Miracle-dz/UniFAR-FTUs huggingface dataset:
Surgical management of deficient alveolar ridges by means of guided bone regeneration in oral implantology

Dimensional changes in the alveolar ridge after extraction often compromises on achieving optimal implant stability and placement of implants in the right prosthodontic positions. These situations demand augmentation of the residual ridge to achieve successful implant placement and long-term survival. A minimum amount of bone width and height is essential for the successful placement of implants. Unfavourable local conditions, due to atrophy, trauma and periodontal disease, may provide insufficient bone volume or an unfavourable interarch relationship, which does not allow correct and a prosthodontically guided positioning of dental implants. Guided bone regeneration, ridge splitting, block graft, or distraction osteogenesis have all been applied for this purpose and have shown some promising results. Nonetheless, autogenous block graft remains one of the main methods for reconstructing severely resorbed maxilla. These block grafts can be harvested from intraoral or extraoral sites. Significant amounts of autogenous bone can be procured from symphysis or ramus region of the mandible. The cortical grafts of this area provide predictable increase in bone volume with a short healing time and yield a highly dense osseous architecture for implant placement.This review discusses the use of autogenous block grafts and bovine bone allograft for predictable bone augmentation in atrophic ridges.
A Diffeomorphic Flow-Based Variational Framework for Multi-Speaker Emotion Conversion

This paper introduces a new framework for non-parallel emotion conversion in speech. Our framework is based on two key contributions. First, we propose a stochastic version of the popular Cycle-GAN model. Our modified loss function introduces a Kullback–Leibler (KL) divergence term that aligns the source and target data distributions learned by the generators, thus overcoming the limitations of sample-wise generation. By using a variational approximation to this stochastic loss function, we show that our KL divergence term can be implemented via a paired density discriminator. We term this new architecture a variational Cycle-GAN (VCGAN). Second, we model the prosodic features of target emotion as a smooth and learnable deformation of the source prosodic features. This approach provides implicit regularization that offers key advantages in terms of better range alignment to unseen and out-of-distribution speakers. We conduct rigorous experiments and comparative studies to demonstrate that our proposed framework is fairly robust with high performance against several state-of-the-art baselines.
Antiviral Drugs Screening for Swine Acute Diarrhea Syndrome Coronavirus

Coronaviruses as possible cross-species viruses have caused several epidemics. The ongoing emergency of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has posed severe threats to the global economy and public health, which has generated great concerns about zoonotic viruses. Swine acute diarrhea syndrome coronavirus (SADS-CoV), an alpha-coronavirus, was responsible for mass piglet deaths, resulting in unprecedented economic losses, and no approved drugs or vaccines are currently available for SADS-CoV infection. Given its potential ability to cause cross-species infection, it is essential to develop specific antiviral drugs and vaccines against SADS-CoV. Drug screening was performed on a total of 3523 compound-containing drug libraries as a strategy of existing medications repurposing. We identified five compounds (gemcitabine, mycophenolate mofetil, mycophenolic acid, methylene blue and cepharanthine) exhibiting inhibitory effects against SADS-CoV in a dose-dependent manner. Cepharanthine and methylene blue were confirmed to block viral entry, and gemcitabine, mycophenolate mofetil, mycophenolic acid and methylene blue could inhibit viral replication after SADS-CoV entry. This is the first report on SADS-CoV drug screening, and we found five compounds from drug libraries to be potential anti-SADS-CoV drugs, supporting the development of antiviral drugs for a possible outbreak of SADS-CoV in the future.
MF-Storm: a maximum flow-based job scheduler for stream processing engines on computational clusters to increase throughput

