Miracle-dz/UniFAR-FTUs huggingface dataset:
How Would Medicare for All Affect Health System Capacity? Evidence from Medicare for Some

Proposals to create a national health care plan such as “Medicare for All” rely heavily on reducing the prices that insurers pay for health care. These changes affect physicians’ short-run incentives for care provision and may also change health care providers’ incentives to invest in capacity, thereby influencing the availability of care in the long term. We provide evidence on these responses using a major Medicare payment change combined with survey data on physicians’ time use. We find evidence that physicians increase their time spent on capacity building when remuneration increases, and that they are subsequently more willing to accept new patients—especially those who may be the residual claimants on marginal capacity. These forces imply that short-run supply curves likely differ from long-run supply curves. Policymakers need to account for how major changes to payment incentives would influence the investments that determine health system capacity.
Removal Methods of Synthetic Dyes from Industrial Wastewater: A review

The textile industry has significant impacts on water through discharging effluents into various receiving bodies involving rivers, ponds and other public sewer. The main contaminants produced by textile industries are from several of their wetprocessing such as scouring, bleaching, mercerizing and dyeing. Dyeing process normally uses large amount of water for dyeing, fixing and washing processes. Dyes are using in several industries, like paper-making, textiles, plastic and foods industries. Wastewater contains dye has become one of the most pollution sources. The textile effluent treatment involves mainly physical, chemical and biological methods. Several treatment technologies are using now a days for removal of dye from industrial wastewater including coagulation, adsorption, biological methods, advanced oxidation processes (AOPs), membrane technologyandelectrochemical methods. Removal of dyes from industrial wastewater using various methods has been reviewed in this paper.
Current progress of blue-light photoreceptors of plant

Blue and ultraviolet-A light regulate a wide range of responses in plants, including phototropism, chloroplast migration and stomatal opening. However, the photoreceptors for these light responses have been identified only recently. Cryptochrome 1 and cryptochrome 2 are firstly elucidated. The phototropins (phot1 and phot2) represent a new class of receptor kinases that appear to be exclusive to plants. Recent genetic analysis has shown that phot1 and phot2 exhibit partially overlapping functions in mediating phototropism, chloroplast migration, and stomatal opening in Arabidopsis. The details of how this excitation activates such different responses remain to be elucidated.
Latency Minimization in a Fuzzy-Based Mobile Edge Orchestrator for IoT Applications

Currently, matching the incoming Internet of Things applications to the current state of computing and networking resources of a mobile edge orchestrator (MEO) is critical for providing the high quality of service while temporally and spatially changing the incoming workload. However, MEO needs to scale its capacity concerning a large number of devices to avoid task failure and to reduce service time. To cope with this issue, we propose MEO with fuzzy-based logic that splits tasks from mobile devices and maps them onto the cloud and edge servers to reduce the latency of handling these tasks and task failures. A fuzzy-based MEO handles the multi-criteria decision-making process to decide where the offloaded task should run by considering multiple parameters in the same framework. Our approach selects the appropriate host for task execution and finds the optimal task-splitting strategy. Compared to the existing approaches, the service time using our proposal can achieve up to 7.6%, 22.6%, 38.9%, and 51.8% performance gains for augmented reality, healthcare, compute-intensive, and infotainment applications, respectively.
A Bimodal Simulation of Defeasibility in the Normative Domain

In the present work we illustrate how two sorts of defeasible reasoning that are fundamental in the normative domain, that is, reasoning about exceptions and reasoning about violations, can be simulated via monotonic propositional theories based on a bimodal language with primitive operators representing knowledge and obligation. The proposed theoretical framework paves the way to using native theorem provers for multimodal logic, such as MleanCoP , in order to automate normative reasoning.
Functions of MicroRNAs in Animals

