Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Primary Tumour and Axillary Lymph Node Response to Neoadjuvant Chemo(Targeted) Therapy with Dedicated Breast [18F]FDG PET/MRI in Breast Cancer

Simple Summary Neoadjuvant chemo(targeted) therapy (NCT) can downstage disease burden in breast cancer, allowing less invasive surgery. The ability of sequential hybrid [18F]FDG PET/MRI to predict the final pathologic primary tumour response to NCT in breast cancer was investigated. In addition, the value of sequential hybrid [18F]FDG PET/MRI in predicting axillary response was investigated separately in clinically node-positive breast cancer patients. In this study, final pathologic primary tumour and axillary lymph node response prediction with qualitative or quantitative [18F]FDG PET/MRI after NCT is not reliable. However, combining the relative decrease in [18F]FDG PET and MR imaging variables halfway through NCT improved diagnostic performance, especially in predicting the final pathologic axillary lymph node response. These findings suggest that sequential hybrid [18F]FDG PET/MRI could have complementary value in the early prediction of the final pathologic response to NCT in breast cancer. Abstract Background: The aim of this study was to investigate whether sequential hybrid [18F]FDG PET/MRI can predict the final pathologic response to neoadjuvant chemo(targeted) therapy (NCT) in breast cancer. Methods: Sequential [18F]FDG PET/MRI was performed before, halfway through and after NCT, followed by surgery. Qualitative response evaluation was assessed after NCT. Quantitatively, the SUVmax obtained by [18F]FDG PET and signal enhancement ratio (SER) obtained by MRI were determined sequentially on the primary tumour. For the response of axillary lymph node metastases (ALNMs), SUVmax was determined sequentially on the most [18F]FDG-avid ALN. ROC curves were generated to determine the optimal cut-off values for the absolute and percentage change in quantitative variables in predicting response. Diagnostic performance in predicting primary tumour response was assessed with AUC. Similar analyses were performed in clinically node-positive (cN+) patients for ALNM response. Results: Forty-one breast cancer patients with forty-two primary tumours and twenty-six cases of pathologically proven cN+ disease were prospectively included. Pathologic complete response (pCR) of the primary tumour occurred in 16 patients and pCR of the ALNMs in 14 cN+ patients. The AUC of the qualitative evaluation after NCT was 0.71 for primary tumours and 0.54 for ALNM responses. For primary tumour response, combining the percentage decrease in SUVmax and SER halfway through NCT achieved an AUC of 0.78. The AUC for ALNM response prediction increased to 0.92 by combining the absolute and the percentage decrease in SUVmax halfway through NCT. Conclusions: Qualitative PET/MRI after NCT can predict the final pathologic primary tumour response, but not the ALNM response. Combining quantitative variables halfway through NCT can improve the diagnostic accuracy for final pathologic ALNM response prediction.
High-Q Slow Sound Mode in a Phononic Fishbone Nanobeam Using an Acoustic Potential Well Cavity

Phononic crystals and phononic metamaterials are popular structures for manipulating acoustic waves with artificially arranged units that have different elastic constants. These structures are also used in acousto-optic coupling and optomechanical structures. In such research, a 1-D nanobeam containing a cavity region sandwiched by two mirror regions is one of the most common designs. However, searching bandgaps for suitable operation modes and the need for the mirror region are limitations in the device design. Therefore, we introduce the slow sound mode as the operating acoustic mode and use an acoustic potential well to further trap the phonons in the cavity. Three types of structures are introduced to investigate the effect of the potential well. The products of the mode frequencies and the quality factors of the modes are used to demonstrate the performance of the structures. The displacement field and the strain field show the concentrated slow sound modes of the potential wells and produce high quality factors.
Electron-impact-ionization dynamics of five C2 to C4 perfluorocarbons

Perfluorocarbons (PFCs) are man-made compounds whose ion physics exhibit complex interplays between statistical and nonstatistical fragmentation and intramolecular rearrangement processes. One probe of such processes is the energy-dependent electron-impact-ionization cross section. Partial electron-impact-ionization cross sections are reported for the fragments arising from five C${}_{2}$ to C${}_{4}$ PFCs, namely, C${}_{2}$F${}_{6}$, C${}_{3}$F${}_{8}$, C${}_{3}$F${}_{6}$, CF${}_{2}$=CF-CF=CF${}_{2}$, and CF${}_{3}$-C\ensuremath{\equiv}C-CF${}_{3}$, over the energy range from threshold to \ensuremath{\sim}210 eV. Care was taken to maximize ion collection efficiency and to minimize discrimination against ions produced with high kinetic-energy release, and the measured cross sections have been calibrated using independent absolute total (gross) ionization efficiency curves measured previously in the same laboratory with an instrument that was designed to essentially have unit detection efficiency. Total ionization cross sections have also been modeled using the binary-encounter Bethe model, and the shortcomings of the model when applied to perfluorinated compounds are discussed. Analysis of the mass spectral fragmentation patterns in combination with ab initio energetics suggests that nonstatistical dissociative ionization processes play a significant role in the fragmentation dynamics of saturated PFCs. In contrast, unsaturated PFCs exhibit long-lived parent ions, which tend to undergo a higher degree of statistical dissociation following ionization, involving considerable intramolecular rearrangement.
Regional Variability within Global-Scale Relations between Passive Microwave Signatures and Raining Clouds over the Tropical Oceans

