Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunological Characteristics of Patients Receiving Ultra-Short Treatment for Chronic Hepatitis C

Reducing the treatment duration for chronic hepatitis C could be an important tool in the effort to reach the elimination goals set by the World Health Organization. The current challenge is to predict the target group who will achieve sustained virological response at week 12 (SVR12) with shorter treatment duration. The aim of this exploratory study was to characterize immune subsets with focus on inhibitory receptors in patients who experienced SVR12 or virological relapse following four weeks treatment with glecaprevir/pibrentasvir with or without ribavirin. A total of 32 patients were included in this study of whom 21 achieved SVR12 and 11 had virological relapse. All available samples at baseline (n = 31) and end of treatment (EOT) (n = 30) were processed for flow cytometric analysis in order to measure the expression of PD-1, 2B4, BY55, CTLA-4, TIM-3 and LAG-3 on 12 distinct T cell subsets. At baseline, patients with SVR12 (n=21) had numerically lower frequencies of inhibitory receptors for 83% (60/72) of the investigated T-cell subtypes. The most significant difference observed between the two groups was a lower frequency of stem cell-like memory T-cells CD4+PD1+ in the SVR group (p = 0.007). Furthermore, we observed a significant positive correlation between baseline viral load and the expression of PD-1 on the total CD8+ T-cells and effector memory T-cells CD4+ and CD8+ for patients with virological relapse. This study suggests a measurable immunologic phenotype at baseline of patients achieving SVR12 after short treatment compared to patients with virological relapse.
Uncertainty quantification for regularized inversion of electromagnetic geophysical data. Part I: Motivation and Theory

We present a method for computing a meaningful uncertainty quantification (UQ) for regularized inversion of electromagnetic (EM) geophysical data that combines the machineries of regularized inversion and Bayesian sampling with a “randomize-then-optimize” (RTO) approach. The RTO procedure is to perturb the canonical objective function in such a way that the minimizers of the perturbations closely follow a Bayesian posterior distribution. In practice, this means that we can compute UQ for a regularized inversion by running standard inversion/optimization algorithms in a parallel for-loop with only minor modification of existing codes. Our work is split into two parts. In Part I we review RTO and extend the methodology to estimate the regularization penalty weight on the fly, not unlike in the Occam inversion. We call the resulting algorithm the RTO-TKO and explain that it samples from a biased distribution which we numerically demonstrate to be nearby the Bayesian posterior distribution. In return for accepting this small bias, the advantage of RTO-TKO over asymptotically unbiased samplers is that it significantly accelerates convergence and leverages computational parallelism, which makes it highly scalable to 2D and 3D EM problems. In Part II, we showcase the versatility and computational efficiency of RTO-TKO and apply it to a variety of EM inversions in 1D and 2D, carefully comparing the RTO-TKO results to established UQ estimates using other methods. We further investigate scalability to 3D, and discuss the influence of prior assumptions and model parameterizations on the UQ.
Research Into the LSTM Neural Network-Based Crystal Growth Process Model Identification

In this paper, a model identification method based on a long short-term memory (LSTM) neural network composed of a network structure and training algorithm is used to build a thermal field model that accurately simulates the crystal growth process. The support vector machine (SVM) approach is then adopted to identify model order and lag to determine network input and to improve precision. The thermal field model reflecting the growth process in the Czochralski crystal furnace is simulated. Experimental results and comparative analysis results both suggest that the method proposed by this paper can build an efficient thermal field model which outperforms other methods in terms of precision.
Research on ship control with mechanical arms based on the PID controller

At present, there are still a large number of ships in operation with no autopilot. The helmsman usually steers the ship manually for a long time, which is prone to fatigue and poses potential safety risks. To address this problem. A control method with a set of mechanical arms is used to solve the problem of the autopilot of ships with low electrification. A PID controller combined with a mechanical arm and based simulation model for ship control is established. The simulation results show that the method and the model preliminarily demonstrate the feasibility of the mechanical arm in ship steering.
Autochthonous Dolomitization and Dissolution in the Microbial Carbonate Rocks of the Fengjiawan Formation in the Ordos Basin

