Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining varying training data-based artificial intelligence models for energy price forecasting

ABSTRACT In this work, the price-forecasting accuracy of an ensemble of seasonal auto-regressive integrated moving average (SARIMA), multiple linear regression (MLR), feed-forward neural network (FFNN), and radial basis function (RBF) network models has been assessed in a single series modeling framework. The methodology involved training the individual models using past data windows of varying sizes and making the forecast for the next five days on a daily rolling basis. The hourly spot price data of the Iberian Electricity Market (MIBEL) is selected as the test case system. All the models have been tested on high and low-volatile data sets to assess their forecasting abilities. The forecast performance has also been assessed by participating in a real-time forecasting competition and comparing it with the earlier models proposed in the literature. The results show that the ensemble model is effective in producing better forecasts. But its forecast accuracy is greatly affected by the size of the training window and the combination of various models. The ensemble of the FFNN and RBF network models performs best when conditions are volatile. Moreover, during volatile periods it is better to use a small window size for training as compared to a large window size.
Optimal single‐electron feedback control

In a closed‐loop controlled single‐electron transistor (SET) the optimal feedback response is investigated, leading to a maximum suppression of shot‐noise. Using a coupled quantum point contact (QPC) charge detector, the tunneling process is monitored in real‐time and the fluctuations are fed back periodically to the tunneling barriers of the SET. The feedback response is applied proportional to the deviation from the target number of average transferred electrons. This leads to a strong suppression and temporal saturation of the cumulants of the full counting statistics. For the optimal feedback response, the saturation value of second cumulant is found to be given by target number. Astonishingly, the feedback works robust even for target numbers much smaller than one.
Corrigendum: Monte Carlo simulated corrections for beam commissioning measurements with circular and MLC shaped fields on the CyberKnife M6 system: a study including diode, microchamber, point scintillator, and synthetic microdiamond detectors (2017 Phys. Med. Biol. 62 1076)

Monte Carlo simulation was used to calculate correction factors for output factor (OF), percentage depth-dose (PDD), and off-axis ratio (OAR) measurements with the CyberKnife M6 System. These include the first such data for the InCise MLC. Simulated detectors include diodes, air-filled microchambers, a synthetic microdiamond detector, and point scintillator. Individual perturbation factors were also evaluated. OF corrections show similar trends to previous studies. With a 5 mm fixed collimator the diode correction to convert a measured OF to the corresponding point dose ratio P Francecon et al Printed in the UK 1076 PHMBA7 © 2017 Institute of Physics and Engineering in Medicine 62 Phys. Med. Biol.
Prevalencia de Giardia lamblia por ecorregiones en preescolares y escolares peruanos: Propuesta de estratificación de riesgo

Introducción. La giardiasis es ocasionada por el protozoario intestinal Giardia lamblia, su transmisión tiene variabilidad geográfica y a pesar de ser muy frecuente, no existe una herramienta de estratificación de riesgo para priorizar las intervenciones. Objetivo. Estimar la prevalencia de G. Lamblia en preescolares y escolares peruanos por ecorregiones entre 1990 a 2018. Métodos. A partir de un metaanálisis previo, se realizó un subanálisis por ecorregiones de la prevalencia de G. lamblia en 26 estudios en preescolares y escolares peruanos entre 1990 a 2018. Se extrajeron los datos por distrito y utilizando Google Earth fueron clasificados en ecorregiones. La heterogeneidad fue analizada mediante la prueba de Q de Cochrane y el sesgo de publicación mediante el método de Egger con StatsDirect versión 3.2. 7. Se utilizó el método de riesgo absoluto para estratificar la prevalencia a nivel de distrito y se definió 4 estratos en base a los percentiles o arbitrariamente. Resultados. Se identificaron 43 datos de prevalencia a nivel de distrito que incluyeron 7606 participantes. Las prevalencias combinadas más altas por el método de efectos aleatorios de G. lamblia fueron de 47,0% (intervalo de confianza (IC) 95%: 40,0 -54,0) en el desierto del Pacífico; 27,9% (IC95%: 22,8 - 33,2) en selva baja y 26,9% (IC95%: 22,5 - 31,5) en la Puna. Conclusiones. De cada 100 preescolares y escolares que viven en las ecorregiones del desierto del Pacífico, selva baja y Puna, 47, 28 y 27 menores de edad, respectivamente, están infectados con G. lamblia. Asimismo, se propone 4 estratos de riesgo en función de la prevalencia: esporádico (0 a <1%), hipoendémico (1 a <25%), mesoendémico (≥25 a <50%) e hiperendémico (≥50%).
Rising dynamics and lift effect in dense segregating granular flows

