Miracle-dz/UniFAR-FTUs huggingface dataset:
A self-managing Smart

Automatically determining the situation of an ad-hoc group of people and devices within a smart environment is a signiﬁcant challenge in pervasive computing systems. Current approaches often rely on an environment expert to corre- late the situations that occur with the available sensor data, while other machine learning based approaches require long training periods before the system can be used. This paper presents a novel approach to situation determination that attempts to overcome these issues by providing a reusable library of general situation spec- iﬁcations that can be easily extended to create new speciﬁc situations, and immediately deployed without the need of an environment expert. The architecture of an accompanying situation determination infrastructure is provided, which au-tonomously optimises and repairs itself in reaction to changes or failures in the environment.
Evaluation of environmental stress tolerance of extracellular vitamin B 12 producing lactobacilli cultures

We investigated environmental stresses tolerance of the extracellular vitamin B 12 producing lactobacilli cultures and confirmed the screening strategy of vitamin B 12 producing Lactobacillus strains, isolated from the infants’ fecal sample. Three cultures ( L. plantarum NCDC958 and NCDC957, and L. rhamnosus NCDC953) endowed with extracellular vitamin B 12 producing ability from our previous work were amplified for cbiK gene with new primers designed in this study and their characteristics in tolerance to environmental stresses (such as temperature, salt, sugar, and ethanol) were studied for the first time with both optical density (OD) measurements and pour plate count method. We confirmed amplification of the 257 bp cbiK gene in these cultures, which codes for important B 12 -structural enzyme cobalt chelatase and successfully selected B 12 -producing strains. These cultures showed tolerance upto 6% NaCl, 30% sucrose, 42 °C temperature and 8% ethanol. Importantly, extracellular vitamin B 12 producing culture L. rhamnosus has first-time been reported for the environmental
Prioritized data synchronization with applications

We are interested on the problem of synchronizing data on two distinct devices with differed priorities using minimum communication. A variety of distributed systems require communication efficient and prioritized synchronization, for example, where the bandwidth is limited or certain information is more time sensitive than others. Our particular approach, P-CPI, involving the interactive synchronization of prioritized data, is efficient both in communication and computation. This protocol sports some desirable features, including (i) communication and computational complexity primarily tied to the number of differences between the hosts rather than the amount of the data overall and (ii) a memoryless fast restart after interruption. We provide a novel analysis of this protocol, with proved high-probability performance bound and fast-restart in logarithmic time. We also provide an empirical model for predicting the probability of complete synchronization as a function of time and symmetric differences. We then consider two applications of our core algorithm. The first is a string reconciliation protocol, for which we propose a novel algorithm with online time complexity that is linear in the size of the string. Our experimental results show that our string reconciliation protocol can potentially outperform existing synchronization tools such like rsync in some cases. We also look into the benefit brought by our algorithm to delay-tolerant networks(DTNs). We propose an optimized DTN routing protocol with P-CPI implemented as middleware. As a proof of concept, we demonstrate improved delivery rate, reduced metadata and reduced average delay.
Distributed Load Balancing with Nonconvex Constraints: A Randomized Algorithm with Application to Electric Vehicle Charging Scheduling

To schedule a large number of EVs with the presence of practical nonconvex charging constraints, a distributed and randomized algorithm is proposed in this paper. The algorithm assumes the availability of a coordinator which can communicate with all EVs. In each iteration of the algorithm, the coordinator receives tentative charging profiles from the EVs and computes a broadcast control signal. After receiving this broadcast control signal, each EV generates a probability distribution over its admissible charging profiles, and samples from the distribution to update its tentative charging profile. We prove that the algorithm converges almost surely to a charging profile in finite iterations. The final charging profile (that the algorithm converges to) is random, i.e., it depends on the realization. We characterize the final charging profile---a charging profile can be a realization of the final charging profile if and only if it is a Nash equilibrium of the game in which each EV seeks to minimize the inner product of its own charging profile and the aggregate electricity demand. Furthermore, we provide a uniform suboptimality upper bound, that scales O(1/n) in the number n of EVs, for all realizations of the final charging profile.
PAPPA2 , an enzyme that cleaves an insulin-like growth factor binding protein, is a candidate gene for a QTL affecting body size in mice

