Miracle-dz/UniFAR-FTUs huggingface dataset:
TAOBench: An End-to-End Benchmark for Social Networking Workloads

The continued emergence of large social network applications has introduced a scale of data and query volume that challenges the limits of existing data stores. However, few benchmarks accurately simulate these request patterns, leaving researchers in short supply of tools to evaluate and improve upon these systems. In this paper, we present a new benchmark, TAOBench, that captures the social graph workload at Meta. We open source workload configurations along with a benchmark that leverages these request features to both accurately model production workloads and generate emergent application behavior. We ensure the integrity of TAOBench's workloads by validating them against their production counterparts. We also describe several benchmark use cases at Meta and report results for five popular distributed database systems to demonstrate the benefits of using TAOBench to evaluate system tradeoffs as well as identify and address performance issues. Our benchmark fills a gap in the available tools and data that researchers and developers have to inform system design decisions.
Addressing Limitations of Slot Attention using a Multiscale Hierarchical Approach

Slot Attention (SA)[1] is an object-centric representation learning module that uses an iterative, competitive process to extract concepts from an unstructured input–e.g images. However, SA has a couple of noted failure points, and is mostly limited to synthetic datasets. Recent work on SA focuses on the decoding pipeline of the model. Analyzing the failure points and the architecture choices of the decoder-focused methods, we postulate that SA also suffers from an underlying encoder issue. For our project we’ll explore these issues on the encoding side; mainly on the limitation of SA to disambiguate textured and complex objects, and on the input sensitivity of SA where strong models fail to capture “easy” datasets.
Activation of SIRT1 Alleviates Ferroptosis in the Early Brain Injury after Subarachnoid Hemorrhage

Ferroptosis is a regulated cell death that characterizes the lethal lipid peroxidation and iron overload, which may contribute to early brain injury (EBI) pathogenesis after subarachnoid hemorrhage (SAH). Although Sirtuin 1 (SIRT1), a class III histone deacetylase, has been proved to have endogenous neuroprotective effects on the EBI following SAH, the role of SIRT1 in ferroptosis has not been studied. Hence, we designed the current study to determine the role of ferroptosis in the EBI and explore the correlation between SIRT1 and ferroptosis after SAH. The pathways of ferroptosis were examined after experimental SAH in vivo (prechiasmatic cistern injection mouse model) and in HT-22 cells stimulated by oxyhemoglobin (oxyHb) in vitro. Then, ferrostatin-1 (Fer-1) was used further to determine the role of ferroptosis in EBI. Finally, we explored the correlation between SIRT1 and ferroptosis via regulating the expression of SIRT1 by resveratrol (RSV) and selisistat (SEL). Our results showed that ferroptosis was involved in the pathogenesis of EBI after SAH through multiple pathways, including acyl-CoA synthetase long-chain family member 4 (ACSL4) activation, iron metabolism disturbance, and the downregulation of glutathione peroxidase 4 (GPX4) and ferroptosis suppressor protein 1 (FSP1). Inhibition of ferroptosis by Fer-1 significantly alleviated oxidative stress-mediated brain injury. SIRT1 activation could suppress SAH-induced ferroptosis by upregulating the expression of GPX4 and FSP1. Therefore, ferroptosis could be a potential therapeutic target for SAH, and SIRT1 activation is a promising method to inhibit ferroptosis.
Controlling StyleGANs using rough scribbles via one‐shot learning

This paper tackles the challenging problem of one‐shot semantic image synthesis from rough sparse annotations, which we call “semantic scribbles. ” Namely, from only a single training pair annotated with semantic scribbles, we generate realistic and diverse images with layout control over, for example, facial part layouts and body poses. We present a training strategy that performs pseudo labeling for semantic scribbles using the StyleGAN prior. Our key idea is to construct a simple mapping between StyleGAN features and each semantic class from a single example of semantic scribbles. With such mappings, we can generate an unlimited number of pseudo semantic scribbles from random noise to train an encoder for controlling a pretrained StyleGAN generator. Even with our rough pseudo semantic scribbles obtained via one‐shot supervision, our method can synthesize high‐quality images thanks to our GAN inversion framework. We further offer optimization‐based postprocessing to refine the pixel alignment of synthesized images. Qualitative and quantitative results on various datasets demonstrate improvement over previous approaches in one‐shot settings.
Electrochemical Determination of Dexrazoxane by Differential Pulse Voltammetry (DPV) Using a Graphene Oxide Nanosheet Modified Pencil Graphite Electrode (PGE)

