Miracle-dz/UniFAR-FTUs huggingface dataset:
Solitary pancreas retransplant: Study of 22 cases

Objective: To present our experience with pancreas retransplant in patients previously submitted to simultaneous pancreas-kidney transplant, pancreas after kidney transplant and pancreas transplant alone. Methods: Between January/1996 and December/ 2005, 330 pancreas transplants were performed: 308 primary transplants and 22 (6%) retransplants of solitary pancreas. The following variables were analyzed: patient age; time elapsed between the first and the second transplant; causes of loss of the first graft; technical characteristics of the transplant and retransplant and the criteria for selecting donors for retransplant. These clinical data were submitted to statistical analysis. Results: The mean age of patients was 34.3 years and the mean elapsed time between the first and second transplant was 19.3 months. The causes of the first graft loss were venous (8; 35%) and arterial (5; 23%) thrombosis, chronic rejection (4; 18%), ischemia/ reperfusion injury (2), reflux pancreatitis (1), primary non-function (1) and sepsis (1). A second transplant was performed in the same iliac fossa in 16 patients (72%). Venous drainage was performed in the iliac vein in 16 patients (72%), in the inferior vena cava in 5 patients (22%) and in the portal vein in one patient. 6 all bladder drainage was the technique used in 18 (82%) cases and enteric drainage, in 4 patients (18%). Immunosuppressive regimen applied to all cases was quadruple therapy with antilymphocyte induction, tacrolimus, mycophenolate mofetil and steroids. There was one early death due to sepsis. One-year patient and pancreas graft survival rates for retransplants were, respectively, 95% and 85%. There was no additional risk for removing the pancreas graft at retransplant. Conclusion: Pancreas retransplant was technically feasible in all cases and results similar to those described in the literature were found for primary pancreas transplant. ORIGINAL ARTICLE
Journal of Institutional Research

Students’ academic performance within the Australian higher education sector is a growing area of institutional research in the country. Its profile has been enhanced with the advent of the learning and teaching performance fund that inter alia includes academic performance as a key performance indicator for the allocation of Commonwealth monies under the scheme to the universities. The present study examines some of the important correlates of the academic performance of students within an Australian technological university. It also examines some of the planning and policy implications of the findings of the research. A key finding of the study is that good teaching, provision of helpful feedback to students, actively engaging students in the learning process and the like all contribute to enhance student performance. Clearly the academic staff play a critical role in these areas and perhaps the institutional researchers can assist them to keep turning “water into wine” by investigating how related value added learning and teaching activities can best be delivered in the classroom or through the virtual medium.
MOUTH DISSOLVING TABLETS- A NOVEL DRUG DELIVERY SYSTEM

The past decade has thrown open the doors for continuous technological advancements in the pharmaceutical sector. Mouth Dissolving Tablets are one of the fruitful results of these technological advancements. MD tablets play a major role in improving the patient's compliance. They rapidly disintegrate in the saliva hence obviating the need of the water. With the increasing incidences of non-compliance among the patients, Mouth dissolving tablets are the perfect answer to all these problems. A variety of drugs can be administered in the form of MD tablets as they give the advantage of the liquid medication in the solid preparation. These novel types of dosage forms have found acceptance among the geriatric, pediatric and dysphagic patients.
Exploring the Stability of Twisted van der Waals Heterostructures.

Recent research showed that the rotational degree of freedom in stacking 2D materials yields great changes in the electronic properties. Here, we focus on an often overlooked question: are twisted geometries stable and what defines their rotational energy landscape? Our simulations show how epitaxy theory breaks down in these systems, and we explain the observed behaviour in terms of an interplay between flexural phonons and the interlayer coupling, governed by moir\'e superlattice. Our argument, applied to the well-studied MoS2/Graphene system, rationalizes experimental results and could serve as guidance to design twistronics devices.
Nondestructive photon counting in waveguide QED