Identifying genes responsible for quantitative variation remains a major challenge. We previously identified a quantitative trait locus (QTL) affecting body size that segregated between two inbred strains of mice. By fine-mapping, we have refined the location of this QTL to a genomic region containing only four protein-coding genes. One of these genes, PAPPA2 , is a strong candidate because it codes for an enzyme that cleaves insulin-like growth factor-binding protein 5 (IGFBP-5), an important stimulator of bone formation. Among littermates that segregate only for the four-gene region, we show that the QTL has a significant effect on the circulating levels of IGFBP-5 and IGFBP-3 (the latter subject to limited degradation by PAPPA2 ), but not on levels of IGFBP-2 and IGFBP-4, which are not cleaved by PAPPA2 . There are fourteen non-synonymous SNPs between QTL alleles, which may affect the activity of the translated protein. The refinement of the target region to four genes and the finding that the QTL affects IGFBP-5 levels suggest that PAPPA2 may be involved with normal postnatal growth. Our mapping results also illustrate the potentially fractal nature of QTL: as we mapped our QTL with increasing resolution, what appeared to be a single QTL resolved into three closely-linked QTL (previous work), and then one of these was further dissected into two in this study.
Method To Detect Only Live Bacteria during PCR Ampliﬁcation (cid:1)

Ethidium monoazide (EMA) is a DNA cross-linking agent and eukaryotic topoisomerase II poison. We previously reported that the treatment of EMA with visible light irradiation (EMA (cid:1) Light) directly cleaved chromosomal DNA of Escherichia coli (T. Soejima, K. Iida, T. Qin, H. Taniai, M. Seki, A. Takade, and S. Yoshida, Microbiol. Immunol. 51:763–775, 2007). Herein, we report that EMA (cid:1) Light randomly cleaved chromosomal DNA of heat-treated, but not live, Listeria monocytogenes cells within 10 min of treatment. When PCR ampliﬁed DNA that was 894 bp in size, PCR ﬁnal products from 10 8 heat-treated L. monocytogenes were completely suppressed by EMA (cid:1) Light. When target DNA was short (113 bp), like the hly gene of L. monocytogenes , DNA ampliﬁcation was not completely suppressed by EMA (cid:1) Light only. Thus, we used DNA gyrase/topoisomerase IV and mammalian topoisomerase poisons (here abbreviated as T-poisons) together with EMA (cid:1) Light. T-poisons could penetrate heat-treated, but not live, L. monocytogenes cells within 30 min to cleave chromosomal DNA by poisoning activity. The PCR product of the hly gene from 10 8 heat-treated L. monocytogenes cells was inhibited by a combination of EMA (cid:1) Light and T-poisons (EMA (cid:1) Light (cid:1) T-poisons), but those from live bacteria were not suppressed. As a model for clinical application to bacteremia, we tried to discriminate live and antibiotic-treated L. monocytogenes cells present in human blood. EMA (cid:1) Light (cid:1) T-poisons completely suppressed the PCR product from 10 3 to 10 7 antibiotic-treated L. monocytogenes cells but could detect 10 2 live bacteria. Considering the prevention and control of food poisoning, this method was applied to discriminate live and heat-treated L. monocytogenes cells spiked into pasteurized milk. EMA (cid:1) Light (cid:1) T-poisons inhibited the PCR product from 10 3 to 10 7 heat-treated cells but could detect 10 1 live L. monocytogenes cells. Our method is useful in clinical as well as food hygiene tests.
Self-Stabilizing Structures for Data Gathering in Wireless Sensor Networks

