Miracle-dz/UniFAR-FTUs huggingface dataset:
Antiviral Activity of Biosynthesized Silver Nanoparticles from Pomegranate (Punica granatum L.) Peel Extract against Tobacco Mosaic Virus

Tobacco mosaic virus (TMV) is a major pathogen affecting tomato plants worldwide. The efficacy of silver nanoparticles (Ag-NPs) mediated by Punica granatum biowaste peel extract in mitigating the negative impact of TMV infection on tomato growth and oxidative stress was investigated through scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-Visible (UV-Vis) spectrophotometer, X-ray Diffraction (XRD), dynamic light scattering (DLS), zeta potential, energy-dispersive X-ray spectroscopy (EDX), and Fourier-transform infrared spectra (FTIR). Results of SEM analysis of green Ag-NPs revealed the presence of condensed spherical or round NPs with diameters ranging between 61 and 97 nm. TEM confirmed the SEM results and showed round-shaped Ag-NPs with an average size of 33.37 ± 12.7 nm. The elemental analysis (EDX) of prepared Ag-NPs revealed the presence of elemental Ag as a major peak (64.43%) at 3–3.5 KeV. The FTIR revealed several functional groups on the prepared Ag-NPs, for which three treatment strategies for Ag-NP applications were evaluated in the greenhouse study and compared to inoculated TMV and control plants: pre-infection treatment (TB), post-infection treatment (TA), and dual treatment (TD). The results showed that the TD strategy is the most effective in improving tomato growth and reducing viral replication, whereas all Ag-NP treatments (TB, TA, and TD) were found to significantly increase expression of the pathogenesis-related (PR) genes PR-1 and PR-2, as well as polyphenolic compounds, HQT, and C4H genes compared to control plants. In contrast, the flavonoid content of tomato plants was not affected by the viral infection, while the phenolic content was significantly reduced in the TMV group. Furthermore, TMV infection led to a significant increase in oxidative stress markers MDA and H2O2, as well as a reduction in the enzymatic activity of the antioxidants PPO, SOD, and POX. Our results clearly showed that the application of Ag-NPs on TMV-infected plants reduces virus accumulation, delays viral replication in all treatments, and greatly enhances the expression of the CHS gene involved in flavonoid biosynthesis. Overall, these findings suggest that treatment with Ag-NPs may be an effective strategy to mitigate the negative impact of TMV infection on tomato plants.
Criticisms on Amnesty for People with Mental Disabilities in Indonesia: Transformative Effort from Substitutive to Supportive Decision Making

The community of persons with disabilities currently disputes the regulation on amnesty. Amnesty is considered discriminatory and violates the rights of persons with disabilities, especially those with mental disabilities. The amplification rule, which means that persons with disabilities do not have legal capacity, is considered inconsistent with the Convention on the Rights of Persons With Disabilities (CRPD), which substantively stipulates that persons with disabilities do have the legal capacity and that the government is obliged to take measures to provide access to the necessary support that is needed, known as the supportive decision-making system. Keywords: Persons with Disabilities, Amnesty, Supportive Decision Making
Subset and sample selection for graphical models: gaussian processes, ising models and gaussian mixture models