Number-resolving single-photon detectors represent a key technology for a host of quantum optics protocols, but despite significant efforts, state-of-the-art devices are limited to few photons. In contrast, state-dependent atom counting in arrays can be done with extremely high fidelity up to hundreds of atoms. In waveguide QED, the problem of photon counting can be reduced to atom counting, if the photonic state is mapped to an atomic one. We show that this can be achieved by engineering a second decay channel of an excited atom to a metastable state. Our scheme is robust to disorder and finite Purcell factors, and its fidelity increases with atom number. We further show that if the initial atomic state is a symmetric Dicke state, dissipation engineering can be used to implement a nondestructive photon number measurement, in which the incident state is re-emitted into the waveguide unchanged. Our results readily generalize to related platforms, including superconducting qubits.
Limits on the electromagnetic counterpart to S190814bv

We derive limits on any electromagnetic counterpart to the compact binary merger S190814bv, whose parameters are consistent with the merger of a black hole and a neutron star. We present observations with the new wide-field optical imager DDOTI and also consider Swift/BAT observations reported by Palmer et al. We show that Swift/BAT would have detected a counterpart with similar properties to a typical on-axis short GRB at the 98 per cent confidence level, whereas our DDOTI observations only rule out such a counterpart at the 27 per cent confidence level. Neither has sufficient sensitivity to rule out an off-axis counterpart like GW 170817. We compare the efficiency of Swift/BAT and DDOTI for future observations, and show that DDOTI is likely to be about twice as efficient as Swift/BAT for off-axis events up to about 100 Mpc.
Time-resolved tomography of a driven adiabatic quantum simulation

A typical goal of a quantum simulation is to find the energy levels and eigenstates of a given Hamiltonian. This can be realized by adiabatically varying the system control parameters to steer an initial eigenstate into the eigenstate of the target Hamiltonian. Such an adiabatic quantum simulation is demonstrated by directly implementing a controllable and smoothly varying Hamiltonian in the rotating frame of two superconducting qubits, including longitudinal and transverse fields and iSWAP-type two-qubit interactions. The evolution of each eigenstate is tracked using time-resolved state tomography. The energy gaps between instantaneous eigenstates are chosen such that depending on the energy transition rate either diabatic or adiabatic passages are observed in the measured energies and correlators. Errors in the obtained energy values induced by finite $T_1$ and $T_2$ times of the qubits are mitigated by extrapolation to short protocol times.
Anomaly detection with density estimation

We leverage recent breakthroughs in neural density estimation to propose a new unsupervised anomaly detection technique (ANODE). By estimating the probability density of the data in a signal region and in sidebands, and interpolating the latter into the signal region, a likelihood ratio of data vs. background can be constructed. This likelihood ratio is broadly sensitive to overdensities in the data that could be due to localized anomalies. In addition, a unique potential benefit of the ANODE method is that the background can be directly estimated using the learned densities. Finally, ANODE is robust against systematic differences between signal region and sidebands, giving it broader applicability than other methods. We demonstrate the power of this new approach using the LHC Olympics 2020 R\&D Dataset. We show how ANODE can enhance the significance of a dijet bump hunt by up to a factor of 7 with a 10\% accuracy on the background prediction. While the LHC is used as the recurring example, the methods developed here have a much broader applicability to anomaly detection in physics and beyond.
A complete catalogue of dusty supernova remnants in the Galactic plane

We search for far-infrared (FIR) counterparts of known supernova remnants (SNRs) in the Galactic plane (360° in longitude and $b = \pm \, 1^{\circ }$) at 70–500 μm with Herschel. We detect dust signatures in 39 SNRs out of 190, made up of 13 core-collapse supernovae (CCSNe), including 4 Pulsar Wind Nebulae (PWNe), and 2 Type Ia SNe. A further 24 FIR detected SNRs have unknown types. We confirm the FIR detection of ejecta dust within G350.1−0.3, adding to the known sample of ∼ 10 SNRs containing ejecta dust. We discover dust features at the location of a radio core at the centre of G351.2+0.1, indicating FIR emission coincident with a possible Crab-like compact object, with dust temperature and mass of Td = 45.8 K and Md = 0.18 M⊙, similar to the PWN G54.1+0.3. We show that the detection rate is higher among young SNRs. We produce dust temperature maps of 11 SNRs and mass maps of those with distance estimates, finding dust at temperatures $15\, \lesssim \, T_d\, \lesssim \, 40$ K. If the dust is heated by shock interactions the shocked gas must be relatively cool and/or have a low density to explain the observed low grain temperatures.
Consistent User-Traffic Allocation and Load Balancing in Mobile Edge Caching

