Miracle-dz/UniFAR-FTUs huggingface dataset:
(τ, m)‐slicedBucket privacy model for sequential anonymization for improving privacy and utility

In a real‐world scenario for privacy‐preserving data publishing, the original data are anonymized and released periodically. Each release may vary in number of records due to insert, update, and delete operations. An intruder can combine, that is, correlate different releases to compromise the privacy of the individual records. Most of the literature, such as τ‐safety, τ‐safe (l, k)‐diversity, have an inconsistency in record signatures and adds counterfeit tuples with high generalization that causes privacy breach and information loss. In this paper, we propose an improved privacy model (τ, m)‐slicedBucket, having a novel idea of “Cache” table to address these limitations. We indicate that a collusion attack can be performed for breaching the privacy of τ‐safe (l, k)‐diversity privacy model, and demonstrate it through formal modeling. The objective of the proposed (τ, m)‐slicedBucket privacy model is to set a tradeoff between strong privacy and enhanced utility. Furthermore, we formally model and analyze the proposed model to show that the collusion attack is no longer applicable. Extensive experiments reveal that the proposed approach outperforms the existing models.
Enhanced rhizosphere competence of Trichoderma viride grown in solid state fermentation on corn cob residue

Abstract A process has been disclosed in the present investigation for the production of a formulation of mycopesticide with enhanced shelf life of Trichoderma viride. A comparative evaluation of talc-based and corn cob formulations in the form of seed coat and soil treatment brought to light that the soil treatment significantly enhanced the plant growth performance of pea, green gram and pigeon pea. Among the two formulations, the corn cob formulation proved to be better as the rhizosphere competence of corn cob formulation was superior to that of talc formulation. Our results suggest that corn cob residue is a better substrate owing to high cellulase and spore production. Solid-state fermentation in batch cultures. The biocontrol ability of both formulations was tested against Fusarium in Cajanus species and it was found that the disease incidence was reduced by 86% when the corn cob formulation was given as soil application.
5G Mobile Technologies and Early 6G Viewpoints

Design of each successor mobile technology assures improved and advanced functionality features compared to its predecessor. Machine Learning and generally Artificial Intelligence (AI) is becoming necessity for further expansion of the beyond 5G mobile world. AI-assisted IoT services, data collection, analytics and storage should become native in the beyond 5G era. 5G introduces New Radio (NR) in sub-6 GHz bands and also in mmWave bands above 24 GHz, network virtualization and softwarization, which means that Next Generation Core and 5G NR access network are built by using different functions in split user and control planes that introduces the network slicing approach. Enhanced Mobile Broadband (eMBB), massive Machine Type Communication (mMTC) and Ultra-Reliable Low-Latency Communication (URLLC), that are provided via separate network slices as logically separated network partitions are the key 5G services that constantly will increase the traffic volume and the number of connected devices. Terahertz and visible light communication and fundamental technologies like compressed sensing theory, new channel coding, large-scale antenna, flexible spectrum usage, AI-based wireless communication, special technical features as Space-Air-Ground-Sea integrated communication and wireless tactile network are few of the novelties that are expected to become a common network standard available beyond 2030.
Radiolysis of NH3:CO ice mixtures – implications for Solar system and interstellar ices

Experimental results on the processing of NH3:CO ice mixtures of astrophysical relevance by energetic (538 MeV 64Ni24+) projectiles are presented. NH3 and CO are two molecules relatively common in interstellar medium and Solar system; they may be precursors of amino acids. 64Ni ions may be considered as representative of heavy cosmic ray analogues. Laboratory data were collected using mid-infrared Fourier transform spectroscopy and revealed the formation of ammonium cation (NH$_4^+$), cyanate (OCN−), molecular nitrogen (N2), and CO2. Tentative assignments of carbamic acid (NH2COOH), formate ion (HCOO−), zwitterionic glycine (NH$_3^+$CH2COO−), and ammonium carbamate (NH$_4^+$NH2COO−) are proposed. Despite the confirmation on the synthesis of several complex species bearing C, H, O, and N atoms, no N–O-bearing species was detected. Moreover, parameters relevant for computational astrophysics, such as destruction and formation cross-sections, are determined for the precursor and the main detected species. Those values scale with the electronic stopping power (Se) roughly as σ ∼ a S$_\mathrm{ e}^n$, where n ∼ 3/2. The power law is helpful for predicting the CO and NH3 dissociation and CO2 formation cross-sections for other ions and energies; these predictions allow estimating the effects of the entire cosmic ray radiation field.
CHARACTERIZATION OF MOLECULAR MECHANISMS DRIVING EPIGENETIC CONVERSION AND PHENOTYPE SWITCH OF FIBROBLASTS INTO INSULIN SECRETING CELLS