In order to explore the rising dynamics and the existence of a lift effect in dense segregating granular flows, we perform two-dimensional discrete numerical simulations in the case of single free intruders and bi-disperse granular mixtures. In both configurations, we do not observe a measurable lift force acting on the larger grains. The large force fluctuations acting on the bigger grains reduce to the weight of the latter, following the mere action-reaction principle. This suggests that the rising dynamics is driven by the force fluctuations, coupled with the properties of the surrounding granular bed itself. We propose the strong asymmetry displayed by granular bed resistance to downward (plunging) and upward (withdrawing) motion, as reported in detail by Hill et al. [“Scaling vertical drag forces in granular media,” Europhys. Lett. 72(1), 137–143 (2005)], as a key ingredient for segregation. Accordingly, moving an object toward the free surface is about 10 times easier than moving an object toward the rigid bottom. This asymmetry allows for an effective upward motion when large grains are submitted to upward force fluctuations, without being counterweighted by sinking episodes when large grains are submitted to downward force fluctuations. In addition to gravity, the existence of two different boundary conditions formed by the free surface and the rigid bottom explains this difference of resistance to motion. In this respect, the mechanism allowing size segregation in dense granular flows would be the same as that allowing legged locomotion in sand [Li et al., “A terradynamics of legged locomotion on granular media,” Science 339, 1408–1412 (2013)]. In order to explore the rising dynamics and the existence of a lift effect in dense segregating granular flows, we perform two-dimensional discrete numerical simulations in the case of single free intruders and bi-disperse granular mixtures. In both configurations, we do not observe a measurable lift force acting on the larger grains. The large force fluctuations acting on the bigger grains reduce to the weight of the latter, following the mere action-reaction principle. This suggests that the rising dynamics is driven by the force fluctuations, coupled with the properties of the surrounding granular bed itself. We propose the strong asymmetry displayed by granular bed resistance to downward (plunging) and upward (withdrawing) motion, as reported in detail by Hill et al. [“Scaling vertical drag forces in granular media,” Europhys. Lett. 72(1), 137–143 (2005)], as a key ingredient for segregation. Accordingly, moving an object toward the free surface is about 10 times easier than moving an object toward th.
Leg-Length and Alignment Changes in Children and Adolescents After Transphyseal Anterior Cruciate Ligament Reconstruction With Soft Tissue Graft: Results at 1-Year Follow-up

