Miracle-dz/UniFAR-FTUs huggingface dataset:
A Scenario-Based Model Comparison for Short-Term Day-Ahead Electricity Prices in Times of Economic and Political Tension

In recent years, energy prices have become increasingly volatile, making it more challenging to predict them accurately. This uncertain market trend behavior makes it harder for market participants, e.g., power plant dispatchers, to make reliable decisions. Machine learning (ML) has recently emerged as a powerful artificial intelligence (AI) technique to get reliable predictions in particularly volatile and unforeseeable situations. This development makes ML models an attractive complement to other approaches that require more extensive human modeling effort and assumptions about market mechanisms. This study investigates the application of machine and deep learning approaches to predict day-ahead electricity prices for a 7-day horizon on the German spot market to give power plants enough time to ramp up or down. A qualitative and quantitative analysis is conducted, assessing model performance concerning the forecast horizon and their robustness depending on the selected hyperparameters. For evaluation purposes, three test scenarios with different characteristics are manually chosen. Various models are trained, optimized, and compared with each other using common performance metrics. This study shows that deep learning models outperform tree-based and statistical models despite or because of the volatile energy prices.
Optical hyperparametric oscillations in a whispering-gallery-mode resonator: Threshold and phase diffusion

We present a theoretical analysis of optical parametric oscillations through four-wave mixing in a nonlinear high-Q whispering-gallery-mode resonator. It is shown that even a small flux of pump photons is sufficient to reach the threshold of the oscillations. We demonstrate that due to narrow bandwidth of the resonator modes as well as the high efficiency of the resonant frequency conversion the oscillator produces a stable narrow-band beat note of the pump, signal, and idler waves making an all-optical secondary frequency reference feasible.
CORRELATION BETWEEN THE 22-YEAR SOLAR MAGNETIC CYCLE AND THE 22-YEAR QUASICYCLE IN THE EARTH'S ATMOSPHERIC TEMPERATURE

According to the variation pattern of the solar magnetic field polarity and its relation to the relative sunspot number, we established the time series of the sunspot magnetic field polarity index and analyzed the strength and polarity cycle characteristics of the solar magnetic field. The analysis showed the existence of a cycle with about a 22-year periodicity in the strength and polarity of the solar magnetic field, which proved the Hale proposition that the 11-year sunspot cycle is one-half of the 22-year solar magnetic cycle. By analyzing the atmospheric temperature field, we found that the troposphere and the stratosphere in the middle latitude of both the northern and southern hemispheres exhibited a common 22-year quasicycle in the atmospheric temperature, which is believed to be attributable to the 22-year solar magnetic cycle.
Comprehensive microsurgical anatomy of the middle cranial fossa: Part II—neurovascular anatomy

In order to master the surgical approaches to the middle cranial fossa, the surgeon needs to understand the relevant bony anatomy. However, she/he also needs to have a clear and sound understanding of the neural and vascular anatomy because, oftentimes, the osseous anatomy (except for the optic apparatus) should be removed to expose and protect the neurovascular anatomy. This is the second of a two-part article discussing the neurovascular anatomy of the middle cranial fossa. A brief discussion of the surgical approaches follows.
Variable Selection in Proteomic Profile Classification by Interval Support Vector Machines (iSVM)

For variable selection in proteomic profile classification, we present a new local modeling procedure called interval support vector machine (iSVM). This procedure builds a series of SVM models in a window that moves over the whole spectral region and then locates useful spectral intervals in terms of the least complexity of SVM models reaching a desired error level. We applied iSVM in variable selection for proteomic profile classification. The results show that the proposed procedure are very promising for classification target-based variable selection and obtain much better classification than full-spectrum SVM model.
Advances and potential of omics studies for understanding the development of food allergy

The prevalence of food allergy continues to rise globally, carrying with it substantial safety, economic, and emotional burdens. Although preventative strategies do exist, the heterogeneity of allergy trajectories and clinical phenotypes has made it difficult to identify patients who would benefit from these strategies. Therefore, further studies investigating the molecular mechanisms that differentiate these trajectories are needed. Large-scale omics studies have identified key insights into the molecular mechanisms for many different diseases, however the application of these technologies to uncover the drivers of food allergy development is in its infancy. Here we review the use of omics approaches in food allergy and highlight key gaps in knowledge for applying these technologies for the characterization of food allergy development.
Far-infrared spectroscopy of galaxies - The 158 micron C(+) line and the energy balance of molecular clouds