s:  Tiziana A.L. Brevini, Elena F.M. Manzoni, Alessandro Zenobi and Fulvio Gandolfi "Epigenetic controls of cell plasticity and commitment", 2nd International Conference on Stem Cells, 2017, Rhodes (Greece);  Manzoni E.F.M, Pennarossa G. , Zenobi A. , Ledda S. , Gandolfi F. and Brevini T.A.L. “Use of a micro-bioreactor to promote 3-dimensional cell rearrangement and induce, maintain, and stabilize high plasticity in epigenetically erased fibroblasts”, 2017, Reproduction, Fertility and Development 29(1) 207-207, https://doi.org/10.1071/RDv29n1Ab196;  Zenobi A. , Gandolfi F. , Brevini T.A.L. “Matrix stiffness and oxygen tension modulate epigenetic conversion of mouse dermal fibroblasts into insulin producing cells”. 2017, International Journal of Health, Animal Science and Food Safety;  Zenobi A. , Luo Y. , Brevini T.A.L. , Gandolfi F. “Use of CRISPR/Cas9 to edit OCT4 gene and investigate high plasticity of epigenetically erased fibroblasts”, 2016, EpiConcept Conference 2016, Giardini Naxos (Italy);  Brevini T.A.L. , Pennarossa G. , Manzoni E.F.M. , Zenobi A. , Gandolfi F. “Combining 3D culture systems to epigenetic tools”, 2016, EPICHEMBIO action meeting “Creating new collaborative research proposals”, Groningen (Netherlands);
A novel in vitro chemotaxis bioassay to assess the response of Meloidogyne incognita towards various test compounds

Abstract Plant-parasitic, root-knot nematodes (Meloidogyne spp.) are a serious problem in agri- and horticultural crops worldwide. Understanding their complex host recognition process is essential for devising efficient and environmental-friendly management tactics. In this study, the authors report a new, simple, inexpensive, efficient, and quantitative method to analyze the chemotaxis of M. incognita second-stage juveniles (J2s) using a combination of pluronic gel and agar in a petri dish. The authors quantitatively defined the concentration gradient formation of acid fuchsin on the assay plate. Using this novel assay method, the authors have accurately measured the nematode response (attraction or repulsion) to various volatile (isoamyl alcohol, 1-butanol, benzaldehyde, 2-butanone, and 1-octanol) and non-volatile (root exudates of tomato, tobacco, and marigold) compounds. Isoamyl alcohol, 1-butanol, and 2-butanone were attractive to J2s through a broad range of concentrations. On the contrary, J2s were repelled when exposed to various concentrations of 1-octanol. Despite being attractive at lower concentrations, undiluted benzaldehyde was repulsive to J2s. Tomato and tobacco root exudates were attractive to J2s while marigold root exudates repelled J2s. The present quantitative assay method could be used as a reference to screen and identify new candidate molecules that attract or repel nematodes.
Exploring Dimensions Of Defense In Cyber Space-A REVIEW