A large class of noncoding small RNAs called microRNAs (miRNAs) was found recently, which is closely related with the regulation of gene expression. Hundreds of miRNA genes have been discovered in various animals, and many of these are phylogenetically conserved. These miRNAs play important roles in physical development, death, proliferation and differentiation of cells, hormone secretion and carcinogenesis. This article reviews the advances in the research of the functions of animal miRNAs in recent years and the mechanism of miRNA action to provide important insight into the roles of microRNAs in the physiological and pathological process in animals.
Processing variations, nutritional and sensory quality of ethnic deep-fried meats from Kenyan pastoral communities

Deep-frying of meats has been done by indigenous pastoral communities from time immemorial for the unique taste, flavor, and exceptional shelf- stability. Traditional pastoral deep-fried meats have great potential as snacks in the global food basket due to their unique nutritional qualities and high satiety. Lost and weakening cultural ties have led to disparities in the deep-frying processing hurdles within and between different communities. The goal of this research was to study the peculiarities and uncover processing variations of ethnic deep-fried meats from indigenous people of the pastoral semi-arid lands and to explore how this translates to nutritional and sensory attributes of selected products from Kenya. A cross-sectional survey was conducted in Turkana, Kajiado, and Marsabit counties with data collected using Focus Group Discussions (FGDs). From each focus group, samples of the deep-fried meats were analyzed for nutritional and sensory characteristics using standard methods. Notable variations in the deep-frying process observed were the size of chunks, pre-drying techniques prior to deep-frying, and choice of deep-frying media. Shelf stability was achieved by oilencapsulating the chunks in solidified deep-frying media, fumigation of traditional packaging containers with smoke, and the use of spices. Variations on proximate contents were observed with moisture ranging between 8.1% and 28.5%, protein between 42.6% and 46.9%, lipids between 15.4% and 37.9%, ash between 3.1% and 4.3%, and energy between 424 Kcal/100g and 542 Kcal/100g. Differences in processing hurdles and storage contributed to variations in sensory attributes with pre-drying, smoking, and choice of deep-frying media contributing to the greatest variabilities. This notwithstanding, the study revealed a limitation on use of semi-trained panelists to bring out deep-cultural rooted ties that play a big role in the sensory acceptability of these indigenous products calling for caution before the interpretation of sensory data. In conclusion, variations in size of chunks, pre-drying technique, choice of deep-frying media, oil-encapsulation, and smoking among ethnic communities during the deepfrying process significantly contribute to differences in nutritional and sensory characteristics of deep-fried products. Key words: pastoral meat, ethnic meat, indigenous, deep-fried meat, nutrition quality, sensory quality
SRM drives an alternative for E-traction

For many designers of electrical machines, the term “soft magnetic materials” automatically means laminated electrical sheet. This is unfortunate, since for many applications, particularly at low frequencies, laminated sheet is rarely the best material choice. Soft magnetic powder materials are available to satisfy the needs of virtually any application imaginable, from plain iron, giving good induction for DC applications, to ultrahigh permeability nickel irons. The use of these materials brings with it all the attendant advantages of powder metallurgical (PM) production: low cost, tight tolerances, complicated forms, and minimal material waste. For high frequency applications, a range of soft magnetic composite materials or SMCs are available which can provide magnetic performance comparable to or surpassing that of laminated sheets, while at the same time allowing much greater freedom to the designer due to their isotropic nature, which permits the implementation of complicated 3D flux paths. This paper presents a review of the available powder-based soft magnetic materials, together with typical applications and a consideration of some of the factors which must be taken into account when producing powder-based components for magnetic applications. Keywords—soft magnetic materials, powder metallurgy, sinter, SMC, dielectromagnetic
Effect of Replacing Maize (Zea mays ) with Barley (Hordeum vulgare ) on Broilers Performance and Carcass Characteristics

