Miracle-dz/UniFAR-FTUs huggingface dataset:
Scaling Optical Interconnects for Hyperscale Data Center Networks

Due to widespread applications and rapid development of cloud computing and Internet services, hyperscale data centers have experienced an unprecedented demand for networking. Data center networks are required not only to handle fast-growing traffic, which doubles almost every one to two years, but also to provide high flexibility and availability to support rapidly changing businesses as well. Therefore, hyperscale data center networks have become one of the main drivers for optical interconnect technologies in recent years. In this article, technologies for scaling optical interconnects for inter-data center interconnects (DCIs) are presented. We first describe hyperscale data center network architectures and requirements, as well as the differences between carrier’s optical transport networks and DCI optical networks, with the main focus on metro-DCI and campus-DCI networks. The scale and fast growth rates of DCI networks require innovations not only in data plane technologies but also in control and management planes as well. In data planes, high-capacity flexible coherent technology, pluggable wavelength-division-multiplexing (WDM) optical transponders, including 100G direct-detection four-level pulse-amplitude modulation (PAM4) and coherent 400ZR/800ZR, and flex-grid and disaggregated reconfigurable optical add-drop multiplexer (ROADM) optical networks are described. Control and management planes are an integral part of optical transport networks and crucial for effectively operating DCI networks. We show that standard protocols, data models, and modular design of a software platform are essential to building a scalable open and disaggregated optical network, which is fundamental to enabling high automation and intelligence in an optical network. An example control and management platform is discussed in detail. With current fiber capacity approaching the nonlinear Shannon limit, challenges to further scale DCI networks and some potential technologies to support ever-increasing traffic growth are discussed at the end.
Application of Machine Learning Techniques to Predict the Mechanical Properties of Polyamide 2200 (PA12) in Additive Manufacturing

Additive manufacturing (AM) is an attractive technology for the manufacturing industry due to flexibility in its design and functionality, but inconsistency in quality is one of the major limitations preventing utilizing this technology for the production of end-use parts. The prediction of mechanical properties can be one of the possible ways to improve the repeatability of results. The part placement, part orientation, and STL model properties (number of mesh triangles, surface, and volume) are used to predict tensile modulus, nominal stress, and elongation at break for polyamide 2200 (also known as PA12). An EOS P395 polymer powder bed fusion system was used to fabricate 217 specimens in two identical builds (434 specimens in total). Prediction is performed for XYZ, XZY, ZYX, and Angle orientations separately, and all orientations together. The different non-linear models based on machine learning methods have higher prediction accuracy compared with linear regression models. Linear regression models only have prediction accuracy higher than 80% for Tensile Modulus and Elongation at break in Angle orientation. Since orientation-based modeling has low prediction accuracy due to a small number of data points and lack of information about the material properties, these models need to be improved in the future based on additional experimental work.
Comments on “Feedback Capacity of Stationary Gaussian Channels”

In the above article <xref ref-type="bibr" rid="ref1">[1]</xref>, the author characterizes the capacity of power-constrained channels with additive stationary Gaussian noise. Specifically, in <xref ref-type="sec" rid="sec3">Section III</xref>, the feedback capacity is shown to correspond with the solution to a variational optimization problem. Section IV gives structural properties of the solution for this optimization problem. Among these properties, it stands out the capacity-achieving optimality of using a short-length input <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> with arbitrarily small variance, and thus a power spectral density <inline-formula> <tex-math notation="LaTeX">$S_{V}$ </tex-math></inline-formula> equal to zero. These structural properties are further developed in its sections V and VI for first- and <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>-th-order autoregressive moving average channel noise, respectively, also showing the capacity-achieving optimality of the Schalkwijk-Kailath scheme for this scenario. In this note, we show that the proof of <xref ref-type="corollary" rid="corollary4.4">Corollary 4.4</xref> in <xref ref-type="bibr" rid="ref1">[1]</xref> (which claims that the choice <inline-formula> <tex-math notation="LaTeX">$S_{V} = 0$ </tex-math></inline-formula> is capacity achieving) is erroneous. As a consequence, the proofs of theorems 4.1, 4.6, 5.3, and 6.1, propositions 4.7 and 5.1, as well as <xref ref-type="remark" rid="remark4.5">remarks 4.5</xref> and 5.2, and Lemma 6.1 in <xref ref-type="bibr" rid="ref1">[1]</xref> are invalid, because they rely upon the optimality of choosing <inline-formula> <tex-math notation="LaTeX">$S_{V} =0$ </tex-math></inline-formula>.
DNA Methylation Difference between Female and Male Ussuri Catfish (Pseudobagrus ussuriensis) in Brain and Gonad Tissues

