investigating ways to make heliostats cheaper to reduce the total cost of a concentrating solar power (CSP) plant. One avenue of research is to use unmanned aerial vehicles (UAVs) to automate and assist with the heliostat calibration process. To do this, the pose estimation error of each UAV must be determined and integrated into a calibration procedure. A computer vision (CV) system is used to measure the pose of a quadcopter UAV. However, this CV system contains considerable measurement errors. Since this is a high-dimensional problem, a sophisticated prediction model must be used to estimate the measurement error of the CV system for any given pose measurement vector. This paper attempts to train and validate such a model with the aim of using it to determine the pose error of a quadcopter in a CSP plant setting.
Research on acceleration and deceleration control algorithm of S-curve

With the continuous improvement of the processing level, the traditional speed planning curve can no longer meet the existing needs, and modern processing and manufacturing continue to develop towards high precision, high speed and high quality. In order to achieve the expected goal of processing and reduce the speed fluctuation caused by the oscillation of the machine in the production process, in recent years, researchers have put forward a variety of solutions on the speed planning curve, and it puts forward higher requirements for the acceleration and deceleration control algorithm of S-curve. This article will review the different S-shaped speed curves proposed by the researchers. Firstly, it introduces the goals of acceleration and deceleration algorithms and the requirements of modern processing levels. Secondly, the article gives the existing commonly used S-shaped acceleration and deceleration control algorithms, as well as the research background and principles, using cubic S-curve acceleration and deceleration, and quadruple S-curve. Acceleration and deceleration, five-order S-curve acceleration and deceleration, and S-curve acceleration and deceleration based on trigonometric functions are the main penetration points. Finally, the current research status and latest developments of S-type acceleration and deceleration control algorithms at home and abroad are reviewed, and the speed planning curve to meet the processing needs in the future is summarized and prospected.
Tarsal intersegmental reflex responses in the locust hind leg

Locomotion is vital for vertebrates and invertebrates to survive. However, the mechanisms for locomotion are partially unknown. Central Pattern Generators and reflex systems have been shown to be the basis of most movements performed by arthropods. Much has been investigated lately on Central Pattern Generators, but little work has been done in reflex systems. Locomotion and motor output in feet (or tarsus in arthropods) has also been disregarded in research. Despite that feet are responsible for stability and agility in most animals, research on feet movements is scarce. In this thesis the tarsal intersegmental reflex of the locust hind leg is investigated. The tarsal reflex consists of a response in the tarsus when there is a change in the femoro-tibial joint. The main objective of the thesis is to describe the system and to develop mathematical and experimental methods to study, model and analyse it. Through a set of experiments is shown that as the knee joint is extended, the tarsus is depressed, and as the knee joint flexes, the tarsus levates. The experiments demonstrated that there is a purely neuronal link between the femoro-tibial joint position and the tibio-tarsal joint position. Moreover, it also reveals the effect of neuromodulatory compounds, such as dopamine, serotonin or octopamine. The tarsal reflex responses are fairly consistent across individuals, although significant variability across animals was found. To model a system where variability is an issue, a mathematical model with strong generalisation abilities is used: Artificial Neural Networks (ANNs). To design the ANNs, a metaheuristic algorithm has been implemented. The resulting ANNs are shown to be as accurate as other mathematical models used in physiology when used in a well known reflex system, the FETi responses. This results showed that ANNs are as good as Wiener methods in predicting responses and they outperform them in prediction of Gaussian inputs. Furthermore, they are able to predict responses in different animals, independently of the variability, with a more limited performance. New experimental methods are also designed to obtain accurate recordings of tarsal movements in response to knee joint changes. These experimental methods facilitate the data acquisition and its accuracy, reducing measurement errors. Using the mathematical methods validated, these responses are modelled and studied, showing responses to Gaussian and sinusoidal inputs, variability across individuals and effects of neuromodulators. With the tarsal reflex described and modelled, it can be used as a tool for further research in disciplines such as medicine, in the diagnose and treatment of euromuscular dysfunction or design of prosthesis and orthoses. This model can also be implemented in robotics to aid in stability when walking on irregular terrain.
CIRCULAR TARGET OBSERVATION OF POINT CLOUD USING LASER REFLECTION INTENSITY BY AN UNMANNED AERIAL VEHICLE EQUIPPED WITH A LASER SCANNER

Abstract. Unmanned aerial vehicles (UAVs) equipped with laser scanners have been widely used for various purposes, such as in construction sites, forestry, and disaster management, as they can obtain high density point clouds with millimeter to centimeter scale accuracy. However, systematic errors in the height of a UAV relative to the earth's surface may occur owing to the method of direct georeferencing using the global navigation system satellite (GNSS) and inertial measurement unit (IMU). Therefore, to enable highly accurate surveying, adjustments must be made using ground control points. However, interpreting the ground control points of a discrete, inhomogeneous density point cloud requires a high degree of skill and effort. In this study, a high-end UAV laser scanner was used to obtain the point clouds of a site using a white circular target enclosed within a black frame in a measurement setup of 500 points/m2. The center coordinates of the circle, calculated using the conventional and proposed methods, were evaluated qualitatively and quantitatively. As a result, the average of 10 error distances was found to be 0.028 m for the weighted center of gravity method, 0.014 m for the fitting circle equation method, and 0.008 m for the proposed method. These results corresponded to one-fifth to one-half of the 0.045-m point intervals of the measurement plan. Thus, using the reflection intensity of point clouds, the circular target observation could be performed.
Max-min threshold-based cancelable biometric templates for low-end devices

Abstract. Biometrics are widely used in security systems, but it has drawbacks such as its nonreusability, being susceptible to getting stolen, and being prone to unauthorized access. These issues can be tackled using cancelable biometrics. In this work, features extracted using Log-Gabor filters are processed according to the proposed max-min thresholding. The resulting binary features are transformed by random projection on a key matrix to create a cancelable template. The method was carefully evaluated using publicly accessible datasets of face near-infrared, palm print, palm vein, dorsal vein, wrist vein, and knuckle print. A significant improvement in performance over many recent methods was observed. Also, the effectiveness of the generated cancelable templates was observed in the general, stolen token, and changeable scenarios. The generated template is 25% of the original input size, which makes it efficient for low-end devices.
Realizing Fee-Free Higher Education in South Africa; Dreams and Nightmares

The component of free rudimentary education is guaranteed and recognized by the 1996 Constitution, the African National Congress (ANC) Freedom Charter as well as other international instruments such as the Universal Declaration of Human Rights (UDHR) and the International Covenant on Economic, Social and Cultural Rights (ICESCR). Conversely that there exists no component of free higher education in South African laws and statutory guidelines, let alone in the international arena advocating for free higher education. Notwithstanding this fact, reality has shown that free higher education has not been realized despite students’ petition which fact has instigated them to take part in severe dissents from the four walls of South Africa. This paper argues that free higher education is not realizable the South African government has limited resources and the economy is on its knees. The paper further argues that for the South African government to fund free higher education it needs a well-resourced economy which is the contrary in South Africa.