A study was conducted to investigate the effect of feeding barley as a replacement for maize on the growth performance and carcass characteristics of Cobb 500 broiler chickens. One hundred and sixty-eight day old chicks were randomly assigned to four treatment diets with three replicates, having 14 chicks in each replication, in a completely randomized design. The treatment diets were maize 100% (T1) and maize substituted withbarley at 33.3% (T2), 66.7% (T3) and 100% (T4). Similar amount of concentrate mix was added to all treatments. The experiment was conducted for a total of 56 days, with the first 1- 21 days being the starter phase and the finisher phase lasted up to 56 days following the end of the starter phase. Feeds offered and refused was recorded every day, while body weight was recorded on a weekly basis. At the end of the experiment, two chickens from each sex were slaughtered per replication to evaluate the carcass components. The current results indicated higher crude protein, ash and crude fiber contents in barley than maize, while higher energy content was obtained from maize compared to barley. Starter phase diets gavesimilar feed intake values among treatments (36.8 - 38.8 g/day), showing a gradually decreasing trend with increasing levels of barley. Weight gains, growth rate and feed conversion ratio were similar up to 66.7% of maize replaced with barley. At finisher phase, daily feed intakes were 134.0-142.3 g with daily gains of 40.4-51.7g. For total period, daily feed intakes were 97.8-103.5 g with daily gains ranged from 31.2-38.8 g. Chicken under T1, T2and T3 showed similar values of feed intake and growth performance in the finisher and total feeding periods. Carcass yield was also similar for T1, T2 and T3. In conclusion, barley could be used as an alternative source of energy in broiler nutrition by replacing 2/3rd of the maize, especially in areas where maize is not available or less productive or where its price is high.
PERFORMANCE EVALUATION OF ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING OVER FREQUENCY SELECTIVE RAYLEIGH FADING HF CHANNEL

The effectiveness of Orthogonal Frequency Division Multiplexing (OFDM) with /4-DQPSK modulation is investigated, for communication over HF channel. The Fast Fourier Transform (FFT) is used to satisfy the orthogonality between subcarriers and reduce the implementation complexity. The system performance is investigated for various delay spreads, coherence time and number of propagation paths. A guard time with cyclic extension is used to reduce channel dispersion, intersymbol and intercarrier interference. Clipping is used to minimize the high peak-to-average power (PAP) ratio. ةصلاخلا ي ف د ماعتملا يددر تلا يمی سقتلا دد عتلا ة موظنم ة یلاعف ن م ق قحتلا م ت ث حبلا اذ ھ ) OFDM ( ة ینقت مادخت سا ع م نیمضتلا   DQPSK 4 /   ددر تلا ة یلاع ة یویدارلا ةا نق ل ثم نمز لا عم ةر یغتم ةا نق ر بع لا صتلال ) HF Channel . ( مدختسا عیرسلا ریروف لیوحت ) FFT ( یقحتل ءا نب ي ف د یقعتلا لیلقتو ةیوناثلا تلاماحلا نیب دماعتلا ق لا ة موظنم . را شتنلاا ریخأ ت ن م ة فلتخم می قب ة موظنملا ءادإ ن م ق قحتلا م ت ) delay spread ( ھكا شتلا ن مز ، ) Coherence time ( تاراسملا ددعو . ةسراحلا ةرتفلا مادختسا مت ) guard time ( يرودلا دادتملاا عم ) cyclic extension ( تلاماحلاو زومرلا نیب لخادتلا لیلقتل . عطقلا ةقیرط مادختسا مت ) clipping method ( ةبسن لیلقتل ةمیقلل ةردقلا – ىلإ – لدعملا ) PAP ( ةیلاعلا .
The internal agenda of Mercosur: interdependence, leadership and institutionalization

