Miracle-dz/UniFAR-FTUs huggingface dataset:
Phytochemical Characterization and Assessment of Crude Extracts From Lantana camara L. for Antioxidant and Antimicrobial Activity

Phytochemicals with antimicrobial and antioxidant properties have tremendous potential in suppressing both plant and human diseases. Screening and identification of such compounds from diverse plant species is the first step toward realizing their medicinal and agricultural application. In agriculture, application of antimicrobial phytochemicals as part of an Integrated Disease Management strategy would reduce the detrimental residual effect of synthetic chemicals. In the present study, an invasive plant species, i.e., Lantana camara L. was screened for potential antimicrobial and antioxidant phytochemicals. Extracts of leaves (LE) and flowers (FE) from L. camara were tested for their polyphenol content (total phenol, total flavonoid, and total alkaloid) and antioxidant potential [total antioxidant activity, iron chelating activity and enzymatic activity (peroxidase and polyphenol oxidase)]. Both extracts exhibited high antioxidant and free radical scavenging activities with relatively stronger antioxidant activity in the case of whole flower extracts. FTIR and GC-MS also carried out for chemical analysis of crude extracts. FTIR spectral study of LE and FE revealed the presence of different functional groups such as N–H, C–H, OH, C = O indicates the existence of various metabolites in the extracts. GC-MS study revealed the presence of 66 bioactive compounds, of which 19 components were predicted to have various functions like anti-inflammatory, antiandrogenic, anti-tumor, antimicrobial, etc. Furthermore, in vitro antifungal and antibacterial studies confirmed the antimicrobial effect of both LE and FE against phytopathogens like Magnaporthe oryzae, Xanthomonas axonopodis pv. glycines (Xag) and Xanthomonas oryzae pv. oryzae (Xoo). Molecular study further revealed that phytochemicals (Loliolide, Eicosapentaenoic acid, Salicylic Acid Methyl Ester, and Phytol) of Lantana camara could targets MAPK1, PDF, and SUH like enzymes of phytopathogens, which could inhibit their growth. Therefore, L. camara extracts can be an important ingredient in the suppression of plant diseases.
Analysis of pathogenic and genetic variability of Corynespora cassiicola based on iPBS retrotransposons

Abstract Corynespora cassiicola is an important plant pathogen with a wide host range. We investigated pathogenic and genetic variation among 69 C. cassiicola isolates from 16 hosts in China. Based on the inter-primer binding sites (iPBS)-retrotransposons, we selected five iPBS primers to analyse the genetic variability of these isolates. All isolates were clustered in two genetic clades (IG1 and IG2). Forty-four C. cassiicola isolates were selected from the collection to investigate their pathogenic profiles. Based on the results of the pathogenicity analysis, these 44 isolates were divided into two pathogenicity groups (PG1 and PG2). A correlation between the genetic and pathogenicity groups was observed in the phylogenetic tree obtained with the iPBS markers, whereas the isolates from rubber tree were clustered in an independent clade. A total of 72 bands were observed, of which 68 were polymorphic (94.44%). The Nei’s genetic identity index of the 16 host populations varied from 0.5035 to 0.9661. The mean Nei’s gene diversity index (H = 0.3042) and the mean Shannon’s information index (I = 0.4598) at the species level were higher than at the population level, suggesting that the genetic diversity within the populations was greater than among the populations. The Nei’s GST (0.7895) and gene flow (0.1333) showed more considerable genetic differentiation among populations and few gene exchanges. The pathogenicity and molecular marker analyses revealed there was a high level of genetic differentiation and diversity in the C. cassiicola isolates studied.
Querying little is enough: Model inversion attack via latent information

