Miracle-dz/UniFAR-FTUs huggingface dataset:
Next Generation Cloud Computing Architectures: Performance and Pricing

Next Generation Cloud Computing Architectures: Performance and Pricing Kunal Mahajan Cloud providers need to optimize the container deployments to efficiently utilize their network, compute and storage resources. In addition, they require an attractive pricing strategy for the compute services like containers, virtual machines, and serverless computing in order to attract users, maximize their profits and achieve a desired utilization of their resources. This thesis aims to tackle the twofold challenge of achieving high performance in container deployments and identifying the pricing for compute services. For performance, the thesis presents a transport-adaptive network architecture (D-TAIL) improving tail latencies. Existing transport protocols such as Homa, pFabric [1, 2] utilize Shortest Remaining Processing Time (SRPT) scheduling policy which is known to have starvation issues for long flows as SRPT prioritizes short flows. D-TAIL addresses this limitation by taking age of the flow in consideration while deciding the priority. D-TAIL shows a maximum reduction of 72%, 29.66% and 28.39% in 99th-percentile FCT for transport protocols like DCTCP, pFabric and Homa respectively. In addition, the thesis also presents a container deployment design utilizing peer-to-peer network and virtual file system with content-addressable storage to address the problem of cold starts in existing container deployment systems. The proposed deployment design increases compute availability, reduces storage requirement and prevents network bottlenecks. For pricing, the thesis studies the tradeoffs between serverless computing (SC) and traditional cloud computing (virtual machine, VM) using realistic cost models, queueing theoretic performance models, and a game theoretic formulation. For customers, we identify their workload distribution between SC and VM to minimize their cost while maintaining a particular performance constraint. For cloud provider, we identify the SC and VM prices to maximize its profit. The main result is the identification and characterization of three optimal operational regimes for both customers and the provider, that leverage either SC or VM only, or both, in a hybrid configuration.
Linking Sensory Properties and Chemical Composition of Vitis vinifera cv. Cabernet Sauvignon Grape Berries to Wine

It is conventional wine industry practice for winemakers and grapegrowers to taste winegrapes to determine their fitness for producing various wine styles of different quality. However, the ability to predict wine style from tasting grapes is unverified, and the relationship among the sensory characters of grapes and wine is poorly understood. The objective of the study was to investigate the sensory properties of Cabernet Sauvignon grapes and the corresponding wines, and to determine the relationships between the two data sets. Grapes were harvested between 23 and 25 Brix from eight locations across the state of South Australia over two vintages and vinified using a standardized protocol. A total of 25 samples from across the eight locations were harvested for each vintage. The grapes and wines were evaluated by a sensory panel trained in descriptive analysis. Grapes were evaluated using the berry sensory assessment (BSA) methodology previously described in the literature, and the basic chemical parameters of the grapes and wines were measured. Samples were consistently discriminated by their chemical and sensory properties within the grape and by wine data sets across the vintages. Five sensory attributes of wine were consistently modeled with moderate to high regressions using BSA attributes and berry-chemical measures. Finding berry sensory attributes that consistently relate to wine style and profile remains challenging. The basic chemical measures, including Brix, anthocyanins, and chroma of grape homogenates, were reliable contributors to wine sensory attributes for both vintages.
Conceptual uncertainties in groundwater and porewater fluxes estimated by radon and radium mass balances

Radium isotopes and radon are routinely used as tracers to quantify groundwater and porewater fluxes into coastal and freshwater systems. However, uncertainties associated with the determination of the tracer flux are often poorly addressed and often neglect all the potential errors associated with the conceptualization of the system (i.e., conceptual uncertainties). In this study, we assess the magnitude of some of the key uncertainties related to the determination of the radium and radon inputs supplied by groundwater and porewater fluxes into a waterbody (La Palme Lagoon, France). This uncertainty assessment is addressed through a single model ensemble approach, where a tracer mass balance is run multiple times with variable sets of assumptions and approaches for the key parameters determined through a sensitivity test. In particular, conceptual uncertainties linked to tracer concentration, diffusive fluxes, radon evasion to the atmosphere, and change of tracer inventory over time were considered. The magnitude of porewater fluxes is further constrained using a comparison of independent methods: (1) 224Ra and (2) 222Rn mass balances in overlying waters, (3) a model of 222Rn deficit in sediments, and (4) a fluid‐salt numerical transport model. We demonstrate that conceptual uncertainties are commonly a major source of uncertainty on the estimation of groundwater or porewater fluxes and they need to be taken into account when using tracer mass balances. In the absence of a general framework for assessing these uncertainties, this study provides a practical approach to evaluate key uncertainties associated to radon and radium mass balances.
A Ku-Band Fractional-N Frequency Synthesizer with Adaptive Loop Bandwidth Control