—Wireless Sensor Networks (WSN) enable a number of applications, with monitoring of habitats, ofﬁce buildings, or restricted areas most prominent among them. All of these applications have one thing in common: the need to communicate. However, the nature of the wireless medium results in quite a few problems. Lossy communication links with transient faults require acknowledgments, retransmissions, and route repair mechanisms. Tree-or similar structures for data gathering scenarios lead to increased load closer to the sink, with congestion, higher buffer space requirements, and energy drain as results. The second problem is often addressed by aggregation and reduction schemes. These schemes are bound to fail, however, when the underlying structure is compromised due to changes in the connectivity between nodes. Therefore, it is necessary to focus on the structures ﬁrst of all. We address the problem of transient faults by using the inherent fault tolerance of self-stabilizing algorithms when building and using tree-or tiers (communication) structures. In this paper we show that self-stabilizing structures are suitable for data gathering scenarios in WSN by comparison of the connectivity achieved by our self-stabilizing tiers algorithm and the tree algorithm from Dolev with that of Collection Tree Protocol (CTP), the standard data-gathering protocol for TinyOS.
DMSO_A_280152 3703..3711

1Department of Nursing, College of Health Science, Assosa University, Assosa, Ethiopia; 2Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia Aim: The incidence of a diabetic foot ulcer (DFU) is increasing over the previous decade with an increasing prevalence of diabetes mellitus (DM). Despite the increasing incidence of DFU, there is limited information about the problem in Ethiopia. Hence, this study aimed to investigate the incidence of DFU and its predictors among newly diagnosed DM patients who were on follow-up at Felege Hiwot Referral Hospital. Methods: Institution-based retrospective follow-up study was conducted at Felege Hiwot Referral Hospital among newly diagnosed DM patients from January 1, 2009, to December 31, 2018. A simple random sampling method was used to select 401 study participants from a total of 723 eligible population. Data was entered using Epi-Data version 3.1 and exported to STATA version 14 for analysis. The incidence rate was estimated using person-years of observation and Nelson–Aalen cumulative hazard function, showing the cumulative probability of diabetic foot ulcer, was done. The best model (Gompertz) was selected using the AIC and log-likelihood method. Hazard ratio (HR) with its 95% confidence interval was computed and variables having a p-value less than 0.05 in the multivariable model were considered to be significantly associated with DFU. Results: A total of 387 patients were followed retrospectively for a median follow-up time of 95 months. Out of all, 66 (17.05%) patients developed DFU with an incidence rate of 4 cases per 100 person-years of observation. Diabetic nephropathy (adjusted hazard ratio (AHR) = 2.37, 95% CI: 1.33–54.24), diabetic retinopathy (AHR = 5.56, 95% CI: 2.64–11.74), and increased body mass index (AHR = 1.13, 95% CI: 1.01–1.27) were found to increase the hazard of DFU. Conclusion: The incidence of DFU was relatively high. Diabetic nephropathy, diabetic retinopathy, and body mass index were its significant predictors. Therefore, close monitoring of patients with co-morbidities and increased body mass index should be considered to reduce DFU.
Methods of preparation and standardization of herbal yoghurt by sensory evaluation

Yogurt is a dairy product made by fermenting milk with a yogurt culture. It provides protein and calcium, and it may enhance healthy gut bacteria. The present study investigate commonly used herbs Aloe barbadensis ( Aloe vera ), Anethum graveolence (dill), Costus igneus (insulin plant) and Hibiscus sabdariffa (roselle) on yoghurt formation . In the preparation of herbal yoghurt plants like Aloe barbadensis , Anethum graveolens , Costus igneus and Hibiscus sabdariffa were standardized for incorporation into yoghurt at the level of 14, 0.6, 0.7 and 0.6 per cent, respectively based on sensory evaluation using nine point scale method. Statistical analysis showed that these concentrations were optimum for inclusion in yoghurt based on significantly ( P ˂0.05) higher sensory scores of sensory panel to the parameters like colour and appearance, flavour and taste, body and texture and overall acceptability.
G LOBAL J OURNAL OF E NGINEERING S CIENCE AND R ESEARCHES NON-BLIND IMAGE WATERMARKING SCHEME USING BI-DIMENSIONAL EMPIRICAL MODE DECOMPOSITION, DWT, DCT AND FUZZY SET

