Miracle-dz/UniFAR-FTUs huggingface dataset:
The use of green ﬂuorescent protein (GFP) to select bovine embryos

A major factor limiting the transgenesis in domestic animals is the inefficiency of maintaining large numbers of recipients carrying nontransgenic foetuses. The objectives of this study were: 1. to determine the influence of green fluorescent protein (GFP) construct injection on the development of bovine embryos, 2. to identify and select the GFP positive bovine embryos, and 3. to determine the rate of mosaicism in transgenic embryos. Cattle oocytes were matured and fertilised in vitro and zygotes were microinjected with pCX-EGFP construct consisting of CMV-IE enhancer, chicken β-actin promoter, cDNA of GFP (EGFP-732 bp) and rabbit β-globin polyadenylation sequences. Embryos from control (64) and microinjected (198) groups were cultured in vitro. After 168 h of culture, morula and blastocysts were observed in 39.06% of control and in 23.23% of injected group. We obtained three GFP positive embryos (1.51% of injected zygotes and 6.52% of morulae/blastocysts). One of them was 100, second 75 and third 25% GFP positive (66.7% of mosaicism). Use of gfp gene reporter to select bovine embryos is useful method to increase transgenic offspring, because GFP marker allows to choice only transgenic embryos and transfer them to recipients.
The Effect of Polymeric Template Density and Solid Loading on the Properties of Ceramic Foam

This paper studies the effect of various polymeric foam template densities and solid loadings on the properties of ceramic foam. The study was based on six different polymeric foam templates with densities ranging from 13.4 to 37.8 kg/m 3 . The templates were impregnated in ceramic slurry with solid loading ranging from 15 to 60 wt. %. Effects of polymeric foam template density and solid loading quantity were evaluated based on porosity, density and mechanical properties of resulted ceramic foam. It was found that the density, porosity and flexural strength of ceramic foam seem to be independent from the template densities when the solid loading is less than 35 wt. %. For the given solid loading, i.e < 35 wt. %, the density and flexural strength are less than 1100 kg/m 3 and 6 MPa, respectively, and porosities are higher than 40 %. The polymer replication method is a versatile method for the production of ceramic foams. It will allow the production of any desired properties of ceramic foam through a simple modification route.
Cold Water Immersion: A Foe for Immediate Leg Strength Recovery Post Strenuous Activity

Recovery post sport activities of demanding nature has become a matter of great concern in present days. To add information in the knowledge bank regarding the rate and trend in lower limbs tiredness recovery due to cold water immersion (CWI) after strenuous workout present research in a highly controlled manner was conducted. Ten participants of equal caliber were selected purposively for the experiment. They ran at Target Heart Rate Zone of 80%-90% of their Maximum Heart Rate for 20 minutes, and had a session of idle CWI (20? C) post activity for 30 minutes. Isometric Leg Strength Test and Sergeant Jump Test were conducted pre activity, post activity and post CWI for availing data. Descriptive statistics, rANOVA and bonferroni post hoc test were employed using IBM SPSS-17. Level of significance choosen was 0.05. Significant decreased state of post workout readings were observed in both the cases. Further post recovery no improvement in state of lower limbs isometric strength was found, whereas decrease in explosive leg strength was evident. Thus it can be concluded that instead of being friend CWI is a foe for immediate leg strength recovery. In future more research having different and prolonged observation points can be framed to have clear idea on this issue. Keyword s : Sports, Recovery, Cold Water Immersion, Isometric Leg Strength, Explosive Leg Strength.
Serum Cystatin C Levels in Children with Nephrosis or Diabetes:A Pilot Study

Background:The glomerular filtration rate is the best overall index of renal function in health and disease.Recently, cystatin C,a low molecular weight pro- tein,freely filtered through the glomeru- lus and almost completely reabsorbed and catabolized by tubular cells,has been proposed as a new and very sensi- tive serum marker of change in glomerular filtration rate. Methods:This study investigated the relationship between cystatin C and cre- atinine in nephrotic and diabetic chil- dren.Serum cystatin C was determined by particle-enhanced immunoturbidime- try using the cystatin PET-kit.Serum creatinine,urea,and albumin were determined by auto-analyzer. Results:Sensitivity and specificity for , , , , .
Comparison of Outcomes after Phacoemulsification with Two Different Corneal Incision Distances Anterior to the Limbus