This paper presents a Ku-band fractional-N frequency synthesizer with adaptive loop bandwidth control (ALBC) to speed up the lock settling process and meanwhile ensure better phase noise and spur performance. The theoretical analysis and circuits implementation are discussed in detail. Other key modules of the frequency synthesizer such as broadband voltage-controlled oscillator (VCO) with auto frequency calibration (AFC) and programable frequency divider/charge pump/loop filter are designed for integrity and flexible configuration. The proposed frequency synthesizer is fabricated in 0.13 μm CMOS technology occupying 1.14 × 1.18 mm2 area including ESD/IOs and pads, and the area of the ALBC is only 55 × 76 μm2. The out frequency can cover from 11.37 GHz to 14.8 GHz with a frequency tuning range (FTR) of 26.2%. The phase noise is −112.5 dBc/Hz @ 1 MHz and −122.4 dBc/Hz @ 3 MHz at 13 GHz carrier frequency. Thanks to the proposed ALBC, the lock-time can be shortened by about 30% from about 36 μs to 24 μs. The chip area and power consumption of the proposed ALBC technology are slight, but the beneficial effect is significant.
An Open Innovation Intraday Implied Volatility for Pricing Australian Dollar Options

This study introduces the intraday implied volatility (IV) for pricing the Australian dollar (AUD) options. The IV is estimated using the at-the-money one-month, two-month, and three-month maturity AUD options traded in the opening, midday, and closing period of a trading day. The Mincer-Zarnowitz regression test evaluates the predictive power of IV to forecast the foreign exchange volatility for the within-week, one-week, and one-month horizon. The mean absolute error, mean squared error, and root mean squared error measures are employed to assess the performance of IV in estimating the price of currency options for the within-week, one-week, and one-month horizon. This study reveals four critical findings. First, a three-month maturity IV does not contain vital information for pricing options. Second, IV incorporated information is not relevant to compute the value of options for a horizon of less than a week. Third, IV in the closing period of Monday or Tuesday subsumes most of the essential information to estimate options price. Fourth, the shorter (longer) maturity IV provides critical information to price options for the shorter (longer) horizon. The intraday IV is a new dimension of unobservable volatility in accurately pricing currency options for researchers and practitioners.
Intermedin promotes breast cancer metastasis via Src/c-Myc-mediated ribosome production and protein translation

Background Breast cancer is the most frequently diagnosed cancer and is the leading cause of cancer-associated mortality in women worldwide. Intermedin (IMD) is an endogenous peptide that belongs to the calcitonin gene-related peptide family and has been reported to play important roles in several types of cancers, including breast cancer. In this study, we sought to investigate how IMD affects the behavior of breast cancer cells, the underlying mechanism of these effects, and whether blockade of IMD has a therapeutic effect against breast cancer. Methods Transcriptome sequencing (RNA-Seq), cell biological experiments, Western blotting (WB), immunoprecipitation (IP), and animal tumor models were used. Results IMD expression was significantly increased in breast cancer samples, and the IMD level was positively correlated with lymph node metastasis and Ki67 expression. Cell biological experiments showed that IMD promoted the anchorage-independent growth, migration, and invasive ability of breast cancer cells. Inhibiting IMD activity with an anti-IMD monoclonal antibody blocked these tumor-promoting effects. In addition, blockade of IMD reduced in situ tumor growth and significantly decreased lung metastasis of 4T1 breast cancer in vivo. IMD induced Src kinase phosphorylation, which triggered the transcription of c-Myc, a major oncoprotein controlling the expression of genes that encode ribosomal components. Our data suggest that IMD is involved in breast cancer cell invasion and metastasis, potentially through increasing ribosome biogenesis and protein translation via the Src/c-Myc signaling pathway. Conclusion These results suggest that IMD may be a novel target for the treatment of breast cancer.
Effect of solution composition on struvite crystallization

BACKGROUND Struvite precipitation has been applied to several types of wastewater for removal and recovery of nutrients. Engineering criteria for these applications, particularly crystallization, have yet to be developed. In the present study, effects of solution composition on the induction period and crystallization rate of struvite were experimentally investigated. Experiments were conducted as batch tests and on synthetically prepared samples. High foreign ion concentrations up to 160 mM were used for the evaluation. RESULTS Effect of ions such as sodium, chloride, sulfate, and acetate that frequently accompany struvite crystallization was evaluated with varying composition of solutions. The induction time decreased with increasing supersaturation. The increase in sodium concentration from 14.25 to 130.52 mM resulted in about a four-fold retardation in induction time. Increasing sulfate concentration to 40.5 mM caused a significant retardation reaching an induction time of 30 minutes. Sulfate ions exhibited a dependence on chloride concentration. Effect of acetic acid was marginal up to 10 mM. Crystallization kinetics was represented by modified first order kinetics. The rate constants varied between 0.0053 –0.1622 min−1. The lowest rate constants were calculated for compositions containing high concentrations of sodium and sulfate ions. CONCLUSION Results of the study indicated that the existence of common ions in wastewaters may give rise to great variations in the induction period and crystallization rate of struvite. Crystallization process was satisfactorily modelled; and the rate constant exhibited a wide range depending on the wastewater composition. The results indicated the need for further studies considering the complex matrix of wastewaters of concern.
A machine learning model for quantifying the effect of lifestyle interventions for patients with type 2 diabetes mellitus

