Miracle-dz/UniFAR-FTUs huggingface dataset:
A wideband CMOS LNA using noise‐canceling topology and gm‐boosting technique

In this letter, a wideband low noise amplifier (LNA) using noise‐canceling topology and gm‐boosting technique is proposed. The noise‐canceling topology is used in the common gate (CG) amplifier to achieved better noise figure (NF) and wideband input matching. Meanwhile, the requirement of the input transconductance can be obviously decreased due to the application of gm‐boosting technique, which effectively alleviate the trade‐off between power consumption and voltage gain. The 3‐dB bandwidth of the LNA is from 2.1 to 4.1 GHz, covering widely used 5 G wireless communication frequency bands (n1, n7, n38, n41, n66, and n78 bands). The proposed LNA shows a flat and low measured NF of 3.3–3.6 dB within the operating bandwidth, while the peak power gain is 18.7 dB. The power consumption of this circuit is 16 mW with 1.2 V supply voltage, and the core area of the circuit is 0.066 mm2 with only one inductor for the whole chip.
The use of the theory of critical distance and the stress-gradient approach in the fatigue life estimation of notched components

Fatigue life prediction for machine components is a fundamental factor in the industrial world, and therefore several methods can be traced in technical literature to estimate life of notched components. The present paper correlates the classical stress-gradient approach, or support factor method, proposed by Siebel, Neuber and Petersen with the more recent theory of critical distance approach by Tanaka and Taylor. On one hand, the main asset of the support factor method is the punctual information about the stresses needed to estimate the effective stress, namely the maximum stress and stress gradient at the hot spot. By contrast, the theory of the critical distance needs the calculation of the stress distribution for a finite depth inside the material. The main drawback of the support factor method is that the material parameter ρ* is available only for a limited series of materials. In order to overcome this limitation, the paper investigates the correlation between the material parameter ρ* and the critical distance L by relying on a parametric stress function. The proposed correlation aims at giving a simple method for the industrial engineers, which often needs straightforward methods to tackle practical problems. A comparison between the two methods is carried out by considering three different benchmark geometries: a typical V-notched specimen, a vessel under internal pressure and a complex industrial hydraulic control valve. In the first two benchmarks, the effective stresses are analytically retrieved and compared using both methods while an elastic finite element analysis is performed for the last one. The close match of the fatigue life prediction between the methods supports the possibility to exploit the data available in literature for the critical distance in order to estimate the effective stresses with the support factor method.
Turbulence in surgical suction heads as detected by MRI

Background: Blood loss is common during surgical procedures, especially in open cardiac surgery. Allogenic blood transfusion is associated with increased morbidity and mortality. Blood conservation programs in cardiac surgery recommend re-transfusion of shed blood directly or after processing, as this decreases transfusion rates of allogenic blood. But aspiration of blood from the wound area is often associated with increased hemolysis, due to flow induced forces, mainly through development of turbulence. Methods: We evaluated magnetic resonance imaging (MRI) as a qualitative tool for detection of turbulence. MRI is sensitive to flow; this study uses velocity-compensated T1-weighted 3D MRI for turbulence detection in four geometrically different cardiotomy suction heads under comparable flow conditions (0–1250 mL/min). Results: Our standard control suction head Model A showed pronounced signs of turbulence at all flow rates measured, while turbulence was only detectable in our modified Models 1–3 at higher flow rates (Models 1 and 3) or not at all (Model 2). Conclusions: The comparison of flow performance of surgical suction heads with different geometries via acceleration-sensitized 3D MRI revealed significant differences in turbulence development between our standard control Model A and the modified alternatives (Models 1–3). As flow conditions during measurement have been comparable, the specific geometry of the respective suction heads must have been the main factor responsible. The underlying mechanisms and causative factors can only be speculated about, but as other investigations have shown, hemolytic activity is positively associated with degree of turbulence. The turbulence data measured in this study correlate with data from other investigations about hemolysis induced by surgical suction heads. The experimental MRI technique used showed added value for further elucidating the underlying physical phenomena causing blood damage due to non-physiological flow.
SC-MAIRL: Semi-Centralized Multi-Agent Imitation Reinforcement Learning