Probabilistic Graphical Models are a popular method of representing complex joint distributions in which stochastic dependence between subsets of random variables is expressed in terms of a graph. In many scenarios, random samples from a graphical model are only partially observed—either only a few random variables may be observed for any sample, or the values of some variables (called hidden variables) are missing from each sample unless explicitly queried. This dissertation considers the following general problem: how to select a small subset of variables to observe for a given sample (called subset selection) or a small subset of samples for which to observe the hidden variables (called sample selection) so as to accurately predict the value of the unobserved variables? We investigate this question for 3 widely-studied classes of graphical models: Gaussian Processes, Ising Models, and Gaussian Mixture Models. We prove that finding an optimal subset selection strategy is NP-hard even for a restricted class of Gaussian Processes, called Gaussian Free Fields (GFF). We give a dynamic programming algorithm for Gaussian Processes on bounded tree-width graphs, which yields a fully polynomial time approximation scheme for the case of GFFs on such graphs. For general Gaussian Processes on bounded tree-width graphs, our algorithm's running time depends polynomially on the condition number of the covariance matrix. We also give a greedy constant-factor approximation algorithm for GFFs on arbitrary graphs. We consider both adaptive and non-adaptive subset selection for Ising Models. For the simple 1-dimensional ferromagnetic Ising Model, we demonstrate that adaptive strategies outperform non-adaptive strategies, and give a simple adaptive strategy whose error is at most a constant times that of the optimal adaptive strategy for the same observation budget. We prove that it is NP-hard to compute an optimal non-adaptive strategy for ferromagnetic Ising Models on general graphs. For mixture models, we define a “maximum-a-posteriori" oracle and discuss how it differs from other oracle models. Then we demonstrate the advantage provided by this oracle by giving an algorithm which estimates the parameters of a mixture of high-dimensional spherical Gaussians under a weaker separation condition and more efficiently than known unsupervised algorithms.
Methodological Challenges in Group-based Randomised Controlled Trials for Intimate Partner Violence Perpetrators: A Meta-summary

ABSTRACT Evidence for treatment effects of group-based Intimate Partner Violence (IPV) perpetrators programmes remains, at best, inconclusive. In the present review, systematic/meta-analytic reviews were used to identify randomised controlled trials and a meta-summary approach was employed to identify methodological challenges in the design and conduct of these trials. Of the fifteen studies identified, seven were comparative effectiveness trials. A range of methodological challenges were also identified by the trialists; source of outcome data, treatment modality, attrition and sample characteristics were the most frequently mentioned. Although there are only a few randomised controlled trials compared to non randomised studies, the findings of both highlight the need to invest in the development of innovative and/or combined IPV treatment programmes to address co-occurring issues such as substance use and trauma. The summary of methodological challenges will provide the first step in the development of methods guidance for researchers working in this area.
Cell Shape and Forces in Elastic and Structured Environments: From Single Cells to Organoids

With the advent of mechanobiology, cell shape and forces have emerged as essential elements of cell behavior and fate, in addition to biochemical factors such as growth factors. Cell shape and forces are intrinsically linked to the physical properties of the environment. Extracellular sti ﬀ ness guides migration of single cells and collectives as well as di ﬀ erentiation and developmental processes. In conﬁned environments, cell division patterns are altered, cell death or extrusion might be initiated, and other modes of cell migration become possible. Tools from materials science such as adhesive micropatterning of soft elastic substrates or direct laser writing of 3 D sca ﬀ olds have been established to control and quantify cell shape and forces in structured environments. Herein, a review is given on recent experimental and modeling advances in this ﬁeld, which currently moves from single cells to cell collectives and tissue. A very exciting avenue is the combination of organoids with structured environments, because this will allow one to achieve organotypic function in a controlled setting well suited for long-term and high-throughput culture.
Numerical Solution to Troesch's Problem Using Hybrid Heuristic Computing

In this paper an evolutionary computational technique, which is stochastic in nature, is applied for the first time to the numerical solution of the Troesch’s problem. An approximate mathematical model employing the linear combinations of log sigmoid basis functions is deduced. A fitness function (FF), containing unknown adjustable parameters and representing the trial solution along with the initial conditions, is developed. The Genetic algorithm (GA) as global optimizer is hybridized with local optimizers, such as Pattern Search (PS) and Interior Point algorithm (IPA), for achieving the unknown adjustable parameters. Comparisons of the numerical results obtained for three special cases of the Troesch’s problem are made with some important deterministic classical approximation methods, as well as, the exact solutions. The numerical results are found to be in sharp agreement with the exact solutions.
QTL Mapping and Transcriptome Analysis Reveal Candidate Genes Regulating Seed Color in Brassica napus

