Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth and Some Physiological Activities of Pepper (Capsicum annuum L.) in Response to Cadmium Stress and Mycorrhizal Symbiosis

A greenhouse experiment was conducted to investigate the effects of mycorrhial fungus (Glomus mosseae ) on cadmium (Cd) toxicity in pepper ( Capsicum annuum L. cv. Zhongjiao 105) plants. Half of plants were inoculated with arbuscular mycorrhizal fungi (AMF). Cd was supplied in the form of cadmium chloride at 0.0, 0.1 and 0.5 mM through irrigation water in the soil. Mycorrhizal colonization was higher in the control than in cadmium - treated soil. Dry weights of root and shoot of mycorrhizal (M) plants were higher than non mycorrhizal (NM) ones in both control and cadmium treatments. Measurements of Cd concentration indicated that M plants immobilized more Cd in the root and partitioned less Cd to the shoots. Cd decreased the leaf chlorophyll content, total sugar and total protein contents, and the concentrations of phosphorous and magnesium. M plants had greater contents of chlorophyll, total sugar, total protein and P and Mg concentrations than NM plants. Moreover, increasing the Cd concentration caused an increase in malondialdehyde (MDA) content in leaves of pepper plants; however, M plants showed a lower MDA content than NM plants. Cd decreased the activity of superoxide dismutase (SOD) in leaves of NM and M plants, on the other hand, it increased the activity of peroxidase (POD) and ascorbate peroxidase (APX) in leaves of NM and M plants. APX was stimulated more than POD in M plants versus NM plants, suggesting that APX is a major player in H 2O2-scavenging in M plants. The study suggests that mycorrhization with G. mosseae can be a suitable way to induce Cd-stress resistance in pepper plants.
The Accumulation of Phenolic Compounds in Genetically Selected Amaranthus hybridus is Influenced by Endophytic Natural Growth Regulator

Amaranth ( Amaranthus spp . L.) ( Amaranthaceae ), an endemic plant in Central and South America, grows worldwide, being cultivated in many temperate and tropical countries. Although several species of amaranth are frequently considered weeds, the plant is recognized as a food, constructive medicine, a source of protein and minerals livestock feed. The plant is widely cultivated, promoted, and increasingly consumed as a leafy vegetable and traditional medicine in Africa. Despite progressive genetic improvement and modern plant growing technologies, unfavorable climatic and ecological factors reduce the yield, and quality of the active plant botanicals. The role of bio-transformed endophytic microbial plant growth regulator formulation (BESF) on yield and accumulation of phenolic compounds in amaranth leaves is poorly understood. The current study assessed the effects of pre-sowing seed treatments with 0.0 %, 0.2 % and 0.4 % concentrations of BESF solution on germination, leaf yield, flavor and phenolic content in genetically selected Amaranthus hybridus var . cruentus . Data collected were subjected to analysis of variance (ANOVA). Significant treatment means were separated using Tukey test at p < 0.05. BESF significantly increased fresh marketable leaf yield by over 360 kg/ha (29 %) compared to the control. The total flavonoid content in the leaves was raised by 34 % and 47 % with 0.2 % and 0.4 % BESF solution treatments respectively, compared to control. Maximum concentration levels of rutin, apigenin, apigetrin, and quercetin was obtained with 0.4% BESF solution treatment. An analysis of the collected data suggest that BESF was effective in overall improvement in leaf yield, chemical content, and flavor of A. hybridus var . cruentus, allowing us to recommend BESF application to raise A. hybridus var . cruentus leaves for nutrition and pharmacological applications.
Protein profiling and physico-chemical characterization of an isolated phage against Brucella abortus strain 19

Bacteriophages have varied practical applications, so we did a basic study of the characteristics of an isolated phage against Brucella abortus for proper understanding of its general properties. Bacteriophage against B. abortus strain 19 was isolated from the sewage samples. Structural protein profiling of the isolated brucellaphage by SDS-PAGE revealed 4 bands of molecular weight: 65.98, 60.46, 48.56 and 43.97 kDa. The brucellaphage was susceptible to heat at and above 60°C temperature. Exposure to sunlight gradually decreased the phage concentration within 3 h. Ultraviolent light (UV) completely inactivated phage within 3 min of exposure. The brucellaphage was susceptible to pH 2, 4 and 10, whereas pH 6 and 8 did not affect the phage activity. The phage was sensitive to SDS, phenol, chloroform, iodine, benzalkonium and formalin, whereas it was insensitive to EDTA treatment. Lysozyme completely inactivated the phage within one hour, while only 0.51% phage survival was observed in the presence of trypsin within 3 h, whereas RNase treatment did not affect the phage titre. The phage isolated was Brucella specific and did not lyse any of the heterologous bacterial species tested. The phage lysed B. abortus vaccine strains S19 and S99; Brucella melitensis andB. abortus field isolates. Key words: Brucellaphage, Brucella abortus strain 19, physicochemical characterization.
A practical system approach for fully autonomous multi-dimensional structural health monitoring

