Miracle-dz/UniFAR-FTUs huggingface dataset:
A study on facial expressions recognition

In terms of communication, postures and facial expressions of such feelings like happiness, anger and sadness play important roles in conveying information. With the development of the technology, recently a number of algorithms dealing with face alignment, face landmark detection, classification, facial landmark localization and pose estimation have been put forward. However, there are a lot of challenges and problems need to be fixed. In this paper, a few technologies have been concluded and analyzed, and they all relate to handling facial expressions recognition and poses like pose-indexed based multi-view method for face alignment, robust facial landmark detection under significant head pose and occlusion, partitioning the input domain for classification, robust statistics face formalization.
OPTIMIZATION OF BACTERIAL INOCULUM CONCENTRATION AND pH FOR THE PRODUCTION OF AMYLASE AND PROTEASE USING Proteus sp. FROM SAGO EFFLUENT.

S. Kavipriya 1 and P. Kousalya 2 . 1. II-M.Sc. Biochemistry, Department of Biochemistry, Bharathidasan College of Arts and Science, Erode, Tamilnadu, India. 2. Assistant Professor, Department of Biochemistry, Bharathidasan College of Arts and Science, Erode, Tamilnadu, India. Manuscript Info Abstract . Manuscript History
In Search of Social Democracy

The national shift to the left, with all its implications for the balance of power, may be accepted as permanent . Any Government which tampered seriously with the basic structure of the full-employment Welfare State would meet with a sharp reverse at the polls . It is this which explains the otherwise curious phenomenon that the Conservatives now fi ght elections largely on policies which twenty years ago were associated with the left, and repudi-ated by the right . The fact that the political battle today is waged mainly on ground chosen by the left is remarkable evidence of the change in national ideology . (C. A. R. Crosland, The Future of Socialism , 1956: 28–9, 61)
Detection and characterization of exercise induced muscle damage (EIMD) via thermography and image processing

Exercise induced muscle damage (EIMD), is usually experienced in i) humans who have been physically inactive for prolonged periods of time and then begin with sudden training trials and ii) athletes who train over their normal limits. EIMD is not so easy to be detected and quantified, by means of commonly measurement tools and methods. Thermography has been used successfully as a research detection tool in medicine for the last 6 decades but very limited work has been reported on EIMD area. The main purpose of this research is to assess and characterize EIMD, using thermography and image processing techniques. The first step towards that goal is to develop a reliable segmentation technique to isolate the region of interest (ROI). A semi-automatic image processing software was designed and regions of the left and right leg based on superpixels were segmented. The image is segmented into a number of regions and the user is able to intervene providing the regions which belong to each of the two legs. In order to validate the image processing software, an extensive experimental investigation was carried out, acquiring thermographic images of the rectus femoris muscle before, immediately post and 24, 48 and 72 hours after an acute bout of eccentric exercise (5 sets of 15 maximum repetitions), on males and females (20-30 year-old). Results indicate that the semi-automated approach provides an excellent bench-mark that can be used as a clinical reliable tool.
The ordinary surface universality class of the three-dimensional 
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 model

We study the critical behavior at the ordinary surface universality class of the three-dimensional O($N$) model, bounded by a two-dimensional surface. Using high-precision Monte Carlo simulations of an improved lattice model, where the leading bulk scaling correction is suppressed, and finite-size scaling analysis of the fourth cumulant of the surface magnetization, we obtain precise estimates of the scaling dimension of the surface field operator for $N=2,3,4$. We also determine the fixed-point values of two renormalization-group invariant observables, which characterize the finite-size scaling behavior at the ordinary transition.
Parallel Private Retrieval of Merkle Proofs via Tree Colorings