Type 2 diabetes is the most common type of diabetes. The cornerstone of type 2 diabetes treatment is healthy lifestyle. This paper proposes a machine learning model for quantifying the effect of lifestyle interventions for patients. In the proposed incremental intervention model, the original physical indicators and the lifestyle interventions were taken as input vectors separately and transformed through different nonlinear functions. We evaluated our method with the dataset of 12,318 patients from a national funding project and compared with MLP and SVR. The experimental results (R 2 =0.85, RMSE= 0.51, MAE=0.35) indicated that the model outperformed those prediction models. Besides, the machine learning based method is cost-effective and time-saving. The proposed method provides new insights into prevention and treatment of chronic diseases.
Validation of atomic data using a plasma discharge

Using a neon discharge as a well-assessed reference, we demonstrate the validation of atomic data for discharge modeling with data from emission spectroscopy. Specifically, a collisional radiative model of a neon dc discharge was set up using a set of structure and collision data from a semirelativistic B-spline R-matrix calculation by Zatsarinny and Bartschat (2004 J. Phys. B: At. Mol. Opt. Phys. 37 2173) and the electron-energy distribution function of the plasma was determined from the spectroscopic measurement by Dodt et al (2008 J. Phys. D: Appl. Phys. 41 205207). Since the model covers almost the entire visible spectrum, considering a large number of emission lines and many important collisional coupling mechanisms, it enables us to thoroughly test the consistency of the modeled excited-state populations. Inconsistencies, which appear as correction factors for the rate coefficients, are extracted by means of Bayesian probability theory. Despite its limitations, the sensitivity of the approach was sufficient to provide critical information about the collision data, especially in cases where standard cross-section measurements using merged electron and atom beams are difficult to perform. The present approach thus complements existing experimental techniques to test theoretical predictions.
Fish Response to Multiple Anthropogenic Stressors in Mediterranean Coastal Lagoons: A Comparative Study of the Role of Different Management Strategies

Transitional waters are among the most productive ecosystems of the world and their biotic communities show high diversity and complex mechanisms of self-regulation that provide valuable ecosystem services and societal goods and benefits. In this work a comparison of the fish assemblages of three non-tidal Mediterranean coastal lagoons is carried out in order to evaluate the impacts of alternative management strategies. The anthropogenic pressures acting on the lagoons were quantified by means of categorical indicators, while the characteristics of the fish assemblages were summarized in multi-metric indices (MMIs). Two MMIs were developed using data collected with a beach seine net and with fyke nets, following an empirical approach that selects, from a pool of 73 metrics, the combination that maximizes the MMI/pressure relationship. The two MMIs include four metrics each, most of which are based on feeding mode functional guilds and habitat use functional guilds, and they are sensitive to anthropogenic pressures. The human activities directly or indirectly affecting water quality are the ones that most influence the fish assemblage, while the presence of artisanal fisheries, a typical and relevant resource use in these lagoons, seems to play a beneficial role. Lagoon fisheries management relies on the maintenance of infrastructures that guarantee the hydraulic functioning of the lagoon, thus ensuring exchanges with the adjacent coastal sea, and therefore indirectly contributing to the habitat quality.
Knowledge and Perception of COVID-19 Pandemic During the First Wave (Feb-May 2020): a Web Based Survey Among Italian Healthcare Workers