There are three sets of conditions for a process of regional integration to develop: demand, supply and inertial conditions. Demand conditions grow out of higher levels of regional interdependence, as transnational transactors perceive that cross-border activities are too costly and request national or supranational authorities to lower transactions costs through cooperation, coordination and, eventually, integration. Supply conditions refer to regional leadership, understood as the capacity and will of one or more actors either to pay a disproportionate share of the costs required by the regional undertaking (usually member states) or to provide monitoring, enforcement and regional coordination (usually supranational agencies). Inertial conditions take the form of demand or supply conditions that become institutionalized, locking in previous agreements and creating pathdependent effects –which may protect the integration process in times of declining demand or supply conditions, but may also turn it too rigid. In Mercosur, demand conditions are low, supply conditions are mostly inactive and very few inertial conditions have been created. This paper evaluates the current state and likely prospects of the bloc by singling out the areas in which these conditions are more likely to develop –or contract. The conclusion stresses the role of direct presidential involvement in deepening, enlarging and institutionalizing Mercosur –or failing to do so– and calls attention to the changing balance between fostering and administering interdependence.
G lobal J ournal of E ngineering S cience and R esearch M anagement

With the development of social network, there is a large amount of variable information has been made by social network users. We can mine these social data from social network, and find the preference latent relationship between user and items. We would make a model for the user and give a recommended items list to user with a suitable recommender algorithm. That is a variable research subject. So our research would achieve a personification recommender system based on matrix factorization. The research will deal with large-scale user-item ratings matrix. In order to improve the recommender systems’ performance we study the social relationship and the implicit feedback of the user. We add a social regularization, demographic information configuration term and users’ consumer records as item’s latent factor bias terms in the matrix factorization optimization function. Through experiments we recommend more accurate results than CF algorithm and SVD algorithm.
Response of planetary albedo to insolation perturbations

In the observations, there is almost a hemispheric symmetry of top-of-atmosphere reflected shortwave radiation (RSUT). This is in contrast to the surface reflected shortwave radiation (RSUS) revealing a clear hemispheric asymmetry. In their article, Voigt et al. (2013) could not rule out that the symmetry of RSUT is accidental, and found that the location of the ITCZ and clouds compensate for the asymmetry of RSUS.
Message passing for probabilistic models on networks with loops

In this paper, we extend a recently proposed framework for message passing on "loopy" networks to the solution of probabilistic models. We derive a self-consistent set of message passing equations that allow for fast computation of probability distributions in systems that contain short loops, potentially with high density, as well as expressions for the entropy and partition function of such systems, which are notoriously difficult quantities to compute. Using the Ising model as an example, we show that our solutions are asymptotically exact on certain classes of networks with short loops and offer a good approximation on more general networks, improving significantly on results derived from standard belief propagation. We also discuss potential applications of our method to a variety of other problems.
Performance-Based Screening of Porous Materials for Carbon Capture

Computational screening methods have changed the way new materials and processes are discovered and designed. For adsorption-based gas separations and carbon capture, recent efforts have been directed toward the development of multiscale and performance-based screening workflows where we can go from the atomistic structure of an adsorbent to its equilibrium and transport properties at different scales, and eventually to its separation performance at the process level. The objective of this work is to review the current status of this new approach, discuss its potential and impact on the field of materials screening, and highlight the challenges that limit its application. We compile and introduce all the elements required for the development, implementation, and operation of multiscale workflows, hence providing a useful practical guide and a comprehensive source of reference to the scientific communities who work in this area. Our review includes information about available materials databases, state-of-the-art molecular simulation and process modeling tools, and a complete catalogue of data and parameters that are required at each stage of the multiscale screening. We thoroughly discuss the challenges associated with data availability, consistency of the models, and reproducibility of the data and, finally, propose new directions for the future of the field.
Information theoretical view of QCD effective model with heavy quarks

To understand the phase transition phenomena, information theoretical approaches can pick up some important properties of the phenomena based on the probability distribution. In this paper, we show information theoretical aspects of the 3-dimensional 3-state Potts model with the external field which is corresponding to the QCD effective model with heavy quarks. The transfer mutual information which represents the information flow of two spin variables is numerically estimated based on the Markov-chain Monte-Carlo method. The transfer mutual information has the peak near the confinement-deconfinement transition, and it may be used to detect the precursors of the transition. Since the transfer mutual information still have the peak even if the Polyakov-loop changes continuously and smoothly, we may pick up some aspects of the confinement-deconfinement nature from the information flow properties. Particularly, the transfer mutual information shows the significantly different behavior below and above the Roberge-Weiss endpoint existed in the pure imaginary chemical potential region, which may indicate the system change by the confinement-deconfinement transition.
Explaining Chemical Toxicity using Missing Features