Motivated by a practical scenario in blockchains in which a client, who possesses a transaction, wishes to privately verify that the transaction actually belongs to a block, we investigate the problem of private retrieval of Merkle proofs (i.e. proofs of inclusion/membership) in a Merkle tree. In this setting, one or more servers store the nodes of a binary tree (a Merkle tree), while a client wants to retrieve the set of nodes along a root-to-leaf path (i.e. a Merkle proof, after appropriate node swapping operations), without letting the servers know which path is being retrieved. We propose a method that partitions the Merkle tree to enable parallel private retrieval of the Merkle proofs. The partitioning step is based on a novel tree coloring called ancestral coloring in which nodes that have ancestor-descendant relationship must have distinct colors. To minimize the retrieval time, the coloring is required to be balanced, i.e. the sizes of the color classes differ by at most one. We develop a fast algorithm to find a balanced (in fact, any) ancestral coloring in almost linear time in the number of tree nodes, which can handle trees with billions of nodes in a few minutes. Our partitioning method can be applied on top of any private information retrieval scheme, leading to the minimum storage overhead and fastest running times compared to existing approaches.
Modelling of Functional Profiles and Explainable Shape Shifts Detection: An Approach Combining the Notion of the Fréchet Mean with the Shape-Invariant Model

A modelling framework suitable for detecting shape shifts in functional profiles combining the notion of the Fréchet mean and the concept of deformation models is developed and proposed. The generalized mean sense offered by the Fréchet mean notion is employed to capture the typical pattern of the profiles under study, while the concept of deformation models, and in particular of the shape-invariant model, allows for interpretable parameterizations of the profile’s deviations from the typical shape. The EWMA-type control charts compatible with the functional nature of data and the employed deformation model are built and proposed, exploiting certain shape characteristics of the profiles under study with respect to the generalized mean sense, allowing for the identification of potential shifts concerning the shape and/or the deformation process. Potential shifts in the shape deformation process are further distinguished into significant shifts with respect to amplitude and/or the phase of the profile under study. The proposed modeling and shift detection framework is implemented to a real-world case study, where daily concentration profiles concerning air pollutants from an area in the city of Athens are modeled, while profiles indicating hazardous concentration levels are successfully identified in most cases.
Approximate Optimal Controller Synthesis for Cart-Poles and Quadrotors via Sums-of-Squares

Sums-of-squares (SOS) optimization is a promising tool to synthesize certifiable controllers for nonlinear dynamical systems. Building upon prior works (Lasserre et al., 2008), (Jiang and Jiang, 2015), we demonstrate that SOS can synthesize dynamic controllers with bounded suboptimal performance for various underactuated robotic systems by finding good approximations of the value function. We summarize a unified SOS framework to synthesize both under- and over- approximations of the value function for continuous-time, control-affine systems, use these approximations to generate approximate optimal controllers, and perform regional analysis on the closed-loop system driven by these controllers. We then extend the formulation to handle hybrid systems with contacts. We demonstrate that our method can generate tight under- and over- approximations of the value function with low-degree polynomials, which are used to provide stabilizing controllers for continuous-time systems including the inverted pendulum, the cart-pole, and the quadrotor as well as a hybrid system, the planar pusher. To the best of our knowledge, this is the first time that a SOS-based time-invariant controller can swing up and stabilize a cart-pole, and push the planar slider to the desired pose.
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation

To achieve the highest perceptual quality, state-of-the-art diffusion models are optimized with objectives that typically look very different from the maximum likelihood and the Evidence Lower Bound (ELBO) objectives. In this work, we reveal that diffusion model objectives are actually closely related to the ELBO. Specifically, we show that all commonly used diffusion model objectives equate to a weighted integral of ELBOs over different noise levels, where the weighting depends on the specific objective used. Under the condition of monotonic weighting, the connection is even closer: the diffusion objective then equals the ELBO, combined with simple data augmentation, namely Gaussian noise perturbation. We show that this condition holds for a number of state-of-the-art diffusion models. In experiments, we explore new monotonic weightings and demonstrate their effectiveness, achieving state-of-the-art FID scores on the high-resolution ImageNet benchmark.
Single‐cell third‐generation sequencing‐based multi‐omics uncovers gene expression changes governed by ecDNA and structural variants in cancer cells

