Miracle-dz/UniFAR-FTUs huggingface dataset:
Leveraging AI players for QoE estimation in cloud gaming

—Quality of Experience (QoE) assessment in video games is notorious for its burdensomeness. Employing human subjects to understand network impact on the perceived gaming QoE presents major drawbacks in terms of resources requirement, results interpretability and poor transferability across different games. To overcome these shortcomings, we propose to substitute human players with artiﬁcial agents trained with state-of-the-art Deep Reinforcement Learning techniques. Equivalently to traditional QoE assessment, we measure the in-game score achieved by an artiﬁcial agent for the game of Doom for varying network parameters. Our results show that the proposed methodology can be applied to understand ﬁne-grained impact of network conditions on gaming experience while opening a lot of new opportunities for network operators and game developers.
Complete genome sequence of Thauera aminoaromatica strain MZ1T

Thauera aminoaromatica strain MZ1T, an isolate belonging to genus Thauera, of the family Rhodocyclaceae and the class the Betaproteobacteria, has been characterized for its ability to produce abundant exopolysaccharide and degrade various aromatic compounds with nitrate as an electron acceptor. These properties, if fully understood at the genome-sequence level, can aid in environmental processing of organic matter in anaerobic cycles by short-circuiting a central anaerobic metabolite, acetate, from microbiological conversion to methane, a critical greenhouse gas. Strain MZ1T is the first strain from the genus Thauera with a completely sequenced genome. The 4,496,212 bp chromosome and 78,374 bp plasmid contain 4,071 protein-coding and 71 RNA genes, and were sequenced as part of the DOE Community Sequencing Program CSP_776774.
Mechanized Semantics for Compiler Verification

The formal veriﬁcation of compilers and related programming tools depends crucially on the availability of appropriate mechanized semantics for the source, intermediate and target languages. In this invited talk, I review various forms of operational semantics and their mechanization, based on my experience with the formal veriﬁcation of the CompCert C compiler.
Comparative Analysis of Selective Forwarding Attacks over Wireless Sensor Networks

potential use of wireless sensor networks (WSNs) in many technological situations is extensive. WSNs are employed in numerous areas, such as battlefields, traffic surveillance, healthcare, and environmental monitoring. Many studies have been conducted to improve various aspects of the performance of WSNs, such as energy efficiency, quality of service (QoS), reliability, mobility, scalability, and extended network lifetime. However, few studies have sought to advance the security of WSNs by focusing on medium access control (MAC), physical, and transport stacks. The network layer is the middle layer that coordinates the lower layers and the upper layers. Thus, the network layer is of paramount significance to the security of WSNs to prevent exploitation of their confidentiality, privacy, availability, integrity, and authenticity. The objective of this study is to address the security laps of WSNs on the network layer, particularly selective forwarding attacks. This paper includes a survey performed from 2003 to 2014. Significant constraints and hazards of physical attacks at the network layer are extensively addressed. The survey includes a benchmark for the comparison of existing approaches for handling the security of WSNs on the network layer and their challenges. Future directions are also comprehensively highlighted in the document. This study will help researchers to understand attacks on the network layer. Keywordssensor network, selective forwarding, and denial of services attacks.
A Comparative Analysis of the Complexity / Accuracy Tradeoff in Power Amplifier Behavior Models

A comparative study of state-of-the-art behavioral models for microwave power amplifiers (PA) is presented in this paper. After establishing a proper definition for accuracy and complexity for power amplifier behavioral models, a shor t description on various behavioral models is presented. The main focus of this paper is on the modeling accuracy as a function o f computational complexity. Data is collected from measurements on two PA’s a general purpose amplifier and a Doherty PA designed for WiMAX and at different output power levels. The models are characteri zed in terms of accuracy and complexity for both in-band and outof-band error. The results show that the generalized memory polynomial behavioral model has the best tradeoff for accur acy vs complexity.
Study on dyslipidemia and oxidative stress in Elderly-A clinical approach to predict cardiovascular disease risk