Yellow seeds are desirable in rapeseed breeding because of their higher oil content and better nutritional quality than black seeds. However, the underlying genes and formation mechanism of yellow seeds remain unclear. Here, a novel yellow-seeded rapeseed line (Huangaizao, HAZ) was crossed with a black-seeded rapeseed line (Zhongshuang11, ZS11) to construct a mapping population of 196 F2 individuals, based on which, a high-density genetic linkage map was constructed. This map, comprising 4174 bin markers, was 1618.33 cM in length and had an average distance of 0.39 cM between its adjacent markers. To assess the seed color of the F2 population, three methods (imaging, spectrophotometry, and visual scoring) were used and a common major quantitative trait locus (QTL) on chromosome A09, explaining 10.91–21.83% of the phenotypic variance, was detected. Another minor QTL, accounting for 6.19–6.69% of the phenotypic variance, was detected on chromosome C03, only by means of imaging and spectrophotometry. Furthermore, a dynamic analysis of the differential expressions between the parental lines showed that flavonoid biosynthesis-related genes were down-regulated in the yellow seed coats at 25 and 35 days after flowering. A coexpression network between the differentially expressed genes identified 17 candidate genes for the QTL intervals, including a flavonoid structure gene, novel4557 (BnaC03.TT4), and two transcription factor genes, namely, BnaA09G0616800ZS (BnaA09.NFYA8) and BnaC03G0060200ZS (BnaC03.NAC083), that may regulate flavonoid biosynthesis. Our study lays a foundation for further identifying the genes responsible for and understanding the regulatory mechanism of yellow seed formation in Brassica napus.
Effects of Nelumbo nucifera Gaertn. Petal Tea Extract on Hepatotoxicity and Oxidative Stress Induced by Mancozeb in Rat Model

Mancozeb (Mz) is one of the most widely used pesticides that has been reported to cause adverse human health risks. White Nelumbo nucifera (N. nucifera) petals have therapeutic properties to prevent toxicity. Hence, this study attempted to determine the effects of N. nucifera extract on hepatotoxicity and oxidative stress in mancozeb-treated rats. Seventy-two male rats were divided into nine groups and designed with a control; N. nucifera extract was administered at the doses of 0.55, 1.1, and 2.2 mg/kg bw/day, Mz was administered at 500 mg/kg bw/day, and the co-treatment groups (N. nucifera and Mz) were administered 0.55, 1.1, and 2.2 mg/kg bw/day of N. nucifera followed by administering Mz 500 mg/kg bw/day daily for 30 days. The results showed that all doses of N. nucifera extract did not induce hepatic toxicity and could suppress the toxicity of mancozeb by increasing body weight gain and decreasing relative liver weight, lobular inflammation, and total injury score. The combination treatment also decreased the molecular markers of oxidative stress (2-hydroxybutyric acid, 4-hydroxynonenal, l-tyrosine, pentosidine, and N6-carboxymethyllysine). Furthermore, the reduced glutathione and oxidized glutathione contents were adjusted close to the normal level. Therefore, N. nucifera extract is a natural antioxidant supplement that could decrease the toxicity of mancozeb and can be safely consumed.
Segmentation of tree seedling point clouds into elementary units

ABSTRACT This article describes a new semi-automatic method to cluster terrestrial laser scanning (TLS) data into meaningful sets of points to extract plant components. The approach is designed for small plants with distinguishable branches and leaves, such as tree seedlings. It first creates a graph by connecting each point to its most relevant neighbours, then embeds the graph into a spectral space, and finally segments the embedding into clusters of points. The process can then be iterated on each cluster separately. The main idea underlying the approach is that the spectral embedding of the graph aligns the points along the shape’s principal directions. A quantitative evaluation of the segmentation accuracy, as well as of leaf area (LA) estimates, is provided on a poplar seedling mock-up. It shows that the segmentation is robust with false-positive and false-negative rates of around 1%. Qualitative results on four contrasting plant species with three different scan resolution levels each are also shown.
Real‐time vibration monitoring and analysis of agricultural tractor drivers using an IoT‐based system