Abstract Dexrazoxane is a drug that protects cancer patients undergoing chemotherapy against heart attacks that may be caused by anthracyclines. However, there is insufficient information about whether taking dexrazoxane increases the risk of developing a new type of cancer. In this study, electrochemical determination of dexrazoxane (Dex) was performed by a graphene oxide (GRPox) based disposable sensor. GRPox was synthesized and characterized by X-ray diffraction (XRD), energy dispersive X-Ray spectroscopy (EDX), and transmission electron microscopy (TEM). The GRPox-modified electrodes provide 25% signal enhancement for dexrazoxane. In this study, a detection limit of 1.24 µg/mL was obtained for dexrazoxane with advantages of disposability, low cost, and easy production.
Evaluation of an infrared thermography camera for measuring body temperature in dairy calves

Graphical Abstract Summary: The objective of this study was to validate an infrared thermography (IRT) camera for measuring calf body temperature. Researchers followed a total of 318 dairy calves daily for 14 consecutive days taking ocular temperatures with IRT and rectal temperatures using a digital thermometer. With reference to the rectal thermometer, the IRT used was neither accurate nor precise, and was biased for estimating body temperature in the calves. We suggest that this IRT system cannot serve as a proxy for rectal temperature.
Dyeing Behavior and Characterization of Recycled Cotton and Chitosan Blended Fabrics

ABSTRACT The cultivation and wet processing of cotton is very harmful to the environment. Recycling of cotton is an important way to reduce its environmental impact. For this purpose, recycled cotton by using it in a mixture with chitosan yarns and the dyeing behavior of fabrics produced from this blend were examined within the scope of sustainable production. Among the reactive, direct and acid dyeings, the highest color depths were obtained from dyeing with direct dye in alkaline medium and in the presence of salt. It was observed that the dyeing temperature was important for leveling dyeing. The fastness results of reactive dyeing were higher than the others. The FTIR analysis interpreted as that polyester might have been mixed during processing into recycled cotton and the presence of chitosan in the blend could be indicated by decreasing band intensities compared to cotton. The SEM images supported the presence of chitosan in the blended fabric. According to the TGA results, the change in temperature at which the maximum weight loss was observed in the blended fabric approached to that of chitosan. The results showed that chitosan and cotton obtained from recycling could be used as a mixture instead of cotton. Graphical abstract
Adaptation of Technology Capability with Special Attention to ASEAN NCAP in Strategic Design and Manufacturing a New Car with Safety Features

This research aims to investigate the relationship between the technology capability and car manufacturer understanding and awareness of the New Car Assessment Program for Southeast Asian Countries (ASEAN NCAP). The surveys were performed to collect the data among Malaysian car manufacturers and 90 sets of questionnaires were returned and analysed using SPSS software with the main statistical analysis highlighted are Pearson correlation and multiple regression to examine the research hypothesis. Interviews were also conducted among the car manufacturers to investigate further the research objective. The research findings concluded that there is a significant relationship between the technology capability and car manufacturers on their understanding and awareness of the ASEAN NCAP requirements. Hence, this study proved that technology capability is the essential factor for car manufacturers and it is one of the main concerns for them in producing a new safer car design.
Improving the mechanical properties of recycled aggregate concrete with graphene