Purpose To compare visual performance and visual quality outcomes after phacoemulsification with two different clear corneal incision (CCI) distances anterior to the limbus in senile cataract patients. Methods Retrospective case series. Patients who had undergone phacoemulsification were divided into two groups according to the CCI distances anterior to the limbus. The CCI distances in group A range from 1 mm to 1.5 mm, while those in group B range from 0.5 mm to 1 mm. The visual acuity, refraction, surgically induced astigmatism (SIA), corneal aberrations, anterior segment parameters, and subjective vision quality were evaluated. Results This study enrolled 54 eyes, with 27 eyes per group. Both groups had significant improvement in postoperative uncorrected visual acuity (UCVA) and corrected distance visual acuity (CDVA) (P < 0.05). There were no statistically significant between-group differences in postoperative UDVA, CDVA, SIA, corneal aberrations, anterior segment parameters, or VF-QOL questionnaire performance (P > 0.05). Conclusions The phacoemulsification with CCI distances ranging from 0.5 mm to 1.5 mm is an effective and safe therapy to senile cataract. The CCI distance anterior to the limbus that ranges from 0.5 mm to 1.5 mm is recommended for routine phacoemulsification.
Spin-orbit interaction driven collective electron-hole excitations in a noncentrosymmetric nodal loop Weyl semimetal

NbP is one member of a new class of nodal loop semimetals characterized by the cooperative effects of spin-orbit coupling (SOC) and a lack of inversion center. Here transport and spectroscopic properties of NbP are evaluated using density functional theory methods. SOC together with the lack of inversion symmetry splits degeneracies, giving rise to “Russian doll nested” Fermi surfaces containing 4 × 10 −4 electron (hole) carriers/f.u. Due to the modest SOC strength in Nb, the Fermi surfaces map out the Weyl nodal loops. Calculated structure around T ∗ ≈ 100 K in transport properties reproduces well the observed transport behavior only when SOC is included, attesting to the precision of the (delicate) calculations and the stoichiometry of the samples. Low-energy collective electron-hole excitations (plasmons) in the 20–60 meV range result from the nodal loop splitting.
Fiscal Policy Interaction with Private Investment: The Case of Jordan

The purpose of this study was to find the impact of fiscal policy on private investment in Jordan. Stepwise regression method was utilized for this purpose. The model expresses private investment (PI) as a function of various levels and components of fiscal policy that include current expenditure (CE), capital expenditure (CI), internal public debt (IPD), external public debt (EPD), and tax revenue (TR). The statistical results indicate that the most effective variable on private investment in Jordan is current expenditure. We found that the coefficient of determination = 0.78 which is reflect the importance of this variable on private investment in Jordan. Recommendations were given based on results.
Training Sketches Training Images Partial Curriculum Construction CPPCL Sketch Features Image Features Cross-Modal Representations CDL Partial Curriculum Construction Self-paced Curriculum Learning Self-paced Curriculum Learning

In this paper we address the problem of learning robust cross-domain representations for sketch-based image retrieval (SBIR). While most SBIR approaches focus on extracting lowand mid-level descriptors for direct feature matching, recent works have shown the benefit of learning coupled feature representations to describe data from two related sources. However, cross-domain representation learning methods are typically cast into non-convex minimization problems that are difficult to optimize, leading to unsatisfactory performance. Inspired by self-paced learning, a learning methodology designed to overcome convergence issues related to local optima by exploiting the samples in a meaningful order (i.e. easy to hard), we introduce the cross-paced partial curriculum learning (CPPCL) framework. Compared with existing self-paced learning methods which only consider a single modality and cannot deal with prior knowledge, CPPCL is specifically designed to assess the learning pace by jointly handling data from dual sources and modality-specific prior information provided in the form of partial curricula. Additionally, thanks to the learned dictionaries, we demonstrate that the proposed CPPCL embeds robust coupled representations for SBIR. Our approach is extensively evaluated on four publicly available datasets (i.e. CUFS, Flickr15K, QueenMary SBIR and TU-Berlin Extension datasets), showing superior performance over competing SBIR methods.
Fracture-induced Q-anisotropy: Inversion for fracture parameters [Электронный ресурс]