Agricultural tractor drivers experience a high amplitude of vibration, especially during soil tillage operations. In the past, most research studied vibration exposure with more focus on the vertical (z) axis than on the fore‐and‐aft (x) and lateral (y) axes. This study examines how rotary soil tillage affects the vibration acceleration and frequency, and the power spectral densities (PSDs) at the seat pan and head along three translational axes in a real‐field multiaxis vibration context. Moreover, this study aimed to identify the characteristics of the seat‐to‐head transmissibility (STHT) response to identifying the most salient resonant frequencies along the x‐, y‐, and z‐axes. Nine (9) male tractor drivers operated the tractor with a mounted rotary tiller throughout the soil tillage process. In the event of a COVID‐19 pandemic, and to respect social distancing, this study developed an Internet of Things (IoT) module with the potential to integrate with existing data loggers for online data transmission and to make the experimentation process more effective by removing potential sources of experimenter errors. The raw acceleration data retrieved at the seat pan and the head were utilized to obtain daily exposure (A(8)), PSDs, and STHT along the x‐, y‐, and z‐axes. The vibration energy was found to be dominant along the z‐axis than the x‐ and y‐axes. A(8) response among tractor drivers exceeds the exposure action value explicitly stated by Directive 2002/44/EU. PSDs along the x‐, y‐, and z‐axes depicted the low‐frequency vibration induced by rotary soil tillage operation. The STHT response exhibited a higher degree of transmissibility along the y‐ and z‐axes when compared with that along the x‐axis. The frequency range of 4–7 Hz may plausibly be associated with cognitive impairment in tractor drivers during rotary soil tillage.
Correlation Between Opioid Drug Prescription and Opioid-Related Mortality in Spain as a Surveillance Tool: Ecological Study

Background Opioid drug prescription (ODP) and opioid-related mortality (ORM) have increased in Spain. However, their relationship is complex, as ORM is registered without considering the type of opioid (legal or illegal). Objective This ecological study aimed to examine the correlation between ODP and ORM in Spain and discuss their usefulness as a surveillance tool. Methods This was an ecological descriptive study using retrospective annual data (2000-2019) from the Spanish general population. Data were collected from people of all ages. Information on ODP was obtained from the Spanish Medicines Agency in daily doses per 1000 inhabitants per day (DHD) for total ODP, total ODP excluding those with better safety protocols (codeine and tramadol), and each opioid drug separately. Rates of ORM (per 1,000,000 inhabitants) were calculated based on deaths registered (International Classification of Diseases, 10th Revision codes) as opioid poisoning by the National Statistics Institute, derived from the drug data recorded by medical examiners in death certificates. Opioid-related deaths were considered to be those that indicated opioid consumption (accidental, infringed, or self-inflicted) as the main cause of death: death due to accidental poisoning (X40-X44), intentional self-inflicted poisoning (X60-X64), drug-induced aggression (X85), and poisoning of undetermined intention (Y10-Y14). A descriptive analysis was carried out, and correlations between the annual rates of ORM and DHD of the prescribed opioid drugs globally, excluding medications of the least potential risk of overdose and lowest treatment tier, were analyzed using Pearson linear correlation coefficient. Their temporal evolution was analyzed using cross-correlations with 24 lags and the cross-correlation function. The analyses were carried out using Stata and StatGraphics Centurion 19. Results The rate of ORM (2000-2019) ranged between 14 and 23 deaths per 1,000,000 inhabitants, with a minimum in 2006 and an increasing trend starting in 2010. The ODP ranged between 1.51 to 19.94 DHD. The rates of ORM were directly correlated with the DHD of total ODP (r=0.597; P=.006), total ODP without codeine and tramadol (r=0.934; P<.001), and every prescribed opioid except buprenorphine (P=.47). In the time analysis, correlations between DHD and ORM were observed in the same year, although not statistically significant (all P≥.05). Conclusions There is a correlation between greater availability of prescribed opioid drugs and an increase in opioid-related deaths. The correlation between ODP and ORM may be a useful tool in monitoring legal opiates and possible disturbances in the illegal market. The role of tramadol (an easily prescribed opioid) is important in this correlation, as is that of fentanyl (the strongest opioid). Measures stronger than recommendations need to be taken to reduce off-label prescribing. This study shows that not only is opioid use directly related to the prescribing of opioid drugs above what is desirable but also an increase in deaths.
Association of Insomnia with 30-Day Postpartum Readmission: A Retrospective Analysis