Background: Growth disturbance to leg length or coronal plane alignment are important considerations in pediatric anterior cruciate ligament (ACL) reconstruction (ACLR). Purpose/Hypothesis: The purpose of this study was to investigate the lower limb alignment and leg length of pediatric patients preoperatively and at approximately 1 year after transphyseal ACLR. Our hypothesis was that there would be no significant change in leg-length discrepancy (LLD) or operated-side alignment at follow-up. Study Design: Case series; Level of evidence, 4. Methods: Data were extracted from the prospective Queensland Children’s Hospital Pediatric ACL Injury Registry. Long-leg alignment radiographs were captured preoperatively and at an approximately 12-month postoperative follow-up. Radiographic measures included leg length, LLD (injured minus uninjured leg length), mechanical axis deviation (MAD), mechanical and anatomical lateral distal femoral angle (mLDFA and aLDFA, respectively), and medial proximal tibial angle. We evaluated the effect of time (annual vs baseline) on imaging measurements with analysis of covariance, using the covariates of age, sex, and body mass index. Results: Data were available for 104 patients, of whom 34 (33%) had >12 months of skeletal growth remaining based on skeletal age. At an average follow-up time of 14.5 months after ACLR, there were no significant differences in mean lower limb alignment or longitudinal growth compared with baseline. However, seven patients demonstrated clinically significant changes to their mechanical axis or LLD (>10 mm change). A subgroup analysis of patients with >12 months of growth remaining (n = 34) demonstrated no statistically significant changes in mean alignment or LLD. Before surgery, LLD was -1.39 mm and the injured limb was in significantly more valgus compared with the uninjured lower limb (mean difference: MAD, 4.79 mm [95% CI, 2.64 to 6.94 mm]; mLDFA, -0.93° [95% CI, -1.29° to -0.57°], and aLDFA, -0.91° [95% CI, -1.31° to -0.50°]). Conclusion: After ACLR, there were no statistically significant changes in mean alignment or longitudinal growth; however, 7 out of 104 patients (6.7%) demonstrated clinically significant changes in alignment or LLD. Preoperatively, the injured limb was statistically significantly in more valgus compared with the uninjured limb with lateralized MAD.
REWRITING THE TROPICAL RECORD BOOKS The Extraordinary Intensification of Hurricane Patricia (2015)

AbstractHurricane Patricia was a historic tropical cyclone that broke many records, such as intensification rate, peak intensity, and overwater weakening rate, during its brief 4-day lifetime in late October 2015 in the eastern Pacific basin. Patricia confounded all of the intensity forecast guidance owing to its rapid intensity changes. Fortunately, the hurricane-penetrating National Oceanic and Atmospheric Administration WP-3D and U.S. Air Force C-130 aircraft and the National Aeronautics and Space Administration WB-57 high-altitude jet, under support of the Office of Naval Research, conducted missions through and over Patricia prior to and during its extreme intensity changes on all 4 days, while an extensive array of pressure sensors sampled Patricia after landfall. The observations collected from these missions include traditional data sources such as airborne Doppler radar and flight-level instruments as well as new data sources like a high-density array of dropsondes released from high-altitude and.
An Application of Fibonacci Sequence on Continued Fractions

Let F0 = 0; F1 = 1; F2 = 1;::: be the Fibonacci sequence. Fix k2 N: We prove that for almost every x2 (0;1), the pattern 1;1;:::;1 (k-digits) appears in the continued fraction expansion x = [a1;a2;:::]
Process Management and One Example Service Sector

The application study has been done in a private bank ABC bank in the form of case study. The observational method and interview method have been used about two types of branch office. A case study will be done about existing branch offices in one of these two branch office types and in the other one about improvement branch office. The information about ABC bank credit operation system has been collected and credit operation process has been explained as systemic in the light of this collected information. The workflow diagrams have been composed by analysing processes. The workflow diagrams have been composed in accordance with credit operation process. The graphics has been drawing in concerned with credit performance of improved branch offices for the purpose of performance review to improvement process. These graphics have been drawing about comparing between cancellations statement and putting into operation of credits that made application covering three months period. Finally, some offers have been presented about pilot branch offices in which improved by bank be subjected to this study.
Comparison between empirical and variational mode decomposition based on percentage variation in entropy feature from glaucoma image

Glaucoma is a type of eye disease; it damages the optic nerve due to gradual increase in the fluid pressure and hence causes blindness. In the paper two decomposition techniques, namely, bi-dimensional empirical mode decomposition (BDEMD) and two dimensional variational mode decomposition (2DvMD) are used and compared to find the better decomposition technique. Images are decomposed by these methods and entropy features are extracted from decomposed sub band images. The percentage variations in entropy features have been calculated from the extracted features for each decomposition technique for normal and glaucoma image. These calculated percentage variations in entropy features are used to compare the two decomposition techniques for normal and glaucoma images. The results obtained put forward that the percentage variation in entropy feature extracted from 2DvMD are higher than BDEMD. Hence, 2DvMD outperforms over BDEMD.
Hippocampal volume in cases of relapsing remitting multiple sclerosis and its correlation with cognitive impairment