We present an SHM system integrating both the impedance and the Lamb wave propagation method on a single board, while sharing the same DSP (Digital Signal Processing) processor and the piezoelectric patches. Three functional blocks, such as signal excitation/generation, signal sensing, and data processing, were implemented to incorporate the Lamb wave method into our existing impedance-based SHM system. Both pitch-and-catch and pulse-and-echo schemes were implemented for damage detection and location, respectively. Through synergetic integration of the two methods, our SHM system can detect various types of simulated damages on aluminum plates.
Financing Long-term Care: Lessons From Japan

Long-term care (LTC) must be carefully delineated when expenditures are compared across countries because how LTC services are defined and delivered differ in each country. LTC’s objectives are to compensate for functional decline and mitigate the care burden of the family. Governments have tended to focus on the poor but Germany opted to make LTC universally available in 1995/1996. The applicant’s level of dependence is assessed by the medical team of the social insurance plan. Japan basically followed this model but, unlike Germany where those eligible may opt for cash benefits, they are limited to services. Benefits are set more generously in Japan because, prior to its implementation in 2000, health insurance had covered long-stays in hospitals and there had been major expansions of social services. These service levels had to be maintained and be made universally available for all those meeting the eligibility criteria. As a result, efforts to contain costs after the implementation of the LTC Insurance have had only marginal effects. This indicates it would be more efficient and equitable to introduce public LTC Insurance at an early stage before benefits have expanded as a result of ad hoc policy decisions.
Chapter 7 External validity of a prediction model for residual mass histology in testicular germ cell cancer : an evaluation for good prognosis patients

We assessed the external validity of a prediction model for nonseminomatous testicular germ cell cancer patients. The model was developed to predict the probability of retroperitoneal metastases being benign (only necrosis/fibrosis) after chemotherapy treatment. Patients with a high probability of benign tissue may be offered observation as opposed to patients with a low probability, which indicates a substantial risk of residual tumour. These patients should undergo retroperitoneal lymph node dissection (RPLND). We compared the observed histology with the predicted probability in 105 patients with good prognosis germ cell cancer who underwent RPLND between 1995 and 1998. We found that predicted probabilities higher than 5% were in good agreement with the observed frequencies of benign tissue. The concordance (c)-statistic was 0.76, suggesting that the model could reasonably discriminate between benign tissue and tumour. However, nearly all predicted probabilities (n=101) were lower than 70%, which might be considered as the lowest value at which observation offers a reasonable alternative to RPLND. Further, 35% of patients currently under observation (84/241) had predicted probabilities lower than 70%. In conclusion, the clinical relevance of the prediction model was limited for the patients who underwent RPLND; use of the model would change the policy from RPLND to observation in only a few. On the other hand, the model might support selection of patients for RPLND, who currently are under observation. Introduction Computer tomography (CT) often shows small remnants of retroperitoneal masses after chemotherapy for metastatic nonseminomatous testicular germ cell cancer. The histology of the residual masses may be benign (entirely necrotic/fibrotic), or may contain tumour elements (mature teratoma or viable cancer cells). Resection of a totally benign mass has no therapeutic value and should preferably not be performed. Most resection policies consider only one prognostic factor to predict the histology of residual masses, i.e. mass size after chemotherapy. Masses smaller than or equal to 10 mm are generally not resected, although more aggressive approaches have been proposed.
A framework for the practical science necessary to restore sustainable, resilient, and biodiverse ecosystems

Demand for restoration of resilient, self‐sustaining, and biodiverse natural ecosystems as a conservation measure is increasing globally; however, restoration efforts frequently fail to meet standards appropriate for this objective. Achieving these standards requires management underpinned by input from diverse scientific disciplines including ecology, biotechnology, engineering, soil science, ecophysiology, and genetics. Despite increasing restoration research activity, a gap between the immediate needs of restoration practitioners and the outputs of restoration science often limits the effectiveness of restoration programs. Regrettably, studies often fail to identify the practical issues most critical for restoration success. We propose that part of this oversight may result from the absence of a considered statement of the necessary practical restoration science questions. Here we develop a comprehensive framework of the research required to bridge this gap and guide effective restoration. We structure questions in five themes: (1) setting targets and planning for success, (2) sourcing biological material, (3) optimizing establishment, (4) facilitating growth and survival, and (5) restoring resilience, sustainability, and landscape integration. This framework will assist restoration practitioners and scientists to identify knowledge gaps and develop strategic research focused on applied outcomes. The breadth of questions highlights the importance of cross‐discipline collaboration among restoration scientists, and while the program is broad, successful restoration projects have typically invested in many or most of these themes. Achieving restoration ecology's goal of averting biodiversity losses is a vast challenge: investment in appropriate science is urgently needed for ecological restoration to fulfill its potential and meet demand as a conservation tool.
Analysis of Power and Threat Manifestation in the Discourse of Traffic Police Officers: A CDA Perspective

