Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized Alternate Mapping Correlated K‐Distribution Method for Atmospheric Longwave Radiative Transfer

Radiative transfer models are widely applied in climate models to simulate vertical temperature perturbations caused by external radiative forcings. A large part of radiative transfer models is the infrared gaseous spectral transmittance scheme, which quantifies the longwave atmospheric absorption. A rapid infrared gaseous spectral transmittance scheme, called the Optimized alternate Mapping Correlated K‐Distribution model (OMCKD), is introduced in this paper. To improve the accuracy of our scheme without increasing pseudo‐monochromatic calculations, we introduce the optimal iteration method to automatically tune the equivalent absorption coefficients in the cumulative probability subspace. In addition, a new expression weighted by black‐body radiation is introduced to calculate the equivalent absorption coefficient. The OMCKD simulates heating rate and radiation flux with errors of less than 0.12 K d−1 and 0.35 W m−2, respectively, below stratopause for standard atmospheric profiles. The OMCKD is also evaluated and compared with the rapid radiative transfer model for general circulation models (RRTMG) in realistic atmospheric profiles. We found that OMCKD can accurately produce heating rates and generally captures radiative forcings associated with large perturbations to the concentrations of main greenhouse gases. Furthermore, the number of pseudo‐monochromatic calculations in OMCKD is 11.4% less than that in RRTMG, which indicates less computational cost.
Adaptive CSI Feedback with Hidden Semantic Information Transfer

Channel state information (CSI) feedback has been a challenging task for downlink frequency division duplex (FDD) system. Meanwhile, sensory data collection in large-scale network is pivotal to support intelligent applications in the central server. In this paper, we propose a deep-learning-empowered adaptive CSI feedback compression and quantization based on the information-bottleneck principle, where the sensory data transmission is hidden within the CSI feedback to eliminate extra communication cost and preserve the data privacy at the same time. To reduce the impact of information hiding on CSI feedback, we focus on hiding data in the semantic level. The tradeoffs among communication efficiency, CSI accuracy, hidden information transfer accuracy, and privacy are jointly optimized. Simulations further verify that the proposed scheme can achieve accurate sensory data collection without resource occupation and accurate CSI feedback with limited feedback overhead simultaneously.
Inorganic Compounds as Remineralizing Fillers in Dental Restorative Materials: Narrative Review

Secondary caries is one of the leading causes of resin-based dental restoration failure. It is initiated at the interface of an existing restoration and the restored tooth surface. It is mainly caused by an imbalance between two processes of mineral loss (demineralization) and mineral gain (remineralization). A plethora of evidence has explored incorporating several bioactive compounds into resin-based materials to prevent bacterial biofilm attachment and the onset of the disease. In this review, the most recent advances in the design of remineralizing compounds and their functionalization to different resin-based materials’ formulations were overviewed. Inorganic compounds, such as nano-sized amorphous calcium phosphate (NACP), calcium fluoride (CaF2), bioactive glass (BAG), hydroxyapatite (HA), fluorapatite (FA), and boron nitride (BN), displayed promising results concerning remineralization, and direct and indirect impact on biofilm growth. The effects of these compounds varied based on these compounds’ structure, the incorporated amount or percentage, and the intended clinical application. The remineralizing effects were presented as direct effects, such as an increase in the mineral content of the dental tissue, or indirect effects, such as an increase in the pH around the material. In some of the reported investigations, inorganic remineralizing compounds were combined with other bioactive agents, such as quaternary ammonium compounds (QACs), to maximize the remineralization outcomes and the antibacterial action against the cariogenic biofilms. The reviewed literature was mainly based on laboratory studies, highlighting the need to shift more toward testing the performance of these remineralizing compounds in clinical settings.
New multifunctional bromine-active polymers: synthesis, properties, and antimicrobial activity

The increase in the frequency and scale of epidemics of infectious diseases gives extreme urgency to the development of new technologies for antiseptic and disinfectant treatment of various media, as well as materials/reagents for their implementation. Antimicrobial polymer materials of various chemical structures, including those containing halogen-active functional groups, are promising in this regard. This work is devoted to the synthesis and investigation of the properties of granular and fibrous polymer materials with immobilized N-bromosulfonamide groups of different structure. It is shown that copolymers of styrene with divinylbenzene and polypropylene can be used as a carrier polymer. A technique has been developed that allows obtaining polymers with a content of up to 23 % of immobilized active bromine. The compliance of the synthesized materials with the declared structure has been proven by IR spectroscopy and a complex of chemical methods. A decrease in the strength of the obtained polymers compared to the original carriers has been observed, especially in the case of fibers. The stability of the synthesized polymers during storage is lower that of the previously described chlorine-active analogs. For the quantitative determination of active bromine in the target materials, a technique based on its rapid diffusion from the polymer into the taurine solution has been developed. Microbiological research has shown that the synthesized polymers have a pronounced antimicrobial activity, which is higher than that of immobilized N-chlorosulfonamides and is manifested even in the presence of a significant organic load. The set of investigated characteristics of synthesized polymers with immobilized N-bromosulfonamide groups suggests the prospect of their use as components of antiseptic dressing materials, antimicrobial filters, devices for obtaining antiseptic solutions, and other medical products
A RANDOM-EFFECTS LOG-LINEAR MODEL WITH POISSON DISTRIBUTIONS