As machine learning (ML) technologies evolve, various online intelligent services use ML models to provide predictions. Unfortunately, attackers can obtain the private information of the model by interacting with the online service, namely model inversion attack (MIA). However, MIA requires large data sets to be transferred to an online service to obtain the predictive value of the inference model. Besides, the huge transmission may cause the administrator's active defense. To overcome this drawback, we propose a novel MIA scheme, which leverages latent information extracted by an auxiliary neural network as high‐dimensional features to simplify what inversion model should learn. The core idea of our scheme is to reuse some parameters of the local pretraining model. Extensive experiments have verified the effectiveness of our method in convolutional neural networks on LFW, pubFig, MNIST data sets. Experimental results show that even with a few queries, our inversion method still work accurately and is superior to other technologies. It is worth mentioning that our method makes it more difficult for administrators to defend against the attack and elicit more investigations for privacy‐preserving.
Genomic pro�le of MYCN non-amplied neuroblastoma and potential for immunotherapeutic strategies in neuroblastoma

Background: MYCN ampli�cation is the most important genomic feature in neuroblastoma (NB). However, limited studies have been conducted on the MYCN non-amplied NB including low-and intermediate-risk NB. Here, the genomic characteristics of MYCN non-amplied NB were studied to allow for the identi�cation of biomarkers for molecular strati�cation. Methods: Fifty-eight whole exome sequencing (WES) and 48 whole transcriptome sequencing (WTS) samples of MYCN non-amplied NB were analysed. Forty-one patients harboured WES and WTS pairs . Results: In the MYCN non-amplied NB WES data, maximum recurrent mutations were found in MUC4 (26%), followed by RBMXL3 (19%), ALB (17%), and MUC16 and SEPD8 (14% each). Two gene fusions, CCDC32 - CBX3 (10%) and SAMD5 - SASH1 (6%), were recurrent in WTS analysis, and these fusions were detected mostly in non-high-risk patients with ganglioneuroblastoma histology. Analysis of risk-group-specic biomarkers showed that several genes and gene sets were differentially expressed between the risk groups, and some immune-related pathways tended to be activated in the high-risk group. Mutational signatures 6 and 18, which represent DNA mismatch repair (MMR) associated mutations, were commonly detected in 60% of the patients. In the tumour mutation burden (TMB) analysis, four patients showed high TMB (> 3 mutations/Mb), and had mutations in genes related to either MMR or homologous recombination. Excluding four outlier samples with TMB > 3 Mb, high-risk patients had signi�cantly higher levels of TMB compared with the non-high-risk patients. Conclusions: This study provides novel insights into the genomic background of MYCN non-amplied NB. Activation of immune-related pathways in the high-risk group and the results of TMB and mutational signature analyses collectively suggest the need for further investigation to discover potential immunotherapeutic strategies for
Can Dizziness Handicap Inventory and Activities-Specific Balance Confidence Scores Assess Vestibular Loss After Vestibular Schwannoma Excision?

Objective: Evaluate and compare the Dizziness Handicap Inventory with Activities-specific Balance Confidence scores shortly after vestibular schwannoma excision. Study Design: Retrospective database review. Setting: Tertiary care center. Patients: Adults undergoing vestibular schwannoma excision between January 2015 and December 2019. Intervention: Diagnostic, therapeutic, and rehabilitative. Main Outcome Measures: Postoperative change in Dizziness Handicap Inventory scores and Activities-specific Balance Confidence scores 2 to 3 weeks after surgical intervention in relation to preoperative vestibular testing. Results: A total of 49 patients met inclusion criteria. The average change in the Dizziness Handicap Inventory was 6 (p = 0.07, 95% CI 0–13). This was weakly correlated to preoperative caloric testing values (r = −0.31, p = 0.03), but not cervical vestibular evoked myogenic potentials (cVEMP) values (r = −0.17, p = 0.23). The average change in Activities-specific Balance Confidence was −10% (p = 0.007, 95% CI −3 to −17%). This change was moderately correlated with preoperative caloric values (r = 0.42, p = 0.006), but it was not correlated with cVEMP (r = 0.07, p = 0.66). Conclusions: In vestibular schwannoma patients, factors other than preoperative vestibular function likely affect postoperative Dizziness Handicap Inventory and Activities-specific Balance Confidence scores. The change in Activities-specific Balance Confidence was slightly more consistent with expected physiological vestibular loss, and it represents another tool in a multidisciplinary vestibular evaluation of the postoperative patient.
Host Defense Effectors Expressed by Hemocytes Shape the Bacterial Microbiota From the Scallop Hemolymph

