Miracle-dz/UniFAR-FTUs huggingface dataset:
In-Network Key-Value Cache with Linearizability

Recently, In-Network Cache (INC) systems have been proposed to promote the performance of remote storage systems. INC offloads cache onto programmable switches between the clients and the servers, responding to clients’ data queries within a sub-RTT time. However, most existing INC solutions do not take applications’ linearizability requirement into consideration, which could lead to query errors and storage state errors in the runtime. We propose a new INC system — NetKV-L, which preserves the high-performance I/O without compromising the linearizability. NetKV-L devises a sequentiality enforcement mechanism, a PSN correction mechanism, and a response memorization mechanism to guarantee linearizability under possible unreliable network conditions. Our prototype and experiments show that NetKV-L could achieve almost the same performance as the state-of-the-art systems while additionally guaranteeing linearizability.
Towards Total Traffic Awareness

A combination of factors render the transportation sector a highly desirable area for data management research. The transportation sector receives substantial investments and is of high societal interest across the globe. Since there is limited room for new roads, smarter use of the existing infrastructure is of essence. The combination of the continued proliferation of sensors and mobile devices with the drive towards open data will result in rapidly increasing volumes of data becoming available. The data management community is well positioned to contribute to building a smarter transportation infrastructure. We believe that efficient management and effective analysis of big transportation data will enable us to extract transportation knowledge, which will bring significant and diverse benefits to society. We describe the data, present key challenges related to the extraction of thorough, timely, and trustworthy traffic knowledge to achieve total traffic awareness, and we outline services that may be enabled. It is thus our hope that the paper will inspire data management researchers to address some of the many challenges in the transportation area.
CACluster: A Clustering Approach for IoT Attack Activities Based on Contextual Analysis

Attacks against IoT have shown a rapid increase in both quantity and complexity. Analysts must handle massive alerts and determine the type of attack manually. In addition, the same attack activity may present polymorphism alert sequences due to overlapping attacks, adaptive attack strategy, error alerts, etc, which poses a severe challenge for human analysis. This manual-dependent and scenario-by-scenario security model is seriously overwhelming security analysts. This paper proposes a contextual-analysis-based clustering approach, CACluster, to aggregate similar attack activities end-to-end. It embeds alert context into vector space and uses an unsupervised clustering method to find similar attack activities based on domain matching and vector distance. Experimental results demonstrate that the CACluster could accurately aggregate similar attack activities, with 0.888 purity, reducing the number of attack activities by 84.8%. It will significantly cut down analysts’ workload.
A low-cost attack on a Microsoft captcha

CAPTCHA is now almost a standard security technology. The most widely deployed CAPTCHAs are text-based schemes, which typically require users to solve a text recognition task. The state of the art of CAPTCHA design suggests that such text-based schemes should rely on segmentation resistance to provide security guarantee, as individual character recognition after segmentation can be solved with a high success rate by standard methods such as neural networks. In this paper, we present new character segmentation techniques of general value to attack a number of text CAPTCHAs, including the schemes designed and deployed by Microsoft, Yahoo and Google. In particular, the Microsoft CAPTCHA has been deployed since 2002 at many of their online services including Hotmail, MSN and Windows Live. Designed to be segmentation-resistant, this scheme has been studied and tuned by its designers over the years. However, our simple attack has achieved a segmentation success rate of higher than 90% against this scheme. It took on average ~80 ms for the attack to completely segment a challenge on an ordinary desktop computer. As a result, we estimate that this CAPTCHA could be instantly broken by a malicious bot with an overall (segmentation and then recognition) success rate of more than 60%. On the contrary, the design goal was that automated attacks should not achieve a success rate of higher than 0.01%. For the first time, this paper shows that CAPTCHAs that are carefully designed to be segmentation-resistant are vulnerable to novel but simple attacks.
TransFlowLog: Log Anomaly Detection Based on Transformer Encoder and Interflow Decoder