† In several applications data are grouped and there are within-group correlations. With continuous data, there are several available models that are often used; with counting data, the Poisson distribution is the natural choice. In this paper a mixed log-linear model based on a Poisson{Poisson conditional distribution is presented. The initial model is a conditional model for the mean of the response variable, and the marginal model is formed thereafter. Random efiects with Poisson distribution are introduced and a variance-covariance matrix for the response vector is formed embodying the covariance structure induced by the grouping of the data.
Soft-constrained predictive control for an overhead crane

Reduction of transient and residual payload swing in crane systems is a key control objective to guarantee the safety and efficiency requirements. The fast and accurate payload positioning with swing suppression within the acceptable range to avoid accidents is the challenging problem due to the underactuated nature of crane systems. Since the actuated motion causes undesirable payload swing, the efficient control method should be developed to ensure fast and precise payload positioning and meet the safety requirements. The standard model predictive control method is not suitable for underactuated mechanical systems. In this article the two, soft and hard-constrained antisway predictive control strategies are compared in experiments carried out on a laboratory scaled overhead travelling crane. The both control schemes are developed based on the linear parameter-varying model of a planar crane system. The recursive least square algorithm with parameter projection is used to estimate the model parameters. The soft-constrained optimization problem is solved using the particle swarm optimization algorithm with the inertia weight linearly decreasing during iteration. The metaheuristic optimizer is applied to determine the sequence of optimal control increments subject to the hard constraint of the control input and soft constraint of the payload swing. The comparison of hard and soft-constrained predictive controllers is carried out on a laboratory stand for different payload deflection constraints.
The Influence of Various Information About Insect Content and Its Advantages on the Acceptance of Foods Containing Insects

ABSTRACT Information about the content of food products affects the potential consumers’ willingness to purchase certain foodstuffs and include them in their diet. The presentation and scope of information are essential in the case of marketing specific products such as insect-based foods. The purpose of our study was to investigate the influence of information about a product’s advantages, coupled with verbal and visual information provided on the packaging, on the participants’ assessment of food containing insects. The participants (N = 659) were informed about the environmental or health benefits of ingesting insects. They were subsequently presented with a picture of a food product with different types of information about the insect content and asked to evaluate the product. The results suggest that providing images of insects on the packaging results in a lower assessment of the food containing insects. A brief presentation of the advantages of entomophagy has no impact on insect-based food assessment.
Towards Low-Power Heart Rate Estimation Based on User’s Demographics and Activity Level For Wearables

Over the past few years, wearable devices have become quite popular, in particular, smartwatches. One reason for this popularity is the possibility to monitor health and well-being in a non-invasive way. Heart Rate (HR) monitoring is one of the most important health features available in wearables. Normally, HR estimation is achieved using photoplethysmography (PPG), a common low-cost optical technique that achieves fair HR estimation in wearables. However, this technique is energy-consuming and significantly affects the device’s battery life for long-term monitoring – such as during physical exercises. In this work, we proposed a model based on linear regression and a Proportional–Integral–Derivative (PID) controller that uses an accelerometer and user’s demographics to estimate HR. The main goal of this model is to reduce power consumption since the accelerometer is a low-power sensor. We perform experiments to evaluate the performance of our method using three datasets containing more than 180 hours of data composed of a large number of different subjects. The results show that our method is competitive with a PPG-based approach and for some occasions, it is plausible to use such a model in order to save battery.
Toward Intelligent Sensing: Optimizing Lidar Beam Distribution for Autonomous Driving

LiDAR (Light Detection And Ranging) sensors have been widely used in autonomous vehicles as the main sensors. According to the specification details of the widely used 3D LiDAR products in the market, the distribution of vertical beam channels is set according to a uniform angular resolution, which is not ideally efficient for specific autonomous tasks. In this paper, we propose a novel approach to find the optimized angular distribution of the vertical beam channels for different application scenarios and installation configurations. The experimental results in a study case suggest that concerning the vehicle detection task, the optimized LiDARs perform almost two times better than the ones with the same number of channels in terms of the detection range, and have perception performances close to the LiDARs with double channels in the long distance.
EVALUATION AND FORECASTING OF THE ATMOSPHERIC CONCENTRATIONS OF ALLERGENIC POLLEN IN EUROPE