Abstract This article presents the results of a preliminary research to explore the feasibility of using graphene to improve mechanical properties of recycled aggregate concrete (RAC). Graphene of different nominal flake sizes (5, 10 and 20 μm) and concentrations of 0.01%, 0.02%, 0.05% and 0.1% of the combined weight of cement and sand were incorporated into RAC with and without crumb rubber. The results indicate that there was no improvement in mechanical properties of recycled aggregates (RAs) concrete with crumb rubber. Also, if aggregates were not washed, even without any crumb rubber, adding graphene was not effective in improving mechanical properties of RAC due to excessive dust of unwashed RAs. However, the results reveal that by agitating RAs in water to remove excessive dust, adding small amount of graphene improves the mechanical properties of RAC. By adding 0.01% graphene flakes, the average compressive and splitting tensile strengths of RAC were increased from those of RAC without graphene by 43.9% and 24.1% to 39.14 and 3.76 MPa, respectively, which are comparable to those of concrete using natural aggregates (NAs). However, using more graphene flakes did not result in any further improvement.
Explainable Fragment‐Based Molecular Property Attribution

“AI & Drug Discovery” mode has significantly promoted drug development and achieved excellent performance, especially with the rapid development of deep learning, making remarkable contributions to protecting human physiological health. However, due to the “black‐box” characteristic of the deep learning model, the decision route and predicted results in different research stages assisted by deep models are usually unexplainable, limiting their application in practice and more in‐depth research of drug discovery. Focusing on the drug molecules, an explainable fragment‐based molecular property attribution technique is proposed for analyzing the influence of particular molecule fragments on properties and the relationship between the molecular properties herein. Quantitative experiments on 42 benchmark property tasks demonstrate that 325 attribution fragments, which account for 90% of the overall attribution results obtained by the proposed method, have positive relevance to the corresponding property tasks. More impressively, most of the attribution results randomly selected are consistent with the existing mechanism explanations. The discovery mentioned above provides a reference standard for assisting researchers in developing more specific and practical drug molecule studies, such as synthesizing molecule with the targeted property using a fragment obtained from the attribution method. An interactive preprint version of the article can be found at: https://www.authorea. com/doi/full/10.22541/au.165279262. 29589148.
With 3 Types of Respiratory Acquisition: 3.0 T Respiratory Triggered Acquisition Can Obtain Higher Quality DWI Images of the Upper Abdomen

Objective To compare the effects of 1.5 T and 3.0 T upper abdominal magnetic resonance diffusion-weighted imaging (DWI) under three acquisition techniques of breath holding, breath triggering, and free breathing, so as to provide a reference for the usage of upper abdominal DWI scanning. Methods Twenty-one healthy subjects were selected from social volunteers and underwent routine magnetic resonance imaging (MRI) and DWI on 1.5 T and 3.0 T, respectively. DWI included three acquisition methods: breath triggering, breath holding, and free breathing, and b values were 100 and 800. The DWI image artifacts, image quality, apparent diffusion coefficient (ADC), and the signal-to-noise ratio (SNR) obtained through the three acquisition methods were compared. Results The 1.5 T free-breathing DWI image quality was the best, while the 3.0 T had the best breath-triggered DWI image quality. The 3.0 T breath-triggered DWI image quality was better than the 1.5 T free-breathing DWI image (P=0.012), and the SNR of free-breathing DWI was the highest. Between the two field intensities, the SNR of the liver in the 3.0 T group was much lower than that in the 1.5 T group, and obvious differences were not observed in ADC values of normal liver, gallbladder, kidney, spleen, and pancreas. Conclusion 3.0 T respiratory-triggered acquisition can obtain higher quality DWI images. But in the case of only 1.5 T field strength, free-breathing acquisition of DWI images should be selected.
High blood pressure and abdominal obesity in adolescents

Objective: To analyze the association between abdominal obesity and high blood pressure among adolescents of public schools from Londrina (PR), Brazil. Methods: The sample was composed by 656 adolescents with age ranging from ten to 13 years old. The following measures were taken: body mass, height, waist circumfer- ence and blood pressure at rest. Mann-Whitney and Stu- dent's t-test were used to compare and analyze numerical variables. The chi-square test analyzed the association between blood pressure and waist circumference. Results: Association between abdominal obesity and high blood pressure was present in both genders (PR 2.7; 95%CI 1.8-4.2). Abdominal obesity was associated with higher blood pressure independently of age. Conclusions: Abdominal obesity was associated to high blood pressure in adolescents.
Unveiling the increasingly altered patterns of wetland ecosystem functional diversity in the lower Delta of the Paraná River

