Miracle-dz/UniFAR-FTUs huggingface dataset:
Adipose Tissue Wasting as a Determinant of Pancreatic Cancer-Related Cachexia

Simple Summary Pancreatic cancer (PC) is one of the deadliest cancers in the US. The poor prognosis of PC is related to diagnostic delay and the presence of unintended weight loss (cachexia) that commonly presents in PC patients even before diagnosis. However, the current understanding of how PC mediates cachexia is limited, and there are few treatments clinically available for cachexia. Based on the current literature, we demonstrate that PC-related cachexia primarily results from the wasting of adipose tissue, once thought to be merely a storage depot but now appreciated as an instrumental metabolic organ in the body. In addition, poor survival in PC patients was found to be associated with adipose tissue loss at diagnosis and during treatment. Therefore, identifying potential mediators and molecular mechanisms underlying adipose tissue loss would promise to pave the way for the development of effective interventions for PC-related cachexia Abstract Pancreatic cancer (PC) is the third leading cause of cancer-related death in the US, and its 5-year survival rate is approximately 10%. The low survival rates largely stem from diagnostic delay and the presence of significant adipose tissue and muscle wasting, commonly referred to as cachexia. Cachexia is present in nearly 80% of PC patients and is a key cause of poor response to treatment and about 20% of death in PC patients. However, there are few clinical interventions proven to be effective against PC-related cachexia. Different cancer types feature distinct secretome profiles and functional characteristics which would lead to cachexia development differently. Therefore, here we discuss affected tissues and potential mechanisms leading to cachexia in PC. We postulate that the most affected tissue during the development of PC-related cachexia is adipose tissue, historically and still thought to be just an inert repository for excess energy in relation to cancer-related cachexia. Adipose tissue loss is considerably greater than muscle loss in quantity and shows a correlation with poor survival in PC patients. Moreover, we suggest that PC mediates adipose atrophy by accelerating adipocyte lipid turnover and fibroblast infiltration.
Green's Function expansion of scalar and vector fields in the presence of a medium

Abstract Based on a canonical approach and functional-integration techniques, a series expansion of Green’s function of a scalar field, in the presence of a medium, is obtained. A series expansion for Lifshitzenergy, in finite-temperature, in terms of the susceptibility of the medium is derived and the whole formalism is generalized to the case of electromagnetic field in the presence of some dielectrics. A covariant formulation of the problem is presented.
THE PHYSICAL CONDITIONS, METALLICITY AND METAL ABUNDANCE RATIOS IN A HIGHLY MAGNIFIED GALAXY AT z = 3.6252

We present optical and near-IR imaging and spectroscopy of SGAS J105039.6+001730, a strongly lensed galaxy at z = 3.6252 magnified by >30×, and derive its physical properties. We measure a stellar mass of log(M*/M☉) = 9.5 ± 0.35, star formation rates from [O ii] λλ3727 and Hβ of 55 ± 25 and 84 ± 24 M☉ yr−1, respectively, an electron density of ne ⩽ 103 cm−2, an electron temperature of Te ⩽ 14,000 K, and a metallicity of 12 + log(O/H) = 8.3 ± 0.1. The strong C iii] λλ1907,1909 emission and abundance ratios of C, N, O, and Si are consistent with well-studied starbursts at z ∼ 0 with similar metallicities. Strong P Cygni lines and He ii λ1640 emission indicate a significant population of Wolf–Rayet stars, but synthetic spectra of individual populations of young, hot stars do not reproduce the observed integrated P Cygni absorption features. The rest-frame UV spectral features are indicative of a young starburst with high ionization, implying either (1) an ionization parameter significantly higher than suggested by rest-frame optical nebular lines, or (2) differences in one or both of the initial mass function and the properties of ionizing spectra of massive stars. We argue that the observed features are likely the result of a superposition of star forming regions with different physical properties. These results demonstrate the complexity of star formation on scales smaller than individual galaxies, and highlight the importance of systematic effects that result from smearing together the signatures of individual star forming regions within galaxies.
A NEW PARADIGM FOR SURFACE REGISTRATION