Many euhedral dolomite crystals and related pores are found in the microbial siliceous stromatolite dolomite and siliceous oolitic dolomite in the Fengjiawan Formation of the Mesoproterozoic Jixian System in the southern Ordos Basin. With the application of the microscope, scanning electron microscope, cathodoluminescence and in‐situ trace element imaging, it can be seen that different from the phase I dolomite that was damaged by silicification, the intact euhedral phase II dolomite occurred through dolomitization after silicification, concentrated mainly in the organic‐rich dark laminae of the stromatolite and the dark spheres and cores of the ooids. A considerable number of phase II dolomite crystals were dissolved, giving rise to mold pores and vugs which constituted the matrix pores and also the major pore space of the Fengjiawan Formation. The formation and dissolution of the dolomite were controlled by the microenvironment favorable, respectively, for carbonate precipitation and dissolution under the influence of microbial biological activities and related biochemical reactions. The driving force and material supply of dolomitization and dissolution were confined to the fabrics enriched with microorganisms, which are highly autochthonous. This mechanism may be a key factor for the development of Precambrian dolomite and related reservoirs, in the context of the domination of microbial rocks.
ENERGY FORMULATIONS OF MEDICAL IMAGE SEGMENTATIONS

The first phase of a radiological revolution is already well underway. New medical imaging modalities produce rich, evocative imagery, and there is a large body of evidence suggesting that a quantitative analysis of this imagery would provide much more telling diagnostic information than is currently extracted qualitatively in mainstream medicine. However, quantitative analyses of these images require some type of unified geometrical description of the anatomy, which is only possible once boundaries between anatomical structures have been segmented. But current state of the art segmentation for medical imagery is still largely an inaccurate, highly repetitive, costly procedure for specially trained technicians, which makes quantitative image analysis unrealistic for large-scale projects. Automated and semi-automated segmentation methods, however, are faster, cheaper, and more repeatable alternatives. One route to more automated medical image segmentation is via energy minimization methods. The goal in energy minimization approaches is to define a segmentation energy which concisely captures the quantitative properties of desirable segmentations– the segmentation is the set of edges and regions which minimize the energy. The comparative advantage of using energy formulations of the segmentation problem compared to competing methods, such as edge detection and active surface methods, is the flexibility of the energy definition and resulting higher-quality segmentations. However, energy
Bazı Postnatal Gelişme Dönemlerinde Tavuk [Gallus gallus domesticus] Ovidukt Mukozasının Histokimyasal Yapısı

Bu calismada yumurta tavugunda [ Gallus gallus domesticus ] bir ve iki aylik civcivler ile uc ve dort aylik piliclerde, ovidukt mukozasinin histokimyasal yapisinin belirlenmesi amaclandi. Calismada her bir donem icin altisar adet saglikli hayvandan alinan ovidukt orneklerinde infundibulum, magnum, isthmus ve uterus bolgeleri farkli histokimyasal teknikler uygulanarak isik mikroskobuyla degerlendirildi. Tum aylarda uterus ortu epitelinde asidik mukosubstans iceren hucreler gozlenirken, sadece iki aylik civciv ve dort aylik pilic magnumunda bu mukosubstans belirlendi. Dort aylik piliclerde orta yogunlukta, bir ve iki aylik civcivlerin isthmusunda ise guclu asidik mukosubstans iceren hucreler saptandi. Dort aylik piliclerde infundibulum, magnum ve isthmus ortu epitelinde baskin notral mukosubstans iceren hucrelere rastlandi. Notral ve asidik mukosubstansi birlikte iceren hucrelere bir aylik civciv ve uc aylik piliclerin uterus ortu epitelinde, dort aylik piliclerde hem magnum hem de uterus ortu epitelinde rastlandi. AM/KOH/PAS/AB pH 2,5 uygulamasinda notral ve asidik mukosubstansi birlikte iceren hucreler bir aylik civcivlerde infundibulum ve uterus ortu epitelinde gozlendi. Benzer durum dort aylik piliclerin isthmus ortu epitelinde de saptandi. AM/KOH/PAS/AB pH 1.0 uygulamasinda uc aylik piliclerde uterus, dort aylik piliclerde ise magnum ve uterus ortu epitelinde PAS/AB pH 2,5 [+] hucreler gozlendi. HID reaksiyonuna bir ve iki aylik civcivlerde infundibulum ortu epitelinde, uc ve dort aylik piliclerde uterus ortu epiteli ve hucrelerinde rastlandi. HID/PAS uygulamasinda bir ve iki aylik civcivlerde HID’nin baskin oldugu belirlendi. Bir aylik civcivlerde ve uc aylik piliclerde notral ve O-sulfat esterli glikoproteinleri birlikte iceren hucreler belirlendi. Bir ve iki aylik civcivlerde infundibulumda, bir aylik civcivlerde ve uc aylik piliclerde ise uterus ortu epitelinde HID/PAS/AB pH 2,5 iceren az sayida hucre saptandi.
Developments of EHM Under the Conditions of Big Data Technology

