Miracle-dz/UniFAR-FTUs huggingface dataset:
A 42Gb/s PAM-8 Transmitter with Feed-Forward Tomlinson-Harashima Precoding in 28nm CMOS

To extend the data rate on the band-limited channel, multi-level signaling such as PAM-N is being adopted to carry multi bits in a single symbol. To fully exploit the available channel bandwidth, equalization of the channel loss is necessary in the transmitter (TX) and/or receiver (RX). However, when the TX incorporates the equalizer with a feed-forward equalizer (FFE), the vertical eye margin (VEM) and the signal integrity of the FFE are reduced as its tap coefficients increase since the maximum driver output level is limited. As a result, employing the FFE on the TX with multi-level signaling is challenging, given that the VEM of the PAM-N is already 1/(N-1) of that of the NRZ. To compensate the channel loss on TX, various techniques have been reported [1–4]. Especially, Tomlinson- Harashima precoding (THP), which offers a signal-to-noise ratio (SNR) gain [5–7], is a good candidate for TX equalization that compensates for a channel loss while adopting multi-level signaling, especially PAM-8. This paper presents a 42Gb/s PAM-8 TX with THP-based equalization.
Data Pipes: Declarative Control over Data Movement

Today’s storage landscape offers a deep and heterogeneous stack of technologies that promises to meet even the most demanding data-intensive workload needs. The diversity of technologies, however, presents a challenge. Parts of it are not controlled directly by the application, e.g., the cache layers, and the parts that are controlled, often require the programmer to deal with very different transfer mechanisms, such as disk and network APIs. Combining these different abstractions properly requires great skill, and even so, expert-written programs can lead to sub-optimal utilization of the storage stack and present performance unpredictability. In this paper, we propose to combat these issues with a new programming abstraction called Data Pipes. Data pipes offer a new API that can express data transfers uniformly, irrespective of the source and destination data placements. By doing so, they can orchestrate how data moves over the different layers of the storage stack explicitly and fluidly. We suggest a preliminary implementation of Data Pipes that relies mainly on existing hardware primitives to implement data movements. We evaluate this implementation experimentally and comment on how a full version of Data Pipes could be brought to fruition.
Identification and validation of a ferroptosis-related lncRNA signature to robustly predict the prognosis, immune microenvironment, and immunotherapy efficiency in patients with clear cell renal cell carcinoma

Background Ferroptosis is a new type of iron- and reactive oxygen species-dependent cell death, studies on ferroptosis-related long noncoding RNAs (FerLncRNAs) in clear cell renal cell carcinoma (ccRCC) are limited. The purpose of this study was to investigate the potential prognostic value of FerLncRNAs and their relationship with the immune microenvironment and immunotherapy response of ccRCC. Methods RNA sequencing data of 526 patients with ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database. The patients with ccRCC in TCGA were randomly divided (1:1) into a training and testing cohort. ICGC and GEO databases were used for validation. Screening for FerLncRNAs was performed using Pearson’s correlation analysis with the reported ferroptosis-related genes. A FerLncRNA signature was constructed using univariate, LASSO, and multivariate Cox regression analyses in the training cohort. Internal and external datasets were performed to verify the FRlncRNA signature. Four major FRlncRNAs were verified through in vitro experiment. Results We identified seven FerLncRNAs (LINC00894, DUXAP8, LINC01426, PVT1, PELATON, LINC02609, and MYG1-AS1), and established a risk signature and nomogram for predicting the prognosis of ccRCC. Four major FRlncRNAs were verified with the prognosis of ccRCC in the GEPIA and K-M Plotter databases, and their expressions were validated by realtime PCR. The risk signature can also effectively reflect the immune environment, immunotherapy response and drug sensitivity of ccRCC. These FRlncRNAs have great significance to the implementation of individualized treatment and disease monitoring of ccRCC patients.
Rapid thermal annealing of InP using GaAs and InP proximity caps