Background A scheduling algorithm tries to schedule multiple computational tasks on a cluster of multiple computing nodes to maximize throughput with optimal utilization of computational and communicational resources. A Stream Processing Engine (SPE) is deployed to run streaming applications (computational tasks) on a computational cluster which helps execution and coordination of these applications. It is observed that there is a gap in the optimal mapping of a computational and communicational load of a streaming application on the underlying computational and communication power of the resources (cluster). Frequently communicated tasks are scheduled at different processing nodes with relatively slow communicating links. This increases network latency with a decrease in resource utilization. Hence, reduces the achieved throughput of the cluster significantly. Methods MF-Storm, a max-flow min-cut based job scheduler is presented to achieve a near-optimum schedule to maximize throughput. It schedules a streaming application by considering the processing, communication demands, available computational and communicational resources in a heterogeneous cluster, dynamically with minimized scheduling cost. To keep the scheduling cost minimum, the scheduler is built in a pipeline with two major stages: in the first stage, the application’s tasks graph is partitioned using the max-flow min-cut algorithm to minimize inter-partition traffic, and in the second stage, these partitions are assigned to computing nodes according to the computational power of the cluster’s nodes. Results Extensive experiments were done to evaluate the performance of MF-Storm using different topologies with multiple scenarios on a physical cluster implementation. Results showed on average 148% improvement in throughput with 30% less computational resources as compared to different state-of-the-art schedulers.
Temperature dependent magnetic properties of highly chemically ordered Fe55−xNixPt45L10 films

Magnetic media using materials with high uniaxial magneto-crystalline anisotropy, KU, combined with a thermal assist to overcome write field limitations have been proposed as one of the potential technologies to extend the areal density of magnetic disk recording beyond the limitations of current technology. Here we present an investigation on structural and temperature dependent magnetic properties of chemically ordered epitaxial Fe55−xNixPt45 thin films. Increasing Ni additions result in a steady reduction of magneto-crystalline anisotropy, saturation magnetization, and Curie temperature. The ability to control thermomagnetic properties over a wide range makes Fe55−xNixPt45 and similar FePt-based pseudo-binary alloys attractive base materials for media applications in thermally assisted magnetic recording.
Apps for Covid-19 in Germany: assessment using the German Mobile App Rating Scale

Abstract Objective The purpose of this study is to provide an overview of apps to help control the spread of Covid-19 in Germany and rate them according to standardized instruments. Materials and methods The Apple App Store and Google Play Store were systematically searched to identify apps dealing with Covid-19 in Germany. The German Mobile App Rating Scale (MARS-G) was used to independently assess app quality by 2 trained reviewers. Results Overall, the quality of the 6 rated apps was good with a mean score of 4.15 (3.88–4.34). The best-rated apps were NINA app (4.34) and Corona Health App (4.29). The best-rated sections were functionality (4.40), aesthetic (4.25), and information (4.25). In contrast, the worst-rated section was engagement (3.63). Even though some of the apps were used by more people than others, there was no correlation between the MARS-G rating and app store rating. In addition, the MARS-G proved to be effective even with rating apps, which have different goals and methods to achieve them. Conclusions To our knowledge, this is the first study that identified and evaluated German Covid-19 mobile health apps available in the German app stores. The review shows that despite the excellent quality in aspects like information and functionality, there is still a gap in the engagement section. To motivate more people to use the Covid-19 apps, new ideas are needed, besides more information and education about the functionality of the apps, to gain trust in app developers and raise the number of downloads.
Conformal Dynamics for TeV Physics and Cosmology

We introduce the topic of dynamical breaking of the electroweak symmetry and its link to unparticle physics and cosmology. The knowledge of the phase diagram of strongly coupled theories plays a fundamental role when trying to construct viable extensions of the standard model (SM). Therefore we present the state-of-the-art of the phase diagram for SU , Sp and SO gauge theories with fermionic matter transforming according to arbitrary representations of the underlying gauge group. We summarize several analytic methods used recently to acquire information about these gauge theories. We also provide new results for the phase diagram of the generalized Bars-Yankielowicz and Georgi-Glashow chiral gauge theories. These theories have been used for constructing grand unified models and have been the template for models of extended technicolor interactions. To gain information on the phase diagram of chiral gauge theories we will introduce a novel all orders beta function for chiral gauge theories. This permits the first unified study of all nonsupersymmetric gauge theories with fermionic matter representation both chiral and non-chiral. To the best of our knowledge the phase diagram of these complex models appears here for the first time. We will introduce recent extensions of the SM featuring minimal conformal gauge theories known as minimal walking models. Finally we will discuss the electroweak phase transition at nonzero temperature for models of dynamical electroweak symmetry breaking.
Photocatalytic Inactivation of Viruses and Prions: Multilevel Approach with Other Disinfectants

