Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of bio-agents and botanical extracts against early blight (Alternaria solani) of Tomato (Solanum lycopersicum L.)

To evaluate the efficacy of bio-agents, viz., Trichoderma viride 2% plant extracts, viz, neem leaf extract, Dathura leaf extract Garlic bulb extract, Aloe vera leaf extract and Tulsi leaf extract, fungicide, viz., carbendazim 50 WP against A. solani in-vivo by growth parameters and disease intensity. The field experiment was laid out in a complete randomized block design with seven treatments and three replication. All the treatments significantly inhibited the disease intensity of A. solani as compared to control Experiments were also carried out in randomized block design with seven treatments and three replications. Neem leaf extract 20% was found to be the most effective treatment and recorded minimum disease intensity (27.72%) followed by Trichoderma viride, Dhatura leaf extract, garlic bulb extract, Aloe vera leaf extract and tulsi leaf extract as compare to treated check carbendazim 50 WP and untreated control. recorded at 45, 60 and 75 DAT respectively).
Dome-Shaped Proximal Tibial Osteotomy For Infantile Genu Varum: Assessment Of Outcomes

Background: The most common deformity of the knee in children is infantile genovarum. We aimed to evaluate the outcome of children with genu varum after proximal tibial dome shaped osteotomy. Patients and methods: a prospective case study was conducted on 12 patients with Persistent physiological infantile genu varum and underwent Dome-Shaped Proximal Tibial Osteotomy. During follow up period, the angle formed by the femoral condyle and the tibial shaft determined by a line drawn parallel to the inferior surface of the femoral condyle intersecting the anatomical axis of the tibia (femoral condyle-tibial shaft angle), normally about 90°, used for assessment of correction in plain X ray to the knee and tibia to avoid need for full length radiograph. All cases were evaluated pre and post-operatively according to Modified Hospital for Special Surgery Knee Scoring System Results: 10 (83.3%) knees had full correction of deformity while 1 knee (8.3%) had under correction and 1 knee (8.3%) showed over-correction of deformity. The mean pre-operative HSSKS scores were 70.16±11.3 while the mean post-operative HSSKS scores were 91.4±2.1. The subjects HSSKS results were improved from pre to post-operatively with a statistically significant difference between them. Conclusion: Dome-Shaped Proximal Tibial Osteotomy is associated with good outcome and the reasonable stability arising from the anteroposterior orientation of the osteotomy and greater surface area for early union, and early weight bearing and active knee exercise indicate a good safety profile and it should be recommended to correct Infantile Genu Varum
Linear-time and post-quantum zero-knowledge SNARKs for R1CS

This paper studies zero-knowledge SNARKs for NP, where the prover incurs O ( N ) ﬁnite ﬁeld operations to prove the satisﬁability of an N -sized R1CS instance. We observe that recent work of Bootle, Chiesa, and Groth (BCG, TCC 20) provides a polynomial commitment scheme that, when combined with the linear-time interactive proof system of Spartan (CRYPTO 20), yields linear-time IOPs and SNARKs for R1CS. Speciﬁcally, for security parameter λ , and for an N -sized R1CS instance over a ﬁeld of size exp( λ ) and ﬁxed (cid:15) > 0, the prover incurs O ( N ) ﬁnite ﬁeld operations to produce a proof of size O λ ( N (cid:15) ) that can be veriﬁed in O λ ( N (cid:15) )—after a one-time preprocessing step, which requires O ( N ) ﬁnite ﬁeld operations. This reestablishes the main result of BCG. Arguably, our approach is conceptually simpler and more direct. Additionally, the polynomial commitment scheme that we distill from BCG is of independent interest; it improves over the prior state of the art by oﬀering the ﬁrst scheme where the time to commit to an N -sized polynomial is O ( N ) ﬁnite ﬁeld operations. We further observe that one can render the aforementioned SNARK zero knowledge and reduce the proof size and veriﬁer time to polylogarithmic—while maintaining a linear-time prover—by outsourcing the veriﬁer’s work via one layer of proof composition with an existing zkSNARK as the “outer” proof system. A similar result can be derived from recent work of Bootle, Chiesa, and Liu (ePrint 2020/1527). We implement the aforementioned polynomial commitment scheme with (cid:15) = 1 / 2 and combine it with Spartan’s interactive proof system to obtain a SNARK for R1CS. We refer to this combination as Cerberus . It uses Reed-Solomon codes in the polynomial commitment scheme, and hence the prover is not asymptotically linear-time. Nonetheless, Cerberus features the fastest known prover (the only exception is Spartan when proving large instances over 256-bit ﬁelds), and is plausibly post-quantum secure.
The importance of family and family values in the formation of a healthy lifestyle