Insomnia is prevalent in pregnancy and is associated with increased use of health services. We aimed to evaluate the association between insomnia diagnosed at the delivery hospitalization and risk of 30-day postpartum readmission. We conducted a retrospective analysis of inpatient hospitalizations from the 2010–2019 Nationwide Readmissions Database. The primary exposure was a coded diagnosis of insomnia at delivery as determined by ICD-9-CM and ICD-10-CM codes. Obstetric comorbidities and indicators of severe maternal morbidity were also determined through coding. The primary outcome was all-cause 30-day postpartum readmission. Survey-weighted logistic regression was used to generate crude and adjusted odds ratios representing the association between maternal insomnia and postpartum readmission. Of over 34 million delivery hospitalizations, 26,099 (7.6 cases per 10,000) had a coded diagnosis of insomnia. People with insomnia experienced a 3.0% all-cause 30-day postpartum readmission rate, compared to 1.4% among those without insomnia. After controlling for sociodemographic, clinical, and hospital-level factors, insomnia was associated with 1.64 times higher odds of readmission (95% CI 1.47–1.83). After adjustment for obstetric comorbidity burden and severe maternal morbidity, insomnia was independently associated with 1.33 times higher odds of readmission (95% CI 1.18–1.48). Pregnant patients with insomnia have higher rates of postpartum readmission, and diagnosis of insomnia is independently associated with increased odds of readmission. Additional postpartum support may be warranted for pregnancies affected by insomnia.
Chaos predication method based on Lyapunov Exponent and its application in water Quality forecast

Based on the fundamental chaos theory,the phase space reconstruction of raw water time series is discussed.And the related parameters of raw water time series in the new phase space,such as delay time τ,embedding dimension m,correlation dimension D and largest Lyapunov,are obtained by means of autocorrelation coefficient,classical G-P Algorithm and improved maximal Lyapunov exponent method.Moreover at the condition of τ=5,m=9,D=4.4891 and λ1=0.0242,the oxygen demand values of raw water in Tianjin headwater plant from 1995 to 2003 are analyzed and predicted by chaotic prediction approach based on Lyapunov exponent.The example indicates that the variation of raw water quality has chaotic features and it is feasible to use chaos theory to predict short-term variation of the raw water quality.
Exploring PV Waste Management Solutions Using Circular Strategies

Australia’s uptake of solar (photovoltaic) energy represents a positive change towards renewable energy. However, the full impact of such energy needs to be understood. Understanding how photovoltaic (PV) panels are manufactured, used and finally managed at end of useful life in Australia, is required. PV waste represents a loss of valuable materials which can be reintroduced into the manufacturing industry, but also pose an environmental and human health hazard. This research is conducted using qualitative research methods. Interviews with academic, government, PV organizations, installers and retailer groups are compared with other text-based data, such as traditional peer review and grey literature review on overseas best practice examples to identify possible strategies to be adopted in Australia. This study presents solutions from an academic and social perspective. Solutions are sought using the 10 R’s of circularity and is complemented by the ReSOLVE framework; as these provide a comprehensive approach to minimize waste across the PV lifecycle stages. The insights of this study show the adoption of circular economy solutions for PV waste management in Australia can take place if regulations and incentives (including fiscal incentives) are established. These point towards the need for a system where tailored solutions for each stage of the lifecycle of a PV panel are designed and specified through standards, responsibilities, costs and logistics; hence, unlocking end markets for second life PV panels and its recovered materials. Such a system of solutions represents a framework that needs to be supported by government and lead by industry demand.