: I NTRODUCTION : I N THIS MODERN AGE , THE WORLD IS ADVANCING IN TERMS OF CONNECTIVITY THROUGH NEW NETWORKING PARADIGMS . T HERE WILL BE GROWTH IN VOLUME , VARIETY AND VERACITY OF THE CYBER DATA ALONG WITH DEVICES , AND IT IS PREDICTED THAT THIS COUNT WILL REACH 200 BILLION BY 2020. D IGITAL C RIMINALS LARGELY DEPEND ON DECEIT STRATEGIES TO EXPLOIT WEAKNESSES AND MASQUERADE THEIR IDENTITY WHICH IN TURN ARE PESSIMISTIC ABOUT CYBER DETERRENCE . T HIS ARTICLE PRESENTS A REVIEW OF C YBER C RIMES - M ETHODS AND WAYS TO TACKLE THEM WITH A BRIEF REVIEW ON C YBER FORENSICS . M ETHODOLOGY : S COPUS D IGITAL L IBRARY AND IEEE EXPLORE WERE SEARCHED FOR RELEVANT E NGLISH PAPERS FROM 2019 TO REVERSE CHRONOLOGICAL ORDER . R ESULTS AND C ONCLUSION : T HERE IS AN ALARMING EMERGENCY TO DESIGN NEW TECHNOLOGIES THAT CAN EFFECTIVELY WITHSTAND ANY KIND OF CYBER - ATTACKS . T HE NEWLY DEVELOPED SECURITY PROTOCOLS SHOULD BE DYNAMIC ENOUGH TO HOLD THEIR GROUND AGAINST THE EVER - CHANGING NATURE OF C YBERCRIMES .
Phenolic Compounds Characterization and Antioxidant Properties of Monocultivar Olive Oils from Northeast Algeria

In Algeria, the olive tree is one of the main fruit species and plays a very important socioeconomic role. The objective of this study was firstly, to identify and quantify the phenolics of some Algerian olive oils, and secondly, to assess the antioxidant activity of the samples. The olive oils used in this study were derived from Algerian cultivars, including Tefahi, Gelb Elfarroudj, Chemlal, and imported cultivar Manzanilla and Zebboudj. For this purpose, gas chromatography—mass spectrometry (GC-MS) was used to identify olive oil fatty acids profile, while the individual phenolic compounds were assessed by ultra-high-performance liquid chromatography–electrospray ionization–high-resolution mass spectrometry (UHPLC-HESI-MS). To verify the antioxidant capacity, five in vitro free radical assays were used. Questionable values of particular physico-chemical parameters, such as the high value of free acidity and the low concentration of monounsaturated fatty acids in oil from the Zebboudj cultivar, indicate that improvements in olive cultivation and oil production practices are needed. Gelb Elfarroudj, Tefahi, and Manzanilla oils contain quantities of monounsaturated fatty acids in accordance with EU regulations. The oil obtained from the Zebboudj cultivar is not usable for food purposes due to the high value in free acidity and the low concentration of monounsaturated fatty acids. Tefahi and Manzanilla cultivars have given oils with the best antioxidant activity as compared to other studied cultivars; this is attributable to their composition in bioactive phenolic compounds, such as secoiridoids, which play an important role in human health as scavengers of free radicals. The results are interesting for producers and consumers to promote the culture of olive oils derived in particular from the Tefahi cultivar. However, in order to improve the health qualities of this oil, the agronomic techniques essentially linked to the time of harvesting of the olives destined for oil production must be improved.
Walking duration in daily travel: an analysis among males and females using a hazard-based model

This study examines how various travel/built environmental and individual/household characteristics influence the walking durations of males and females in the city of Rasht, Iran, using data from the 2007 Rasht Household Travel Survey (RHTS). Accelerated hazard (AH) modelling, as a new approach in walking-related studies, was used to predict walking durations. The survival curve analysis showed that the ideal walking time was five minutes, but walking up to ten minutes was also acceptable. The AH models indicated that the walking duration of males and females varied under different conditions and contexts. For example, female workers were likely to walk longer trips relative to non-workers; however, this was the opposite among males. Household characteristics such as car ownership were found with greater negative effect on walking duration of males than females. Furthermore, zones with higher land use mix and higher connectivity led to shorter walking duration in both models.
Sleep and the Gut Microbiome in Psoriasis: Clinical Implications for Disease Progression and the Development of Cardiometabolic Comorbidities