Multi-agent reinforcement learning (MARL) is a challenging branch of reinforcement learning that requires cooperation of interactive learning agents to achieve individual objectives as well as shared team objectives. Existing MARL algorithms generally use either centralized global state representation or decentralized local observation to perform training and execution. In this paper, we introduce a novel MARL learning paradigm, centralized training with semi-centralized execution (CTSCE), and present a new MARL algorithm for addressing multi-agent problems: Semi-Centralized Multi-Agent Imitation Reinforcement Learning (SC-MAIRL). The semi-centralized approach aggregated with agents’ spatial and temporal information serves as a joint knowledge base to facilitate a learning agent to discover team objectives and make fine-grained decisions. We also utilize a pre-trained performant teacher policy to guide an untrained model towards positive game states as a form of imitation learning, significantly increasing the agent’s learning speed. In addition, to encourage agents to learn both offensive and defensive behaviors and smooth the high-dimensional learning curve, we present a new set of reward-shaping functions to further improve SC-MAIRL’s learning performance. Our approach is evaluated using one of the most challenging scenarios within the StarCraft Multi-Agent Challenge environment, and the results show that SC-MAIRL outperforms the state-of-the-art MARL algorithm MAPPO in several metrics and allows our agents to learn and employ novel, complex macro strategies more effectively.
Selection and Validation of Optimal RT-qPCR Reference Genes for the Normalization of Gene Expression under Different Experimental Conditions in Lindera megaphylla

Lindera megaphylla, a broad-leaved evergreen that is used as a landscape ornamental plant and medicinal plant, is an ecologically important and dominant tree species. However, little is known about the molecular mechanisms of its growth, development, and metabolism. The selection of suitable reference genes is critical for molecular biological analyses. To date, no research on reference genes as a foundation for gene expression analysis has been undertaken in L. megaphylla. In this study, 14 candidate genes were selected from the transcriptome database of L. megaphylla for RT-qPCR assay under different conditions. Results showed that helicase-15 and UBC28 were most stable in different tissues of seedlings and adult trees. For different leaf developmental stages, the best combination of reference genes was ACT7 and UBC36. UBC36 and TCTP were the best under cold treatment, while PAB2 and CYP20-2 were the best under heat treatment. Finally, a RT-qPCR assay of LmNAC83 and LmERF60 genes were used to further verify the reliability of selected reference genes above. This work is the first to select and evaluate the stability of reference genes for the normalization of gene expression analysis in L. megaphylla and will provide an important foundation for future genetic studies of this species.
QNH: Design and Test of a Quasi-Nonhydrostatic Model for Mesoscale Weather Prediction

Abstract A new mesoscale weather prediction model, called QNH, is described. It is characterized by a parameter that multiplies the hydrostatic terms in the vertical equation of motion. Models of this type are referred to generically as “quasi-nonhydrostatic. ” The quasi-nonhydrostatic parameter gives the model a character that is essentially nonhydrostatic, but with properties that are theoretically thought to result in smoother, more accurate, and stable predictions. The model is unique in a number of other aspects, such as its treatment of lateral boundary conditions, the use of explicit calculation in the vertical direction, and the use of the bounded derivative theory for initialization. This paper reports on the design and test of the QNH model, which represents the first time the applicability of this type of model has been demonstrated for full-physics, mesoscale weather prediction. The dynamic formulation, discretization, numerical formulation, and physics packages of the model are described. The .
Observation of a (Lambda Lambda)He-6 double hypernucleus

A double-hyperfragment event has been found in a hybrid-emulsion experiment. It is identified uniquely as the sequential decay of ( 6)(LambdaLambda)He emitted from a Xi(-) hyperon nuclear capture at rest. The mass of ( 6)(LambdaLambda)He and the Lambda-Lambda interaction energy DeltaB(LambdaLambda) have been measured for the first time devoid of the ambiguities due to the possibilities of excited states. The value of DeltaB(LambdaLambda) is 1.01+/-0.20(+0.18)(-0.11) MeV. This demonstrates that the Lambda-Lambda interaction is weakly attractive.
Effect of Project-Based STEAM Acquire on Student Creativity in Science Learning During the Pandemic Period