We report a new approach for matching regular surfaces in a Rie- mannian setting. In this setting a deformation vector eld is dened on the surface directly and the motion of the surface does not involve motion of the ambient space. This is in contrast to LDDMM, in which a prescribed defor- mation of the ambient space drags along an embedded surface. In particular, this approach performs matching using an inner metric dened on the space of surfaces. We also show how to discretize the corresponding geodesic equation and compute the gradient of the cost functional using nite elements.
The Herschel/PACS view of the Cep OB2 region : global protoplanetary disk evolution and clumpy star formation

A.S. A. acknowledges support by the Spanish MICINN/MINECO “Ramon y Cajal” program, grant number RYC-2010-06164. A.S. A. and M.F. acknowledge support by the action “Proyectos de Investigacion fundamental no orientada”, grant number AYA2012-35008. C.E. is partly supported by Spanish MICINN/MINECO grant AYA2011-26202. V.R. is supported by the DLR grant number 50 OR 1109 and by the Bayerischen Gleichstellungsforderung (BGF). T.B. acknowledges support from NASA Origins of Solar Systems grant NNX12AJ04G.
VALIDATING A KNOWLEDGE MANAGEMENT ORIENTATION CONSTRUCT IN THE PRIVATE UNIVERSITIES CONTEXT IN JORDAN: AN EMPIRICAL STUDY

This study is an attempt to validate one of the knowledge managements constructs that is called knowledge management orientation (KMO), which was proposed and validated already by Wang and Ahmed (2004). The reason for this revalidation of the f KMO construct is to work in a different context where it will be applied to measure knowledge management performance in the private universities in Jordan. To achieve this, a random sample of 296 managerial position employees was selected from different private universities in Jordan, where confirmatory factor analysis was applied to test for model fit. The results revealed a modified model with only 19 items rather than the initial 30 items, where all the five factors remain the same. As for reliability and validity, the analysis shows the quality of measurement by conducting Internal and composite Reliability and Convergent and Discriminant validity.
The Corbino Paradox for Hydrodynamic Electrons

Our thinking about electron transport is usually rooted in Ohm’s law, J(x) = σ(x)E(x), which is a conveniently local relation between the current density J(x) and the electric field E(x) at some point x. Underlying Ohm’s law is an assumption that the rate of momentum relaxation, and therefore of energy dissipation, is determined by spatially local processes. Even though we often analogize the flow of electric current to the flow of water, such locality is not generally how actual fluids behave. Instead, fluids typically relax their momentum by viscous shearing, which arises from gradients of current density. Thus, viscosity generates a “nonlocality” in transport, where the local electric field depends on gradients of the current. Where viscous effects exist, the linearized equation of motion (for steady-state, incompressible flow) becomes( 1 σ(x) − η n2e2 ∇ ) J(x) = E(x). (1)
Asymptotically optimal function estimation by minimum complexity criteria

The minimum description length principle applied to function estimation can yield a criterion of the form log(likelihood)+const/spl middot/m instead of the familiar log(likelihood)+(m/2) log n where m is the number of parameters and n is the sample size. The improved criterion yields minimax optimal rates for redundancy and statistical risk. The analysis suggests an information-theoretic reconciliation of criteria proposed by Rissanen (1983), Schwarz (1978), and Akaike (1973). <<ETX>>
A 121.4-dB DR Capacitively Coupled Chopper Class-D Audio Amplifier

This article presents a class-D amplifier (CDA) with high dynamic range (DR). To eliminate the typically dominant noise contribution of a resistive feedback network, the input and feedback signals are chopped and applied to a capacitive feedback network. However, this leads to high-voltage (HV) transients at the input of the loop filter, which, due to timing and impedance mismatch in the chopped feedback network, could degrade linearity and even overstress low-voltage (LV) core devices. Robust processing of the HV chopped feedback signal is guaranteed with chopper timing skew correction, chopper impedance matching, and deadbanding. The prototype, implemented in a 180-nm bipolar-CMOS-DMOS (BCD) process, achieves 121.4 dB of DR, 5.9 dB higher than state-of-the-art closed-loop CDAs, and 8-<inline-formula> <tex-math notation="LaTeX">$\mu \text{V}_{\mathrm {RMS}}$ </tex-math></inline-formula> output-referred noise (A-weighted). It also achieves a peak total harmonic distortion (THD) + N of −109.8 dB and a peak efficiency of 93%/88% while driving 15 W/26 W into an 8-/4-<inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> load.
Accurately specifying storm‐time ULF wave radial diffusion in the radiation belts