Logs are valuable resources that record the health status of systems. Analyzing logs to uncover and investigate abnormal behaviors has become an essential approach of ensuring system security. However, some potential anomalies may be missed when performing log anomaly detection, and even a seemingly insignificant abnormal behavior can lead to a series of severe anomalies or continuous negative impact on the performance of systems. Therefore, the reliability and security of systems are facing significant challenges. To address this issue, in this study, we propose TransFlowLog, an Encoder-Decoder architecture-based approach for log anomaly detection. It utilizes the Transformer Encoder, a state-of-the-art sequence modeling technique, to comprehensively understand contextual relationships using self-attention mechanism. Moreover, we introduce the Interflow Decoder, which considers information exchange between channels in embedded log sequences. The Interflow Decoder enhances the features encoded by the Transformer Encoder in both sequence and channel dimensions, thereby capturing interdependence between different channels. Comparative experiments conducted on three real-world datasets demonstrate the effectiveness of the proposed method, as it achieves higher F1-score and reduces the number of false negatives.
The biology of diplostomatid eyeflukes of fishes

Eyeflukes of freshwater fishes are larval strigeoid digeneans associated with a number of genera including Diplostomum and Tylodelphys. Their geographical distribution is very wide and they must be regarded as extremely common parasites of many species of freshwater fishes. The fish is the second intermediate host in a complex, three host life cycle. Eyeflukes can be pathogenic to fish and therefore of particular significance in aquaculture where farmed salmonids (some species of trout) and cyprinids (carp) are especially susceptible and may develop rapid and dramatic lesions that include poor growth, growth deformities and blindness which, in certain situations, culminate in mass mortalities within a short period of time (Chappell et ah, 1994). This short review will focus on selected aspects of the biology of eyeflukes in fishes and will highlight those areas where there are clear lacunae in our knowledge that warrant further exploration. The approach reflects the personal perspective of the author rather than an attempt to be comprehensive.
Radiographic Sizing for Meniscal Transplantation Using 3-D CT Reconstruction

Abstract In meniscus transplantation, allograft size mismatch causes increased contact pressures and early degeneration of the knee. The purpose of this study is to compare the accuracy and reliability of sizing the tibial plateau using three-dimensional (3-D) computed tomography (CT) scans versus plain radiographs (XR). Anteroposterior (AP) and lateral XR as well as CT with 3-D reconstructions were performed on 16 cadaveric knees. Sagittal and coronal dimensions of the hemiplateaus were measured on each imaging modality and then on the disarticulated specimens. CT estimates of plateau size were closer to anatomic measurements compared with radiographic estimates in all dimensions and these differences were statistically significant (p < 0.0001). CT scan fell within 5 mm of anatomic measurements 100% of the time versus 76.5% for XR and within 2 mm 71.9% of the time versus 34.4%. The proportion of CT measurements within 2 mm of actual values was significantly higher for CT for the lateral meniscus on AP (p = 0.0011) and lateral (p = 0.0039) views. 3-D CT has less error in measurement of the tibial plateau than XR and estimates were more likely to be within 2 and 5 mm of actual size. This may decrease the likelihood of allograft size mismatch.
Muscle Sympathetic Nerve Activity Is Related to a Surrogate Marker of Endothelial Function in Healthy Individuals

Background Evidence from animal studies indicates the importance of an interaction between the sympathetic nervous system and the endothelium for cardiovascular regulation. However the interaction between these two systems remains largely unexplored in humans. The aim of this study was to investigate whether directly recorded sympathetic vasoconstrictor outflow is related to a surrogate marker of endothelial function in healthy individuals. Methods and Results In 10 healthy normotensive subjects (3 f/7 m), (age 37±11 yrs), (BMI 24±3 kg/m2) direct recordings of sympathetic action potentials to the muscle vascular bed (MSNA) were performed and endothelial function estimated with the Reactive Hyperaemia- Peripheral Arterial Tonometry (RH-PAT) technique. Blood samples were taken and time spent on leisure-time physical activities was estimated. In all subjects the rate between resting flow and the maximum flow, the Reactive Hyperemic index (RH-PAT index), was within the normal range (1,9–3,3) and MSNA was as expected for age and gender (13–44 burst/minute). RH-PAT index was inversely related to MSNA (r = −0.8, p = 0.005). RH-PAT index and MSNA were reciprocally related to time (h/week) spent on physical activity (p = 0.005 and p = 0.006 respectively) and platelet concentration (PLT) (p = 0.02 and p = 0.004 respectively). Conclusions Our results show that sympathetic nerve activity is related to a surrogate marker of endothelial function in healthy normotensive individuals, indicating that sympathetic outflow may be modulated by changes in endothelial function. In this study time spent on physical activity is identified as a predictor of sympathetic nerve activity and endothelial function in a group of healthy individuals. The results are of importance in understanding mechanisms underlying sympathetic activation in conditions associated with endothelial dysfunction and emphasise the importance of a daily exercise routine for maintenance of cardiovascular health.
Application of Nodal Discontinuous Glaerkin Methods in Acoustic Wave Modeling