Abstract Background Cancer cells often exhibit large‐scale genomic variations, such as circular extrachromosomal DNA (ecDNA) and structural variants (SVs), which have been highly correlated with the initiation and progression of cancer. Currently, no adequate method exists to unveil how these variations regulate gene expression in heterogeneous cancer cell populations at a single‐cell resolution. Methods Here, we developed a single‐cell multi‐omics sequencing method, scGTP‐seq, to analyse ecDNA and SVs using long‐read sequencing technologies. Results and Conclusions We demonstrated that our method can efficiently detect ecDNA and SVs and illustrated how these variations affect transcriptomic changes in various cell lines. Finally, we applied and validated this method in a clinical sample of hepatocellular carcinoma (HCC), demonstrating a feasible way to monitor the evolution of ecDNA and SVs during cancer progression.
The analysis of fecal calprotectin as a diagnostic marker for anastomotic leakage after rectal cancer surgery: a pilot study

Abstract A prospective pilot study was conducted on 11 patients with rectal cancer to investigate fecal calprotectin (FC) as a diagnostic tool for detecting anastomotic leakage (AL) after low anterior resection. Among the 11 patients, 1 patient (9.1%) experienced AL (Clavien-Dindo Grade IIIa). During the post-operative course until post-operative day (POD) 5, the white blood cell count of the patient with AL was within the normal range. The C-reactive protein level in the AL and non-AL groups showed a similar time course. On the other hand, the FC level in patient with AL dramatically increased on POD5, while the FC level of the non-AL group remained relatively stable. There was no significant correlation between the preoperative FC level and the tumor circumference rate, tumor size, depth of invasion or stage. This pilot study showed the possibility of FC as a useful diagnostic tool for the detection of AL after low anterior resection for rectal cancer.
Smart Decisions by Small Adjustments: Iterating Denoising Autoencoders

An iterative neural architecture based on repeated application of the Denoising Autoencoder is introduced. The architecture is placed in the family of other approaches involving networks of simple units and iteration at the exploitation stage. It is shown that repeated feeding of a pattern to a Denoising Autoencoder often yields non-trivial sensible improvements of the pattern. This statement is supported by a classification experiment, in which the data transformed by our architecture is shown to be more linearly separable than the original samples.
Convergence and divergence in spherical harmonic series of the gravitational field generated by high‐resolution planetary topography—A case study for the Moon

Theoretically, spherical harmonic (SH) series expansions of the external gravitational potential are guaranteed to converge outside the Brillouin sphere enclosing all field‐generating masses. Inside that sphere, the series may be convergent or may be divergent. The series convergence behavior is a highly unstable quantity that is little studied for high‐resolution mass distributions. Here we shed light on the behavior of SH series expansions of the gravitational potential of the Moon. We present a set of systematic numerical experiments where the gravity field generated by the topographic masses is forward‐modeled in spherical harmonics and with numerical integration techniques at various heights and different levels of resolution, increasing from harmonic degree 90 to 2160 (~61 to 2.5 km scales). The numerical integration is free from any divergence issues and therefore suitable to reliably assess convergence versus divergence of the SH series. Our experiments provide unprecedented detailed insights into the divergence issue. We show that the SH gravity field of degree‐180 topography is convergent anywhere in free space. When the resolution of the topographic mass model is increased to degree 360, divergence starts to affect very high degree gravity signals over regions deep inside the Brillouin sphere. For degree 2160 topography/gravity models, severe divergence (with several 1000 mGal amplitudes) prohibits accurate gravity modeling over most of the topography. As a key result, we formulate a new hypothesis to predict divergence: if the potential degree variances show a minimum, then the SH series expansions diverge somewhere inside the Brillouin sphere and modeling of the internal potential becomes relevant.
Understanding of Macroscopic, Microscopic and Symbolic Representations Among Form Four Students in Solving Stoichiometric Problems