Ultralow frequency (ULF) waves can contribute to the transport, acceleration, and loss of electrons in the radiation belts through inward and outward diffusion. However, the most appropriate parameters to use to specify the ULF wave diffusion rates are unknown. Empirical representations of diffusion coefficients often use Kp; however, specifications using ULF wave power offer an improved physics‐based approach. We use 11 years of ground‐based magnetometer array measurements to statistically parameterize the ULF wave power with Kp, solar wind speed, solar wind dynamic pressure, and Dst. We find that Kp is the best single parameter to specify the statistical ULF wave power driving radial diffusion. Significantly, remarkable high energy tails exist in the ULF wave power distributions when expressed as a function of Dst. Two‐parameter ULF wave power specifications using Dst as well as Kp provide a better statistical representation of storm‐time radial diffusion than any single variable alone.
Efficient technique to measure the concentration value of a scattering suspension using Bouguer-Lambert-Beer law

The efficient technique based on the Bouguer-Lambert-Beer law for experimental measurement of the concentration value of an optically scattering medium is presented. The software for batch analysis of intensity distributions of scattered laser beam is developed and tested. An experimental laboratory setup to measure the concentration value of a scattering suspension of polystyrene microbeads is assembled.
Enzymatic Construction of DARPin-Based Targeted Delivery Systems Using Protein Farnesyltransferase and a Capture and Release Strategy

Protein-based conjugates have been extensively utilized in various biotechnological and therapeutic applications. In order to prepare homogeneous conjugates, site-specific modification methods and efficient purification strategies are both critical factors to be considered. The development of general and facile conjugation and purification strategies is therefore highly desirable. Here, we apply a capture and release strategy to create protein conjugates based on Designed Ankyrin Repeat Proteins (DARPins), which are engineered antigen-binding proteins with prominent affinity and selectivity. In this case, DARPins that target the epithelial cell adhesion molecule (EpCAM), a diagnostic cell surface marker for many types of cancer, were employed. The DARPins were first genetically modified with a C-terminal CVIA sequence to install an enzyme recognition site and then labeled with an aldehyde functional group employing protein farnesyltransferase. Using a capture and release strategy, conjugation of the labeled DARPins to a TAMRA fluorophore was achieved with either purified proteins or directly from crude E. coli lysate and used in subsequent flow cytometry and confocal imaging analysis. DARPin-MMAE conjugates were also prepared yielding a construct manifesting an IC50 of 1.3 nM for cell killing of EpCAM positive MCF-7 cells. The method described here is broadly applicable to enable the streamlined one-step preparation of protein-based conjugates.
International Journal of Evaluation and Research in Education (IJERE)

Habiburrahim Habiburrahim, Saiful Akmal, Ika Kana Trisnawati, Suryanto Suryanto, Maira Mustiranda, Safrul Muluk Department of English Language Education, Faculty of Education, Universitas Islam Negeri Ar-Raniry, Banda Aceh, Indonesia Department of English Language Education, Faculty of Islamic Studies, Universitas Muhammadiyah Aceh, Banda Aceh, Indonesia Department of English Language Education, Faculty of Language Education, Universitas Muhammadiyah Yogyakarta, Yogyakarta, Indonesia
Quantum Effects In Low Temperature Bosonic Systems