The traffic of digital images has increased rapidly in the wide networks. The protection of this kind of data becomes important for many reasons such as confidentiality, authenticity and security. Nowadays, the most important engine to provide authenticity is watermarking. In this paper we present a method of invisible and robust hybrid watermarking to guarantee the authenticity and the confidentiality of images. This method or algorithm combines Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Bi-dimensional Empirical Mode Decomposition (BEMD) . In fact we propose to apply the BEMD to the original image then we take the First Intrinsic Mode Function (IMFs) decomposition of the image, we apply the Discrete Wavelet Transform (DWT) level 2, then we apply the Discrete Cosine Transform (DCT), to obtained news coefficients. It is here that we proceed with the integration of the mark coefficients after use of fuzzy set, DWT and DCT transforms. The method is not blind because it makes use of the original image for extracting the mark. The method is robust to certain usual attacks such as, filtering, adding noise and rotation. Results tested on different pictures by some attacks, are Satisfactory in terms of imperceptibility and robustness with measures of peak signal-to-noise ratio (PSNR).
NDT_A_306300 1375..1384

1Department of Psychiatry, School of Medicine, College of Health Science, Debre Tabor University, Debre Tabor, Ethiopia; 2Departments of Psychiatry, College of Health Science, Debre Markos University, Debre Markos, Ethiopia; 3Department of Psychiatry, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia Background: The coronavirus has affected nearly every aspect of our lives. Most importantly the health-care workers (HCWs) are under insurmountable psychological pressures which lead them to various mental health problems, such as anxiety, stress, and depression. Objective: This study aimed to assess mental health adverse effects of COVID-19 pandemic on health-care workers in North West Ethiopia 2020. Materials and Methods: Institutional-based cross-sectional study was conducted. A simple random sampling technique was applied and 419 participants completed the questionnaire. Mental health adverse effects were measured using the depression, anxiety and stress scale (DASS-21). Data were entered into Epi data version 4.4. 2 then exported to SPSS version 24 for analysis. Descriptive, bivariate, and multivariate binary logistic regressions with odds ratios and 95% confidence interval were employed. The level of significance of association was determined at a p-value < 0.05. Results: Prevalence of depression, anxiety, and stress in this study was 58.2%, 64.7%, and 63.7%, respectively Those who had a medical illness, and mental illness, contact with confirmed COVID-19 pts, and poor social support showed a statistically significant association with depression. Female sex, participants who had families with chronic illness, had contact with confirmed COVID-19 case and poor social support had statistically significant association with anxiety, whereas participants who had families with chronic illness had contact with confirmed COVID-19 cases, and those participants who had poor social support were predictors of stress during COVID-19 pandemic. Conclusion: The magnitudes of mental health problems were higher and the concerned body should emphasize the continuous assessment of the mental health of health-care workers during this pandemic.
Policy Based Context Aware Service Level Agreement (SLA) Management in the Cloud

—The lack of security and the inexistence of Quality of Service tracking mechanisms limit the success of cloud computing as a new technology, even if it demonstrates great capabilities of solving a number of problems that almost all organizations suffer from. This paper presents a novel way of expressing Service Level Agreements (SLAs) and tracking them to assure the client about the security and Quality of Service that are provided by the Cloud Service Provider. Allowing the client to combine specific security and Quality of Service metrics with context information within SLAs, when they are expressed as software policies, increases tremendously their expressiveness and precision.
Topics and sentiments on Twitter during lockdown in London

The aim of this study is to investigate the topics that people discussed in Greater London during the Coronavirus disease 2019 (COVID-19) lockdown period. The Latent Dirichlet Allocation (LDA) method was used to investigate the topics discussed by people, then the sentiments and perceptions of social media users were evaluated by using Syuzhet R package, and the spatial patterns of urban green space visitation were also studied. LDA analysis identified eight topic groups, among which the word “lockdown” was frequently mentioned. Further, the sentiment analysis showed that users posted Tweets that were more negative when they referred to ‘lockdown’ during this period.
The n ELBE ( n ,fis) experiment