This paper explores the role of big data technology development in the promotion of aero engine health management (EHM) technology. Firstly, the research and development history of EHM is elaborated in detail, and then the key technologies for EHM research are analyzed. Finally, according to the existing difficulties and technical problems, the method of combining computer science engineering and aerospace science and technology is proposed to improve Chinese aviation EHM technology.
Ruby: Improving Hardware Efficiency for Tensor Algebra Accelerators Through Imperfect Factorization

Finding high-quality mappings of Deep Neural Network (DNN) models onto tensor accelerators is critical for efficiency. State-of-the-art mapping exploration tools use remainderless (i.e., perfect) factorization to allocate hardware resources, through tiling the tensors, based on factors of tensor dimensions. This limits the size of the search space, (i.e., mapspace), but can lead to low resource utilization. We introduce a new mapspace, Ruby, that adds remainders (i.e., imperfect factorization) to expand the mapspace with high-quality mappings for user-defined architectures. This expansion allows us to allocate resources more precisely by generating tile sizes that better conform to hardware resources. However, this mapspace expansion also incurs an increase in the number of unique mappings. Consequently, this paper studies the trade-off between Ruby’s mapspace expansion and mapping quality. We propose Ruby-S (Spatial) to only employ imperfect factorization towards improved parallelism. Ruby-S incurs a moderate mapspace expansion while reducing energy-delay product (EDP) up to 50% when implementing ResNet-50 on an Eyeriss-like architecture with an average improvement of 20%. For the most part, this improvement can be attributed to higher compute utilization. EDP on a Simba-like architecture improves up to 40% with an average of 10%. For DeepBench workloads Ruby-S yields improvements of up to 45% with an average improvement of 10% on an Eyeriss-like architecture. Ruby-S is robust to accelerator configurations and improves EDP by 20% on average, with a maximum improvement of 55% when implementing ResNet-50 on different accelerator configurations. Ruby-S mappings form a new Pareto frontier, improving the performance of previous configurations by an average of 30% and 20% for ResNet-50 and DeepBench workloads respectively.
A Review of Planning of Integrated Energy System in Nigeria

The recent global concerns on traditional energy depletion, intermittency of renewable energy, and goal towards carbon neutrality has led to the emergence of multiple energy generation systems to satisfy multiple loads via conversion and distribution devices. This new power system is known as the Integrated Energy System (IES). Studies on planning and operation of IES have received great attention in developed nations for energy security and efficiency. However, in developing countries such as Nigeria, it is still at infancy and rarely explored despite its many benefits and the energy challenges in the country. In this study, review of the status of IES development in Nigeria is presented. The barriers to IES studies and possible strategies to its planning and operation in Nigeria are expounded as well. At the end of this paper, it is concluded that Nigeria must create and promote new energy policies while investing in infrastructures to support IES planning and operation in the country.
Genetic Diversity and Gene Flow Observed in Two Cereal Aphid (Hemiptera: Aphididae) Species and Populations in the Chinese Corn Belt Region