In the first part, we investigate the effect of long range particle exchange in ideal bosonic chains. We establish that by using the Heisenberg formalism along with matrix product state representation we can study the evolution as well as the ground state of bosonic arrangements while including terms beyond next-neighbour hopping. The method is then applied to analyse the quench dynamics of condensates in a trapping potential and also to study the emergence of entanglement as a result of collision in boson chains. In the second part, we study the ground state as well as the dynamics of 1D boson arrangements with local repulsive interactions and nearest-neighbour exchange using numerical techniques based on time evolving block decimation (TEBD). We focus on the development of quantum correlations between the terminal places of these arrangements. We find that long-range entanglement in the ground state arises as a result of intense boson tunnelling taking place across the whole chain in systems with appropriate hopping coefficients. Additionally, we identify the perturbations necessary to increase the entanglement between the end sites above their ground state values. In the final part, we study the wave function of a kicked condensate using a perturbative approach and compare the results obtained in this way with numerical simulations.
Heart Valve Diseases Detection Based on Feature-Fusion and Hierarchical LSTM Network

Early detection and diagnosis of heart valve diseases (HVDs) can prevent cardiac arrest. This work proposes a novel feature fusion method for detecting HVDs using a phonocardiogram (PCG) signal. In the proposed method, first, the raw PCG signal is preprocessed. Then, two feature fusion models are proposed based on mel-frequency cepstral coefficients (MFCCs) and linear prediction cepstral coefficients (LPCCs). One model is the series feature fusion (SFF) model. Another is the parallel feature fusion (PFF) model. We propose a hierarchical long-short-term memory (HLSTM) network with a self-attention (SA) mechanism for both models. HLSTM encodes the sequential information of the fused features in different abstractions. Then, the SA module aggregates these encoded vectors based on their clinical relevance to detect HVDs. The efficacy of the proposed method is evaluated using two publicly available databases offered by Physionet challenge (CinC) 2016 and the GitHub repository. The CinC 2016 database is used for binary classification. The results show an overall accuracy (OA) of 98.76% and 98.29% for binary classification using SFF-HLSTM and PFF-HLSTM models. The heart sound murmur (HSM) database in the GitHub repository is used for multiclass classification. The results show an OA of 99.10% and 98.71% for multiclass classification using the SFF-HLSTM and PFF-HLSTM models, respectively. The promising results show that the proposed method is compelling enough for the preliminary automated diagnosis of HVDs in cardiac care units (CCUs).
KINEMATIC ORIGIN OF CORRELATIONS BETWEEN GAMMA-RAY BURST OBSERVABLES

Recently, several new correlations between gamma-ray burst (GRB) observables have been discovered. Like previously well-established correlations, they challenge GRB models. Here, we show that in the cannonball (CB) model of GRBs, the newly discovered correlations have the same simple kinematic origin as those discovered earlier. They all result from the strong dependence of the observed radiations on the Lorentz and Doppler factors of the jet of highly relativistic plasmoids (CBs) that produces the observed radiations by interaction with the medium through which it propagates.
Evaluation Method of Vocal Music Teaching Quality for Music Majors Based on the Theory of Multiple Intelligences

The quality evaluation of vocal music teaching for music majors is of great significance to music education. Based on the theory of multiple intelligences, this paper constructs a model for evaluating the quality of vocal music teaching for music majors and introduces the theory of multiple intelligences into the operation form, design requirements, and recommended lesson examples of music teaching unit design. The experimental data and questionnaire data collected by the model verify that this operation is beneficial to the improvement of students’ music listening scores, vocal music comprehension scores, and total scores and solves the quantitative problem of vocal music teaching quality evaluation. In the simulation process, the engineering testing and analysis method uses the correlation rate and correlation strength as the analysis indicators, comparing the platforms for the quality evaluation of vocal music teaching in music majors and the corresponding quality evaluation data preprocessing process. The experimental results show that the algorithm performance evaluation is carried out based on the three aspects of quality evaluation association rules, algorithm running time, and algorithm memory consumption. The multiple intelligence algorithm is applied to vocal music teaching analysis of association rules for quality evaluation: when 4000 tasks call for 20–40 virtual resources, the total time spent is reduced by 61.7%, which has a significant positive effect on the knowledge expansion and ability improvement of music majors.
Accurate camera performance prediction using optical and imaging simulation pipeline for super wide-angle lens