This work will explore the discontinuous Galerkin finite element method (DG-FEM) for solving acoustic wave equations in heterogeneous material. High order convergence of DG-FEM will be verified by examples. The numerical error using DG-FEM has the same components as using finite-difference method: grid dispersion and misalignment between numerical grids and material interfaces. Both error components can be reduced by high order schemes and mesh techniques respectively as I expect. The numerical experiments suggest two possible techniques to eliminate the error component associated with the mesh misalignment. The absorbing boundary conditions are implemented for infinite or semi-infinite domain problems. Plane wave as well as point source wave experiments are constructed to make validity and convergence tests of DG. INTRODUCTION In physics, the acoustic wave equation, governing the acoustic wave propagation through material media, describes the evolution of acoustic pressure and particle velocity as a function of space and time. Seismologists gain the knowledge of geological structure of subsurface by sending seismic waves and recording the reflected wave. Inversion of these recorded data is essential for geoscientists to understand the mystery under the surface of earth. In each inversion process, many forward wave propagation problems need to be solved. So accurately and efficiently solving acoustic wave equation is the first step for constructing an inverse solver. FDTD for simulation of acoustic wave propagation have been studied by (Alford et al., 1974(2); Alterman and Karal, 1968(3); Boore, 1970(5), 1972(6); Dablain, 1986(8); Kelly et al., 1976(11)). There are many successful implementations of FDTD within seismic applications. Among them, the very recent software iwave by (Igor Terentyev, 2008(15)), providing a parallel framework using staggered-grid finite difference method, sets up an instrument for comparing FDTD with other numerical methods. DG-FEM has recently become popular for fluid dynamics and electromagnetic problems
Nitrogen Fixing Biofertilizers; Mechanism and Growth Promotion: A Review

Nitrogen is generally considered one of the major limiting nutrients in plant growth. The biological process responsible for reduction of molecular nitrogen into ammonia is referred to as nitrogen fixation. A wide diversity of nitrogen-fixing bacterial species belonging to most phyla of the Bacteria domain has the capacity to colonize the rhizosphere and to interact with plants. Leguminous and actinorhizal plants can obtain their nitrogen by association with rhizobia or Frankia via differentiation on their respective host plants of a specialized organ, the root nodule. Other symbiotic associations involve heterocystous cyanobacteria, while increasing numbers of nitrogen-fixing species have been identified as colonizing the root surface and, in some cases, the root interior (Nitrogen fixing endophytes) of a variety of cereal crops and pasture grasses. Bacterial mechanisms of plant growth promotion include biological nitrogen fixation (BNF), synthesis of phytohormones, environmental stress relief, inhibition of plant ethylene synthesis, as well as increasing availability of nutrients like iron through production of siderophores.
Height estimation from vector fields of surface normals

We consider the problem of recovering the height information from a field of surface normals defined as three-dimensional (3-D) vectors. The algorithm starts from a certain location on the lattice and updates iteratively the heights in a neighbourhood. Then it proceeds to the neighbours of the already calculated heights. The updating rule is based on a gradient descent minimising the vector difference between the given surface normal, and the surface normal, extracted from the estimated height map at each site. The proposed algorithm is applied for recovering height information from synthetic aperture radar (SAR) images of the terrain.
Proposed model to estimate the most important factors affecting customer satisfaction with Egyptian handicrafts A case study in the area of (Khan Al-Khalili - Al-Azhar - Al-Fustat)