The reason for this think about was to look at the impact of Project-based STEAM acquisition on college inventive considering and basic considering aptitudes. The ponder utilized a quasi-experimental plan using a nonequivalent pretest-posttest control gather plan. The populace for ponder were all understudies in Sunan Ampel State Islamic University, Surabaya whereas the test utilized included one department of Biology for the test course and one department of Engineering, utilized as the control lesson. The purpose of this study is to provide an overview in the form of a description of the implementation of STEAM-based acquisition for children aged 5-6 years at Al-Azhar Syifa Budi Surakarta Kindergarten. The information collected was at that point analyzed utilizing the ANOVA test. The pjBL-based STEAM acquisition had a critical impact on understudies’ imaginative considering abilities (P 0.000 < 0.005; Fcount = 25.551). The pjBL-Based STEAM acquisition had a critical impact on understudies’ basic considering aptitudes (P 0.003<0.05, Fcount=9,401). So, PjBL-Based STEAM acquire can be utilized as elective acquire to enable 21st-century abilities.
FTPipeHD: A Fault-Tolerant Pipeline-Parallel Distributed Training Approach for Heterogeneous Edge Devices

With the increasing proliferation of Internet-of-Things (IoT) devices, there is a growing trend towards distributing the power of deep learning (DL) among edge devices rather than centralizing it at the cloud. To deploy deep and complex models at edge devices with limited resources, model partitioning of deep neural network (DNN) models has been widely studied. However, most of the existing literature only considers distributing the inference model while still training the model at the cloud. In this paper, we propose FTPipeHD, a novel DNN training approach that trains DNN models across distributed heterogeneous devices with the fault-tolerance mechanism. To accelerate the training with the time-varying computing power of each device, we optimize the partition points dynamically according to real-time computing capacities. We also propose a novel weight redistribution approach that replicates the weights to both the neighboring nodes and the central node periodically, which combats the failure of multiple devices during training while incurring limited communication costs. Our numerical results demonstrate that FTPipeHD is 6.8 times faster in training than the state-of-the-art method when the computing capacity of the best device is 10 times greater than the worst one. It is also shown that the proposed method is able to accelerate the training even with the existence of device failures.
Internal Friction Study on the Influence of Pre-Deformation on Hydrogen Embrittlement Sensitivity of Dual-Phase Steel

in this study, an electrochemical method was used to permeate hydrogen through annealed DP590 steel under various pre-strain conditions (0-15%). Stress-strain and internal friction-temperature curves of the dual phase (DP) steel were obtained from slow strain-rate tensile tests and internal friction measurements, respectively. The diffusion of interstitial atoms, formation of Cottrell atmospheres, and embrittlement mechanism of DP steel were investigated under different prestress conditions before and after hydrogen permeation. The results show that the tensile strength of DP steel first decreases and then increases and the elongation sharply decreases with increasing pre-strain. The strength and ductility present similar trends with changes in pre-strain before and after hydrogen charging, however, after hydrogen charging, an obvious increase in tensile strength and decrease in elongation are observed. Furthermore, the γ peak amplitude decreases and the Snoek-Ke-Koster (SKK) peak amplitude increases with increasing internal pre-strain according to the friction-temperature curve. The γ peak and SKK peak exhibit the same trends with increasing pre-strain before and after hydrogen charging and both the γ peak and SKK peak decrease with hydrogen charging. The dislocation density in DP steel increases after hydrogen charging.
Cardiovascular Disease-Related Health Promotion and Prevention Services by Pharmacists in Saudi Arabia: How Well Are They Prepared?