Background. Multiple sclerosis (MS) is a chronic inflammatory immune-mediated disease, distinguished by demyelination and oligodendropathy in the central nervous system. Cognitive impairment (CI) can impact patients at any stage of MS, including those with clinically isolated syndrome (CIS). Patients and methods. This is a prospective cross-sectional study which enrolled 60 patients with RRMS. They were subjected to cognitive scale assessment, routine brain MRI study and volumetric assessment of hippocampus. Results. This study found a significant positive correlation between duration of disease and Subjective memory complaints questionnaire (r=0.525, p=0.001). A significant negative correlation existed between disease duration and MMSE score (r=-0.404, p=0.001) and between disease duration and MoCA score (r=-0.310, p=0.016). No significant difference between both groups regarding the relative hippocampal volume. Mean relative right hippocampal volume is 0.0026 for cases versus 0.0027 among control group and mean relative left hippocampal volume is 0.0025 for cases versus 0.0026 among control group. Conclusion. Multiple sclerosis disease duration had an impact on cognitive state. However, hippocampal volume assessment did not predict the cognitive affection in patient with RRMS.
Stretching of a Polymer Below the Θ Point

The unfolding of a polymer below the θ point when pulled by an external force is studied both in d = 2 on the lattice and in d = 3 off lattice. A ground state analysis of finite length chains shows that the globule unfolds via multiple steps, corresponding to transitions between different minima, in both cases. In the infinite length limit, these intermediate minima have a qualitative effect only in d = 2. The phase diagram in d = 2 is determined using transfer matrix techniques. Energy‐entropy and renormalization group arguments are given which predict a qualitatively correct phase diagram and a change of the order of the transition from d = 2 to d = 3.
Prognostic-related genes for pancreatic cancer typing and immunotherapy response prediction based on single-cell sequencing data and bulk sequencing data

Background Pancreatic cancer is associated with high mortality and is one of the most aggressive of malignancies, but studies have not fully evaluated its molecular subtypes, prognosis and response to immunotherapy of different subtypes. The purpose of this study was to explore the molecular subtypes and the key genes associated with the prognosis of pancreas cancer patients and study the clinical phenotype, prognosis and response to immunotherapy using single-cell seq data and bulk RNA seq data, and data retrieved from GEO and TCGA databases. Methods Single-cell seq data and bioinformatics methods were used in this study. Pancreatic cancer data were retrieved from GEO and TCGA databases, the molecular subtypes of pancreatic cancer were determined using the six cGAS-STING related pathways, and the clinical phenotype, mutation, immunological characteristics and pathways related to pancreatic cancer were evaluated. Results Pancreatic cancer was classified into 3 molecular subtypes, and survival analysis revealed that patients in Cluster3 (C3) had the worst prognosis, whereas Cluster1 (C1) had the best prognosis. The clinical phenotype and gene mutation were statistically different among the three molecular subtypes. Analysis of immunotherapy response revealed that most immune checkpoint genes were differentially expressed in the three subtypes. A lower risk of immune escape was observed in Cluster1 (C1), indicating higher sensitivity to immunotherapeutic drugs and subjects in this Cluster are more likely to benefit from immunotherapy. The pathways related to pancreatic cancer were differentially enriched among the three subtypes. Five genes, namely SFRP1, GIPR, EMP1, COL17A and CXCL11 were selected to construct a prognostic signature. Conclusions Single-cell seq data were to classify pancreatic cancer into three molecular subtypes based on differences in clinical phenotype, mutation, immune characteristics and differentially enriched pathways. Five prognosis-related genes were identified for prediction of survival of pancreatic cancer patients and to evaluate the efficacy of immunotherapy in various subtypes.
On contraction of nonlinear difference equations with time‐varying delays