The interaction between host immune response and the associated microbiota has recently become a fundamental aspect of vertebrate and invertebrate animal health. This interaction allows the specific association of microbial communities, which participate in a variety of processes in the host including protection against pathogens. Marine aquatic invertebrates such as scallops are also colonized by diverse microbial communities. Scallops remain healthy most of the time, and in general, only a few species are fatally affected on adult stage by viral and bacterial pathogens. Still, high mortalities at larval stages are widely reported and they are associated with pathogenic Vibrio. Thus, to give new insights into the interaction between scallop immune response and its associated microbiota, we assessed the involvement of two host antimicrobial effectors in shaping the abundances of bacterial communities present in the scallop Argopecten purpuratus hemolymph. To do this, we first characterized the microbiota composition in the hemolymph from non-stimulated scallops, finding both common and distinct bacterial communities dominated by the Proteobacteria, Spirochaetes and Bacteroidetes phyla. Next, we identified dynamic shifts of certain bacterial communities in the scallop hemolymph along immune response progression, where host antimicrobial effectors were expressed at basal level and early induced after a bacterial challenge. Finally, the transcript silencing of the antimicrobial peptide big defensin ApBD1 and the bactericidal/permeability-increasing protein ApLBP/BPI1 by RNA interference led to an imbalance of target bacterial groups from scallop hemolymph. Specifically, a significant increase in the class Gammaproteobacteria and the proliferation of Vibrio spp. was observed in scallops silenced for each antimicrobial. Overall, our results strongly suggest that scallop antimicrobial peptides and proteins are implicated in the maintenance of microbial homeostasis and are key molecules in orchestrating host-microbiota interactions. This new evidence depicts the delicate balance that exists between the immune response of A. purpuratus and the hemolymph microbiota.
Ontology of Value, Risk and Cognitive Biases for an IT Portfolio Decision Making

Decisions about whether or not to kill an ongoing project of an IT portfolio may be critical. A bad decision to continue with a project with a high probability of making things worse, in exchange of a small chance of avoiding a large loss, often turns manageable failures into disasters. However, these decisions can be negatively impacted by cognitive biases of decision makers, such as the loss aversion, which are enhanced when uncertainty is substantial and information incomplete. As a result, it is important to reduce the biases in these decisions. This paper introduces an ongoing research that aims to create an ontology to improve the understanding of these cognitive biases. It can be used as part of a strategy to reduce biases in a risk and value analysis.
Review of gait recognition approaches and their challenges on view changes

Gait or walking pattern has been known as one of the alternative biometric solutions used in surveillance monitoring and control. The methods of gait recognition have been developed for decades using various techniques in different concepts. This study is a review paper collecting gait recognition approaches in both perspectives of model-based approaches relying on key joints/parts of the human body and appearance-based approaches relying on gait silhouettes. The existing methods addressing one of the most important real-world challenges, i.e. view changes, are emphasised and summarised in this study. Also, recent methods based on convolutional neural network solving the gait recognition and their challenges of view changes are illustrated. In addition, the publicly-available gait datasets and corresponding recognition performance and comparison are concluded in each section. The state-of-the-art gait recognition methods can achieve up to a perfect score of 100% accuracy for the normal walking, and above 80% in average for the view changes ranging from 0° to 180°.
Relating existing powerful proof systems for QBF

We advance the theory of QBF proof systems by showing the first simulation of the universal checking format QRAT by a theory-friendly system. We show that the sequent system G fully p-simulates QRAT, including the Extended Universal Reduction (EUR) rule which was recently used to show QRAT does not have strategy extraction. Because EUR heavily uses resolution paths our technique also brings resolution path dependency and sequent systems closer together. While we do not recommend G for practical applications this work can potentially show what features are needed for a new QBF checking format stronger than QRAT.
Performance of non-orthogonal multiple access: analysis using compute-and-forward cooperative relaying in 5G networks