Aging is characterized by systemic deterioration of biomolecules and increased incidence of oxidative stress. In addition, occurrence of dyslipidemia in elderly significantly contributes the development of cardiovascular disease. It is conceivable that association of dyslipidemia with oxidative stress enhances the future the risk of cardiovascular disease (CVD) in older population. The aim is to estimate the plasma lipid profile and marker of oxidative stress in elderly and to determine their role in predicting CVD risk. The study population consists of 90 subjects. Out of 90 subjects, 60 healthy individuals were categorized into two groups: Group I (40-55 years) and Group II (≥ 56 years) and statistically compared it with that of 30 younger controls (20-30 years) by using student’s t-test. Plasma lipid profile levels were measured along with erythrocyte malondialdehyde (MDA) levels. Data were statistically analyzed using standard methods. Plasma total cholesterol, triglycerides, LDL-cholesterol HDL-cholesterol and MDA levels were significantly high (p<0.05) in group III subjects as compared to healthy controls. However, these levels were altered insignificantly (p<0.1) in group II subjects. Similarly, plasma CRP levels were found to be significantly high (P<0.001) in Group III as compared to younger controls. Thus, alteration in lipid profile along with enhanced oxidative stress authenticates the fact that these markers are more efficient than conventional lipid profile parameters in prediction of CVD risk in older population.
Exploring Multicultural Education: A Case Study of Singkawang

This article investigates multicultural education in Singkawang, Indonesia, where diverse ethnicities coexist. Rapid social changes often trigger ethnic migration, leading to a convergence of cultures. Ethnocentrism can impede inter-ethnic communication, fostering stereotypes and ethnic conflicts. Multicultural education, emphasizing democratic, humanistic, and pluralistic values, is proposed to address these issues. Singkawang, recognized for its ethnic diversity, serves as a unique case study. The research method involves qualitative analysis with interviews from students, teachers, and parents from various ethnic backgrounds. Findings revealed the city's friendly atmosphere, preserved harmony, and respectful behavior, especially among students. "Ngopi bareng" (coffee gathering) is identified as a key practice among adult localsstated by parents of students in maintaining multiculturalism. Schools also actively promote tolerance through democratic practices, curriculum diversity, and inclusive instructional strategies. The article concludes that multicultural education is vital in fostering acceptance, understanding, and appreciation of diversity, emphasizing the dynamic nature of this approach in shaping open-minded individuals in a diverse society. Further research is recommended to explore this topic's nuances.
Survival with inoperable lung cancer. An integration of prognostic variables based on simple clinical criteria

The objectives are to identify and integrate through regression analysis those fundamental clinical variables predicting survival of patients with inoperable lung cancer managed in a modern setting. Median survival time from first treatment in 129 patients with limited disease and 187 patients with extensive disease was 36 and 14 weeks, respectively. Within the proposed survival model for limited disease, weight loss was the major prognosticator followed by symptom status, supraclavicular metastases, and age. Within extensive disease, symptom status and age were dominant variables followed by weight loss and metastases to liver, opposite hemithorax, brain, and bone. Survival by cell type was similar within the limited and extensive disease groups. The data identify the essential factors which must be controlled or accounted for in studies analyzing survival as a dependent variable.
Fibromyalgia in patients with rheumatoid arthritis: driven by depression or joint damage?