DNA methylation has been found to be involved in sex determination and differentiation in many aquaculture species. The Ussuri catfish (Pseudobagrus ussuriensis) is a popular aquaculture fish in China with high economic value in which male-biased sex dimorphism was observed in terms of body size and body weight. In this study, DNA methylation-sensitive RAD sequencing (Methyl-RAD) was used to explore the epigenetic difference between adult male and female samples in brain and gonad tissues. In brain tissues, 5,442,496 methylated cytosine sites were found and 9.94% of these sites were from symmetric CCGG or CCWGG sites. Among these sites, 321 differential DNA methylation sites (DMSs) in 171 genes were identified, while in gonad tissues, 4,043,053 methylated cytosines sites were found in total and 11.70% of them were from CCGG or CCWGG. Among these sites, 78 differential DNA methylation sites were found which were located in 64 genes. We also found several sex-determination genes among these differential methylated genes, such as amh, gsdf and hsd11b2 in brain tissues and slco3a1, socs2 and trim47 in gonad tissues. These results provided evidence for understanding the function of DNA methylation in the sex differentiation in Pseudobagrus ussuriensis, which further deepens the relationship between gene regulation and epigenetics.
Corn planting quality assessment in very high-resolution RGB UAV imagery using Yolov5 and Python

Abstract. Uniform plant spacing along crop rows is a primary concern in maximising yield in precision agriculture, and research has shown that variation in this spacing uniformity has a detrimental effect on productive potential. This irregularity needs to be evaluated as early and efficiently as possible to facilitate effective decision-making. Traditionally, variation in seedling spacing is sampled manually on site, however recent technological developments have made it possible to refine, scale and automate this process. Using machine-learning (ML) object detection techniques, plants can be detected in very high-resolution RGB (redgreen-blue) imagery acquired by an unmanned aerial vehicle (UAV), and after processing and geometric analysis of the results a measurement of the variability in intra-row plant distances can be obtained. This proposed technique is superior to traditional methods since the sampling can be made over more area in less time, and the results are more representative and objective. The main benefits are speed, accuracy and cost reduction. This work aims to demonstrate the feasibility of automatically assessing sowing quality in any number of images, using ML object detection and the Shapely Python library for geometrical analysis. The prototype model can detect 99.35% of corn plants in test data from the same field, but also detects 1.89% false positives. Our geometric analysis algorithm has been shown to be robust in finding planting rows orientation and interplant lines in test cases. The result is a coefficient of variation (CV) calculated per sample image, which can be visualised geographically to support decision-making.
Probabilistic Lightning Forecast Guidance for Aviation

Thunderstorms account for a significant percentage of air traffic delays. To provide tactical support for air traffic management, more graphical and probabilistic weather forecast guidance is needed at higher resolution and for shorter time periods than the guidance currently available. Using statistical techniques, the Meteorological Development Laboratory (MDL) has produced automated probabilistic thunderstorm guidance for many years. Traditional MDL Model Output Statistics (MOS; Glahn and Lowry 1972) products support aviation weather operations by providing sitespecific forecast guidance for wind, ceiling height, sky cover, visibility, obstruction to vision, and thunderstorms for over 1500 locations, most of which are airports. The equations to predict the probability of thunderstorms are developed for the contiguous United States (CONUS) by using observed lightning data and output from numerical weather prediction models. More details describing the equation development are provided later in this paper.
A Structural Model to Explain Influences of Organisational Communication on the Organisational Commitment of Primary School Staff

Organisational commitment is a job attitude frequently linked to employee morale, motivation and behaviour. High organisational commitment has been associated with increased effort and productivity, while low commitment has been associated with low productivity, absenteeism and turnover. There is evidence to suggest aspects of organisational communication are important in this regard. This article reports the results of a study that investigated the relationships between a comprehensive set of aspects of organisational communication and general organisational commitment, while also identifying those that had the most important effects on organisational commitment. Participants were 1575 staff members from government and non-government primary schools across all states and territories of Australia. Data were gathered using a survey comprising the Organisational Communication in Primary Schools Questionnaire and a five-item general organisational commitment scale. Exploratory and confirmatory factor analyses were used to identify and validate constructs for measurement. Structural equation modelling was used to identify important relationships. Of the ten aspects of organisational communication identified, five had significant effects on general organisational commitment. The most important of these concerned openness between principals and staff, supportive communication among colleagues (positive effects) and communication overload (negative effects). Implications for school leadership and school culture are discussed along with directions for further research.
Generic Development of Bin Pick-and-Place System Based on Robot Operating System