Background: Cardiovascular diseases (CVDs) have been identified as the leading reason for morbidity and mortality in Saudi Arabia. Pharmacists play a major role in CVD prevention and health promotion. We aimed to assess the knowledge, attitudes, and involvement of pharmacists in CVD prevention and evaluate the influence of continuing medical education in CVD-prevention services in Saudi Arabia. Method: A cross-sectional study was conducted to evaluate the involvement of pharmacists in CVD-related prevention services along with their knowledge and attitudes. A 34-item questionnaire was developed and distributed among the participants. Results: A total of 324 responses were included in the study. More than 60% of pharmacists had provided counseling regarding the importance of healthy lifestyles and self-monitoring CVD risk factors. About half of the participants (49.1%) had never received any CVD-related continuing medical education. Overall, more than 60% of the participants reported positively towards their role in CVD prevention. Lack of time (66%) and lack of educational materials and tools (41%) were the top perceived barriers for providing CVD-prevention and health-promotion activities, followed by lack of skills in using tools (36%) and lack of privacy/space (33%). Conclusions: The involvement of pharmacists in the prevention of CVD is limited in this study. Further education and capacity building are required to strengthen pharmacists’ involvement in CVD-prevention and health-promotion activities.
Robust and Discordant Evidence: Methodological Lessons from Clinical Research

The concordance of results that are “robust” across multiple scientific modalities is widely considered to play a critical role in the epistemology of science. But what should we make of those cases where such multimodal evidence is discordant? Jacob Stegenga has recently argued that robustness is “worse than useless” in these cases, suggesting that “different kinds of evidence cannot be combined in a coherent way. ” In this article I respond to this critique and illustrate the critical methodological role that robustness plays as an aim of scientific inquiry.
The Shift-Invert Residual Arnoldi Method and the Jacobi-Davidson Method: Theory and Algorithms ∗

Using a new analysis approach, we establish a general convergence theory of the ShiftInvert Residual Arnoldi (SIRA) method for computing a simple eigenvalue nearest to a target σ and/or the associated eigenvector. In SIRA, a subspace expansion vector at each step is obtained by solving a certain inner linear system. We prove that the inexact SIRA method mimic the exact SIRA well provided that the inner linear systems are iteratively solved with low or modest accuracy. The results demonstrate that SIRA is superior to the inexact Shift-Invert Arnoldi (SIA) method, where the inner linear system involved must be solved with very high accuracy whenever the approximate eigenpair is of poor accuracy and are only solved with decreasing accuracy after the approximate eigenpair starts converging. Based on the theory, we design a practical stopping criterion for inner solvers. For practical purpose, we propose a restarted SIRA algorithm. Our analysis approach applies to the JD method as well, a general convergence theory is obtained similarly for the standard Jacobi–Davidson (JD) method with a fixed target, and a practical JD algorithm is developed. Numerical experiments confirm our theory and the considerable superiority of the (non-restarted and restarted) inexact SIRA to the inexact SIA, and demonstrate that the inexact SIRA and JD are similarly effective and mimic the exact SIRA very well.
Weak and Strong Cross-Section Dependence and Estimation of Large Panels

This paper introduces the concepts of time-specific weak and strong cross section dependence. A double-indexed process is said to be cross sectionally weakly dependent at a given point in time, t, if its weighted average along the cross section dimension (N) converges to its expectation in quadratic mean, as N is increased without bounds for all weights that satisfy certain 'granularity' conditions. Relationship with the notions of weak and strong common factors is investigated and an application to the estimation of panel data models with an infinite number of weak factors and a finite number of strong factors is also considered. The paper concludes with a set of Monte Carlo experiments where the small sample properties of estimators based on principal components and CCE estimators are investigated and compared under various assumptions on the nature of the unobserved common effects.
Rarely Encountered Gram-Negative Rods and Lung Transplant Recipients: A Narrative Review

The respiratory tract of lung transplant recipients (LTR) is likely to be colonized with non-fermentative Gram-negative rods. As a consequence of the improvements in molecular sequencing and taxonomy, an increasing number of bacterial species have been described. We performed a review of the literature of bacterial infections in LTR involving non-fermentative Gram-negative rods with exclusion of Pseudomonas aeruginosa, Stenotrophomonas maltophilia, Achromobacter spp. and Burkholderia spp. Overall, non-fermenting GNR were recovered from 17 LTR involving the following genera: Acetobacter, Bordetella, Chryseobacterium, Elizabethkinga, Inquilinus, and Pandoraea. We then discuss the issues raised by these bacteria, including detection and identification, antimicrobial resistance, pathogenesis, and cross-transmission.
Subterranean Fauna of the Lukina Jama–Trojama Cave System in Croatia: The Deepest Cave in the Dinaric Karst