AbstractEmpirical orthogonal function (EOF) analysis of radiance vectors associated with emission and scattering indices for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) has been performed to examine the regional variability in relations between brightness temperature and rain rate over portions of the tropical oceans known to exhibit regional differences due to different thermodynamic environments and different large-scale forcing. The TMI indices and rain rates used in this study are the products of the Goddard profiling algorithm (GPROF), version 6. The EOF framework reduces the nine-dimensional space of the brightness temperatures and their polarizations to just two dimensions associated with the EOF coefficients. Vertical profiles of reflectivity from the TRMM precipitation radar (PR) are used to show that the statistically obtained EOFs represent bulk physical characteristics of raining clouds. Hence, EOF analysis provides an efficient framework for diagnosing regional diffe.
Age-Related Dysfunction in Proteostasis and Cellular Quality Control in the Development of Sarcopenia

Sarcopenia is a debilitating skeletal muscle disease that accelerates in the last decades of life and is characterized by marked deficits in muscle strength, mass, quality, and metabolic health. The multifactorial causes of sarcopenia have proven difficult to treat and involve a complex interplay between environmental factors and intrinsic age-associated changes. It is generally accepted that sarcopenia results in a progressive loss of skeletal muscle function that exceeds the loss of mass, indicating that while loss of muscle mass is important, loss of muscle quality is the primary defect with advanced age. Furthermore, preclinical models have suggested that aged skeletal muscle exhibits defects in cellular quality control such as the degradation of damaged mitochondria. Recent evidence suggests that a dysregulation of proteostasis, an important regulator of cellular quality control, is a significant contributor to the aging-associated declines in muscle quality, function, and mass. Although skeletal muscle mammalian target of rapamycin complex 1 (mTORC1) plays a critical role in cellular control, including skeletal muscle hypertrophy, paradoxically, sustained activation of mTORC1 recapitulates several characteristics of sarcopenia. Pharmaceutical inhibition of mTORC1 as well as caloric restriction significantly improves muscle quality in aged animals, however, the mechanisms controlling cellular proteostasis are not fully known. This information is important for developing effective therapeutic strategies that mitigate or prevent sarcopenia and associated disability. This review identifies recent and historical understanding of the molecular mechanisms of proteostasis driving age-associated muscle loss and suggests potential therapeutic interventions to slow or prevent sarcopenia.
Spacecraft Navigation Using Celestial Gamma-Ray Sources

As the future progresses for space exploration endeavors, spacecraft that are capable of autonomously determining their position and velocity will provide clear navigation advances to mission operations. Thus, new techniques for determining spacecraft navigation solutions using celestial gamma-ray sources have been developed. Most of these sources offer detectable, bright, high-energy events that provide well-defined characteristics conducive to accurate time alignment among spatially separated spacecraft. Using assemblages of photons from distant gamma-ray bursts, relative range between two spacecraft can be accurately computed along the direction to each burst’s source based upon the difference in arrival time of the burst emission at each spacecraft’s location. Correlation methods used to time-align the high-energy burst profiles are provided. A simulation of the newly devised navigation algorithms has been developed to assess the system’s potential performance. Using predicted observation capabilities.
Active-Varying Sampling-Based Fault Detection Filter Design for Networked Control Systems

This paper is concerned with fault detection filter design for continuous-time networked control systems considering packet dropouts and network-induced delays. The active-varying sampling period method is introduced to establish a new discretized model for the considered networked control systems. The mutually exclusive distribution characteristic of packet dropouts and network-induced delays is made full use of to derive less conservative fault detection filter design criteria. Compared with the fault detection filter design adopting a constant sampling period, the proposed active-varying sampling-based fault detection filter design can improve the sensitivity of the residual signal to faults and shorten the needed time for fault detection. The simulation results illustrate the merits and effectiveness of the proposed fault detection filter design.
π-superconducting quantum interference device from ultracold fermionic atomic gases