The past years have witnessed great momentum for the development of craft and heritage industries in Egypt, as some laws and legislation were issued and amended that aim to develop the industry and provide financing and technical components to advance it and enhance its competitive capabilities to keep pace with Egypt’s Vision 2030. These policies also aimed to integrate these industries into the sector. Officially, many entities concerned with supporting craft industries have also been developed. This study was conducted with the aim of identifying the factors affecting the decision to purchase Egyptian handicrafts among tourists. The size of the research sample was 150 individuals selected from three areas in Cairo (Khan Al-Khalili - Al-Fustat - Al-Khayamiya in Al-Azhar) using the appropriate sampling method. Primary research data was collected through a questionnaire form prepared for this purpose using the personal interview method. The data was analyzed using a five-point Likert scale. The results of the study showed that there is a positive correlation between the level of satisfaction and the quality, price, promotional activities and motivation for handicraft products. The study recommended the need to focus on these factors to stimulate the movement of handicraft sales among tourists.
Digital Forensic Investigation on Social Media Platforms: A Survey on Emerging Machine Learning Approaches

An online social network is a platform that is continuously expanding, which enables groups of people to share their views and communicate with one another using the Internet. The social relations among members of the public are significantly improved because of this gesture. Despite these advantages and opportunities, criminals are continuing to broaden their attempts to exploit people by making use of techniques and approaches designed to undermine and exploit their victims for criminal activities. The field of digital forensics, on the other hand, has made significant progress in reducing the impact of this risk. Even though most of these digital forensic investigation techniques are carried out manually, most of these methods are not usually appropriate for use with online social networks due to their complexity, growth in data volumes, and technical issues that are present in these environments. In both civil and criminal cases, including sexual harassment, intellectual property theft, cyberstalking, online terrorism, and cyberbullying, forensic investigations on social media platforms have become more crucial. This study explores the use of machine learning techniques for addressing criminal incidents on social media platforms, particularly during forensic investigations. In addition, it outlines some of the difficulties encountered by forensic investigators while investigating crimes on social networking sites.
Strain Improvement for the Increased Production of Beta-carotene by Rhodotorula minuta (3359)

Carotenoids are chemical compounds, synthesized by plants, fungi, algae bacteria and yeast. Rhodotorula minuta (3359) is a yeast species (pink red in colour), producing various carotenoids such as beta-carotene, astaxanthin, torularhodine, and torulene. Beta-carotene acts as an anti-oxidant as well as increases pigmentation and colouration of organisms. To increase production of beta-carotene form Rhodotorula minuta , strain improvement program was carried out. To improve beta-carotene production physical and chemical mutagens are used, which block the biosynthesis of other carotenoids and so the golden colonies were formed. These colonies are selected for media optimisation to increase in production of beta-carotene from mutant Rhodotorula minuta .
High System-Code Security with Low Overhead

Security vulnerabilities plague modern systems because writing secure systems code is hard. Promising approaches can retrofit security automatically via runtime checks that implement the desired security policy, these checks guard critical operations, like memory accesses. Alas, the induced slowdown usually exceeds by a wide margin what system users are willing to tolerate in production, so these tools are hardly ever used. As a result, the insecurity of real-world systems persists. We present an approach in which developers/operators can specify what level of overhead they find acceptable for a given workload (e.g., 5%), our proposed tool ASAP then automatically instruments the program to maximize its security while staying within the specified "overhead budget. " Two insights make this approach effective: most overhead in existing tools is due to only a few "hot" checks, whereas the checks most useful to security are typically "cold" and cheap. We evaluate ASAP on programs from the Phoronix and SPEC benchmark suites. It can precisely select the best points in the security-performance spectrum. Moreover, we analyzed existing bugs and security vulnerabilities in RIPE, Open SSL, and the Python interpreter, and found that the protection level offered by the ASAP approach is sufficient to protect against all of them.
Preparation of a Nanosized As2O3/Mn0.5Zn0.5Fe2O4 Complex and Its Anti-Tumor Effect on Hepatocellular Carcinoma Cells