Cache-equipped Base-Stations (CBSs) is an attractive alternative to offload the rapidly growing backhaul traffic in a mobile network. New 5G technology and dense femtocell enable one user to connect to multiple base-stations simultaneously. Practical implementation requires the caches in BSs to be regarded as a cache server, but few of the existing works considered how to offload traffic, or how to schedule HTTP requests to CBSs. In this work, we propose a DNS-based HTTP traffic allocation framework. It schedules user traffic among multiple CBSs by DNS resolution, with the consideration of load-balancing, traffic allocation consistency and scheduling granularity of DNS. To address these issues, we formulate the user-traffic allocation problem in DNS-based mobile edge caching, aiming at maximizing QoS gain and allocation consistency while maintaining load balance. Then we present a simple greedy algorithm which gives a more consistent solution when user-traffic changes dynamically. Theoretical analysis proves that it is within 3/4 of the optimal solution. Extensive evaluations in numerical and trace-driven situations show that the greedy algorithm can avoid about 50% unnecessary shift in user-traffic allocation, yield more stable cache hit ratio and balance the load between CBSs without losing much of the QoS gain.
Direct evidence of weakly dispersed and strongly anharmonic low frequency optical phonons at low temperature in hybrid organolead perovskites

Hybrid organolead perovskites (HOP) have started to establish themselves in the field of photovoltaics, mainly due to their great optoelectronic properties and steadily improving solar cell efficiency. Study of the lattice dynamics is key in understanding the electron-phonon interactions at play, responsible for such properties. In this work, we investigate the optical phonon spectrum below 40 meV - via inelastic neutron scattering and Raman spectroscopy - in single crystals of four different hybrid lead halide perovskites: MAPbBr$_3$, FAPbBr$_3$, MAPbI$_3$, and $\alpha$-FAPbI$_3$. Low temperature spectra reveal weakly dispersive optical phonons, at energies as low as 2-5~meV, which seem to be the origin of the limit of the charge carrier mobilities in these materials. The temperature dependence of the neutron spectra reveals a significant anharmonic behaviour, resulting in optical phonon overdamping at temperatures as low as 80~K, questionning the validity of the quasi-particle picture for the low energy optical modes at room temperature where the solar cells operate.
Learning and Suggesting Source Code Changes from Version History: A Systematic Review

Context: Software systems are in continuous evolution through source code changes to fixing bugs, adding new functionalities and improving the internal architecture. All these practices are recorded in the version history, which can be reused as an advantage in the development process. Objective: This paper aims to investigate approaches and techniques related to the learning of source code changes, since the change identification step, learning, and reuse in recommending strategies. Method: We conducted a systematic review related to primary studies about source code changes. The search approach identified 2410 studies, up to and including 2012, which resulted in a final set of 39 selected papers. We grouped the studies according to each established research question. This review investigates how source code changes, which were performed in the past of software, can support the improvement of the software project. Results: The majority of approaches and techniques have used repetitiveness behavior of source code changes to identify structural or metrics patterns in software repositories, trough the evaluation of sequences of versions. To extract the structural patterns, the approaches have used programming-by-example techniques to differencing source code changes. In quality metrics analysis, the studies have applied mainly complexity and object-oriented metrics. Conclusion: The main implication of this review is that source code changes as examples, to support the improvement of coding practice during the development process, in which we presented some relevant strategies to guide each step, since identifying until the suggesting of source code changes.
Hamiltonian Monte Carlo Swindles