Simulations of the nELBE 235U and 242Pu parallel plate fission ionization chambers are presented using finite element methods and extensive GEANT4 simulations. The homogeneity of the electrical field was improved and the optimal amount of target material determined. Pile-up effects due to the high α activity of the plutonium targets have been considered in a realistic geometry.
Proteolytic Cleavage of Protein Tyrosine Phosphatase M Regulates Glioblastoma Cell Migration Experimental Therapeutics, Molecular Targets, and Chemical Biology

Glioblastoma multiforme (GBM), the most common malignant primary brain tumor, represents a significant disease burden. GBM tumor cells disperse extensively throughout the brain parenchyma, and the need for tumor-specific drug targets and pharmacologic agents to inhibit cell migration and dispersal is great. The receptor protein tyrosine phosphatase M (PTP M ) is a homophilic cell adhesion molecule. The full-length form of PTP M is down-regulated in human glioblastoma. In this article, overexpression of full-length PTP M is shown to suppress migration and survival of glioblastoma cells. Additionally, proteolytic cleavage is shown to be the mechanism of PTP M down-regulation in glioblastoma cells. Proteolysis of PTP M generates a series of proteolytic fragments, including a soluble catalytic intracellular domain fragment that translocates to the nucleus. Only proteolyzed PTP M fragments are detected in human glioblastomas. Short hairpin RNA–mediated down-regulation of PTP M fragments decreases glioblastoma cell migration and survival. A peptide inhibitor of PTP M function blocks fragment-induced glioblastoma cell migration, which may prove to be of therapeutic value in GBM treatment. These data suggest that loss of cell surface PTP M by proteolysis generates catalytically active PTP M fragments that contribute to migration and survival of glioblastoma cells. [Cancer down-regulation of PTP A fragments decreases cell migration and growth factor–independent survival in glioblastoma cells.
LUB AC determines chemotherapy resistance in squamous cell lung cancer

Lung squamous cell carcinoma (LSCC) and adenocarcinoma (LADC) are the most common lung cancer subtypes. Molecular targeted treatments have improved LADC patient survival but are largely ineffective in LSCC. The tumor suppressor FBW7 is commonly mutated or down-regulated in human LSCC, and oncogenic KRasG12D activation combined with Fbxw7 inactivation in mice (KF model) caused both LSCC and LADC. Lineage-tracing experiments showed that CC10 + , but not basal, cells are the cells of origin of LSCC in KF mice. KF LSCC tumors recapitulated human LSCC resistance to cisplatin-based chemotherapy, and we identified LUB AC-mediated NF-κB signaling as a determinant of chemotherapy resistance in human and mouse. Inhibition of NF-κB activation using TAK1 or LUB AC inhibitors resensitized LSCC tumors to cisplatin, suggesting a future avenue for LSCC patient treatment.
Communication Sucrose Synthase and Invertase in Isolated Vascular Bundles1

Vascular bundles were isolated from grapefruit (Citrus paradisi Macf.) during periods of rapid sucrose translocation into fruit. Invertase and sucrose synthase activities were assayed in these strands and compared with immediately adjacent tissues (inner most peel and segment epidermis) and phloem-free juice sacs during four growing seasons. Although sucrose synthase was present in sink cells, the significantly greater activity in vascular strands (per unit fresh weight and protein) indicated that the role of this enzyme in translocation may include a vascular function in addition to its proposed involvement in metabolism of importing cells.
EMPIRICAL RISK MINIMIZATION IN INVERSE PROBLEMS 1

We study estimation of a multivariate function f : R d → R when the observations are available from the function Af , where A is a known linear operator. Both the Gaussian white noise model and density estimation are studied. We deﬁne an L 2 -empirical risk functional which is used to deﬁne a δ -net minimizer and a dense empirical risk minimizer. Upper bounds for the mean integrated squared error of the estimators are given. The upper bounds show how the difﬁculty of the estimation depends on the operator through the norm of the adjoint of the inverse of the operator and on the underlying function class through the entropy of the class. Corresponding lower bounds are also derived. As examples, we consider convolution operators and the Radon transform. In these examples, the estimators achieve the optimal rates of convergence. Furthermore, a new type of oracle inequality is given for inverse problems in additive models.