With the increasing demand for high-speed mobile transmissions for 5G networks, the cooperative relay-aided non-orthogonal multiple access (CR-NOMA) has been highly considered. An efficient and reliable CR-NOMA not only depends on the network mechanism but on the network coding strategy at the relay. Even though conventional strategies have broadly been studied, they suffer from noise accumulation and interference. Lately, the compute-and-forward (CpF) strategy has been identified as a potential technique to mitigate interference and enhance outage probability. In this study, the authors present a mathematical formulation to examine the performance of CpF on downlink CR-NOMA. In the proposed formulation, a two-stage downlink cooperative relay network is considered to obtain analytical closed-form expressions of outage probability and bit error rate. The outage probabilities and bit error rates of existing relaying strategies are compared regarding the network model. The theoretical analysis shows that CpF requires half the number of relays desirable in amplify-and-forward and decode-and-forward strategies to achieve a proportionate outage probability in CR-NOMA. Finally, we present results to show that at a lower signal-to-noise ratio, the integration of CpF and NOMA enhances error performance irrespective of the number of users.
3-5 GHz multifinger CMOS LNA using a simultaneous noise and impedance matching technique by a significant reduction of broadband impedance variation of metal-oxide-semiconductor field effect transistor

This work provides a new simultaneous noise and impedance matching (SNIM) methodology for designing a 3–5 GHz ultrawideband low-noise amplifier (LNA) in 0.18 μm complementary metal–oxide–semiconductor (CMOS) process using the advanced design system platform. To justify the proposed method, common gate (CG)and common source (CS)-inputmatched LNAs are designed where the variation of input impedance over the whole operating band is significantly reduced by applying the multifinger layout technique and employing shunt passive elements for the input device without degenerating the structure, respectively. As part of the proposed SNIM method, a two-dimensional contour plot-based process variation tolerant bias voltage set up protocol is developed which can optimise forward gain (S21), noise figure (NF) and stability factor simultaneously. The regulation of amplifier port parameters with bias settling contour plots and finger parameters results in the proposed SNIM technique. For the CG-input-matched LNA, the post-layout electromagnetic simulated NF is between 3.08 and 4.1 dB, the average power gain of 25.52 dB with a power consumption of 20.19 mW and the CS-input-matched LNA achieves an NF in between 2.772 and 3.04 dB, the average power gain of 17.98 dB while the dissipated power is 20.73 mW.
Investigating Hadoop Architecture and Fault Tolerance in Map-Reduce

Map-Reduce is often used in implementation of critical and important tasks such as analysis of the scientific data. However, evidences in the past indicate the presence of optional errors that can destroy the results of Map-Reduce. Of course, run times of Map-Reduce like Hadoop can tolerate crash errors, but do not tolerate arbitrary or Byzantine errors. Hence in this paper, at first, the Hadoop architecture in distributed system will be investigated and then Hadoop will be compared with Map-Reduce and finally the Map-Reduce fault tolerance will be investigated.
HEAT TRANSFER CONSIDERATIONS IN A PRESSURE VESSEL BEING CHARGED

Abstract : Experimental data for the charging of an air receiver is presented and interpreted in detail. The data indicates a substantial departure from the adiabatic behavior. The experimental results are used to evaluate existing closed form expressions for the thermodynamic state of a gas in a receiver. A method for experimentally determining the convective heat transfer coefficient is developed, evaluated and used in conjunction with these expressions.
A Reliable BioFET Immunosensor for Detection of p53 Tumour Suppressor in Physiological-Like Environment

The concentration of wild-type tumour suppressor p53wt in cells and blood has a clinical significance for early diagnosis of some types of cancer. We developed a disposable, label-free, field-effect transistor-based immunosensor (BioFET), able to detect p53wt in physiological buffer solutions, over a wide concentration range. Microfabricated, high-purity gold electrodes were used as single-use extended gates (EG), which avoid direct interaction between the transistor gate and the biological solution. Debye screening, which normally hampers target charge effect on the FET gate potential and, consequently, on the registered FET drain-source current, at physiological ionic strength, was overcome by incorporating a biomolecule-permeable polymer layer on the EG electrode surface. Determination of an unknown p53wt concentration was obtained by calibrating the variation of the FET threshold voltage versus the target molecule concentration in buffer solution, with a sensitivity of 1.5 ± 0.2 mV/decade. The BioFET specificity was assessed by control experiments with proteins that may unspecifically bind at the EG surface, while 100pM p53wt concentration was established as limit of detection. This work paves the way for fast and highly sensitive tools for p53wt detection in physiological fluids, which deserve much interest in early cancer diagnosis and prognosis.
Investigation of Kenaf Paper in the Presence of PVA for Transformers Application