Ultracold fermionic atomic gas with Bardeen-Cooper-Schrieffer pairing between hyperfine states is studied. It is shown that a {pi}-Josephson contact [superfluid-normal-gas-superfluid (S/N/S)] can be realized in systems where the left and right banks S are superfluids and the weak link N is a normal gas with the finite mismatch in chemical potentials {delta}{sub {mu}{sub N}}{ne}0. If such a {pi}-junction is part of a closed superfluid ring the superfluid mass-current flows spontaneously--the ultracold atomic {pi}-superconducting quantum interference device ({pi}-SQUID). This situation is realized if the radius of the ring R is larger than the critical one R{sub c}. The same effect will be realized also for {delta}{sub {mu}{sub N}}>>{delta}, where {delta} is the superfluid gap in S. The sensitivity of the {pi}-SQUID to inertial effects is discussed in the case of rotational motion.
Arecaceae Seeds Constitute a Healthy Source of Fatty Acids and Phenolic Compounds

Seeds of most Arecaceae species are an underutilized raw material that can constitute a source of nutritionally relevant compounds. In this work, seeds of 24 Arecaceae taxa were analyzed for fatty acids (FAs) by GC-FID, for phenolics by HPLC-DAD and LC-MS, and for their antitumor activity against the HT-29 colorectal cancer cell line by the MTT assay. Lauric, oleic, and linoleic acids were the prominent FAs. Cocoseae species contained total FAs at 28.0–68.3 g/100 g seeds, and in other species total FAs were from 1.2 (Livistona saribus) to 9.9 g/100 g (Washingtonia robusta). Sabal domingensis, Chamaerops humilis, and Phoenix dactylifera var. Medjool had unsaturated/saturated FA ratios of 1.65, 1.33–1.78, and 1.31, respectively, and contained 7.4, 5.5–6.3, and 6.4 g FAs/100 g seeds, respectively. Thus, they could be used as raw materials for healthy oilseed production. Phenolics ranged between 39 (Livistona fulva) and 246 mg/100 g (Sabal palmetto), and of these, caffeic acid, catechin, dactylifric acid, and rutin had the highest values. (-)-Epicatechin was identified in most seed extracts by LC-MS. Hydroalcoholic extracts from five species showed a dose-dependent inhibitory effect on HT-20 cells growth at 72 h (GI50 at 1533–1968 µg/mL). Overall, Arecaceae seeds could be considered as a cheap source of health-promoting compounds.
Waist Circumference Is an Essential Factor in Predicting Insulin Resistance and Early Detection of Metabolic Syndrome in Adults

Background: Metabolic syndrome (Met-S) is considered one of the most important health problems of the 21st century. It includes a group of metabolic disorders that increase the risk of cardiovascular diseases such as overweight and obesity, elevated lipid profile and blood pressure and insulin resistance (IR). Based on the information mentioned above in which there seems to be a relationship between IR and Met-S, the objective of this work was twofold: on the one hand, to assess the relationship between the values of different insulin resistance risk scales and Met-S determined with three different scales, and on the other, to determine whether any of the components of Met-S predispose more to the appearance of IR. Methods: A descriptive cross-sectional study of 418,343 workers. Waist circumference was measured and evaluated together with six formulas to assess the insulin resistance index. Categorical variables were evaluated by calculating the frequency and distribution of each one. For quantitative variables, mean and standard deviation were determined, and Student’s t-test was applied, while for qualitative variables, the chi-square test was performed. The usefulness of the different risk scales for insulin resistance for predicting metabolic syndrome was evaluated using ROC curves, the area under the curve (AUC), as well as their cut-off points for sensitivity, specificity, and the Youden index. Results: People with metabolic syndrome applying any criteria had higher values in the IR risk scales. The different IR scales made it possible to adequately classify people with metabolic syndrome. Of the three definitions of Met-S, the one that showed the greatest relationship with IR was IDF. Conclusions: Most risk scales for insulin resistance enable the presence of metabolic syndrome to be adequately classified, finding the best ones if the International Diabetes Federation (IDF) criteria are applied. Of the elements included in the Met-S, the one that seems to increase the risk of presenting IR the most is waist circumference; hence, the Met-S definition that is most related to IR is that of the IDF, which is the only one of the three in which a high value of waist circumference is necessary to be able to diagnose Met-S. Waist circumference can be considered the central essential component for detecting insulin resistance and, therefore, the early detection of metabolic syndrome.
A Review of Commercial and Non-Commercial Wearables Devices for Monitoring Motor Impairments Caused by Neurodegenerative Diseases