Ag, Cu, Zn, Ti, and Au nanoparticles show enhanced photocatalytic properties. Efficient indoor disinfection strategies are imperative to manage the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Virucidal agents, such as ethanol, sodium hypochlorite, 222-nm UV light, and electrolyzed water inactivate SARS-CoV-2 in indoor environments. Tungsten trioxide (WO3) photocatalyst and visible light disinfect abiotic surfaces against SARS-CoV-2. The titanium dioxide (TiO2)/UV system inactivates SARS-CoV-2 in aerosols and on deliberately contaminated TiO2-coated glass slide surfaces in photocatalytic chambers, wherein 405-nm UV light treatment for 20 min sterilizes the environment and generates reactive oxygen species (ROS) that inactivate the virus by targeting S and envelope proteins and viral RNA. Mesoscopic calcium bicarbonate solution (CAC-717) inactivates pathogens, such as prions, influenza virus, SARS-CoV-2, and noroviruses, in fluids; it presumably acts similarly on human and animal skin. The molecular complexity of cementitious materials promotes the photocatalysis of microorganisms. In combination, the two methods can reduce the pathogen load in the environment. As photocatalysts and CAC-717 are potent disinfectants for prions, disinfectants against prionoids could be developed by combining photocatalysis, gas plasma methodology, and CAC-717 treatment, especially for surgical devices and instruments.
Generating Safe Autonomous Decision-Making in ROS

The Robot Operating System (ROS) is a widely used framework for building robotic systems. It offers a wide variety of reusable packages and a pattern for new developments. It is up to developers how to combine these elements and integrate them with decision-making for autonomous behavior. The feature of such decision-making that is in general valued the most is safety assurance. In this research preview, we present a formal approach for generating safe autonomous decision-making in ROS. We first describe how to improve our existing static verification approach to verify multi-goal multi-agent decision-making. After that, we describe how to transition from the improved static verification approach to the proposed runtime verification approach. An initial implementation of this research proposal yields promising results.
A Novel Strategy for Identifying NSCLC MicroRNA Biomarkers and Their Mechanism Analysis Based on a Brand-New CeRNA-Hub-FFL Network

Finding reliable miRNA markers and revealing their potential mechanisms will play an important role in the diagnosis and treatment of NSCLC. Most existing computational methods for identifying miRNA biomarkers only consider the expression variation of miRNAs or rely heavily on training sets. These deficiencies lead to high false-positive rates. The independent regulatory model is an important complement to traditional models of co-regulation and is more impervious to the dataset. In addition, previous studies of miRNA mechanisms in the development of non-small cell lung cancer (NSCLC) have mostly focused on the post-transcriptional level and did not distinguish between NSCLC subtypes. For the above problems, we improved mainly in two areas: miRNA identification based on both the NOG network and biological functions of miRNA target genes; and the construction of a 4-node directed competitive regulatory network to illustrate the mechanisms. NSCLC was classified as lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) in this work. One miRNA biomarker of LUAD (miR-708-5p) and four of LUSC (miR-183-5p, miR-140-5p, miR-766-5p, and miR-766-3p) were obtained. They were validated using literature and external datasets. The ceRNA-hub-FFL involving transcription factors (TFs), microRNAs (miRNAs), mRNAs, and long non-coding RNAs (lncRNAs) was constructed. There were multiple interactions among these components within the net at the transcriptional, post-transcriptional, and protein levels. New regulations were revealed by the network. Meanwhile, the network revealed the reasons for the previous conflicting conclusions on the roles of CD44, ACTB, and ITGB1 in NSCLC, and demonstrated the necessity of typing studies on NSCLC. The novel miRNA markers screening method and the 4-node directed competitive ceRNA-hub-FFL network constructed in this work can provide new ideas for screening tumor markers and understanding tumor development mechanisms in depth.
Homogeneous Ring Oscillator with Staggered Layout for Gate-level Delay Characterization