Rapid thermal annealing of InP in an inert atmosphere is demonstrated using face‐to‐face GaAs and InP proximity caps to protect the active surface from decomposition. No surface damage of any kind is detected by optical microscopy, photoluminescence spectroscopy, or Raman scattering on samples annealed for 4 s at temperatures up to 850 °C. As application, the rapid thermal annealing of Si‐implanted InP samples is carried out. Full activation of the implanted species is obtained at annealing temperatures of 850 °C. Rapid thermal annealing of InP using a GaAs proximity cap promises to be a practical technology for the fabrication of semiconductor devices based on InP.
Revisiting the Timing of Insemination at Spontaneous Estrus in Dairy Cattle

Simple Summary The possibility of artificial insemination (AI), mainly in dairy cattle, revolutionized animal and human reproduction procedures over the 20th century. In effect, AI in dairy cattle is considered the most important technological advancement in the field of animal breeding. Cows show estrous behavior over an 8-to-20 h period yet they are refractory to the bull some 10–12 h before ovulation. As spermatozoa need to persist in the female reproductive tract for 6–8 h before they are capable of fertilization, in the past 80 years the time interval for AI in cattle with fresh or frozen-thawed semen has been 24–6 h before ovulation. Recent evidence suggests this interval should be reduced. Abstract Cows show spontaneous estrus over 8–20 h but become refractory to the bull about 10–12 h before ovulation. This indicates that ovulation occurs 10–12 h after the end of estrus behavior, yet spermatozoa from the bull ejaculate need to undergo maturation and capacitation for 6 to 8 h in the female reproductive tract before they are capable of fertilization. Traditionally, the onset of estrus has been considered the best timing for artificial insemination (AI) in cattle, that is, 6 to 24 h from the first signs of estrus. However, recent findings suggest this interval should be reduced to 16 to 6 h before ovulation, bringing it closer to the end of estrus. In this review, the end of estrus rather than its onset is proposed as the best guide for AI timing in dairy cattle, and physiological indicators of late estrus are discussed such as relaxation of the intravaginal part of the uterus, a lower cervical mucus viscosity and a softer pre-ovulatory follicular consistency as simple cues indicating a cow is ready for service.
DNASE1L3 regulation by transcription factor FOXP2 affects the proliferation, migration, invasion and tube formation of lung adenocarcinoma

Lung adenocarcinoma (LUAD) is prone to bone metastasis, resulting in poor prognosis. The present study aimed to detect the expression of deoxyribonuclease 1-like 3 (DNASE1L3) and forkhead-box P2 (FOXP2) in LUAD cells to investigate the role of DNASE1L3 in the regulation of proliferation, migration, invasion and tube formation of LUAD cells and how FOXP2 affects DNASE1L3 expression. The expression of DNASE1L3 and FOXP2 in LUAD cells was analyzed by reverse transcription-quantitative PCR (RT-qPCR) and western blotting. The transfection efficiency of DNASE1L3 overexpression plasmids, FOXP2 overexpression or interference plasmids into A549 cells was also confirmed by RT-qPCR and western blotting. The viability, proliferation, migration and invasion and tube formation of LUAD cells following transfection was in turn detected by MTT, EdU staining, wound healing, Transwell and tube formation assay. The expression of proteins associated with epithelial-mesenchymal transformation and tube formation was detected by western blotting. Binding between DNASE1L3 and FOXP2 was confirmed by dual-luciferase reporter assay and chromatin immunoprecipitation. Gene Expression Profiling Interactive Analysis database predicted that underexpression of DNASE1L3 in LUAD was associated with poor prognosis. DNASE1L3 expression was decreased in LUAD cells and overexpression of DNASE1L3 inhibited the proliferation, migration, invasion and tube formation of LUAD cells. Transcription factor FOXP2 positively regulated DNASE1L3 transcription in LUAD cells. FOXP2 was also underexpressed in LUAD cells and downregulation of FOXP2 promoted proliferation, migration, invasion and tube formation of LUAD cells, which was reversed by overexpression of DNASE1L3. In conclusion, DNASE1L3 was positively regulated by transcription factor FOXP2 and overexpression inhibited proliferation, migration, invasion and tube formation of LUAD cells.
The effect of different sensory modalities on inattentional blindness in a virtual environment for attentional loss improvement