Bin pick-and-place is an important topic in factory automation and warehouse automation. In this paper, a bin pick-and-place system based on robot operating system (ROS) is implemented to make a six-degree-of-freedom (6-DOF) robot manipulator to complete multiple pick-and-place tasks. The proposed system uses ROS to integrate an object perception module and a pick-and-place module, where the former uses an RGB-D camera to capture images inside the bin, and the latter controls a 6-DOF robot manipulator and two self-made vacuum tools. To estimate the pose of the target object, a YOLOv4 object detector is implemented, and an object sorting method is proposed to find the target object in the image. Then, a pose estimation method based on computer aided design (CAD) is proposed to estimate the pose of target object. To perform the object pick-and-place operations, a coordinate transformation node is designed to transfer the pose of the target object into the workspace. Then, a link distance-based bin collision avoidance method is proposed to avoid collisions. Finally, the angle of the 1-DOF vacuum tool and the picking and placement poses of the robot manipulator are obtained from the result of the bin collision avoidance and the pose of the target object. In this study, a total of ten ROS nodes are designed, and the solutions that make each function easier to implement and reproduce are proposed. In the experiments, we set up four experiments with two task types and two object types to verify the effectiveness of the implemented bin pick-and-place system.
High-Toughness Aluminum-N-Doped Polysilicon Wiring for Flexible Electronics

One of the essential requirements of any flexible substrate electronic system is the availability of reliable, high density, fine pitch interconnects between components. In this work, we demonstrate a high-toughness two-layer (aluminum, N-doped polysilicon) composite wiring scheme. The top aluminum layer carries most of the current while the polysilicon underlayer electrically bridges any cracks present on the top aluminum induced by flexing thus maintaining electrical conductivity even at very high stresses. When composite and Al control wires on a flexible tape were subject to 4000 cycles of bending, we observed that Al control wires fracture at a 2.5 mm radius of curvature but the composite wires maintain electrical conduction with an increased resistance.
English language teaching pedagogical reforms in Vietnam: External factors in light of teachers’ backgrounds

Abstract The Vietnamese government has implemented many changes to improve the English competencies of the Vietnamese people. However, the results seemed unsatisfactory because the English as a foreign language teachers had been affected by many external factors. Thus, this study addressed two main research questions, including (1) What external factors affect EFL teachers’ responses to English language teaching pedagogical reforms? and (2) How these factors affect different groups of teachers in light of their backgrounds? This study was designed as a mixed-methods approach using a questionnaire and semi-structured interviews to answer those questions. The current study involved 102 EFL high school teachers working in the Southwest of Vietnam. The results showed that the factor on students’ learning outcomes was the most influential external factor. Besides, the influence level of external factors was differed by the teachers’ educational qualifications in the influence level of some external factors, namely previous educational policies, students’ learning outcomes, and school facilities. At the end of this paper, some critical discussions, educational implications, limitations, and recommendations for further research are presented.
Human Amniotic Fluid Stem Cells Ameliorate Thioglycollate-Induced Peritonitis by Increasing Tregs in Mice

Mesenchymal stem cells (MSCs) affect immune cells and exert anti-inflammatory effects. Human amniotic fluid stem cells (hAFSCs), a type of MSCs, have a high therapeutic effect in animal models of inflammation-related diseases. hAFSCs can be easily isolated and cultured from amniotic fluid, which is considered a medical waste. Hence, amniotic fluid can be a source of cells for MSC therapy of inflammatory diseases. However, the effect of hAFSCs on acquired immunity in vivo, especially on regulatory T cells, has not yet been fully elucidated. Therefore, in this study, we aimed to understand the effects of hAFSCs on acquired immunity, particularly on regulatory T cells. We showed that hAFSCs ameliorated the thioglycollate-induced inflammation by forming aggregates with host immune cells, such as macrophages, T cells, and B cells in the peritoneal cavity. Further, the regulatory T cells increased in the peritoneal cavity. These results indicated that, in addition to helping the innate immunity, hAFSCs could also aid the acquired immune system in vivo against inflammation-related diseases by increasing regulatory T cells.
Systematic Investigation on the Glass Transition Temperature of Binary and Ternary Sugar Mixtures and the Applicability of Gordon–Taylor and Couchman–Karasz Equation