Background: Sleep dysfunction and sleep disorders are important comorbidities of psoriasis. Not only do these sleep comorbidities contribute to reduced quality of life, but they may also lead to worsening psoriasis and increased susceptibility to cardiometabolic diseases. While psoriasis and sleep dysfunction are thought to be linked by itch, depression, and immune system dysregulation, the relationship between psoriasis and sleep dysfunction is not yet fully understood. Objective: We sought to compare previous studies characterizing the gut microbiome in psoriasis and sleep dysfunction and examine the potential relevance of shared findings on cardiometabolic and overall health. Methods: We performed literature searches of PubMed and Embase databases to find studies evaluating the gut microbiome in psoriasis, sleep dysfunction, and cardiometabolic diseases. Results: Studies characterizing the gut microbiome in psoriasis and sleep dysfunction reveal shared findings, specifically an increased Firmicutes to Bacteroidetes ratio and reduced abundance of short-chain fatty acid–producing bacteria. These dysbiotic features have also been shown to promote systemic inflammation and cardiometabolic disease. Conclusion: In favoring an increased Firmicutes to Bacteroidetes ratio and reduced abundance of short-chain fatty acid–producing bacteria, sleep dysfunction could be contributing to worsening psoriasis and cardiometabolic comorbidities through intestinal dysbiosis. Future studies are needed to determine whether gut- and sleep-targeting interventions could be therapeutic in patients with psoriasis having poor sleep.
Genome-wide marker-trait association analysis in a core set of Dolichos bean germplasm

Abstract Association mapping (AM), an alternative method of quantitative trait loci (QTL) discovery, exploits historic linkage disequilibrium (LD) present in natural populations. AM is effective in self-pollinated crops such as Dolichos bean as LD extends over longer genomic distance driven-by low rate of recombination and thereby requiring fewer markers for exploring marker-traits associations. A core set of Dolichos bean germplasm consisting of 64 accessions was evaluated for nine quantitative traits (QTs) during 2014 and 2015 rainy seasons and genotyped using 234 simple sequence repeats (SSR) markers. Substantial diversity was observed among the core set accessions at loci controlling QTs and 95 of the 234 SSR markers were found polymorphic. The structure analysis and low magnitude of fixation indices suggested weak population structure, which in-turn indicated the low possibility of false discovery rates in the marker-QTs association. The marker allele's scores were regressed onto phenotypes at nine QTs following general linear model and mixed linear model for exploring marker-QTs associations. Significantly higher number of SSR markers was found associated with genomic regions controlling nine QTs. A few of the markers such as KT Dolichos (KTD) 200 for days to 50% flowering, KTD 273 for fresh pod yield per plant and KTD 130 for fresh pods per plant explained ≥10% of the trait variations. The study could also identify a few SSR markers such as KTD 273, KTD 271 and KTD 130 linked to multiple traits. These linked SSR markers are suggested for validation for their use in marker-assisted Dolichos bean improvement programmes.
CCSD(T) study on the structures and chemical bonds of AnO molecules (An = Bk–Lr)

The molecular geometries and dissociation energies of AnO (An = Bk–Lr) molecules were first obtained at the coupled-cluster single-, double-, and perturbative triple-excitations [CCSD(T)] level of theory. Four hybrid functionals, B3LYP, M06-2X, TPSSh, and PBE0, were also employed in the calculations for the sake of comparison. In comparison of the CCSD(T) results, B3LYP, TPSSh, and PBE0 functionals can obtain more appropriate results than M06-2X and MP2. The analyses on molecular orbitals show that the 7s, 6d, and 5f atomic orbitals of actinide (An) atoms participate in the bonding of An–O bonds. The partial covalent nature between An and O atoms is revealed by QTAIM analyses.
A theory‐based framework for understanding the establishment, persistence, and diffusion of community‐based conservation