OBJECTIVES Studies have shown an increased incidence of fibromyalgia (FMS) in RA patients. The aims of this study were to explore the effect of mood and disease damage on the prevalence of FMS. METHODS RA patients underwent a standardised clinical assessment, including disease activity (DAS-28), disease damage (mechanical joint score, MJS), fibromyalgia tender point assessment and the Hospital Anxiety and Depression Scale (HADS) and Health Assessment Questionnaire (HAQ). Patients were classified with FMS using two criteria a) tender-swollen joint count was ≥7 or b) tender point score of ≥11/18. RESULTS 44/285 (15%) patients were classified as having FMS using the joint count difference of ≥7, compared to 18/285 (6%) using the tender point score of >11. Using the joint count difference to classify patients as having FMS, those with FMS had higher HAQ scores than those without FMS (2.12 vs. 1.5, p<0.0001). Although the DAS-28 was higher in this group (5.4 vs. 3.82, p<0.0001), the MJS was similar (8 vs. 7, p=0.19), suggesting similar levels of joint damage. Those classified as having FMS were more likely to have HAD-D scores of >11 (25% vs. 6%, p=0.0001). CONCLUSIONS Coexistent FMS was common in our cohort, although using the tender point count to define FMS classified fewer patients with FMS. Within this group those with FMS had higher levels of depression but similar scores for joint damage indicating that in this cohort FMS and poorer physical functioning is mediated by low mood rather than joint damage.
The 3D-Pitoti Dataset: A Dataset for high-resolution 3D Surface Segmentation

The development of powerful 3D scanning hardware and reconstruction algorithms has strongly promoted the generation of 3D surface reconstructions in different domains. An area of special interest for such 3D reconstructions is the cultural heritage domain, where surface reconstructions are generated to digitally preserve historical artifacts. While reconstruction quality nowadays is sufficient in many cases, the robust analysis (e.g. segmentation, matching, and classification) of reconstructed 3D data is still an open topic. In this paper, we target the automatic segmentation of high-resolution 3D surface reconstructions of petroglyphs. To foster research in this field, we introduce a fully annotated, large-scale 3D surface dataset including high-resolution meshes, depth maps and point clouds as a novel benchmark dataset, which we make publicly available. Additionally, we provide baseline results for a random forest as well as a convolutional neural network based approach. Results show the complementary strengths and weaknesses of both approaches and point out that the provided dataset represents an open challenge for future research.
Predictors of the incident metabolic syndrome in adults: the Insulin Resistance Atherosclerosis Study.

OBJECTIVE To prospectively investigate predictors of the incident metabolic syndrome in nondiabetic adults. RESEARCH DESIGN AND METHODS This analysis included 714 white, black, and Hispanic participants in the Insulin Resistance Atherosclerosis Study (IRAS) who were free of the metabolic syndrome at baseline; 139 of these developed the metabolic syndrome in the subsequent 5 years. We examined measures of glucose (fasting and 2 h), insulin (fasting and 2 h, acute insulin response, insulin sensitivity [Si], and proinsulin), lipids (HDL and triglycerides), blood pressure (systolic and diastolic), waist circumference, and baseline physical activity (total energy expenditure) as predictors of the metabolic syndrome. Logistic regression models were adjusted for age, sex, study site, ethnicity, and impaired glucose tolerance. Signal detection analysis was used to identify the characteristics of the highest risk group. RESULTS The best predictors of incident metabolic syndrome were waist circumference (odds ratio [OR] 1.7 [1.3-2.0] per 11 cm), HDL cholesterol (0.6 [0.4-0.7] per 15 mg/dl), and proinsulin (1.7 [1.4-2.0] per 3.3 pmol/l). Signal detection analysis identified waist circumference (>89 cm in women, >102 cm in men) as the optimal predictor. CONCLUSIONS These findings suggest that obesity may precede the development of other metabolic syndrome components. Interventions that address obesity and reduce waist circumference may reduce the incidence of the metabolic syndrome in nondiabetic adults.
African Journal of Plant Science

African violets ( Streptocarpus ionanthus ), originally native to the Eastern Arc Mountains of Africa and adjacent submontane or montane forests in Kenya and Tanzania, are commonly grown as ornamental plants and have been extensively studied by horticulturists. However, there is a lack of laboratory data regarding their ecophysiology. Given the growing interest in conserving African violets in their threatened natural habitats, it would be beneficial to establish baseline data on their physiological ecology, helping to document their response to changing environmental conditions in their natural environment. To address this need, we conducted an analysis of the net photosynthesis rate, respiration rate, and leaf fluorescence of mini and standard strains of African violet plants within a controlled laboratory setting. Additionally, we examined variations in the photosynthesis rate, respiration rate, and leaf fluorescence data for leaves of different ages (phenology) in the standard strain. The results showed that the mean net photosynthesis rate in the older whorl of leaves was approximately 50% of the rate observed in the younger leaves. Furthermore, the mature leaf respiration rate accounted for about 25 to 30% of the net photosynthesis. This particular metric, the ratio of respiration to net photosynthesis, is significant in estimating the carbon balance of the plants. It helps us understand how much carbon (C) is gained through photosynthesis compared to the amount of carbon lost through respiration.
Access to Drug Abuse Treatment Under Treatment On Demand Policy in San Francisco