General nonlinear difference equations with time‐varying delays are considered. Explicit criteria for contraction of such equations are presented. Then some simple sufficient conditions for global exponential stability of equilibria and for stability of invariant sets are derived. Furthermore, explicit criteria for existence, uniqueness and global exponential stability of periodic solutions are derived. Finally, the obtained results are applied to time‐varying discrete‐time neural networks with delay.
Pose and Illumination Invariance of Attribute Detectors in Person Re-identification

The use of attributes in person re-identification and video surveillance applications has grabbed attentions of many researchers in recent times. Attributes are suitable tools for mid-level representation of a part or a region in an image as it is more similar to human perception as compared to the quantitative nature of the normal visual features description of those parts. Hence, in this paper, the preliminary experimental results to evaluate the robustness of attribute detectors against pose and light variations in contrast to the use of local appearance features is discussed. Results attained proven that the attribute-based detectors are capable to overcome the negative impact of pose and light variation towards person re-identification activities. In addition, the degree of importance of different attributes in re-identification is evaluated and compared with other previous works in this field.
Off-Grid Error Calibration for DOA Estimation Based on Sparse Bayesian Learning

Compared with the traditional subspace-based methods, sparse signal recovery (SSR) based methods have obvious advantages in performing the direction of arrival (DOA) estimation of an array, such as working well on the limited number of snapshots, good noise robustness, and so on. However, the occurrence of grid mismatch limits the estimation accuracy of these methods. To solve the problem that the grid mismatch impacts DOA estimation accuracy, this article presents a new method for off-grid DOA estimation using weighted Sinc interpolation, referred to as OGWSISBL. Specifically, the off-grid error is represented as the parameter to be estimated in the observation model. Then, under the sparse Bayes learning (SBL) framework, the off-grid error is calculated using the variational Bayesian expectation maximization (VBEM) method and eliminated by updating the grids with weighted Sinc interpolation. The proposed method can work well in both single and multiple snapshots. Simulation and actual measurement results illustrate that the proposed method is superior to the state-of-the-art methods reported.
Orthogonal polynomial interpretation of Δ-Toda equations

In this paper a discretization of Toda equations is analyzed. The correspondence between these Δ-Toda equations for the coefficients of the Jacobi operator and its resolvent function is established. It is shown that the spectral measure of these operators evolve in t like ( 1 + x ) 1 − t d &mgr; ( x ) ? > where d &mgr; ? > is a given positive Borel measure. The Lax pair for the Δ-Toda equations is derived and characterized in terms of linear functionals, where orthogonal polynomials which satisfy an Appell condition with respect to the forward difference operator Δ appear in a natural way. In order to illustrate the results of the paper we work out two examples of Δ-Toda equations related with Jacobi and Laguerre orthogonal polynomials.
Toe Gangrene as the First Presenting Symptom of Essential Thrombocythemia: A Case Report

Essential thrombocythemia is a myeloproliferative neoplasm. Thrombosis and bleeding complications are common with myeloproliferative neoplasms, particularly essential thrombocythemia and polycythemia vera. Here, we report the case of a 52-year-old female who presented initially with painful toe swelling and discoloration. Initial imaging showed a small abscess. An incision and drainage, and debridement of toe dry gangrene were performed twice in two months with no improvement in her complaint and worsening discoloration, ending in a toe amputation. Two years later, the patient was referred to a hematology clinic for a high platelet count. On review of her medical records, the patient had the same numbers during the initial presentation. The patient’s condition was diagnosed retrogradely by a hematologist as essential thrombocythemia. This case sheds light on myeloproliferative neoplasm as a differential diagnosis in patients with atypical thrombosis. Thinking in such a way could have diagnosed our patient two years earlier.
Some Properties of Hessenberg Matrices with Conditional Elements

Hessenberg matrices are a class of structured matrices that play a fundamental role in various areas of mathematics and scientific computing. These matrices have diverse applications in numerical analysis, optimization, graph theory, and quantum mechanics, among others. This paper provides the determinants of the conditional Hessenberg matrices whose elements are the generalized bi-periodic Fibonacci numbers. Moreover, we find the inverse of some special type matrices which help us to find the determinant of the conditional Hessenberg matrices.