Abstract The cereal aphids, Rhopalosiphum maidis (Fitch) and Rhopalosiphum padi (L.) (Hemiptera: Aphididae), are serious pests of maize, Zea mays L. , globally. Basic information about the genetic structure of these aphids is unknown. We, therefore, estimated the genetic diversity and genetic flow from partial fragments of the mitochondrial cytochrome oxidase I gene collected from different geographic populations of aphids throughout the Songliao Plain of northeastern China. Our analysis of a 425-bp sequence on 297 R. maidis and 287 R. padi individuals revealed 17 and 3 variable sites, respectively. Fifteen haplotypes were obtained among the R. maidis populations, and only haplotype RM1 was shared. Three shared haplotypes were obtained among the R. padi populations. No obvious geographical trends were detected based on the haplotype network and neighbor-joining tree. Relatively low haplotype diversity indices were observed in the R. maidis populations (haplotype diversity [Hd] = 0.14207, average number of nucleotide differences [K] = 0.17340, and nucleotide diversity [Pi] = 0.00041), whereas relatively high haplotype diversity indices were observed in the R. padi populations (Hd = 0.53249, K = 1.46614, and Pi = 0.00345). There was moderate gene flow (number of migrants [Nm] = 2.33) among R. maidis populations, but there was low gene flow (Nm = 0.82) among R. padi populations. Analysis of molecular variance showed high genetic differentiation within populations. Genetic distance and geographic distance were not significantly associated according to the Mantel test. The results suggest that the difference in the aphids' existence strategies has resulted in a different mitochondrial evolution pattern in the Songliao Plain region, and they provide a foundation for accurately forecasting systems against this pest.
Participation in Low Back Pain Management: It Is Time for the To-Be Scenarios in Digital Public Health

Low back pain (LBP) carries a high risk of chronicization and disability, greatly impacting the overall demand for care and costs, and its treatment is at risk of scarce adherence. This work introduces a new scenario based on the use of a mobile health tool, the Dress-KINESIS, to support the traditional rehabilitation approach. The tool proposes targeted self-manageable exercise plans for improving pain and disability, but it also monitors their efficacy. Since LBP prevention is the key strategy, the tool also collects real-patient syndromic information, shares valid educational messages and fosters self-determined motivation to exercise. Our analysis is based on a comparison of the performance of the traditional rehabilitation process for non-specific LBP patients and some different scenarios, designed by including the Dress-KINESIS’s support in the original process. The results of the simulations show that the integrated approach leads to a better capacity for taking on patients while maintaining the same physiotherapists’ effort and costs, and it decreases healthcare costs during the two years following LBP onset. These findings suggest that the healthcare system should shift the paradigm towards citizens’ participation and the digital support, with the aim of improving its efficiency and citizens’ quality of life.
A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction

Machine learning has shown utility in detecting patterns within large, unstructured, and complex datasets. One of the promising applications of machine learning is in precision medicine, where disease risk is predicted using patient genetic data. However, creating an accurate prediction model based on genotype data remains challenging due to the so-called “curse of dimensionality” (i.e., extensively larger number of features compared to the number of samples). Therefore, the generalizability of machine learning models benefits from feature selection, which aims to extract only the most “informative” features and remove noisy “non-informative,” irrelevant and redundant features. In this article, we provide a general overview of the different feature selection methods, their advantages, disadvantages, and use cases, focusing on the detection of relevant features (i.e., SNPs) for disease risk prediction.
Effects of Permafrost Degradation on Soil Carbon and Nitrogen Cycling in Permafrost Wetlands