Failure to notice salient objects even looking directly at them happens when individuals' attention is preoccupied, known as inattentional blindness (IB). As a form of attentional loss, IB occurrence might cause severe outcomes due to limited cognitive resources. Varied methods have been explored to reduce the IB effect and avoid neglect of critical information. Attenuating attentional loss via aided guidance with different sensory modalities intervention could be a possible way to address this issue. This study investigates how different sensory modalities affect the cognitive performance and IB effect from behaviour and neural changes in the human brain and how could we apply this in attention training for attentional loss improvement. Two experimental sessions were conducted, with a multisensory oddball task designed in virtual reality (VR) as the main task to attract individuals' attention. In session 1, participants responded to the main task without being informed of the unexpected task-irrelevant patterns in the background, while in session 2, they were informed of the unexpected patterns but still attended to the main task. Thus, participants were divided into IB (unaware of the pattern) and Aware (aware of the pattern) groups based on their awareness of patterns in the first session. Our results revealed that this VR-based design successfully induced the IB occurrence, with four out of nine participants reporting being unaware of the unexpected patterns. Further, the multisensory oddball task showed better performance in cross-modal stimuli (visual-auditory, VA) with higher accuracy and shorter reaction time than in uni-modal (A or V) conditions. Interestingly, in session 1, the IB group showed better performance than the Aware group, indicating that the IB group was not distracted during the task since they were unaware of the patterns. These findings supported our aims to explore the impact of different sensory modalities on cognitive performance and provided a potential solution to attenuate attentional loss via manipulating the attentional set with different stimuli modalities.
Cost–Benefit Analysis of Metavariable Variation in Convolutional Autoencoders Applied to Acoustic Backscattering Data from Small Underwater Targets

With an end goal of physically interpretable results, we build on progress towards finding generalized low dimension encodings of acoustic backscattering data from sonar measurements of small targets submerged in water. The data set in use is TREX-13. The initial effort succeeded in learning non-invertible mappings (encodings) of the data to a low-dimensional vector space with convolutional autoencoders and sparse convolutional autoencoders. The prior work largely used default values for various “metavariables” according to the Keras and Tensorflow library specifications. Mitigating the failure rate of network training as well as ancillary increases in signal reconstruction accuracy and network training speed are the goals of our current efforts. The metavariables in question are the number of convolutional kernels in each network layer, the layer count, the size of the convolutional kernels, the technique for randomly initializing the values of the kernels, and the choice of nonlinear activation functions between network layers. We perform some cost benefit analysis for the modifications in terms of training time, reconstruction accuracy, and GPU memory utilization, and decide whether to continue using the variations in further research.
The Effect Of Local Government Commitment And Audit Opinion On Disclosure Of Local Government Financial Reports In Indonesia

In this study, the authors are interested in examining how the influence of heads of local government commitment and audit opinions on the disclosure of local government financial statements in Indonesia with the level of public education as a moderating variable. This study used a population of all provinces in Indonesia from 2019 to 2021, totaling 34 samples, according to the criteria needed in this study. This study uses logistic regression analysis with the results of the study that heads of local government commitment has a positive effect on local government financial statement disclosures, and audit opinions have a positive effect on local government financial statement disclosures. The level of education moderation variable can only strengthen the positive influence of heads of local government commitment on local government financial statement disclosures and weaken the positive effect of audit opinions on local government financial statement disclosures.
Effects of Human Capital on Energy Consumption: The Role of Income Inequality

High-quality human capital (HC) development has a strong influence on achieving a win-win target of economic growth and energy consumption mitigation based on the background of the contemporary “carbon neutrality” constraints in China. We here aim to empirically assess the effect of HC on energy consumption (EC) in 30 provinces of China from 2000 to 2019. Moreover, we broaden the literature by discussing the effect of HC in terms of impact mechanism and nonlinear relationship. Based on methods of the augmented mean group (AMG), the estimation of long-term impacts indicates that the improvement of HC significantly discourages the increase in EC. The intrinsic mechanism shows that the accumulation of HC significantly promotes the decline of EC through economic structure adjustment and technological innovation. Moreover, the threshold model indicates that income equality lifts the inhibitory impact of HC on EC. Accordingly, the development of HC should be involved in the policy preference of China’s provincial and national development strategies considering its effectiveness in stimulating the reduction of energy consumption.
An experimental and numerical investigation of drag reduction in a turbulent boundary layer using a rigid rodlike polymer