Observations of the 158 microns fine-structure line of C(+) toward the nuclei of six gas-rich galaxies are presented. The observations are compared with observations of the CO J = 1-0 and H I 21 cm lines, observations of far-IR continuum emission, and observations of forbidden C II emission with the Galaxy. The forbidden C II line comes from dense, warm gas in UV-illuminated photodissociation regions at the surfaces of molecular clouds. This line is probably optically thin in all but the brightest of galactic sources. The variation of forbidden C II brightness from source to source and its ratio to the integrated infrared continuum intensity agree well with the theoretical prediction that UV absorption by dust controls the C(+) column density. The forbidden C II line is a tracer of molecular clouds, especially those near intense sources of UV radiation.
Typical properties of periodic Teichmueller geodesics

Call a property for periodic orbits of the Teichmueller flow acting on the moduli space Q of area one abelian differentials on a surface of genus g typical if the growth rate of orbits with this property is maximal. We show that the following property is typical. The eigenvalues of the symplectic matrix defined by the orbit are arbitrarily close to the Lyapunov exponents of Q, its trace field is a totally real splitting field of degree g over Q. If g>2 then periodic orbits whose SL(2,R)-orbit closure equals Q are typical. We show that for every $l\geq 2$, there are finitely many affine invariant manifolds in Q of rank l which contain all affine invariant manifolds in Q of rank l, and we establish finiteness of algebraically primitive Teichmueller curves.
Design and Implementation of Hybrid DC-DC Converter: A Review

The advancement in Power Management Integrated Circuit (PMIC) has driven the dc-dc conversion technology into a System-on-Chip (SoC) solutions, leveraging CMOS technology scaling from 180nm to 22nm and on-chip passive element integration. Concurrently, as the applications demand smaller form factor solution towards device portability with optimized power qualities, switched-capacitor-inductor hybrid architectures with fully-integrated passives have become a popular choice for a compact and high efficiency converter solution, in contrast to bulky and discrete component based alternatives. This article reviews the latest advancements in hybrid dc-dc topologies, specifically for low-power applications to address the downsides such as charge sharing loss, high current ripple, limited conversion ratio, low-power density, and efficiency. An overview of capacitor and inductor technology is discussed in terms of on-chip parasitic losses, and miniaturization. A comprehensive comparison in the state-of-the-art hybrid dc-dc converter work is tabulated with power density and efficiency as the primary performance metrics, highlighting their operability in low-power applications. Moreover, a discussion is included with quantified benchmarks to justify the viability of converters, along with the future recommendation of realizing ultra-high switching frequency for smaller footprint inductor and design approach to resolve the current tradeoff bottlenecks.
Functional Neuroplasticity of Adults with Partial or Complete Denture Rehabilitation with or without Implants: Evidence from fMRI Studies

Tooth loss may affect food ingestion and, consequently, nutrition intake. The neuroimaging literature using functional magnetic resonance imaging (fMRI) was reviewed to summarize the changes in brain functions in response to denture rehabilitation in patients with partial or complete edentulous dentition. Overall, this review covered nine fMRI studies on denture rehabilitation. Eight recruited complete edentulous patients, whereas one recruited partially edentulous patients. The risk-of-bias assessment revealed concerns regarding all nine studies. Due to the heterogeneity of the studies and the lack of brain coordinates reported, a meta-analysis could not be conducted, and this review could only summarize the findings without statistical validation. The evidence from jaw-clenching studies suggested that implant-supported fixed dentures could be the best option, as compared to implant-supported overdentures and complete dentures, as it was associated with higher brain activity levels in various brain regions, including those corresponding to the primary sensory (postcentral gyrus) and motor cortices (precentral gyrus). Gum-chewing studies indicated that perhaps the medial and middle frontal gyri were associated with food comminuting and food mixing, which could be improved by the full replacement of the dental arch, instead of only partial replacement. All the fMRI studies described the functional neuroplasticity of the patients undergoing denture rehabilitation and suggested that certain rehabilitation options were more beneficial in restoring masticatory functions, as well as their associated brain activity levels.
Hypoelliptic and Gevrey hypoelliptic invariant differential operators on certain symmetric spaces

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Therapeutic potential of a novel peripherally restricted CB1R inverse agonist on the progression of diabetic nephropathy