The purpose of this article is to determine the levels of understanding for solving Stoichiometry problems from the aspect of macroscopic, microscopic and symbolic representations of high, average and low achieving students after infusion of metacognitive skills. Nine form four students aged sixteen years old from a secondary school in Kuala Lumpur, Malaysia were involved in this research. Data were collected through thinking aloud sessions and documents of students’ worksheets. Findings showed that the level of understanding from the aspect of the macroscopic, microscopic and symbolic representations among high achieving students appeared high and solved all the Stoichiometry problems related to balancing chemical equations at the end of the infusion. The average and low achieving students also seemed to understand the three levels of representations and could solve most of the problems except that they could not understand the mole ratio in balancing chemical equations. This implies that the understanding of the mole ratio is necessary for solving stoichiometric problems
Platelet Function Decreases with Increasing Severity of Liver Cirrhosis and Portal Hypertension—A Prospective Study

BACKGROUND AND AIMS Cirrhotic patients display an increased risk for both bleeding and thrombosis. We investigated platelet activation across Child-Pugh stages (CPSs) and portal hypertension (PH) severity. METHODS A total of 110 cirrhotic patients were prospectively included. CPS and hepatic venous pressure gradient (HVPG) were determined. Platelet surface expression of P-selectin and activated glycoprotein (GP) IIb/IIIa were measured by flow cytometry before/after stimulation with protease-activated receptor (PAR)-1 (thrombin receptor activating peptide, TRAP) and PAR-4 (AYPGKF) agonists, epinephrine, and lipopolysaccharide (LPS). RESULTS Platelet count was similar across CPS but lower with increasing PH severity. Expression of P-selectin and activated GPIIb/IIIa in response to TRAP and AYPGKF was significantly reduced in platelets of CPS-B/C versus CPS-A patients (all p < 0.05). Platelet P-selectin expression upon epinephrine and LPS stimulation was reduced in CPS-C patients, while activated GPIIb/IIIa in response to these agonists was lower in CPS-B/C (all p < 0.05). Regarding PH severity, P-selectin and activated GPIIb/IIIa in response to AYPGKF were lower in HVPG ≥20 mmHg patients (both p < 0.001 vs. HVPG < 10 mmHg). Similarly, activated GPIIb/IIIa was lower in HVPG ≥20 mmHg patients after TRAP stimulation (p < 0.01 vs. HVPG < 10 mmHg). The lower platelet surface expression of P-selectin and activated GPIIb/IIIa upon stimulation of thrombin receptors (PAR-1/PAR-4) in CPS-B/C and HVPG ≥20 mmHg patients was paralleled by reduced antithrombin-III levels in those patients (all p < 0.05). Overall, PAR-1- and PAR-4-mediated platelet activation correlated with antithrombin-III levels (p < 0.001). CONCLUSION Platelet responsiveness decreases with increasing severity of liver cirrhosis and PH but is potentially counterbalanced by lower antithrombin-III levels.
ShinyBioHEAT: an interactive shiny app to identify phenotype driver genes in E.coli and B.subtilis

Abstract Summary In any population under selective pressure, a central challenge is to distinguish the genes that drive adaptation from others which, subject to population variation, harbor many neutral mutations de novo. We recently showed that such genes could be identified by supplementing information on mutational frequency with an evolutionary analysis of the likely functional impact of coding variants. This approach improved the discovery of driver genes in both lab-evolved and environmental Escherichia coli strains. To facilitate general adoption, we now developed ShinyBioHEAT, an R Shiny web-based application that enables identification of phenotype driving gene in two commonly used model bacteria, E.coli and Bacillus subtilis, with no specific computational skill requirements. ShinyBioHEAT not only supports transparent and interactive analysis of lab evolution data in E.coli and B.subtilis, but it also creates dynamic visualizations of mutational impact on protein structures, which add orthogonal checks on predicted drivers. Availability and implementation Code for ShinyBioHEAT is available at https://github.com/LichtargeLab/ShinyBioHEAT. The Shiny application is additionally hosted at http://bioheat.lichtargelab. org/.
Workplace and non-workplace cannabis use and the risk of workplace injury: Findings from a longitudinal study of Canadian workers