Over decades, biodiversity conservation researchers and practitioners have developed theories and conceptual frameworks to inform the planning, implementation, and evaluation of community‐based conservation (CBC). While a diversity of mechanisms for understanding and supporting CBC has helped tailor approaches to local needs and conditions, the absence of a unified lens to understand CBC has limited the capacity for integrating foundational theory into practice more systemically, and for learning across different projects, stakeholders, and institutions. We introduce a theory‐based framework called “the CBC framework” that draws upon three foundational theories from sociology, economics, and political science to understand the establishment, persistence, and diffusion of CBC. Experience applying aspects of the framework within different conservation organizations demonstrates how this integrative approach can provide a gateway for practitioners to engage with social science theory to understand the status and context of CBC interventions and efforts. For practitioners, scientists, evaluators, and strategists, the framework can guide the design of CBC interventions and monitoring and evaluation systems to facilitate theory‐based learning and enable evidence‐informed decision‐making. Approaches like the CBC framework that facilitate collaborative planning, evaluation, and research can help better integrate social science theory in conservation practice while increasing the capacity for conservation scientists, practitioners, and stakeholders to learn together and adaptively manage CBC to deliver positive results for both people and nature.
The Prediction of Traffic Flow Based on Long Short-Term Memory Network for All Weather

To set up a schedule of toll collector in advance and reduce the queue length and traffic congestion of toll stations, this paper proposes a short-term forecasting method for toll stations based on long short-term memory network. First, we analyze the quality of highway toll data. Then, a data preprocessing method based on the cubical smoothing algorithm with five-point approximation is designed. Moreover, we establish the traffic data set which is associated with the toll stations information and time. Then we construct a traffic flow prediction model. Taking the Airport Station of Airport Highway in Guangzhou as an example, then test the validity and real-time performance of our model. The results show that the mean absolute percentage error of the prediction is about 3.6% when the forecast horizon of prediction is 5 minutes; when the forecast horizon of prediction is 10 minutes, the mean absolute percentage error is about 6.07%; when the forecast horizon of prediction is 15 minutes, the mean absolute percentage error is about 8.68%, therefore, the model can accurately predict the traffic flow of toll stations. At the same time, compared with the KNN algorithm and GBDT algorithm, the model of this paper not only has higher prediction accuracy, but also has better adaptability to predict the peak, and when weather is adverse, the algorithm of this paper also can predict accurately through extracting the relevance of time in data set effectively.
Rain, Rain, Go Away: 176 Potential Exclusion-Restriction Violations for Studies Using Weather as an Instrumental Variable

Instrumental variable (IV) analysis assumes that the instrument only affects the dependent variable via its relationship with the independent variable. Other possible causal routes from the IV to the dependent variable are exclusion-restriction violations and make the instrument invalid. Weather has been widely used as an instrumental variable in social science to predict many different variables. The use of weather to instrument different independent variables represents strong prima facie evidence of exclusion violations for all studies using weather as an IV. A review of 217 social science studies reveals 176 variables which have been linked to weather, all of which represent potential exclusion violations. I conclude with practical steps to systematically review existing literature to identify possible exclusion violations when using IV designs. I demonstrate how sensitivity analysis can quantify the vulnerability of a particular IV estimate to exclusion restriction violations in the literature.
Double deep Q‐learning coordinated control of hybrid energy storage system in island micro‐grid

It is difficult for a single energy storage to meet both power and energy requirements in the island micro‐grid because of the randomness of wind and solar irradiation. A reasonable way is to use hybrid energy storage in the island micro‐grid. For the energy management and optimization control of energy storage systems, there are various problems with traditional methods, such as the large computational complexity in dynamic programming. Q‐learning has recently been applied to the optimal control of energy storage systems. Due to the limitations of the Q‐learning algorithm in the state space, this article uses the Double deep Q‐learning (DQN) algorithm to design the control strategy of energy storage systems. It is applied to an island Micro‐grid system consisting of photovoltaic (PV), wind turbine, hydrogen storage (long‐term energy storage devices), and battery (short‐term energy storage devices). Transform the coordinated control of the hybrid energy storage system into a sequence decision problem. Due to the influence of renewable energy, load and other factors, different control strategies have different effects. DDQN algorithm combines the perception ability of deep learning with the decision‐making ability of reinforcement learning which can realize real‐time online decision control after training. Experimental results show that, the method of this article can be effectively processed for different weather scenarios and increase utilization of renewable energy.