Objective This study assessed the efficacy of INV-202, a novel peripherally restricted cannabinoid type-1 receptor (CB1R) inverse agonist, in a streptozotocin-induced type-1 diabetes nephropathy mouse model. Methods Diabetes was induced in 8-week-old C57BL6/J male mice via intraperitoneal injection of streptozotocin (45 mg/kg/day for 5 days); nondiabetic controls received citrate buffer. Diabetic mice were randomized to 3 groups based on blood glucose, polyuria, and albuminuria, and administered daily oral doses for 28-days of INV-202 at 0.3 or 3 mg/kg or vehicle. Results INV-202 did not affect body weight but decreased kidney weight compared with the vehicle group. While polyuria was unaffected by INV-202 treatment, urinary urea (control 30.77 ± 14.93; vehicle 189.81 ± 31.49; INV-202 (0.3 mg/kg) 127.76 ± 20; INV-202 (3 mg/kg) 93.70 ± 24.97 mg/24h) and albumin (control 3.06 ± 0.38; vehicle 850.08 ± 170.50; INV-202 (0.3 mg/kg) 290.65 ± 88.70; INV-202 (3 mg/kg) 111.29 ± 33.47 µg/24h) excretion both decreased compared with vehicle-treated diabetic mice. Compared with the vehicle group, there was a significant improvement in the urinary albumin to creatinine ratio across INV-202 groups. Regardless of the dose, INV-202 significantly reduced angiotensin II excretion in diabetic mice. The treatment also decreased Agtr1a renal expression in a dose-dependent manner. Compared with nondiabetic controls, the glomerular filtration rate was increased in the vehicle group and significantly decreased by INV-202 at 3 mg/kg. While the vehicle group showed a significant loss in the mean number of podocytes per glomerulus, INV-202 treatment limited podocyte loss in a dose-dependent manner. Moreover, in both INV-202 groups, expression of genes coding for podocyte structural proteins nephrin (Nphs1), podocin (Nphs2), and podocalyxin (Pdxl) were restored to levels similar to nondiabetic controls. INV-202 partially limited the proximal tubular epithelial cell (PTEC) hyperplasia and normalized genetic markers for PTEC lesions. INV-202 also reduced expression of genes contributing to oxidative stress (Nox2, Nox4, and P47phox) and inflammation (Tnf). In addition, diabetes-induced renal fibrosis was significantly reduced by INV-202. Conclusions INV-202 reduced glomerular injury, preserved podocyte structure and function, reduced injury to PTECs, and ultimately reduced renal fibrosis in a streptozotocin-induced diabetic nephropathy mouse model. These results suggest that INV-202 may represent a new therapeutic option in the treatment of diabetic kidney disease.
The Interplay between Integrins and Immune Cells as a Regulator in Cancer Immunology

Integrins are a group of heterodimers consisting of α and β subunits that mediate a variety of physiological activities of immune cells, including cell migration, adhesion, proliferation, survival, and immunotolerance. Multiple types of integrins act differently on the same immune cells, while the same integrin may exert various effects on different immune cells. In the development of cancer, integrins are involved in the regulation of cancer cell proliferation, invasion, migration, and angiogenesis; conversely, integrins promote immune cell aggregation to mediate the elimination of tumors. The important roles of integrins in cancer progression have provided valuable clues for the diagnosis and targeted treatment of cancer. Furthermore, many integrin inhibitors have been investigated in clinical trials to explore effective regimens and reduce side effects. Due to the complexity of the mechanism of integrin-mediated cancer progression, challenges remain in the research and development of cancer immunotherapies (CITs). This review enumerates the effects of integrins on four types of immune cells and the potential mechanisms involved in the progression of cancer, which will provide ideas for more optimal CIT in the future.
Editorial: Genetic approaches for crop yield enhancement

mechanisms of chemical macronutrients such as nitrogen, phosphorus and sulfur on crop yield and quality. Liu et al. investigated applications of sulfur, 0 kg·ha − 1 versus 60 kg·ha − 1 , at three seed development stages of bread wheat ( Triticum aestivum ) and conducted transcriptomic and metabolomic comparisons. Their results showed that some MYB transcription factors (TFs) may play important roles in the process of sulfur metabolism. This provides excellent sources for identifying the key transcriptional regulators related to sulfur metabolism for wheat seed development and yield improvement.
Conduction system pacing in pediatric and congenital heart disease

Conduction system pacing (CSP) has evolved rapidly to become the pacing method of choice for many adults with structurally normal hearts. Studies in this population have repeatedly demonstrated superior hemodynamics and outcomes compared to conventional pacing with the recruitment of the native conduction system. Children and patients with congenital heart disease (CHD) are also likely to benefit from CSP but were excluded from original trials. However, very recent studies have begun to demonstrate the feasibility and efficacy of CSP in these patients, with growing evidence that some outcomes may be superior in comparison to conventional pacing techniques. Concerns regarding the technical challenges and long-term lead parameters of His Bundle Pacing (HBP) have been overcome to many extents with the development of Left Bundle Branch Area Pacing (LBBAP), and both techniques are likely to play an important role in pediatric and CHD pacing in the future. This review aims to assimilate the latest developments in CSP and its application in children and CHD patients.
Whole Sun Month at solar minimum: An introduction