Findings of previous studies examining the relationship between cannabis use and workplace injury have been conflicting, likely due to methodological shortcomings, including cross-sectional designs and exposure measures that lack consideration for timing of use. The objective was to estimate the association between workplace cannabis use (before and/or at work) and non-workplace use and the risk of workplace injury. Canadian workers participating in a yearly longitudinal study (from 2018 to 2020) with at least two adjacent years of survey data comprised the analytic sample (n = 2745). The exposure was past-year workplace cannabis use (no past-year use, non-workplace use, workplace use). The outcome was past-year workplace injury (yes/no). Absolute risks and relative risks (RR) with 95% confidence intervals (CIs) were estimated between workplace and non-workplace cannabis use at one time point and workplace injury at the following time point. Models were adjusted for personal and work variables and were also stratified by whether respondents’ jobs were safety-sensitive. Compared to no past-year cannabis use, there was no difference in workplace injury risk for non-workplace cannabis use (RR 1.09, 95%CI 0.83–1.44). However, workplace use was associated with an almost two-fold increased risk of experiencing a workplace injury (RR 1.97, 95%CI 1.32–2.93). Findings were similar for workers in safety-sensitive and non-safety-sensitive work. It is important to distinguish between non-workplace and workplace use when considering workplace safety impacts of cannabis use. Findings have implications for workplace cannabis use policies and substantiate the need for worker education on the risks of workplace cannabis use.
Azvudine therapy of common COVID‐19 in hemodialysis patients

There is no antiviral study on hemodialysis patients infected with coronavirus disease 2019 (COVID‐19), especially on the application of 2′‐deoxy‐2′‐β ‐fluoro‐4′‐azidocytidine (Azvudine, FNC) antiviral therapy. We conducted a multicenter observational study involving 1008 hemodialysis patients. After matching for age, sex, and other factors, 182 patients in the basic treatment group and 182 in the FNC group were included. The negative nucleic acid conversion rate of the FNC group was significantly higher than that of the basic treatment group, and viral loads, interleukin‐6, and C‐reactive protein were significantly lower than those of the basic treatment group (p < 0.05). There were no significant differences in liver function, renal function, or the number of adverse events between the two groups (p > 0.05). In conclusion, our study has provided novel evidence suggesting that the FNC scheme may be safe and effective compared to the basic treatment of hemodialysis patients with common COVID‐19.
DISCONTINUOUS GALERKIN METHOD WITH REDUCED INTEGRATION SCHEME FOR THE BOUNDARY TERMS IN ALMOST INCOMPRESSIBLE LINEAR ELASTICITY

A problem of incompressibility is explored in this paper with application of a discontinuous Galerkin (dG) method with reduced integration. We apply two reduced integration schemes, namely fully and mixed reduced integrations for the Incomplete Interior Penalty Galerkin (IIPG) class of the dG method. The numerical results show convergent solutions with respect to a sufficiently large value of the penalty term and number of elements. Additionally, a comparison between the standard continuous Galerkin (cG) method and the dG method are established to compare and contrast the behavior. Finally, the dG method shows a faster convergence with respect to the number of elements.
Optimal Summary Statistics for X-ray Polarization

We develop two new highly efficient estimators to measure the polarization (Stokes parameters) in experiments that constrain the position angle of individual photons such as scattering and gas-pixel-detector polarimeters, and analyse in detail a previously proposed estimator. All three of these estimators are at least fifty percent more efficient on typical datasets than the standard estimator used in the field. We present analytic estimates of the variance of these estimators and numerical experiments to verify these estimates. Two of the three estimators can be calculated quickly and directly through summations over the measurements of individual photons.