Objectives: We evaluated whether implementation of Treatment on Demand (TOD) policy in San Francisco was associated with improved access to drug abuse treatment. Methods: Data came from San Francisco's treatment program waiting list over 4 years spanning the implementation of TOD policy. Access measures were monthly applicants waiting and days waited by treatment admissions. Quantitative analyses with 69 treatment facilities contrasted those receiving vs. not receiving TOD funds. Qualitative data came from interviews with facility administrators. Results: There was a small statistically significant decline in monthly waiting lists in the number of people waiting for treatment during the study period. The days waited by those admitted to treatment, however, significantly increased in TOD-funded facilities. Facilities used varied criteria for completing the access measures, which limit the utility of the measures. Conclusions: Access to treatment improved slightly with implementation of TOD policy.
Feature scale and identifiability: How much information do point hydraulic measurements provide about heterogeneous head and conductivity fields?

We systematically investigate how the spacing and type of point measurements impacts the scale of subsurface features that can be identified by groundwater flow model calibration. To this end, we consider the optimal inference of spatially heterogeneous hydraulic conductivity and head fields based on three kinds of point measurements that may be available at monitoring wells: of head, permeability, and groundwater speed. We develop a general, zonation-free technique for Monte Carlo (MC) study of field recovery problems, based on Karhunen-Loève (K-L) expansions of the unknown fields whose coef-5 ficients are recovered by an analytical, continuous adjoint-state technique. This allows unbiased sampling from the space of all possible fields with a given correlation structure and efficient, automated gradient-descent calibration. The K-L basis functions have a straightforward notion of period, revealing the relationship between feature scale and reconstruction fidelity, and they have an a priori known spectrum, allowing for a non-subjective regularization term to be defined. We perform automated MC calibration on over 1100 conductivity-head field pairs, employing a variety of point measurement geometries and evaluating 10 the mean-squared field reconstruction accuracy, both globally and as a function of feature scale. We present heuristics for feature scale identification, examine global reconstruction error, and explore the value added by both the groundwater speed measurements and by two different types of regularization. We find that significant feature identification becomes possible as feature scale exceeds four times measurement spacing and identification reliability subsequently improves in a power law fashion with increasing feature scale.
Horus: Granular In-Network Task Scheduler for Cloud Datacenters

Short-lived tasks are prevalent in modern interactive data-center applications. However, designing schedulers to assign these tasks to workers distributed across the whole datacenter is challenging, because such schedulers need to make decisions at a microsecond scale, achieve high throughput, and minimize the tail response time. Current task schedulers in the literature are limited to individual racks. We present Horus, a new in-network task scheduler for short tasks that operates at the datacenter scale. Horus efficiently tracks and distributes the worker state among switches, which enables it to schedule tasks in parallel at line rate while optimizing the scheduling quality. We propose a new distributed task scheduling policy that minimizes the state and communication overheads, handles dynamic loads, and does not buffer tasks in switches. We compare Horus against the state-of-the-art in-network scheduler in a testbed with programmable switches as well as using simulations of datacenters with more than 27K hosts and thousands of switches handling diverse and dynamic workloads. Our results show that Horus efficiently scales to large data-centers, and it substantially outperforms the state-of-the-art across all performance metrics, including tail response time and throughput.
Multipath Parameter Extraction in 5G-NR Multi-cell Network Using Interference Cancellation Method