The Whole Sun Month was a collaborative project of the IACG Campaign 4 and the SOHO Joint Observing Programs to characterize and model the structure of the global corona during solar minimum conditions. This introduction provides a brief description of the campaign objectives, the missions, and observatories involved and highlights some of the scientific results reported elsewhere in this special section.
Nonlinear mixing of surface acoustic waves propagating in opposite directions

The parametric mixing of two modulated surface acoustic waves propagating in opposite directions is studied with reference to nonlinear signal processing applications by the coupled mode theory of nonlinear surface waves. In the case of propagation in opposite directions the combination frequency waves generated out of the nonlinear interaction of the two primary waves and their harmonics with one another do not satisfy the phase‐matching condition. Hence there exists no mode coupling between the primary waves. At the same time the amplitude of each combination frequency wave is proportional to the product of a harmonic amplitude of one of the interacting waves with a harmonic amplitude of the other wave. The variation of these harmonic amplitudes as functions of the slow scale variables are governed by two sets of coupled amplitude equations, each set pertaining to one primary wave and its harmonics. It is further shown that, in addition to surface wave modes, there also exist bulk wave modes in a certai.
Context-based biometric key generation for Iris

In this study, a generic treatment of how to generate biometric keys from binary biometric templates is presented. A context-based analysis of iris biometric feature vectors based on which stable biometric keys are extracted is proposed. Most reliable bits in binary iris codes are detected and utilised to construct keys from fuzzy biometric data. The proposed key-generation scheme is adapted to diverse iris biometric feature extraction algorithms, evaluated on a comprehensive database and compared against existing iris biometric cryptosystems. In addition, the scheme is extended to provide fully revocable biometric keys, long enough to be applied in generic cryptosystems. Experimental results confirm the soundness of the approach.
Deep RNN Based Prediction of Driver’s Intended Movements at Intersection Using Cooperative Awareness Messages

This paper presents an early prediction framework to classify drivers’ intended intersection movements in a connected vehicle environment. Intersections are considered accident blackspots with major traffic violations that cause property damage, injuries and fatalities. An accurate perception of drivers’ intended movements at intersections is required for advanced red-light (ARLW) or turning warnings for vulnerable road users (TWVR). Early prediction of intersection movement and adequate warning assistance will ensure road users’ safety at the intersection. In this study, we adopted recurrent neural networks (RNN): long short-term memory (LSTM) and gated recurrent units (GRU) networks to predict driver intended movements at intersections using the vehicle kinematics extracted from the Cooperative Awareness Messages (CAMs). We used naturalistic driving data of the Ipswich Connected Vehicle Pilot (ICVP) project, Queensland, which was collected from 351 participants who drove their connected vehicles during the pilot period. The pilot study installed roadside equipment at 29 signalised intersections to enable the Cooperative Intelligent Transportation System (C-ITS) use cases. Vehicle speed, speed limit, longitudinal acceleration, lateral acceleration, and yaw rate are used as predictors and monitored in 100-millisecond intervals for 1s to 4s at different warning distances from the stop line. Separate prediction models are trained based on different monitoring windows. Furthermore, drivers’ intended intersection movements are predicted at two individual intersections to evaluate intersection-specific prediction performance and are found with improved prediction accuracy than overall prediction models trained with all 29 intersections data. Overall prediction models are useful for some intersections which lack available data for individual intersection-based prediction.
NONHSAT021545/miR-330-3p/EREG: A Cooperative Axis in Breast Cancer Prognosis and Treatment

Lymphatic metastasis is the most common form in breast cancer (BC) progression. Previously, we observed that lnc045874, a most conservative homology of Homo Sapiens NONHSAT021545 (lnc021545), miR-330-3p, and EREG may have some effects in mouse hepatocarcinoma cell lines with different lymphatic metastasis potentials. Through data from TCGA and GEO database analysis, we speculated that miR-330-3p might be a tumor promoter, while EREG could be a tumor suppressor in BC. MiR-330-3p was upregulated, while lnc021545 and EREG were downregulated in 50 BC tissues. MiR-330-3p advanced the metastatic behaviors of BC cells, whereas lnc021545 and EREG resulted in the opposite effects. The three molecules’ expressions were correlated respectively and showed that miR-330-3p targeted lnc021545 and EREG to affect their expressions. Lnc021545/miR-330-3p axis affected BC metastasis by regulating EREG in epithelial-to-mesenchymal transition. In 50 BC patients, these three molecules and their cooperation are associated with aggressive tumor phenotypes, patient outcomes, and trastuzumab therapy. We finally discovered that lnc021545, miR-330-3p, and EREG formed a multi-gene co-regulation system that affected the metastasis of BC and the cooperation reflects the synergistic effects of the three molecules, recommending that their cooperation may provide a more accurate index for anti-metastasis therapeutic and prognostic evaluation of BC.