Hamiltonian Monte Carlo (HMC) is a powerful Markov chain Monte Carlo (MCMC) algorithm for estimating expectations with respect to continuous un-normalized probability distributions. MCMC estimators typically have higher variance than classical Monte Carlo with i.i. d. samples due to autocorrelations; most MCMC research tries to reduce these autocorrelations. In this work, we explore a complementary approach to variance reduction based on two classical Monte Carlo "swindles": first, running an auxiliary coupled chain targeting a tractable approximation to the target distribution, and using the auxiliary samples as control variates; and second, generating anti-correlated ("antithetic") samples by running two chains with flipped randomness. Both ideas have been explored previously in the context of Gibbs samplers and random-walk Metropolis algorithms, but we argue that they are ripe for adaptation to HMC in light of recent coupling results from the HMC theory literature. For many posterior distributions, we find that these swindles generate effective sample sizes orders of magnitude larger than plain HMC, as well as being more efficient than analogous swindles for Metropolis-adjusted Langevin algorithm and random-walk Metropolis.
Limits on Mode Coherence in Pulsating DA White Dwarfs Due to a Nonstatic Convection Zone

The standard theory of pulsations deals with the frequencies and growth rates of infinitesimal perturbations in a stellar model. Modes that are calculated to be linearly driven should increase their amplitudes exponentially with time; the fact that nearly constant amplitudes are usually observed is evidence that nonlinear mechanisms inhibit the growth of finite-amplitude pulsations. Models predict that the mass of convection zones in pulsating hydrogen-atmosphere (DAV) white dwarfs is very sensitive to temperature (i.e., ), leading to the possibility that even low-amplitude pulsators may experience significant nonlinear effects. In particular, the outer turning point of finite-amplitude g-mode pulsations can vary with the local surface temperature, producing a reflected wave that is out of phase with what is required for a standing wave. This can lead to a lack of coherence of the mode and a reduction in its global amplitude. In this paper we show that (1) whether a mode is calculated to propagate to the base of the convection zone is an accurate predictor of its width in the Fourier spectrum, (2) the phase shifts produced by reflection from the outer turning point are large enough to produce significant damping, and (3) amplitudes and periods are predicted to increase from the blue edge to the middle of the instability strip, and subsequently decrease as the red edge is approached. This amplitude decrease is in agreement with the observational data while the period decrease has not yet been systematically studied.
Improving Geometric and Dynamical Constraints on Cosmology with Intrinsic Alignments of Galaxies

We show that the spatial correlation of the intrinsic alignments (IAs) of galaxies, measured in galaxy redshift surveys, offers a precision route to improve the geometrical and dynamical constraints on cosmology. The IA has been treated as a contaminant against cosmological probes such as weak gravitational lensing experiments. However, the large-scale correlation of IAs is expected to follow the coherent large-scale matter inhomogeneities. Here, making use of its anisotropic nature, we show that the large-scale IA correlations help to improve the measurements of the geometric distances and growth of structure. In combination with the conventional galaxy clustering statistics, we find that constraints on equation-of-state parameter for dark energy and Hubble parameter can be tighter than those from the clustering statistics alone by a factor of more than 1.5.
Early Ultraviolet Observations of Type IIn Supernovae Constrain the Asphericity of Their Circumstellar Material

We present a survey of the early evolution of 12 Type IIn supernovae (SNe IIn) at ultraviolet and visible light wavelengths. We use this survey to constrain the geometry of the circumstellar material (CSM) surrounding SN IIn explosions, which may shed light on their progenitor diversity. In order to distinguish between aspherical and spherical CSM, we estimate the blackbody radius temporal evolution of the SNe IIn of our sample, following the method introduced by Soumagnac et al. We find that higher-luminosity objects tend to show evidence for aspherical CSM. Depending on whether this correlation is due to physical reasons or to some selection bias, we derive a lower limit between 35% and 66% for the fraction of SNe IIn showing evidence for aspherical CSM. This result suggests that asphericity of the CSM surrounding SNe IIn is common—consistent with data from resolved images of stars undergoing considerable mass loss. It should be taken into account for more realistic modeling of these events.
Robo-AO M-dwarf Multiplicity Survey: Catalog