Ring oscillator circuits are useful for the characterization of MOS transistors under switching operation. Accurate characterization of per-gate variation becomes difficult when the ring oscillator consists of many stages or contains heterogeneity. We propose a homogeneous ring oscillator structure with a staggered layout for the accurate characterization of per-gate characteristics. Using a header transistor instead of a NAND gate for oscillation control, our proposed structure can realize a 3-stage RO where the three stages have equal delay contributions. Measurement results from a 65 nm test chip confirm our proposed structure for gate-level characterization.
Optical Single-Shot Object Recognition in the Terahertz Spectral Domain

Imaging in the terahertz spectral region is costly and complex. Machine learning yields tools that allow the recognition of objects more efficiently than plain imaging. We present a single-shot optical machine learning approach for detecting objects in the terahertz spectral region by using a single pixel detector paired with a terahertz spatial light modulator.
On the origin of globular cluster bimodality

Abstract Globular cluster systems in most large galaxies display bimodal color and metallicity distributions, which are frequently interpreted as indicating two distinct modes of cluster formation. The metal-rich (red) and metal-poor (blue) clusters have systematically different locations and kinematics in their host galaxies. However, the red and blue clusters have similar internal properties, such as their masses, sizes, and ages. It is therefore interesting to explore whether both metal-rich and metal-poor clusters could form by a common mechanism and still be consistent with the bimodal distribution. We show that if all globular clusters form only during mergers of massive, gas-rich protogalactic disks, their metallicity distribution could be statistically consistent with that of the Galactic globulars. We take the galaxy assembly history from cosmological dark-matter simulations and couple it with the observed scaling relations for the amount of cold gas available for star formation. In the best-fitting model, early mergers of smaller hosts create exclusively blue clusters, while subsequent mergers of progenitor galaxies with a range of masses create both red and blue clusters. Thus, bimodality arises naturally as the result of a small number of late, massive merger events. We calculate cluster mass loss, including the effects of two-body scattering and stellar evolution, and find that more blue than red clusters are disrupted by the present time because of their lower initial masses and older ages. The present-day mass function in the best-fitting model is consistent with the Galactic distribution. However, the spatial distribution of model clusters is much more extended than observed and is independent of the parameters of our model.
Post-Operative Kidney Function Using Deep Hypothermic Circulatory Arrest (DHCA) in Aortic Arch Operation

Background Although deep hypothermic circulatory arrest (DHCA) is a useful option to protect the central nervous system during aortic arch operations, the influence of simultaneous renal ischemia remains controversial. Patients and Methods This is a retrospective observational study. Sixty-three patients who underwent thoracic aortic surgery with DHCA and 24 patients who underwent cardiac surgery without DHCA were included in this study. The mean age, preoperative serum creatinine (Cr) level, preoperative estimated glomerular filtration rate (eGFR), peak serum Cr level up to 48 hrs post-operative, elevation rate of Cr compared to the preoperative serum Cr, urine volume rate up to 48 hrs post-operative and AKI staging using the KDIGO criteria were estimated for each patient. Clinical parameters for 3 months after the operation and the 3-month post-operative mortality rate were assessed. Mean values indicating kidney function or distribution of the AKI stages were compared between patients with and without DHCA. Patients with DHCA were further divided according to the duration of ischemia to compare the values for the kidney function of each group, distribution of AKI stages and mortality. Results The parameters indicating AKI of the patients with DHCA were significantly more severe than those without DHCA. Patients who had undergone an ischemic state for more than 40 min revealed significantly higher peak serum Cr, elevation rate of serum Cr, less urine volume up to 48 hrs post-operative compared with those without DHCA. Distribution of the AKI stages was related to the duration of ischemia. The 3-month post-operative mortality of the patients with DHCA was significantly higher than those without DHCA. Limitations This study had limitations such as its retrospective design and small number patients, and the data will be required confirmation with other prospective studies. Conclusion DHCA is closely related to AKI up to 48 hrs post-operative and death during the 3 months following surgery.
Genome-Wide Identification of Membrane-Bound Fatty Acid Desaturase Genes in Three Peanut Species and Their Expression in Arachis hypogaea during Drought Stress