The Dinaric Karst is a global hotspot for subterranean diversity, with two distinct peaks of species richness in the northwest and southeast, and an area of a lower species richness in the central part. In this article, we present a species list and describe the ecological conditions of the Lukina jama–Trojama cave system, located in the central part of the Dinaric Karst. This cave system is the deepest and one of the most logistically challenging cave systems sampled so far in the Dinaric Karst. Repeated sampling resulted in a list of 45 species, including 25 troglobionts, 3 troglophiles, 16 stygobionts, and 1 stygophile. Most of the recorded species are endemic to the Velebit Mountain, while three species are endemic to the Lukina jama–Trojama cave system. Within the system, species richness peaks in the deepest third of the cave, most likely reflecting the harsh ecological conditions in the upper parts, including ice, cold winds, and occasional waterfalls. Milder and more stable deeper parts of the cave contain a rich subterranean species community, part of which is associated with two very distinct aquatic habitats, the cave hygropetric and the phreatic zone. The newly recognized hotspot of subterranean biodiversity in the central Dinaric Karst, which has emerged between the two known centers of biodiversity, further highlights the species richness in large cave systems, but also challenges the diversity patterns in the Dinaric Karst overall.
Motivation Behind Managing Employee Information in the Banking Sector: Comparative Study Between Sri Lanka and New Zealand

The purpose of this study is to investigate motivations behind managing employee information in banking sector in Sri Lanka and New Zealand. Specially, this study answers for two research questions first, why does the banking sector in Sri Lanka manage employee information and second, how does the motivations to manage employee information in banking sector in Sri Lanka different to New Zealand. Qualitative method was employed in this study and data was collected through in-depth interviews. Responses were analysed using content analysis. The findings revealed that both banking sectors in Sri Lanka and New Zealand manage employee information to achieve two purposes; internal management and external reporting. Although the study identified various differences, some of the reasons for managing employee information in both Sri Lanka and New Zealand appear similar.
Structural Characterization and In Vitro Antioxidant, Hypoglycemic and Hypolipemic Activities of a Natural Polysaccharide from Liupao Tea

This study extracted and purified a natural polysaccharide (TPS-5) that has a molecular weight of 48.289 kDa from Liupao tea, a typical dark tea with many benefits to human health. TPS-5 was characterized as a pectin-type acidic polysaccharide. It has a backbone composed of → 2,4)- α- L-Rhap-(1) → 4)- α- D-GalAp-(1) →, with a branch composed of → 5)- α- L-Ara-(1 → 5,3)- α- L-Ara-(1 → 3)- β- D-Gal-(1 → 3,6)- β- D-Galp-(1) →. The in vitro biological activity evaluation illustrated that TPS-5 has free radical scavenging, ferric-ion-reducing, digestive enzyme inhibitory, and bile-salt-binding abilities. These results suggest that TPS-5 from Liupao tea has potential applications in functional foods or medicinal products.
400-nm InGaN-GaN and InGaN-AlGaN multiquantum well light-emitting diodes

The 400-nm In/sub 0.05/Ga/sub 0.95/N-GaN MQW light-emitting diode (LED) structure and In/sub 0.05/Ga/sub 0.95/N-Al/sub 0.1/Ga/sub 0.9/N LED structure were both prepared by organometallic vapor phase epitaxy. It was found that the use of Al/sub 0.1/Ga/sub 0.9/N as the material for barrier layers would not degrade crystal quality of the epitaxial layers. It was also found that the 20-mA electroluminescence intensity of InGaN-AlGaN multiquantum well (MQW) LED was two times larger than that of the InGaN-GaN MQW LED. The larger maximum output intensity and the fact that maximum output intensity occurred at larger injection current suggest that AlGaN barrier layers can provide a better carrier confinement and effectively reduce leakage current.