Glass transition temperatures (Tg) of carbohydrate mixtures consisting of only one monomer and glycosidic binding type (aldohexose glucose, α1-4-glycosidic bonded) were studied by differential scanning calorimetry (DSC). The aim of this work was to systematically assess the predictability of Tg of anhydrous binary and ternary sugar mixtures focusing on the components Tg, molecular chain length, and shape. Binary systems were investigated with glucose as a monosaccharide and its linear di-, tri-, tetra-, penta-, hexa-, and heptasaccharides. Additionally, the Tg of ternary carbohydrate systems prepared with different glucose/maltose/maltotriose mass fractions were studied to evaluate the behavior of more complex mixtures. An experimental method to prepare fully amorphized, anhydrous mixtures were developed which allows the analysis of mixtures with strongly different thermodynamic pure-component properties (Tg, melting temperature, and degradation). The mixtures’ Tg is systematically underestimated by means of the Couchman–Karasz model. A systematic, sigmoidal deviation behavior from the Gordon–Taylor model could be found, which we concluded is specific for the investigated glucopolymer mixtures. At low concentrations of small molecules, the model underestimates Tg, meeting the experimental values at about equimolarity, and overestimates Tg at higher concentrations. These deviations become more pronounced with increasing Tg differences and were explained by a polymer mixture-specific, nonlinear plasticizing/thermal volume expansion effect.
TUDCA protects against tunicamycin-induced apoptosis of dorsal root ganglion neurons by suppressing activation of ER stress

The existence of endoplasmic reticulum (ER) stress in neurodegenerative diseases has been well established. Tauroursodeoxycholic acid (TUDCA) is a bile acid taurine conjugate derived from ursodeoxycholic acid, which has been reported to exert cytoprotective effects on several types of cells by inhibiting ER stress. The present study explored the effects of TUDCA on primary cultured rat dorsal root ganglion (DRG) neurons. Cell viability and apoptosis of DRG neurons treated with TUDCA and tunicamycin were detected by CellTiter-Blue assay and TUNEL staining, respectively. The protein levels and phosphorylation of apoptosis and ERS-related signaling pathway molecules were detected by western blot, and the mRNA levels of related genes were assessed by reverse transcription-quantitative PCR. Notably, TUDCA had no significant cytotoxic effect on DRG neurons at concentrations ≤250 µM. In addition, the apoptosis induced by tunicamycin exposure was markedly suppressed by TUDCA, as indicated by the percentage of TUNEL-positive cells, the activities of caspases and the changes in expression levels of critical apoptosis factors. Furthermore, the cytotoxicity of tunicamycin in DRG neurons was accompanied by an increase in malondialdehyde (MDA) content, reactive oxygen species (ROS) and lactate dehydrogenase (LDH) production, and a decrease in glutathione (GSH) levels. The changes in oxidative stress-related factors (ROS, LDH, MDA and GSH) were reversed by TUDCA. Furthermore, as determined by western blotting, the increase in C/EBP homologous protein, glucose-regulated protein 78 and cleaved caspase-12 expression following tunicamycin treatment suggested the activation of ER stress. Downregulation of ER stress components and unfolded protein response sensors by TUDCA confirmed the implication of ER stress in the effects of TUDCA on DRG neurons. In conclusion, the present study indicated that TUDCA may protect against tunicamycin-induced DRG apoptosis by suppressing the activation of ER stress. The protective effect and the therapeutic value of TUDCA in nervous system injury require further study in animal models.
Self-Attention-Based Edge Computing Model for Synthesis Image to Text through Next-Generation AI Mechanism

Image synthesis based on natural language description has become a research hotspot in edge computing in artificial intelligence. With the help of generative adversarial edge computing networks, the field has made great strides in high-resolution image synthesis. However, there are still some defects in the authenticity of synthetic single-target images. For example, there will be abnormal situations such as “multiple heads” and “multiple mouths” when synthesizing bird graphics. Aiming at such problems, a text generation single-target model SA-AttnGAN based on a self-attention mechanism is proposed. SA-AttnGAN (Attentional Generative Adversarial Network) refines text features into word features and sentence features to improve the semantic alignment of text and images; in the initialization stage of AttnGAN, the self-attention mechanism is used to improve the stability of the text-generated image model; the multistage GAN network is used to superimpose, finally synthesizing high-resolution images. Experimental data show that SA-AttnGAN outperforms other comparable models in terms of Inception Score and Frechet Inception Distance; synthetic image analysis shows that this model can learn background and colour information and correctly capture bird heads and mouths. The structural information of other components is improved, and the AttnGAN model generates incorrect images such as “multiple heads” and “multiple mouths. ” Furthermore, SA-AttnGAN is successfully applied to description-based clothing image synthesis with good generalization ability.
Compact Design of Modified Pentagon Shaped Monopole Antenna for UWB Applications

 In this work detailed analysis of a modified, pentagon-shaped planar antenna is presented for ultra-wide bandwidth (UWB) applications. The proposed antenna was designed on an FR-4 substrate and has a compact size of 12 × 22 × 1.6 mm. It achieves an impedance bandwidth of 8.73 GHz (3.8–12.53 GHz) in the UWB range. The design has a uniform gain and stable radiation pattern in the operating