We analyze observations from Robo-AO’s field M dwarf survey taken on the 2.1 m Kitt Peak telescope and perform a multiplicity comparison with Gaia DR2. Through its laser-guided, automated system, the Robo-AO instrument has yielded the largest adaptive optics M dwarf multiplicity survey to date. After developing an interface to visually identify and locate stellar companions, we selected 11 low-significance Robo-AO detections for follow-up on the Keck II telescope using NIRC2. In the Robo-AO survey we find 553 candidate companions within 4″ around 534 stars out of 5566 unique targets, most of which are new discoveries. Using a position cross-match with DR2 on all targets, we assess the binary recoverability of Gaia DR2 and compare the properties of multiples resolved by both Robo-AO and Gaia. The catalog of nearby M dwarf systems and their basic properties presented here can assist other surveys which observe these stars, such as the NASA TESS mission.
Delay Time Distributions of Type Ia Supernovae from Galaxy and Cosmic Star Formation Histories

We present analytical reconstructions of SN Ia delay time distributions (DTDs) by way of two independent methods: by a Markov Chain Monte Carlo best-fit technique comparing the volumetric SN Ia rate history to today’s compendium cosmic star formation history, and second through a maximum likelihood analysis of the star formation rate histories of individual galaxies in the GOODS/CANDELS field, in comparison to their resultant SN Ia yields. We adopt a flexible skew-normal DTD model, which could match a wide range of physically motivated DTD forms. We find a family of solutions that are essentially exponential DTDs, similar in shape to the β ≈ −1 power-law DTDs, but with more delayed events (>1 Gyr in age) than prompt events (<1 Gyr). Comparing these solutions to delay time measures separately derived from field galaxies and galaxy clusters, we find the skew-normal solutions can accommodate both without requiring a different DTD form in different environments. These model fits are generally inconsistent with results from single-degenerate binary population synthesis models, and are seemingly supportive of double-degenerate progenitors for most SN Ia events.
Growth and Productivity of Ammi visnaga as Affected by Organic Fertilizers Rate and Antioxidants Level

Two field experiments were conducted during two consecutive seasons of 2014 / 2015 and 2015 / 2016 at the Experimental Farm Faculty of Agriculture, Al-Azhar University to study the effect of organic fertilizers (compost at 10 or 20 and cattle manure at 15 or 30 m/feddan) and antioxidants (0.0, 75, 150 or 300 ppm from salicylic and citric acids, each applied individually) as well as, their combination treatments on vegetative growth parameters, fruit yield and active ingredients of khella (Ammi visnaga) plants under Assiut Governorate conditions. The obtained results cleared that using organic fertilization increased the values of plant height, herb dry weight per plant, fruit yield per plant and per feddan and khellin, visnagin and total chromones of khella plant. Since compost at 20 m per fed. was the superior treatment in this respect. Similarly, the highest values of such parameters were occurred salicylic acid at 75 ppm during both seasons. The interaction effects among different treatments appeared that the best results were achieved by the combination treatment between organic fertilization of compost at 20 m per feddan plus salicylic acid at 75 ppm. These combination treatments will promise in the development of sustainable crop production with a limited use of external inputs. That could be used by the farmers under Assiut Governorate conditions because this treatment has the most profitable rate and level with the greatest yield advantages.
Learning Classifiers from Declarative Language

Humans can efficiently learn new concepts using natural language communications. For example, a doctor can describe the concept of a malignant tumor through explanations such as ‘large tumors are usually malignant’. Here, the explanation does not only specify what attribute is important for learning the target concept (large size of a tumor), but the quantifier ‘usually’ also describes an expectation of its occurrence under the target model. In this work, we propose a framework through which such human advice can be converted to probabilistic constraints, which can drive the training of classification models without access to any labeled instances . We use semantic parsing to map sentences to probabilistic assertions that are grounded in observable attributes of the data, and employ a training framework that depends on the differential associative strength of linguistic quantifiers (e.g., ‘usually’ vs ‘always’). Our preliminary experiments show that this paradigm can reduce sample complexity of learning, and represents an encouraging direction for guiding machine learning using declarative knowledge.