Background Italy was the first country in Europe to face the coronavirus pandemic. Healthcare workers (HCWs) were at higher risk of contracting COVID-19, because of their closer contact with patients. The present study aimed to analyze HCWs’ knowledge, practices, and attitude towards COVID-19.MethodsWe set up a cross-sectional survey through SurveyMonkey® and circulated the link in Facebook and Whatsapp closed groups. It was conducted in Italy from the end of February to the first week of May 2020. The study participants were general practitioners, pediatricians and other health professionals. Data were collected using a well-structured questionnaire including demographic, scope of knowledge, awareness and practice assessment section.ResultsA total of 958 participants were included. Of these, 320 (33.4%) were general practitioners, 248 (25.9%) were pediatricians and 390 (40.7%) were other health professionals. The highest response rate was from Northern Italy (48.1%), followed by the Center (29.9%) and Southern Italy (22.0%). The reported risk of having contact with a patient affected by Covid-19 was higher in the lockdown period than the pre-lockdown period (19.4% vs 10.2%, p=0.002). Respondents reported to have changed their clinical practice, more during lockdown period (81.1%) than in the pre-lockdown (46.3%). Particularly, they increased the use of masks (87.1%, p<0.001), disinfection and sanitization of doctors’ offices (75.8%, p<0.001), the use of protective glasses (71.2%, p<0.001), alcoholic hand solution (71.2%, p<0.001), and hand washing (31.8%, p=0.028). ConclusionsThe majority of HCWs felt prepared to face the pandemic, and increased significantly their knowledge on infection prevention and control measures less known in the routine clinical practice (such as use of protective glasses and alcoholic hand solution), compared to other well-known measures (such as hand washing). HCWs are at high risk of infection and need extensive knowledge and awareness of the disease to take adequate precautionary measures and they are crucial to disseminate good practices.
H-V2X Mode 4 Adaptive Semipersistent Scheduling Control for Cooperative Internet of Vehicles

Due to the rapidly growing number of autonomous vehicles, establishing an intelligent transportation system (ITS) supported by the Internet-of-Vehicles (IoV) technology is important. The need for IoV technology is emphasized even more because recent accidents relating to autonomous vehicles show that there are limitations in the reliability of autonomous vehicles only using vehicle onboard sensors. In addition, a highly reliable support system for many vehicular applications is in strong demand, which is why there is a need for advanced vehicle-to-everything (V2X) technology. The two major types of V2X technology are dedicated short-range communication (DSRC) and cellular-V2X (C-V2X). Many vehicles are already equipped with DSRC; however, the use of C-V2X is highly supported by many mobile communication companies and the 5GAA, which is why C-V2X is expected to be very widely used. In this article, a hybrid V2X (H-V2X) scheme is proposed, which adaptively controls C-V2X to satisfy the key-performance indicator (KPI) requirements as much as possible, and uses DSRC transmission when the C-V2X required performance cannot be reliably supported. The performance analysis graphs show that the gain in performance of the proposed H-V2X scheme can provide an improved performance compared to other V2X schemes, which makes it more suitable to support reliable autonomous vehicles.
Investigation of Coalescence-Induced Droplet Jumping on Mixed-Wettability Superhydrophobic Surfaces

Coalescence-induced droplet jumping has received more attention recently, because of its potential applications in condensation heat transfer enhancement, anti-icing and self-cleaning, etc. In this paper, the molecular dynamics simulation method is applied to study the coalescence-induced jumping of two nanodroplets with equal size on the surfaces of periodic strip-like wettability patterns. The results show that the strip width, contact angle and relative position of the center of two droplets are all related to the jumping velocity, and the jumping velocity on the mixed-wettability superhydrophobic surfaces can exceed the one on the perfect surface with a 180° contact angle on appropriately designed surfaces. Moreover, the larger both the strip width and the difference of wettability are, the higher the jumping velocity is, and when the width of the hydrophilic strip is fixed, the jumping velocity becomes larger with the increase of the width of the hydrophobic strip, which is contrary to the trend of fixing the width of the hydrophobic strip and altering the other strip width.
Factors Influencing the Use of Wireless Sensor Networks in the Irrigation Field

Battle control, natural disasters discovery, water monitoring, smart homes, agricultural applications, health care, weather forecasts, smart buildings, intrusion detection, medical devices, and more are the application areas of wireless sensor networks (WSNs). WSNs can help bring about revolutionary changes in important areas of our world. As a result, this technology has become a particularly interesting technology, which can be used to meet the specific requirements of a particular application because of its distinctive characteristics. In this context, WSNs are a promising approach in the agricultural sector and irrigation in particular for overcoming the world's major problems (e.g., the global water crisis). When implementing WSN in the irrigation field, many factors, like limited sensor node resources, limited sensor node power, costs, hardware constraints, and type of deployment environment, must be taken into account in order to improve WSN performance and achieve the desired results. In this paper, we will study and analyze the main factors that affect WSNs in the irrigation field. We will also provide a set of measures and solutions that need to be taken to overcome the challenges of deploying a WSN in irrigation. In this regard, we will also highlight several factors for improvement to achieve an efficient and consistent irrigation system using WSN.
The role of subjective social status in living well for carers of people with dementia: findings from the Improving the experience of Dementia and Enhancing Active Life programme

We investigated how carers of people with dementia evaluate their standing in their community and wider society, and if this is related to ‘living well’. We used baseline data from the Improving the experience of Dementia and Enhancing Active Life programme and found that carers rated their standing in society higher than in their local community. Higher evaluations of both were associated with enhanced life satisfaction, well-being and quality of life. Initiatives that increase support or engagement in the community or wider society may help to increase carers’ perceptions of their social status, enhancing their ability to ‘live well’.