Diseases in the respiratory system due to aeroallergens, such as rhinitis and asthma, are major causes of a demand for increased healthcare, loss of productivity and an increased rate of morbidity. Pollenosis accounts for 12 45 % of overall allergy cases. The sensitisation to pollen allergens is increasing in most European regions. The adverse health effects of allergens can be reduced by preemptive medical measures. However, their planning requires reliable forecasts of high atmospheric pollen concentrations (Rantio-Lehtimäki, 1994), (Rantio-Lehtimäki & Matikainen 2002).
Atomic Force Microscopy Probing and Analysis of Polyimide Supramolecular Systems for Sensor Devices

A series of polyimide supramolecular systems containing different amounts of azochromophore were tested as flexible supports that can be used in the fabrication of certain devices, such as sensors for monitoring the temperature changes, by coating them with conductive metals. That is why it is required to have good interfacial compatibility between the flexible substrate and the inorganic layer. The interface of the sensor elements must be designed in such a way as to improve the sensitivity, accuracy, and response time of the device. Laser irradiation is one of the commonly employed techniques used for surface adaptation by patterning polyimides to increase contact and enhance device reliability and signal transmission. In this context, this work highlights unreported aspects arising from the azo-polyimide morphology, local nanomechanical properties and wettability, which are impacting the compatibility with silver. The texture parameters indicate an improvement of the modulations’ quality arising after laser irradiation through the phase mask, increasing the bearing capacity, fluid retention, and surface anisotropy when the amount of the azochromophore increases. The force curve spectroscopy and wettability studies indicated that the modification of the polymer morphology and surface chemistry lead to a better interfacial interaction with the metal lines when the azo component and the polyamidic acid are in equimolar quantities.
Genetic Profiling of Sodium Channels in Diabetic Painful and Painless and Idiopathic Painful and Painless Neuropathies

Neuropathic pain is a frequent feature of diabetic peripheral neuropathy (DPN) and small fiber neuropathy (SFN). Resolving the genetic architecture of these painful neuropathies will lead to better disease management strategies, counselling and intervention. Our aims were to profile ten sodium channel genes (SCG) expressed in a nociceptive pathway in painful and painless DPN and painful and painless SFN patients, and to provide a perspective for clinicians who assess patients with painful peripheral neuropathy. Between June 2014 and September 2016, 1125 patients with painful-DPN (n = 237), painless-DPN (n = 309), painful-SFN (n = 547) and painless-SFN (n = 32), recruited in four different centers, were analyzed for SCN3A, SCN7A-SCN11A and SCN1B-SCN4B variants by single molecule Molecular inversion probes-Next Generation Sequence. Patients were grouped based on phenotype and the presence of SCG variants. Screening of SCN3A, SCN7A-SCN11A, and SCN1B-SCN4B revealed 125 different (potential) pathogenic variants in 194 patients (17.2%, n = 194/1125). A potential pathogenic variant was present in 18.1% (n = 142/784) of painful neuropathy patients vs. 15.2% (n = 52/341) of painless neuropathy patients (17.3% (n = 41/237) for painful-DPN patients, 14.9% (n = 46/309) for painless-DPN patients, 18.5% (n = 101/547) for painful-SFN patients, and 18.8% (n = 6/32) for painless-SFN patients). Of the variants detected, 70% were in SCN7A, SCN9A, SCN10A and SCN11A. The frequency of SCN9A and SCN11A variants was the highest in painful-SFN patients, SCN7A variants in painful-DPN patients, and SCN10A variants in painless-DPN patients. Our findings suggest that rare SCG genetic variants may contribute to the development of painful neuropathy. Genetic profiling and SCG variant identification should aid in a better understanding of the genetic variability in patients with painful and painless neuropathy, and may lead to better risk stratification and the development of more targeted and personalized pain treatments.
The Dynamical Behavior of a Two Patch Predator-Prey Model

A two-patch Rosenzweig-MacArthur system describing predatorprey interaction in a spatially inhomogeneous environment is investigated. The global stability of equilibrium solutions for the homogeneous case is proved using Lyapunov functional, and stability analysis for the coexistence equilibrium is also given. Numerical bifurcation diagrams and numerical simulations of the limit cycle dynamics for the inhomogeneous case are obtained to compliment theoretical approach. Some of our results help to explain and clarify possible solutions to the Paradox of Enrichment in ecological studies.
On the Quantization of Recurrent Neural Networks for Smiles Generation