This paper presents an investigation on the physio-mechanical properties and AC breakdown voltage of the Kenaf paper in the presence of Polyvinyl Alcohol (PVA) for transformers application. Kenaf bast fibers were used in order to produce the paper through the soda pulping process. The pulps were subjected to beating up to 12,000 revolutions, whereby the PVA was added to the pulps at a different weight percentage concentration up to 12%. Morphological study was carried out on the Kenaf paper based on Scanning Electron Microscopy (SEM). The apparent density, Tensile Index (TI), Burst Index (BI), Tear Index (TeI), and AC breakdown voltage of the Kenaf paper were measured. It is found that the TI and BI of Kenaf paper can be slightly improved through the introduction of PVA. On other hand, the TeI of the Kenaf paper decreases with the increment of the PVA. The AC breakdown voltage of the Kenaf paper slightly increases with the increment of PVA weight percentage concentration.
Exploring the psychometric properties of the Working Alliance Inventory in general practice: a cross-sectional study

Background The therapeutic alliance is a framework from psychology that describes three components: goals, tasks, and bond. The Working Alliance Inventory adapted for general practice (WAI-GP) measures the strength of the therapeutic alliance between the patient and the clinician, and it could be useful in both research and clinical settings. Aim To determine if the patient score on WAI-GP can delineate the three components (goals, tasks, and bond), and to test concurrent validity with the Consultation and Relational Empathy (CARE) measure and the Patient Perception of Patient-Centredness (PPPC) measure. Design & setting A cross-sectional study took place in 12 general practice waiting rooms in Australia. Method The research instruments included the 12-item WAI-GP (the patient version), the CARE and PPPC measures, plus a survey of demographics and reason for consultation. To perform a principal components factor analysis of the WAI-GP, this dataset was combined with an existing dataset. The Spearman rank correlation was used to determine concurrent validity between the WAI-GP and the CARE and PPPC measures. Results Participants (97–99%) reported a strong positive alliance after the consultation (average WAI-GP mean 4.27 ± 0.67 out of 5, n = 146). Factor analysis could not separate the three components (one factor, eigenvalue >1; Cronbach’s α = 0.957; n = 281). Concurrent validity was supported by moderate correlations with the other measures (PPPC ρ = –0.51, P<0.005, CARE ρ = 0.56, P<0.005). Conclusion Three components could not be identified, but the WAI-GP has a high internal consistency and concurrent validity with moderate correlations with the CARE and PPPC. A more diverse sample may better distinguish the three components leading to more specific feedback to clinicians on their consultation practices.
H-RACS: a handy tool to rank anti-cancer synergistic drugs

Though promising, identifying synergistic combinations from a large pool of candidate drugs remains challenging for cancer treatment. Due to unclear mechanism and limited confirmed cases, only a few computational algorithms are able to predict drug synergy. Yet they normally require the drug-cell treatment results as an essential input, thus exclude the possibility to pre-screen those unexplored drugs without cell treatment profiling. Based on the largest dataset of 33,574 combinational scenarios, we proposed a handy webserver, H-RACS, to overcome the above problems. Being loaded with chemical structures and target information, H-RACS can recommend potential synergistic pairs between candidate drugs on 928 cell lines of 24 prevalent cancer types. A high model performance was achieved with AUC of 0.89 on independent combinational scenarios. On the second independent validation of DREAM dataset, H-RACS obtained precision of 67% among its top 5% ranking list. When being tested on new combinations and new cell lines, H-RACS showed strong extendibility with AUC of 0.84 and 0.81 respectively. As the first online server freely accessible at http://www.badd-cao.net/h-racs, H-RACS may promote the pre-screening of synergistic combinations for new chemical drugs on unexplored cancers.