Since climate, environmental and anthropic controls affect ecosystem functioning simultaneously, wetlands are permanently changing at different spatio–temporal scales. Thus, regionalizations based not only on structural, but also on functional features of ecosystems constitute a much‐needed baseline towards proper decision‐making and environmental management in the context of land degradation and water management infrastructure. Our aim was to identify and characterize the spatio‐temporal patterns of ecosystem functional diversity in a highly diverse and altered mosaic of wetland ecosystems and assess its environmental and anthropic controls. The characterization was based on satellite‐derived functional units (FUs), involving seven rasterized traits derived from complementary time‐series decomposition techniques applied to a 15‐year n…. v…… d… i…. (NDVI) product (2001–2015). The study area exhibited a vast functional heterogeneity, strongly related to differing anthropic and hydro‐geomorphological features. Vegetation dynamics were increasingly restricted by the precipitation regime in areas naturally or anthropically decoupled from the flood pulse, which also exhibited the lowest ecosystem functional richness. Depicted as morpho‐dynamically stable, areas still subject to recurring overflow events and higher water permanence exhibited sustained NDVI values during the growing season. Our study addresses a proper case of globally widespread land degradation processes occurring across several wetland ecosystems on Earth. Particularly, development of unrestricted water management infrastructure and decouplement from the hydrologic regime suggests an ongoing loss of ecosystem functional diversity and constrained carbon gain dynamics. In this context, the spatio‐temporal accuracy of our study constitutes a reliable and replicable foundation, suitable for improvement of environmental management in wetland ecosystems.
Tele-Rehabilitation System as an Application of MPEG-2 System

A Distributed Tele-Rehabilitation System is an application that helps remotely located clinicians work in a process of patient rehabilitation. With this system, clinicians are able to share medical information through the network to make diagnoses and discuss medical treatment for a patient. To enable the mentioned functionalities, the system uses MPEG-2 as an infrastructure. There are two kind of medical data that need special place in MPEG-2, Medical Rehabilitation Signal and Patient Medical Record. As a result of study literature and analysis process the following decision can be taken. Medical Rehabilitation Signal should be incorporated into PES Packet Data with elementary stream ID 0xBD. Patient Medical Record should be placed as descriptors in Program Map Table. Further on PDU format for Medical Rehabilitation Signal and Patient Medical Record has been decided. A prototype implementation shows that the Tele-Rehabilitation system can works well using MPEG-2 as an infrastructure. Abstract in Bahasa Indonesia : SSistem Tele-Rehabilitasi Terdistribusi adalah sebuah aplikasi yang membantu tenaga medis untuk melakukan proses rehabilitasi terhadap pasien. Dengan sistem ini, tenaga medis bisa melakukan diskusi jarak jauh dengan tenaga medis lain untuk memberikan perawatan yang paling tepat terhadap pasien. Untuk itu, MPEG-2 dipakai sebagai infrastruktur. Ada dua jenis data medis yang memerlukan tempat khusus dalam MPEG-2, Sinyal Rehabilitasi Medis dan Catatan Medis Pasien. Sebagai hasil dari literatur studi dan proses analisa, keputusan berikut telah diambil. Sinyal Rehabilitasi Medis seharusnya ditempatkan dalam Paket Data PES dengan stream elementer yang mempunyai ID 0xBD. Catatan Medis Pasien seharusnya ditempatkan sebagai descriptor dalam Program Map Table. Lebih jauh, format PDU untuk Sinyal Rehabilitasi medis dan Catatan Medis Pasien juga sudah ditentukan. Sebuah prototipe sudah diimpelementasikan dan menunjukkan bahwa Sistem Tele-Rehabilitasi dapat bekerja dengan baik menggunakan MPEG-2 sebagai infrastruktur. Kata kunci : MPEG-2, Distribusi Tele-Rehabilitasi Sistem.
Are students barking up the wrong tree? A causal model of factors driving effective student–faculty interactions