—Passive channel sounding in live cellular network, where downlink signals of in-service base stations (BSs) are acquired to extract multipath propagation parameters, has at-tracted great interest from academia and industry in recent years. In this work, downlink signals of live 5G new radio (NR) multi-cell BSs were measured with a recent home-developed multi-antenna passive channel sounder. It was found out that the performance of multipath parameter extraction algorithm is severely affected by the existence of many interfering neighbor cells (which share the same frequency band as the serving cell) in the multi-cell measurements. For this reason, a novel algorithm based on the interference cancellation principle is proposed, which can effectively mitigate the impact of multi-cell interference and thus improve the parameter extraction performance. The effectiveness and robustness of the proposed algorithm is finally demonstrated by the passive channel sounding campaigns in live 5G NR multi-cell cellular network.
Linear algebra algorithms for divisors on an algebraic curve

We use an embedding of the symmetric dth power of any algebraic curve C of genus g into a Grassmannian space to give algorithms for working with divisors on C, using only linear algebra in vector spaces of dimension O(g), and matrices of size O(g2) × O(g). When the base field k is finite, or if C has a rational point over k, these give algorithms for working on the Jacobian of C that require O(g4) field operations, arising from the Gaussian elimination. Our point of view is strongly geometric, and our representation of points on the Jacobian is fairly simple to deal with; in particular, none of our algorithms involves arithmetic with polynomials. We note that our algorithms have the same asymptotic complexity for general curves as the more algebraic algorithms in Florian Hess' 1999 Ph.D. thesis, which works with function fields as extensions of k[x]. However, for special classes of curves, Hess' algorithms are asymptotically more efficient than ours, generalizing other known efficient algorithms for special classes of curves, such as hyperelliptic curves (Cantor 1987), superelliptic curves (Galbraith, Paulus, and Smart 2002), and Cab curves (Harasawa and Suzuki 2000); in all those cases, one can attain a complexity of O(g2).
DETERMINE THE GALAXY BIAS FACTORS ON LARGE SCALES USING THE BISPECTRUM METHOD

We study whether the bias factors of galaxies can be unbiasedly recovered from their power spectra and bispectra. We use a set of numerical N-body simulations and construct large mock galaxy catalogs based upon the semi-analytical model of Croton et al. We measure the reduced bispectra for galaxies of different luminosity, and determine the linear and first nonlinear bias factors from their bispectra. We find that on large scales down to that of the wavenumber k = 0.1 h Mpc−1, the bias factors b1 and b2 are nearly constant, and b1 obtained with the bispectrum method agrees very well with the expected value. The nonlinear bias factor b2 is negative, except for the most luminous galaxies with Mr < −23 which have a positive b2. The behavior of b2 of galaxies is consistent with the b2 mass dependence of their host halos. We show that it is essential to have an accurate estimation of the dark matter bispectrum in order to have an unbiased measurement of b1 and b2. We also test the analytical approach of incorporating halo occupation distribution to model the galaxy power spectrum and bispectrum. The halo model predictions do not fit the simulation results well on the precision requirement of current cosmological studies.
MyStore: A High Available Distributed Storage System for Unstructured Data

Although some NoSQL systems such as Dynamo, Cassandra, MongoDB have provided different advantages for unstructured data management, no one can provide flexible query functions like MongoDB, while guarantee the availability and scalability as Cassandra simultaneously. This paper introduces a new methodology and implementation for improving the availability of unstructured data by presenting a new distributed storage system called MyStore, based on the combination of MongoDB and some advantages from other NoSQL systems. Consistent hash is used to distribute data on multiple MongoDB nodes, NWR mode is applied to provide automatic backup operation and guarantee data consistency. Gossip protocol is taken for exchanging information of failures in the system. Based on above strategies, a high available and scalable system for storing unstructured data is realized, which can also provide complex query functions like rational database. Moreover, this system is applied in a multi-discipline virtual experiment platform named VeePalms that requires high availability and high access efficiency for its unstructured data such as XML scene, video guideline. Experimental evaluation shows that the methodology is powerful enough not only to enhance the data availability, but also to improve the server's scalability.