The present study was an attempt to capture the relationship between the role of social status and discourse in relation to choice of words and tone of the speakers. The way people put the words together and express it can sometimes be the source of coercion, threat and somehow extorting the others. In this article, the discourse of traffic police officers and drivers was precisely scrutinized in order to analyze the discriminatory or oppressive linguistic usage observable in exchanges among given social actors. In so doing, the study’s focal point was on instances of illegitimate conversation exchanges between drivers plying highways and the traffic police officers who were controlling the drivers’ speeding and traffic violations. A critical discourse analysis of such conversations, recorded through interview with the fined drivers, unveiled that illegitimate dealings are committed, and that whenever the monetary demand of officers is resisted, there are undesirable consequences for the drivers. In addition, the traffic police officers displayed their power in the language they used and, consequently, they were bribed on the sly by the drivers.
MIMO-Based Forward-Looking SAR Imaging Algorithm and Simulation

Multiple-input multiple-output (MIMO) radar imaging can provide higher resolution and better sensitivity and thus can be applied to targets detection, recognition, and tracking. Missile-borne forward-looking SAR (MFL-SAR) is a new and special MIMO radar mode. It has advantage of two-dimensional (2D) imaging capability in forward direction over monostatic missile-borne SAR and airborne SAR. However, it is difficult to obtain accurate 2D frequency spectrum of the target echo signal due to the high velocity and descending height of this platform, which brings a lot of obstacles to imaging algorithm design. Therefore, a new imaging algorithm for MFL-SAR configuration based on the method of series reversion is proposed in this paper. This imaging method can implement range compression, secondary range compression (SRC), and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm.
Data-Driven Discovery of Immune Contexture Biomarkers

Background: Features characterizing the immune contexture (IC) in the tumor microenvironment can be prognostic and predictive biomarkers. Identifying novel biomarkers can be challenging due to complex interactions between immune and tumor cells and the abundance of possible features. Methods: We describe an approach for the data-driven identification of IC biomarkers. For this purpose, we provide mathematical definitions of different feature classes, based on cell densities, cell-to-cell distances, and spatial heterogeneity thereof. Candidate biomarkers are ranked according to their potential for the predictive stratification of patients. Results: We evaluated the approach on a dataset of colorectal cancer patients with variable amounts of microsatellite instability. The most promising features that can be explored as biomarkers were based on cell-to-cell distances and spatial heterogeneity. Both the tumor and non-tumor compartments yielded features that were potentially predictive for therapy response and point in direction of further exploration. Conclusion: The data-driven approach simplifies the identification of promising IC biomarker candidates. Researchers can take guidance from the described approach to accelerate their biomarker research.
Investigation of Feature Extraction for Unsupervised Learning in Human Activity Detection

The ability to understand what humans are doing is crucial for any intelligent system to autonomously support human daily activities. Technologies to enable such ability, however, are still undeveloped due to the many challenges in human activity analysis. Among them are the difficulties in extracting human poses and motions from raw sensor data, either recorded from visual sensor or wearable sensor and the need to recognize activities not seen before using unsupervised learning. Furthermore, human activity analysis usually requires expensive sensors or sensing environment. With the availability of low-cost RGBD (RGB-depth) sensor, the new form of data can provide human posture data with high degree of confidence. In this paper, we present our approach to extract features directly from such data (joint positions) based on human range of movement and the results of tests performed to check their effectiveness to distinguish sixteen (16) example activities are reported. Simple unsupervised learning, K-means clustering was used to evaluate the effectiveness of the features. The results indicate that the features based on range of movement significantly improved clustering performance.
Nigeria's Potential Growth and Output Gap: Application of Different Econometrics Filters