Aligned vertical fractures are common in the Earth’s crust due to tectonic stresses and/or hydraulic fracturing. These fractures lead to azimuthally varying velocities and attenuations of P-, SVand SH-waves. We have extended Schoenberg’s elastic linear slip model of fractured medium to anelastic case. We invert synthetic data on velocities and attenuations in the cases of two anisotropic models, that is Transversely Isotropic with Horizontal symmetry axis (HTI) model and Orthorhombic (ORT) model. The first model, HTI, corresponds to a single set of parallel vertical fractures embedded in isotropic background. The second model, ORT, is for the same set of fractures, which are embedded in VTI background. We find fracture parameters – complex-valued weaknesses ∆N and ∆T – by inverting HTIand ORT-data on phase velocities and attenuations of P-, SVand SH-waves. Simulation examples are given for the inversion of VSP-type synthetic data. The aim of this work is to clarify how much would be the errors in the inversion for the fracture weaknesses if one uses HTI model instead of the more complicated but more realistic ORT model of fractured formation. The inversion results have clearly shown that both real and imaginary parts of normal weakness ∆N occurred to be extremely high in the case of the HTI-model employing instead of the actual ORT model. This may lead to false conclusion on dry fractures, whereas they were actually fluid-filled.
Fast Ignition: Physics Progress in the US Fusion Energy Program and Prospects for Achieving Ignition

Fast ignition (FI) has significant potential advantages for inertial fusion energy and it is therefore being studied as an exploratory concept in the US fusion energy program. FI is based on short pulse isochoric heating of pre-compressed DT by intense beams of laser accelerated MeV electrons or protons. Recent experimental progress in the study of these two heating processes is discussed. The goal is to benchmark new models in order to predict accurately the requirements for full-scale fast ignition. An overview is presented of the design and experimental testing of a cone target implosion concept for fast ignition. Future prospects and conceptual designs for larger scale FI experiments using planned high energy petawatt upgrades of major lasers in the US are outlined. A long-term roadmap for FI is defined.
Semantic Neural Machine Translation Using AMR

It is intuitive that semantic representations can be useful for machine translation, mainly because they can help in enforcing meaning preservation and handling data sparsity (many sentences correspond to one meaning) of machine translation models. On the other hand, little work has been done on leveraging semantics for neural machine translation (NMT). In this work, we study the usefulness of AMR (abstract meaning representation) on NMT. Experiments on a standard English-to-German dataset show that incorporating AMR as additional knowledge can significantly improve a strong attention-based sequence-to-sequence neural translation model.
Haemoglobin switching modulator SNPs rs5006884 is associated with increased HbA2 in β-thalassaemia carriers

Introduction Haemoglobin A2 (HbA2), the tetramer of α- and δ-globin chains, is used as a diagnostic biomarker for β-thalassaemia carriers. The HbA2 levels are regulated by the presence of HPFH, δ-thalassaemia, HbA1/2 gene triplication, and variants of KLF1, β-globin gene, and HbF regulating QTLs. Saudi Arabia has a high incidence of borderline HbA2 levels, thereby making it difficult to classify the haemoglobinopathies. This study aims to investigate the association of known HbF enhancer QTL gene SNPs with HbA2 levels Material and methods 14 Specific SNPs in BCL11A, HMIP, OR51B6, HBBP1, and HBG2 loci were genotyped in 164 Saudi β-thalassaemia carriers by TaqMan assay to validate their role as regulators of HbA2 levels. HbA2 levels were determined using the Variant II β-Thalassemia Short Program Recorder kit. The non-random association of these SNPs was tested using HaploView software. Protein interaction was assessed using 3D structure modelling for OR51B6 (rs5006884), comparative energy minimisation, and root-mean-square deviation (RMSD) prediction. Results Elevated HbA2 levels were associated with SNPs in HBBP1, OR51B6, and TCT haplotype from HBG2 promoter region. The bioinformatics modelling and prediction revealed that the exonic rs5006884 had RMSD value deviations and significantly varied binding energy minimisation. α-globin variations were found in 57.92% of individuals but were not associated with elevated HbA2. Conclusions The haemoglobin switching modulators rs2071348, rs7482144, and rs5006884 are involved in regulation of HbA2 level with rs5006884 influencing the tetramer formation. Screening for haemoglobinopathies should take these SNPs into consideration, specifically in borderline HbA2 cases. Assiduous analysis of rs5006884 as HbA2 modulator for amelioration of disease severity is recommended.
Disruption of Cerebellar Prediction in Verbal Working Memory