The drag reduction in a zero pressure gradient (ZPG) turbulent boundary layer (TBL) using a rigid rodlike polymer was experimentally and numerically investigated. Using injection of the rigid polysaccharide scleroglucan, drag reductions of approximately 10–15 % were observed, with three distinct drag reduction regimes: a non-Newtonian flow region near the injector, followed by a region of nearly constant drag reduction, and finally a region of negligible drag reduction. Decreasing the effective rotary Peclet number reduced the drag reduction effectiveness. Increasing the concentration did not improve the drag reduction, but instead shifted the spatial development of the drag reduction further downstream. A complementary direct numerical simulation of the ZPG TBL using the rigid rod constitutive equation was performed at a matching inlet Reynolds number. The simulation assumed a homogeneous concentration distribution and used estimated effective parameters for the rodlike additive. Spatial evolution of the.
Reliability optimisation of complex system using intuitionistic fuzzy optimisation technique

In this paper, we have presented intuitionistic fuzzy optimisation technique to find out the optimum system reliability of complex systems subject to constraint on system cost. In general, the system costs as objective goal have not been stated clearly. Here the system cost is considered as intuitionistic fuzzy in nature. This imprecise reliability optimisation model is solved through the intuitionistic fuzzy optimisation method. It is shown that the intuititionistic fuzzy optimisation technique is more efficient in reliability optimisation than the analogous fuzzy technique. Examples are shown to illustrate the proposed method.
Asymptotic N‐wave Solutions of the Nonplanar Burgers Equation

In this paper, we construct asymptotic N‐wave solutions for the nonplanar Burgers equation as t→∞ via a balancing argument. These constructed asymptotics are compared with the approximate solutions of the nonplanar Burgers equation obtained by an approach due to Parker (Acoust. Lett. 4 (1981)). We also present a computationally convenient form for the N‐wave solution of the nonplanar Burgers equation modifying Sachdev et al.'s (Stud. Appl. Math. 103 (1999)) approach. The asymptotic N‐wave solutions obtained by balancing argument and modification to Sachdev et al.'s approach are validated by a careful numerical study.
Validity Test Using Principal Component Analysis (PCA) Involving Research Instruments on Learner-Centeredness, Knowledge-Centeredness, and Assessment-Centeredness

Instrument is an important element in research, including in educational research. In measuring learning environment formed in a teaching process, discrete variables need to be involved. Thence, understanding that teaching-learning process has varied pedagogical outcome(s), teachers and instructors can focus on their teaching orientation—learner-centeredness, knowledge-centeredness, or assessment-centeredness—and can avoid zoning-out of context during teaching with these factorial discrete variables. There are 15 factors determining the centeredness propensity in a research instrument developed based on Bransfrod et al. (2001). This study aims to simplify and reduce these factors to obtain dominant factors that influence the centeredness in a learning environment by using Principal Component Analysis (PCA). The study was conducted by collecting data through questionnaires to 10 respondents. Finally, 5 major factors were obtained. The main factor has an Eigenvalue of 3.95 with a variance of 26.38%. The second factor has an Eigenvalue of 3.51 with a variance of 23.43%. The third factor has an Eigenvalue of 2.46 with a variance of 16.44%. The fourth factor has an Eigenvalue of 1.95 with a variance of 12.99%. The fifth factor has an Eigenvalue of 1.10 with a variance of 7.37%. The overall factor gives a cumulative diversity proportion of 86.64%. Keywords: Construct validity, Assessment, Eigenvalue, and Principal Component Analysis.
Latest developments in engineered skeletal muscle tissues for drug discovery and development