Chemical toxicity prediction using machine learning is important in drug development to reduce repeated animal and human testing, thus saving cost and time. It is highly recommended that the predictions of computational toxicology models are mechanistically explainable. Current state of the art machine learning classifiers are based on deep neural networks, which tend to be complex and harder to interpret. In this paper, we apply a recently developed method named contrastive explanations method (CEM) to explain why a chemical or molecule is predicted to be toxic or not. In contrast to popular methods that provide explanations based on what features are present in the molecule, the CEM provides additional explanation on what features are missing from the molecule that is crucial for the prediction, known as the pertinent negative. The CEM does this by optimizing for the minimum perturbation to the model using a projected fast iterative shrinkage-thresholding algorithm (FISTA). We verified that the explanation from CEM matches known toxicophores and findings from other work.
Matrix-Monotonic Optimization $-$ Part II: Multi-Variable Optimization

In contrast to Part I of this treatise (Xing, 2021) that focuses on the optimization problems associated with single matrix variables, in this paper, we investigate the application of the matrix-monotonic optimization framework in the optimization problems associated with multiple matrix variables. It is revealed that matrix-monotonic optimization still works even for multiple matrix-variate based optimization problems, provided that certain conditions are satisfied. Using this framework, the optimal structures of the matrix variables can be derived and the associated multiple matrix-variate optimization problems can be substantially simplified. In this paper several specific examples are given, which are essentially open problems. Firstly, we investigate multi-user multiple-input multiple-output (MU-MIMO) uplink communications under various power constraints. Using the proposed framework, the optimal structures of the precoding matrices at each user under various power constraints can be derived. Secondly, we considered the optimization of the signal compression matrices at each sensor under various power constraints in distributed sensor networks. Finally, we investigate the transceiver optimization for multi-hop amplify-and-forward (AF) MIMO relaying networks with imperfect channel state information (CSI) under various power constraints. At the end of this paper, several simulation results are given to demonstrate the accuracy of the proposed theoretical results.
Novel special affine wavelet transform and associated uncertainty principles

{. 2in} {\small {\bf Abstract. } Due to the extra degrees of freedom, special affine Fourier transform (SAFT) has achieved a respectable status within a short span and got versatile applicability in the areas of signal processing, image processing,sampling theory, quantum mechanics. However, due to its global kernel, SAFT fails to obtain local information of non-transient signals. To overcome this, we in this paper introduce the concept of novel special affine wavelet transform (NSAWT) and extend key harmonic analysis results to NSAWT analogous to those for the wavelet transform. We first establish some fundamental properties including Moyal's principle, Inversion formula and the range theorem. Some Heisenberg type inequalities and Pitt's inequality are established for SAFT and consequently Heisenberg uncertainity principle is derived for NSAWT.
Sound, Complete, Linear-Space, Best-First Diagnosis Search

Various model-based diagnosis scenarios require the computation of the most preferred fault explanations. Existing algorithms that are sound (i.e., output only actual fault explanations) and complete (i.e., can return all explanations), however, require exponential space to achieve this task. As a remedy, to enable successful diagnosis on memory-restricted devices and for memory-intensive problem cases, we propose RBF-HS, a diagnostic search method based on Korf's well-known RBFS algorithm. RBF-HS can enumerate an arbitrary fixed number of fault explanations in best-first order within linear space bounds, without sacrificing the desirable soundness or completeness properties. Evaluations using real-world diagnosis cases show that RBF-HS, when used to compute minimum-cardinality fault explanations, in most cases saves substantial space (up to 98 %) while requiring only reasonably more or even less time than Reiter's HS-Tree, a commonly used and as generally applicable sound, complete and best-first diagnosis search.