Climate change is one of the greatest threats to high-latitude permafrost and leads to serious permafrost degradation. However, few attention has been paid to whether peat soil carbon or nitrogen is sensitive to permafrost degradation. This study has selected three typical sample areas (MoHe-continuous permafrost, TaHe-Island-shaped melting permafrost, Jagdaqi-Island-shaped melting permafrost) as research object to compare the response rate and degree of peat soil carbon and nitrogen under permafrost degradation. The results show that soil organic carbon and nitrogen contents are the highest in 0–10 cm soil and permafrost regions show obvious surface aggregation. The carbon content of different types of frozen soil decreases with the depth of soil layer, and the differences are significant (p < 0.01). The distribution pattern of total nitrogen content in each soil layer among different permafrost types is Mohe < Tahe < Jagedaqi. And when it is getting vertically deeper than the surface layer, there is no significant difference between the soil layers in soil profile. The study also focuses on the variations of carbon and nitrogen content in different soil layers of peatland in typical permafrost regions. The results show that soil carbon responds faster to the degradation of frozen soil than soil nitrogen. Moreover, the accumulation degree of soil carbon is also significantly higher than soil nitrogen. Under climate change and for better permafrost conservation, it is necessary to study how the peatland’s soil carbon and the nitrogen are influenced by the permafrost degradation in high latitude.
Preservation of Cerebellar Afferent Pathway May Be Related to Good Hand Function in Patients with Stroke

Many chronic stroke patients suffer from worsened hand function, and functional recovery of the hand does not occur well after six months of stroke. Therefore, predicting final hand function after stroke through acute phase imaging would be an important issue in counseling with the patients or their family. Thus, we investigated the remaining white matter integrity in the corticospinal tract (CST) and cortico-ponto-cerebellar tract (CPCT) at the acute stage of stroke and chronic hand function after stroke, and present the cut-off value of fiber number (FN) and fractional anisotropy (FA) of CST and CPCT at the acute stage for predicting final hand function after the recovery period. This retrospective case-control study included 18 stroke patients who were classified into two groups: poor hand function with stroke (n = 11) and good hand function with stroke (n = 7). DTI was done within two months ± 15 days after onset, and the Jebson’s Hand Function test was conducted 6–12 months after onset. The investigation of white matter was focused on the values of FN and FA for CST and CPCT, which were measured separately. The normalized (affected/non-affected) FA and FN values in the CPCT in the good hand function group were higher than those in the poor hand function group. The normalized FN and FA values in the CST were not significantly different between the poor hand function group and the good hand function group. The normalized cut-off value that distinguished the good hand function group from the poor hand function group was 0.8889 for FA in the CPCT. The integrity of the CPCT in the acute stage was associated with hand function in the chronic stage after a stroke. Ultimately, the integrity of the CPCT in the early stage after onset can be used to predict chronic hand function. Based on these results, cerebellar afferent fiber measurements may be a useful addition to predict hand function and plan specific rehabilitation strategies in stroke patients.
In Silico Molecular Docking and Toxicity Studies of Bioactive Fucoidan Compound from Brown Seaweed as Potential of Antihypertensive

Angiotensin Converting Enzyme (ACE) is an enzyme that can convert angiotensin 1 to angiotensin 2 peptide, which is a strong vasoconstrictor that causes hypertension. Fucoidan (4,5-dihydroxy-2,6-dimethyltetrahydro-2H-pyran-3-yl hydrogen sulfate) is one of the polysaccharide chemical compounds found in seaweed and is reported to have the ability to inhibit ACE activuty in vitro. The aim of this study is to predict of the binding interaction between fucoidan and amino acids in ACE and to use the native captopril ligand (MCO702) as the standard ligand. Analysis of the molecular docking of fucoidan and captopril compounds against ACE (1UZF) using Molegro 6.0 and Chemoffice Professional 17.1 Software and for toxicity analysis using pkCMS online tools. The results of the docking prediction showed that fucoidan had MolDock and Rerank Score values of -82.311 kcal/mol and -70.872 kcal/mol, respectively, which were not much different from captopril, namely -84.816 kcal/mol and -74.758 kcal/mol. Fucoidan and captopril are also easily absorbed and have good permeability and are classified as low toxicity, but are dangerous if ingested in the 2000 LD50≤ 5000 mg/kg range. Fucoidan has the potential as a candidate for antihypertensive drugs because it is predicted that in silico has the same ability as captopril.