ABSTRACT Introduction With the advances in skeletal muscle tissue engineering, new platforms have arisen with important applications in biology studies, disease modeling, and drug testing. Current developments highlight the quest for engineering skeletal muscle tissues with higher complexity . These new human skeletal muscle tissue models will be powerful tools for drug discovery and development and disease modeling. Areas covered The authors review the latest advances in in vitro models of engineered skeletal muscle tissues used for testing drugs with a focus on the use of four main cell culture techniques: Cell cultures in well plates, in microfluidics, in organoids, and in bioprinted constructs. Additional information is provided on the satellite cell niche. Expert opinion In recent years, more sophisticated in vitro models of skeletal muscle tissues have been fabricated. Important developments have been made in stem cell research and in the engineering of human skeletal muscle tissue. Some platforms have already started to be used for drug testing, notably those based on the parameters of hypertrophy/atrophy and the contractibility of myotubes. More developments are expected through the use of multicellular types and multi-materials as matrices . The validation and use of these models in drug testing should now increase.
Identification of wind turbine gearbox weak compound fault based on optimal empirical wavelet transform

A double modulation phenomenon is found in wind turbine gearbox compound fault signals, consisting of a resonance modulation frequency band and an asymmetric modulation frequency band. The modal aliasing and the double modulation phenomena make it difficult to use empirical wavelet transform to obtain the spectral components in the meshing modulation regions. Our main contribution is to establish an optimal empirical wavelet transform (OEWT) framework for weak feature extraction of compound faults, which incorporates the optimal velocity synchronous linear chirplet transform (OVSLCT) and the simulated annealing (SA) algorithm to obtain the optimal parameters of the filter bank. The frequency boundary of the fault component is obtained through OVSLCT rather than the extreme value of the spectrum. A filter transition band width optimization scheme is proposed in which the optimal transition band width of the filter bank in EWT is optimized by the SA algorithm. Compared with the original EWT and variational mode decomposition, OEWT can better obtain the compound fault characteristic frequency and solve the mode aliasing problem.
Massive and Evolved Galaxies at z ≥ 5

Abstract We search for massive and evolved galaxies at z ≥ 5 in the Great Observatories Origins Deep Survey (GOODS) southern field. Combining HST ACS, VLT ISAAC and Spitzer IRAC broad–band photometric data, we develop a color selection technique to identify candidates for being evolved galaxies at high redshifts. The color selection is primarily based on locating the Balmer–break using the K- and 3.6 μm bands. Stellar population synthesis models are fitted to the SEDs of these galaxies to identify the final sample. We find 11 candidates with photometric redshifts in the range 4.9 < z < 5.6, dominated by an old stellar population, with ages 0.2-1.0 Gyr, and stellar masses in the range (0.7 − 5) × 1011 M⊙. Most of the candidates have modest amounts of internal dust extinction. The majority of the stars in these galaxies were formed at z>9 and the current star formation activity is a few percent of the inferred initial star formation rate.
ON TWO POLYCELIS SPECIES FROM ROMANIA – POLYCELIS PANTHERINA SP. NOV. AND POLYCELIS FELINA LOMENSIS BABALEAN, 2019 WITH EMENDATION AND COMPLETION OF THE 2019 NOMENCLATURAL ACT UNDER ARTICLE 10.1 (PLATYHELMINTHES, TRICLADIDA, PLANARIIDAE)

This paper presents a new Polycelis species – Polycelis pantherina from S-W Romania, which can be separated from all the other Polycelis species by the general habitus and especially by the reproductive biology – asexual population with reproduction by fission/fragmentation. The description of the subspecies Polycelis felina lomensis Babalean, 2019 is emended and completed according to ICZN art. 10.1 The subspecies Polycelis felina lomensis is elevated at the species rank by reassigning it from the genus Polycelis to the genus Ijimia: Ijimia lomensis.
Structural characterization of InAs/GaAs quantum-dot nanostructures

We have performed high-resolution x-ray diffraction measurements on vertically aligned InAs/GaAs quantum-dot nanostructures. The measurements were carried out for both the symmetric (004) and asymmetric (113) and (224) Bragg reflections. Theoretical simulations of the rocking curves indicate that the x-ray signal is primarily from the pseudomorphically strained (In,Ga)As wetting layers. The average thickness and indium composition in the wetting layers, as determined from simulations of the rocking curves, were, respectively, 0.72 nm and 88%. Transmission electron microscopy studies show the creation and annihilation of quantum dots with no observable dislocations.