Mounting evidence suggests that the right cerebellum contributes to verbal working memory, but the functional role of this contribution remains unclear. In an established theory of motor control, the cerebellum is thought to predict sensory consequences of movements through an internal “forward model. ” Here, we hypothesize a similar predictive process can generalize to cerebellar non-motor function, and that the right cerebellum plays a predictive role that is beneficial for rapidly engaging the phonological loop in verbal working memory. To test this hypothesis, double-pulse transcranial magnetic stimulation (TMS) was administered over either the right cerebellum or right occipital lobe (control site), on half the trials, to interrupt the rehearsal of a 6-letter sequence. We found that cerebellar stimulation resulted in greater errors in participants’ report of the letter in the current position. Additional analyses revealed that immediately after cerebellar TMS, participants were more likely to use out of date information to predict the next letter in the sequence. This pattern of errors is consistent with TMS causing a temporary disruption of state estimation and cerebellar forward model function, leading to prediction errors in the phonological loop.
An Energy-efficient Time-domain Analog VLSI Neural Network Processor Based on a Pulse-width Modulation Approach

A time-domain analog-weighted-sum calculation model based on a pulse-width modulation (PWM) approach is proposed. The proposed calculation model can be applied to any types of network structure including multi-layer feedforward networks. We also propose very large-scale integrated (VLSI) circuits to implement the proposed model. Unlike the conventional analog voltage or current mode circuits used in computing-in-memory circuits, our time-domain analog circuits use transient operation in charging/discharging processes to capacitors. Since the circuits can be designed without operational amplifiers, they can be operated with extremely low power consumption. However, they have to use very high-resistance devices, on the order of giga-ohms. We designed a CMOS VLSI chip to verify weighted-sum operation based on the proposed model with binary weights, which realizes the BinaryConnect model. In the chip, memory cells of static-random-access memory (SRAM) are used for synaptic connection weights. High-resistance operation was realized by using the subthreshold operation region of MOS transistors unlike the ordinary computing-in-memory circuits. The chip was designed and fabricated using a 250-nm fabrication technology. Measurement results showed that energy efficiency for the weighted-sum calculation was 300~TOPS/W (Tera-Operations Per Second per Watt), which is more than one order of magnitude higher than that in state-of-the-art digital AI processors, even though the minimum width of interconnection used in this chip was several times larger than that in such digital processors. If state-of-the-art VLSI technology is used to implement the proposed model, an energy efficiency of more than 1,000~TOPS/W will be possible. For practical applications, development of emerging analog memory devices such as ferroelectric-gate field effect transistors (FeFETs) is necessary.
Identification of Potential Candidate Genes of Oral Cancer in Response to Chronic Infection With Porphyromonas gingivalis Using Bioinformatical Analyses

Recent investigations revealed the relationship between chronic periodontitis, Porphyromonas gingivalis and cancer. However, host genes that change in response to chronic infection with P. gingivalis and may contribute to oral cancer have remained largely unknown. In the present study, we aimed to comprehensively analyze microarray data obtained from the chronic infection model of immortalized oral epithelial cells that were persistently exposed to P. gingivalis for 15 weeks. Using protein-protein interaction (PPI) networks and Ingenuity Pathway Analysis (IPA), we identified hub genes, major biological processes, upstream regulators and genes potentially involved in tumor initiation and progression. We also validated gene expression and demonstrated genetic alteration of hub genes from clinical samples of head and neck cancer. Overall, we utilized bioinformatical methods to identify IL6, STAT1, LYN, BDNF, C3, CD274, PDCD1LG2, and CXCL10 as potential candidate genes that might facilitate the prevention and treatment of oral squamous cell carcinoma (OSCC), the most common type of head and neck squamous cell carcinoma (HNSCC).
When Energy Trading meets Blockchain in Electrical Power System: The State of the Art