The concept of potential output and the corresponding output gap had received considerable attention by both policy makers and academic researchers, particularly in the developed countries. This is a reflection of not only its theoretical significance, but also its policy relevance. Output gap is used to model price and wage inflation, in estimating fiscal balance and the impact of structural reforms on the economy, hence an important indicator of fiscal policy trust. Most importantly, to a central banker it is critical in modelling monetary policy decision making process, as it serves as an input into central banks economic projections which forms an integral part of monetary policy decision and the setting of monetary policy rates. This paper measures the potential output and the corresponding output gap for Nigeria using Hodrick-Prescott filter, Baxter-King filter and both fixed and full length Christiano-Fitzgerald filters. The methods yielded different results, but with strong similarities in their evolution over time. According to all the methods, on the average, the economy was over heated during the early part of the sample period (2004:Q1 to 2005:Q4) but operated below capacity between 2008:Q1 and 2009:Q4. Interestingly, a fairly strong and stable relationship exists between inflation and the estimated output gaps. With this noticeable connection, using output gap to compliment expert judgement, in monetary policy decision making, would conceptually be a good decision. Keywords: Potential growth, output gap, econometric filtering, Nigeria
NUMERICAL APPROXIMATION OF DENSITY DEPENDENT DIFFUSION IN AGE-STRUCTURED POPULATION DYNAMICS

We study a numerical method for the diusion of an age-structured population in a spatial environment. We extend the method proposed in [2] for linear diusion problem, to the nonlinear case, where the diusion coecients depend on the total population. We integrate separately the age and time variables by nite dierences and we discretize the space variable by nite elements. We provide stability and convergence results and we illustrate our approach with some numerical result.
A damage mechanics model for power-law creep and earthquake aftershock and foreshock sequences

SUMMARY It is common practice to refer to three independent stages of creep under static loading conditions in the laboratory: namely transient, steady-state, and accelerating. Here we suggest a simple damage mechanics model for the apparently trimodal behaviour of the strain and event rate dependence, by invoking two local mechanisms of positive and negative feedback applied to constitutive rules for time-dependent subcritical crack growth. In both phases, the individual constitutive rule for measured strain e takes the form e(t)=e 0 [1+t/mt]m, where t is the ratio of initial crack length to rupture velocity. For a local hardening mechanism (negative feedback), we find that transient creep dominates, with 0<m<1. Crack growth in this stage is stable and decelerating. For a local softening mechanism (positive feedback), m<0, and crack growth is unstable and accelerating. In this case a quasi-static instability criterion eA2 can be defined at a finite failure time, resulting in the localization of damage and the formation of a throughgoing fracture. In the hybrid model, transient creep dominates in the early stages of damage and accelerating creep in the latter stages. At intermediate times the linear superposition of the two mechanisms spontaneously produces an apparent steady-state phase of relatively constant strain rate, with a power-law rheology, as observed in laboratory creep test data. The predicted acoustic emission event rates in the transient and accelerating phases are identical to the modified Omori laws for aftershocks and foreshocks, respectively, and provide a physical meaning for the empirical constants measured. At intermediate times, the event rate tends to a relatively constant background rate. The requirement for a finite event rate at the time of the main shock can be satisfied by modifying the instability criterion to having a finite crack velocity at the dynamic failure time, dx/dtA V R , where V R is the dynamic rupture velocity. The same hybrid model can be modified to account for dynamic loading (constant stress rate) boundary conditions, and predicts the observed loading rate dependence of the breaking strength. The resulting scaling exponents imply systematically more non-linear behaviour for dynamic loading.
Learning to See Clear: Quantification and Multidimensional Assessment of Value Stream Mapping Alternatives Considering Variability

The prior quantification and validation of future state maps in lean production and optimization projects mostly is not taken into consideration in the traditional value stream mapping approaches. Furthermore the implementation of future states is based upon the trial and error principle. The effects of proactively changing production systems often are unknown and could underlie vast variations due to the planned outcome. So for many managers hard facts are missing and the uncertainties included in such a value stream optimization project are very high. This prevents a necessary system change accompanied by the adoption of lean methods. Thus in this paper a comprehensive value stream optimization approach is presented which primarily focuses upon chances for prior static and dynamic future state map quantification. Under consideration of parameter variability a downstream multidimensional assessment of possible design alternatives is proposed using a fuzzy decision making method to facilitate transparency in the selection of the most adequate future state map. The method described in this paper will be discussed at an industrial case study.
An Iterative Approach to Reduce the Variance of Stochastic Dynamic Systems ?

In this paper, we study the variance optimization problem in Markov decision processes (MDP). The objective is to find the optimal policy which has the minimal average variance of the system rewards. As the variance function is quadratic and the variance of rewards are correlated mutually, the associated variance minimization problem is not a linear program. The traditional approaches of classical MDP theory, which are good at solving linear problems, are inapplicable to this problem. In this paper, we define a fundamental quantity called variance potential and derive a variance difference equation which quantifies the difference of variances of Markov systems under any two policies. Based on the variance difference equation, we propose an iterative algorithm, which is similar to the policy iteration in classical MDP theory, to reduce the reward variance of Markov systems. Although this algorithm converges to a local optimum, it is very efficient compared with the traditional gradient-based algorithms. Numerical experiments demonstrate the main idea of this paper.