Optical design process consists in minimizing aberrations using optimization methods. It relies on key performance indicators (KPIs), such as point spread function (PSF), Modulated transfer function (MTF), or relative illumination (RI) and spot sizes, that depend on lens elements aberrations. Their target values need to be defined -either for human or machine perception- at early stage of the design, which can be complex to do for challenging designs such as extended field of view. We developed an optical and imaging simulation pipeline able to render the effects of complex optical designs and image sensor on an initial aberration-free image. Extracting files from ray tracing software for simulating the PSF and sensor target information, the algorithm accurately renders off-axis aberrations with Zernike polynomials representation combined with noise contribution and relative illumination. The obtained image faithfully represents an optical system performance from the optics to the sensor component and we can then study the impact of additional aberration introduction.
Software Requirements Classification using Deep-learning Approach with Various Hidden Layers

Software requirement classification is becoming increasingly crucial for the industry to keep up with the demand of growing project sizes. Based on client feedback or demand, software requirement classification is critical in segregating user needs into functional and quality requirements. However, because there are numerous machine learning (ML) and deep-learning (DL) models that require parameter tuning, the use of ML to facilitate decision-making across the software engineering pipeline is not well understood. Five distinct word embedding techniques were applied to the functional and quality software requirements in this study. The imbalanced classes in the dataset are balanced using Synthetic Minority Oversampling technique (SMOTE). Then, to reduce duplicate and unnecessary features, feature selection and dimensionality reduction techniques are used. Dimensionality reduction is accomplished with Principal Component Analysis (PCA), while feature selection is accomplished with the Rank-Sum Test (RST). For binary categorization into functional and non-functional needs, the generated vectors are provided as inputs to eight distinct Deep Learning classifiers. The findings of the research show that using a combination of word embedding and feature selection techniques in conjunction with various classifiers can accurately classify functional and quality software requirements.
Astrochemistry in external galaxies: how to use molecules as probes of their physical conditions

Abstract It is now well established that chemistry in external galaxies is rich and complex. In this review I will explore whether one can use molecular emissions to determine their physical conditions. There are several considerations to bear in mind when using molecular emission, and in particular molecular ratios, to determine the densities, temperatures and energetics of a galaxy, which I will briefly summarise here. I will then present an example of a study that uses multiple chemical and radiative transfer analyses in order to tackle the too often neglected ‘degeneracies’ implicit in the interpretation of molecular ratios and show that only via such analyses combined with multi-species and multi-lines high spatial resolution data one can truly make molecules into powerful diagnostics of the evolution and distribution of molecular gas.
Increasing the coherence time of single electron spins in diamond by high temperature annealing

Negatively charged nitrogen-vacancy (NV−) centers in diamond produced by ion implantation often show properties different from NVs created during the crystal growth. We observe that NVs created from nitrogen ion implantation at 30–300 keV show much shorter electron spin coherence time T2 as compared to the “natural” NVs and about 20% of them show switching from NV− to NV0. We show that annealing the diamond at T=1200 °C substantially increases T2 and at the same time the fraction of NVs converting from NV− to NV0 is greatly reduced.
Numerical research on ablation and wear of the artillery barrel based on UMESHMOTION user‐defined subroutine

During the firing process, the gun barrel bears the thermal and chemical erosion of high‐temperature gunpowder gas and the wear of the rotation band. The forced cone tended to the most severely worn part of the barrel, which directly affects the life of the barrel. Combined with the erosion test and wear test of gun steel materials, this research studied the forcing cone of a medium caliber naval gun barrel. With the commercial finite element software ABAQUS as the platform, we took advanced adaptive mesh method combined with secondary development technology. This method used in our study in order to better realize the numerical simulation of the radial erosion wear of the forced projectile cone in the continuous firing environment. At the same time, we compared the numerical simulation with the actual firing test data, and proposed a new calculation method of barrel life. In conclusion, the results of this study showed that this method can better calculate the radial erosion wear of the forced cone, and provide guidance for improving the life of the gun barrel in the future.