With the rapid growth of renewable energy resources, energy trading has been shifting from the centralized manner to distributed manner. Blockchain, as a distributed public ledger technology, has been widely adopted in the design of new energy trading schemes. However, there are many challenging issues in blockchain-based energy trading, e.g., low efficiency, high transaction cost, and security and privacy issues. To tackle these challenges, many solutions have been proposed. In this survey, the blockchain-based energy trading in the electrical power system is thoroughly investigated. Firstly, the challenges in blockchain-based energy trading are identified and summarized. Then, the existing energy trading schemes are studied and classified into three categories based on their main focuses: energy transaction, consensus mechanism, and system optimization. Blockchain-based energy trading has been a popular research topic, new blockchain architectures, models and products are continually emerging to overcome the limitations of existing solutions, forming a virtuous circle. The internal combination of different blockchain types and the combination of blockchain with other technologies improve the blockchain-based energy trading system to better satisfy the practical requirements of modern power systems. However, there are still some problems to be solved, for example, the lack of regulatory system, environmental challenges and so on. In the future, we will strive for a better optimized structure and establish a comprehensive security assessment model for blockchain-based energy trading system.
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch

advertorch is a toolbox for adversarial robustness research. It contains various implementations for attacks, defenses and robust training methods. advertorch is built on PyTorch (Paszke et al., 2017), and leverages the advantages of the dynamic computational graph to provide concise and efficient reference implementations. The code is licensed under the LGPL license and is open sourced at this https URL .
MRI Robot for Prostate Focal Laser Ablation: An Ex Vivo Study in Human Prostate

Purpose: A novel grid-template-mimicking MR-compatible robot was developed for in-gantry MRI-guided focal laser ablation of prostate cancer. Method: A substantially compact robot was designed and prototyped to meet in-gantry lithotomy ergonomics and allow for accommodation in the perineum. The controller software was reconfigured and integrated with the custom-designed navigation and multi-focal ablation software. Three experiments were conducted: (1) free space accuracy test; (2) phantom study under computed tomography (CT) guidance for image-guided accuracy test and overall workflow; and (3) magnetic resonance imaging (MRI)-guided focal laser ablation of an ex vivo prostate. The free space accuracy study included five targets that were selected across the workspace. The robot was then commanded five times to each target. The phantom study used a gel phantom made with color changing thermos-chromic ink, and four spherical metal fiducials were deployed with the robot. Then, laser ablation was applied, and the phantom was sliced for gross observation. For an MR-guided ex vivo test, a prostate from a donor who died of prostate cancer was obtained and multi-focally ablated using the system within the MRI gantry. The tissue was sliced after ablation for validation. Results: free-space accuracy was 0.38 ± 0.27 mm. The overall system targeting accuracy under CT guidance (including robot, registration, and insertion error) was 2.17 ± 0.47 mm. The planned ablation zone was successfully covered in both acrylamide gel phantom and in human prostate tissue. Conclusions: The new robot can accurately facilitate fiber targeting for MR-guided focal laser ablation of targetable prostate cancer.
Point Cloud Denoising Based on Tensor Tucker Decomposition

In this paper, we propose a new algorithm for point cloud de-noising based on the tensor Tucker decomposition. We first represent the local surface patches of a noisy point cloud to be matrices by their distances to a reference point, and stack the similar patch matrices to be a 3rd order tensor. Then we use the Tucker decomposition to compress this patch tensor to be a core tensor of smaller size. We consider this core tensor as the frequency domain and remove the noise by manipulating the hard thresholding. Finally, all the fibers of the denoised patch tensor are placed back, and the average is taken if there are more than one estimators overlapped. The experimental evaluation shows that the proposed algorithm outperforms the state-of-the-art graph Laplacian regularized (GLR) algorithm when the Gaussian noise is high (σ = 0.1), and the GLR algorithm is better in lower noise cases (σ = 0.04, 0.05, 0.08).