Abstract Student–faculty interactions that promote learning are essential contributors to student retention, academic success and satisfaction. But the factors that causally initiate and frame these interactions are not well understood. Only if students evaluate these interactions as positive will they seek them. We conducted a survey experiment with students (n = 375) from a tuition-fee-free German business school, using conditional process analysis to assess which factors frame effective interactions. We focus on out-of-classroom standard and non-standard requests that students make to faculty, then investigate how faculty and student gender and students’ academic entitlement influence the interaction. Our study examines how students evaluate the interaction with faculty: when they seek interaction, their expectations of getting their requests approved, and their disappointment when their requests are declined. We find a significant influence of the request type along with moderating effects of faculty gender, student gender and student entitlement, particularly for non-standard work requests. We conclude with policy implications for university management: developing target-group-specific measures that facilitate the desired and positively evaluated student–faculty interactions might benefit all university stakeholders.
Numerical Investigation of Square Footing Positioned on Geocell Reinforced Sand By Using Abaqus Software

Abstract The usage of geocell reinforcement for foundations supported on weak soil has been increased these days. The purposed study uses FEM-based ABAQUS software to analyse the behaviour of square footing supported on geocell reinforced sands subjected to static vertical loading. Numerical analysis was performed to find the optimum combination of the different geometric parameters of the geocell reinforcement. Three distinct types of sands were employed in the study with relative densities of 30%, 50%, and 70%. The geometric parameters of the geocell, such as the placement depth of geocell (u), the width (b), and the height (h) of the geocell, were modified in relation to the footing width (B) to access the optimum combination ratios. The inclusion of the geocell reinforcement increases the load-carrying capacity up to 5-6 times compared to unreinforced sand. The results obtained from the numerical analysis were intended to correlate well with the experimental data available in the literature.
An Efficient Machine Learning-Based Feature Optimization Model for the Detection of Dyslexia

Dyslexia is among the most common neurological disorders in children. Detection of dyslexia therefore remains an important pursuit for the research works across various domains which is illustrated by the plethora of work presented in diverse scientific articles. The work presented herein attempted to utilize the potential of a unified gaming test of subjects (dyslexia/controls) in tandem with principal components derived from data to detect dyslexia. The work aims to build a machine learning model for dyslexia detection using comprehensive gaming test data. We have attempted to explore the potential of various kernel functions of the Support Vector Machine (SVM) on different number of principal components to reduce the computational complexity. A detection accuracy of 92% is obtained from the radial basis function with 5 components, and the highest detection accuracy obtained from the radial basis function with 3 components is 93%. On the contrary, the Artificial Neural Network(ANN) shows an added advantage with minimal number of hyperparameters with 3 components for obtaining an accuracy of 95%. The comparison of the proposed method with some of the existing works shows efficacy of this method for dyslexia detection.
Fusion VIO: An Extendable Sensor Fusion Framework for Unmaned Vehicles

Real-time perception based on the simultaneous localization and mapping (SLAM) technology is of immense application potential in the industry filed. In this work, we provide an extended Kalman filter (EKF) based visual SLAM framework named Fusion VIO, which contains HDR imaging system, hardware synchronization, object detection, filter based sensor fusion, and semantic fusion. Notably, Fusion VIO well fuses loop closure information, which takes effects in solving the error problem during operation of the robot and improving the robustness of the system. Besides, experimental validation shows that Fusion VIO not only maintains high accuracy but also cost one-third resources compared to the common VINS fusion. Our work demonstrates a novel sensor fusion framework for unmaned vehicles.
Innovative Collaborative Design of Ru Porcelain Shape Based on Digital Shape Technology

Under the background of digital technology, computer-aided design is still in the initial stage of application in the field of design and manufacture of ceramic products. In order to improve the informatization degree of ceramic industry, advance the efficiency of product design, and satisfy the demand of personalized customization, in this paper, Ru porcelain is selected as the research object, and according to its shape characteristics, based on the 3D evolution of data combined with the image shape method and entity design, the design process of Ru porcelain shape was put forward, and the collaborative design of Ru porcelain was implemented with Yuhu spring bottle as the representative. The simulation results show that the model is highly practical and helpful to realize the convenient design of ceramic products.