As a crop irrigated primarily by rain, the quality and yield of peanuts are significantly limited by drought. To date, many studies have indicated that fatty acid desaturase (FAD) genes enhance plant tolerance to drought stresses. In this study, 16, 15, and 31 FADs were identified in Arachis duranensis, Arachis ipaensis, and Arachis hypogaea, respectively. All the FADs were divided into four subfamilies, which had relatively conserved gene structures, motifs, and domains. The synteny relationships and chromosomal position analysis showed that the FADs in subgenome pairs, A. duranensis-A. hypogaea (AA) and A. ipaensis-A. hypogaea (BB), were homologous, and their physical locations were consistent. The Ka/Ks results indicated that nine FAD genes underwent a purifying selection, and Ah|FAD3.2 experienced positive selection during tetraploid peanut speciation. Various cis-acting elements related to hormone signaling and stress responsiveness in promoters and the predicted miRNA targeting Ah|FADs suggested that these genes play crucial roles in drought tolerance. The expression profiles of Ah|FADs in 22 tissues and drought-tolerant and -sensitive cultivars under drought stress suggested that 4 and 6 FADs were putative genes related to oil accumulation and drought, respectively. These findings will help provide insight into the potential functional roles of the FAD genes, which may aid in dealing with plant drought stress.
Kinetic or thermal AGN feedback in simulations of isolated and merging disc galaxies calibrated by the M-σ relation

We investigate two modes of coupling the feedback energy from a central AGN to the neighbouring gas in galaxy simulations: kinetic - velocity boost, and thermal - heating. We formulate kinetic feedback models for energy-driven wind (EDW) and momentum-driven wind (MDW), using two free parameters: feedback efficiencyǫf, and AGN wind velocity vw. A novel numerical algorithm is implemented in the SPH code GADGET-3, to prevent the expansion of a hole in the gas distribution around the BH. We perform simulations of isolated evolution and merger of disk galaxies, of Milky-Way mass as well as lower and higher masses. We find that in the isolated galaxy BH kinetic feedback generates intermittent bipolar jet-like gas outflows. We infer that current prescriptions for BH subgrid physics in galaxy simulations can grow the BH to observed values even in an isolated disk galaxy. The BH growth is enhanced in a galaxy merger, which consequently requires different model parameters to fit the observations than an isolated case. Comparing the [MBH σ⋆] relation obtained in our simulations with observational data, we conclude that it is possible to find parameter sets for a fit in all the models (e.g. vw = 10000 km/s and ǫf = 0.25 for BH kinetic EDW), except for the case with MDW feedback in a galaxy merger, in which the BH is always too massive. The BH thermal feedback implementation of Springel, Di Matteo & Hernquist (2005) within the multiphase star-formation model is found to have negligible impact on gas properties; and the effect claimed in all previous studies is attributed to gas depletion around the BH by the creation of an artificial hole. The BH mass accretion rate in our simulations exhibit heavy fluctuations. The star formation rate is quenched with feedback by removal of gas. The circumgalactic medium (CGM) gas at galactocentric distances (20 100)h 1 kpc are found to give the best metallicity observational diagnostic to distinguish between BH models.