Neurodegenerative diseases (NDDs) are among the 10 causes of death worldwide. The effects of NDDs, including irreversible motor impairments, have an impact not only on patients themselves but also on their families and social environments. One strategy to mitigate the pain of NDDs is to early identify and remotely monitor related motor impairments using wearable devices. Technological progress has contributed to reducing the hardware complexity of mobile devices while simultaneously improving their efficiency in terms of data collection and processing and energy consumption. However, perhaps the greatest challenges of current mobile devices are to successfully manage the security and privacy of patient medical data and maintain reasonable costs with respect to the traditional patient consultation scheme. In this work, we conclude: (1) Falls are most monitored for Parkinson’s disease, while tremors predominate in epilepsy and Alzheimer’s disease. These findings will provide guidance for wearable device manufacturers to strengthen areas of opportunity that need to be addressed, and (2) Of the total universe of commercial wearables devices that are available on the market, only a few have FDA approval, which means that there is a large number of devices that do not safeguard the integrity of the users who use them.
Fault Identification and Localization of a Time−Frequency Domain Joint Impedance Spectrum of Cables Based on Deep Belief Networks

To improve the accuracy of shallow neural networks in processing complex signals and cable fault diagnosis, and to overcome the shortage of manual dependency and cable fault feature extraction, a deep learning method is introduced, and a time−frequency domain joint impedance spectrum is proposed for cable fault identification and localization based on a deep belief network (DBN). Firstly, based on the distribution parameter model of power cables, we model and analyze the cables under normal operation and different fault types, and we obtain the headend input impedance spectrum and the headend input time−frequency domain impedance spectrum of cables under various operating conditions. The headend input impedance amplitude and phase of normal operation and different fault cables are extracted as the original input samples of the cable fault type identification model; the real part of the headend input time–frequency domain impedance of the fault cables is extracted as the original input samples of the cable fault location model. Then, the unsupervised pre−training and supervised inverse fine−tuning methods are used for automatically learning, training, and extracting the cable fault state features from the original input samples, and the DBN−based cable fault type recognition model and location model are constructed and used to realize the type recognition and location of cable faults. Finally, the proposed method is validated by simulation, and the results show that the method has good fault feature extraction capability and high fault type recognition and localization accuracy.
Surface plasmon propagation in microscale metal stripes

Addressing the fundamental question of miniaturization of light guiding and routing towards nanoscale optics, we study experimentally surface plasmon propagation in silver and gold thin films of finite widths in the micrometer range. Spatially confined excitation of surface plasmons is realized by a prism coupling arrangement involving an opaque aluminum screen for a distinct separation of excitation and propagation (measurement) region. The surface plasmon propagation length as a function of film widths is measured by detecting stray light due to surface plasmon scattering with a conventional optical microscope.
Al intermediate oxidation states observed by core level photoemission spectroscopy

Aluminum oxidation states in stoichiometric or substoichiometric configuration are studied by core level photoemission spectroscopy on different substrates (SiO2, graphite). They are compared with recent results reported for the interface Si–Aln+O. Three Al oxidation states have been identified and their space distribution (binding energy, intensity, and width) is determined in the region from the interface with the substrate up to the surface of a thick overlayer. The Al2+–O intermediate oxidation state is shown to be confined at the interface; on the contrary, the Al1+–O oxidation state and the stoichiometric oxide (alumina) are present beyond the interface region. From the attenuation of the substrate core level peak, the deposition morphology and the attenuation length of the photoelectrons have been deduced.
Virtual reality: a reality for future military pilotage?

Virtual reality (VR) systems provide exciting new ways to interact with information and with the world. The visual VR environment can be synthetic (computer generated) or be an indirect view of the real world using sensors and displays. With the potential opportunities of a VR system, the question arises about what benefits or detriments a military pilot might incur by operating in such an environment. Immersive and compelling VR displays could be accomplished with an HMD (e.g., imagery on the visor), large area collimated displays, or by putting the imagery on an opaque canopy. But what issues arise when, instead of viewing the world directly, a pilot views a "virtual" image of the world? Is 20/20 visual acuity in a VR system good enough? To deliver this acuity over the entire visual field would require over 43 megapixels (MP) of display surface for an HMD or about 150 MP for an immersive CAVE system, either of which presents a serious challenge with current technology. Additionally, the same number of sensor pixels would be required to drive the displays to this resolution (and formidable network architectures required to relay this information), or massive computer clusters are necessary to create an entirely computer-generated virtual reality with this resolution. Can we presently implement such a system? What other visual requirements or engineering issues should be considered? With the evolving technology, there are many technological issues and human factors considerations that need to be addressed before a pilot is placed within a virtual cockpit.
Nonequilibrium Relaxation of Fluctuations of Physical Quantities

The nonequilibrium relaxation (NER) process of fluctuations of physical quantities is studied simulationally. It is shown that the NER method, which is a convenient technique for studying the phase and transition, is useful not only for identifying the phase and locating the transition point, but also for estimating both static and dynamical exponents. As an example, the cubic-lattice ferromagnetic Ising model is analyzed. The transition inverse-temperature is estimated to be K c =0.2216595(15). The exponents of correlation length, magnetization, and specific heat are estimated to be ν=0.635(5), β= 0.325(5) and α= 0.14(2), respectively. The dynamical exponent z is estimated to be 2.055(10).