This paper focuses on the effects of applying quantization during training to Recurrent Neural Networks (RNNs) used in Simplified Molecular-Input Line-Entry System (SMILES) generation, a form of line notation for molecular information used in the development of pharmaceutical drugs, from the PubChem database. It offers the flexibility to choose the precision used by the model, by defining the number of bits at each layer. The RNNs are the focus of the current study, by comparing the performance of three of the most used algorithms, Simple RNN, Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The models were trained on a selection of SMILES. By exploiting the QK-eras library, quantization performance was compared to their floating-point equivalent for several combinations of parameters. The goal of the testing program developed is to generate a large number of novel SMILES, facilitating the process of Drug Discovery which is traditionally long, and thus very expensive and difficult. By understanding how the behavior of quantized networks deviates from the regular model, in relation to the parameters used, we are able to control the process of choosing whether to quantize a model and to which degree it becomes more or less efficient. In this study, we observed good performance even for 4-bit models making use of LSTM and GRU layers, the same way we concluded that Simple RNN quantization does not compensate the effort.
Role of Macroautophagy in Mammalian Male Reproductive Physiology

Physiologically, autophagy is an evolutionarily conserved and self-degradative process in cells. Autophagy carries out normal physiological roles throughout mammalian life. Accumulating evidence shows autophagy as a mechanism for cellular growth, development, differentiation, survival, and homeostasis. In male reproductive systems, normal spermatogenesis and steroidogenesis need a balance between degradation and energy supply to preserve cellular metabolic homeostasis. The main process of autophagy includes the formation and maturation of the phagophore, autophagosome, and autolysosome. Autophagy is controlled by a group of autophagy-related genes that form the core machinery of autophagy. Three types of autophagy mechanisms have been discovered in mammalian cells: macroautophagy, microautophagy, and chaperone-mediated autophagy. Autophagy is classified as non-selective or selective. Non-selective macroautophagy randomly engulfs the cytoplasmic components in autophagosomes that are degraded by lysosomal enzymes. While selective macroautophagy precisely identifies and degrades a specific element, current findings have shown the novel functional roles of autophagy in male reproduction. It has been recognized that dysfunction in the autophagy process can be associated with male infertility. Overall, this review provides an overview of the cellular and molecular basics of autophagy and summarizes the latest findings on the key role of autophagy in mammalian male reproductive physiology.
Pave Israel 96 DESIGN THEORY AND METHOD OF INTERLOCKING CONCRETE BLOCK PAVING FOR PORT AREAS

L. Sun Tongji University Shanghai. P.R. China Since 1984, the interlocking concrete block pavement has been increasingly used for the paving of port areas, and corresponding studies, including the tests in laboratory and in situ, and the mechanical analysis based on the finite element method, have been conducted in P.R. China. Based on the results of the tests and analysis, the design method with multi _criteria, including deflection, rutting depth and flexural stress at the underside of semiJigid basecourses, has been developed. Introduction In P.R. China, the interlocking concrete block pavement is a new type of pavement. In 1984, the concrete block paving for port areas were constructed in Huangpu harbour, Guangzhou, which is first trial application of block pavement in China. Since then, the block paving has increasingly been used in the port areas because it is more economical and has better suitability to the poor foundations than other forms of paving. As compared with the design of highway pavements, the port paving have a lot of special features, especially in the considerations of the loads. The range of the loads carried out by port paving are very wide (from 20kN to 500 kN), and the number of load repetitions are much less than on highway pavements. In the structural design of port paving, the concentrated and heavy loads playa dominant role so as to it won't proper if the design criteria, design methods and design parameters for the highway asphalt pavements are directly used for the port paving. In order to clarifY the load spreading mechanism of interlocking block layer and to develop a structural design method of block paving suitable for port areas, author conducted the full scale plate_loading_tests in laboratory and insitu respectively in 1984-1985 and 1991-1992. On the basis of the results ofthe tests,a model for the mechanic analysis of block paving and corresponding computer software were developed, and in conjunction with the design experience and design custom, the design method and design nomograph for port paving,
Fuzzy Shortest Route Algorithm for Telephone Line Connection

In computer science, there are many algorithm that finds a minimum spanning tree for a connected weighted undirected fuzzy graph. This means it finds a subset of the edge- set that forms a fuzzy spanning tree that includes every vertex, where the total weight of all the edges in the fuzzy tree is minimized. Generally algorithm has many applications, such as landline (intercom) phone connection to a particular college in order to minimize the shortest distance, which applies Nearest Neighbor Algorithm, Sorted Edges Algorithm, Kruskal's Algorithm to a randomly weighted fuzzy graph. In this paper, we find the solution for the problem, that A.V. V.M. Sri Pushpam College, (Autonomous), Poondi, Thanjavur District, South India need to connect updated intercom lines connecting all the departments using fuzzy shortest route algorithm. The problem is to minimize the amount of new line using Kruskal's Algorithm with fuzzy graph. These algorithm continuously increases the size of a fuzzy tree, one edge at a time, starting with a fuzzy tree consisting of a single vertex, until it spans all vertices of the fuzzy graph.