Manganese-zinc-ferrite nanoparticles (Mn0.5Zn0.5Fe2O4, MZF-NPs) prepared by an improved co-precipitation method and were characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD) and energy dispersive spectrometry (EDS). Then thermodynamic testing of various doses of MZF-NPs was performed in vitro. The cytotoxicity of the Mn0.5Zn0. 5Fe2O4 nanoparticles in vitro was tested by the MTT assay. A nanosized As2O3/Mn0.5Zn0. 5Fe2O4 complex was made by an impregnation process. The complex’s shape, component, envelop rate and release rate of As2O3 were measured by SEM, EDS and atom fluorescence spectrometry, respectively. The therapeutic effect of nanosized As2O3/Mn0.5Zn0. 5Fe2O4 complex combined with magnetic fluid hyperthermia (MFH) on human hepatocelluar cells were evaluated in vitro by an MTT assay and flow cytometry. The results indicated that Mn0.5Zn0. 5Fe2O4 and nanosized As2O3/Mn0.5Zn0. 5Fe2O4 complex were both prepared successfully. The Mn0.5Zn0. 5Fe2O4 nanoparticles had powerful absorption capabilities in a high-frequency alternating electromagnetic field, and had strong magnetic responsiveness. Moreover, Mn0.5Zn0. 5Fe2O4 didn’t show cytotoxicity in vitro. The therapeutic result reveals that the nanosized As2O3/Mn0.5Zn0. 5Fe2O4 complex can significantly inhibit the growth of hepatoma carcinoma cells.
On the Accuracy Limits of Misspeciﬁed Delay-Doppler Estimation

This work derives compact closed-form expressions of the misspecified Cramér-Rao bound and pseudo-true parameters of time-delay and Doppler for a high dynamics signal model. Those expressions are validated by analyzing the mean square error (MSE) of the misspecified maximum likelihood estimator. A noteworthy outcome of these MSE results is that, for some magnitudes of acceleration and signal-to-noise ratios, neglecting the acceleration is beneficial in the MSE sense. The variance performance improvement is obtained at the cost of a systematic error in the true parameter estimation. This can be seen as a specific case of the trade-off between bias and variance. Neglecting the acceleration can improve the Doppler estimation when the error induced on the misspecified model is less than the variance increase due to including an extra parameter to estimate. Then, for some non-zero acceleration magnitudes and short integration times, the Doppler estimation using a misspecified model outperforms a correctly specified model in the MSE sense.
3D modeliranje pomoću fotografije

U radu cemo se osvrnuti na problematiku automatskog segmentiranja predmeta i pozadine krutih 3D objekata promatranih kroz seriju fotografija koje su kalibrirane kroz položaj kamere. Takva segmentacija se može koristiti da bi se dobio oblik reprezentacije potencijalnih neteksturiranih objekata kroz izracun vizualne ljuske. Zagovra se automatski pristup gdje je objekt koji ce biti segmentiran identificiran kroz položaj kamere umjesto korisnickog unosa podataka kao sto su određivanje granicnog prostora ili potezi kista. Kljucni element ove metode je parna MRF (Markov Random Field) mreža koja kombinira (a) izgleda predmeta/pozadine, (b) epipolarno ogranicenje i (c) slabu stereo korespondenciju u jedinstvenu funkciju segmentacije koja se vrlo efikasno može rjesiti pomocu presijeka grafova (Graph-cuts). Segmentacija koja se tim putem dobiva dalje je poboljsana kroz dodavanje koherencije silueta i koristena za unapređivanje izgleda modela predmeta i pozadine koji se zatim unose u racunicu presjeka grafova. Ta dva koraka su iterirana dok segmentacija ne konvergira. Ova metoda je u stanju automatski pružiti 3D povrsinu cak i kod neteksturiranih scena gdje MVS (Multi View Stereo) metode zakazuju. Taj nacin segmentacije omogucava koristenje bilokakvih fotoaparata u stvaranju 3D modela, sto se pokazalo vrlo jednostavno i intuitivno. Obratit ce se pozornost na moguce pogreseke i tehnike kojima se ovakva segmentacija može koristiti.