The health status of the younger generation is the most important factor in the sustainable development of society and an indicator of the potential of the state. However, today the main indicators of the health of children and adolescents have persistent negative trends for reasons of socio-economic, environmental and spiritual and moral nature. Among the factors that have adversely affected the health of children in recent years, there are: the low standard of living of many families; decline in the general culture of the population; the progressive destruction of the institution of the family and poor health of the parents; environmental pollution; lack of fashion for health in the country; replication by the mass media of forms of behavior that contribute to the destruction of the physical and spiritual health of a person, and much more. The health status of children depends both on internal factors (type of constitution, gender, age, etc.) and on environmental factors (total school load, living in urban or rural conditions, playing sports, etc.).
An Empirical Study on Companies listed in the Egyptian Stock Exchange

The purpose of this study is to examine the role of audit quality proxied by auditor's firm size and auditor's industry specialization in reducing agency costs and cost of equity capital. The study further contributes to prior literature by investigating whether these two roles will differ according to size of the audit client by classifying sampled firms based on their market capitalization. The study utilized regression model analysis using 111 for a sample of non-financial firms listed in the Egyptian Stock Exchange for the period from 2013 to 2016, comprising 444 firm-year observations. Results show a positive and significant relationship between audit quality (auditor's firm size, auditor's industry specialization) and asset utilization ratio as the proxy for agency costs, providing evidence that audit quality can contribute in reducing agency costs. However, results did not show statistical significance for the effect of audit quality proxied by auditor's firm size on cost of equity capital. In contrast, results show statistical significance for the effect of audit quality proxied by auditor's industry specialization on the cost of equity capital. Finally, the study provided that the role of audit quality is more pronounced in smaller clients than in larger clients.
CORPORATE GOVERNANCE MECHANISMS AND FINANCIAL REPORTING QUALITY OF LISTED COMMERCIAL BANKS IN NIGERIA

This study examined corporate governance mechanisms and financial reporting quality of listed commercial banks in Nigeria. The population of the study consists of all listed commercial banks on the stock exchange as at 31 December 2018. A sample of nine (9) listed commercial banks were selected and data were collected over the period 2008 to 2018. Descriptive statistics and panel Least Square regression were used for the data analysis. The findings reveal that board size and audit committee were negative and exerted significant impact on financial reporting quality of listed commercial banks while board independence is significant and exerts a positive influence on financial reporting quality of listed commercial banks in Nigeria. Female directorship does not have a significant relationship with financial reporting quality of listed commercial banks in Nigeria. The study therefore recommends that steps should be taken by regulators to stipulate stiffer penalty on firms engaging in earnings smoothing capable of undermining corporate governance ethics and framework for banks in Nigeria as this will serve as deterrent to others and further entrench sanity.
(Folic Acid Enrichment of Fermented Banana Juice with Lactic Acid Bacteria)

Folic acid (Vitamin B9) involved in numerous metabolisms. Folate deficiency is responsible for some negative health problems. The fermentation of foodstuffs to produce rich content of folic acid beverages using lactic acid bacteria (LAB) is an effort to overcome the health issues. This study aimed to determine the effect of banana juice fermentation using LAB on the folic acid content of the banana juice. Banana juice was fermented for 48 hours at 37C with monoculture of Lactobacillus plantarum and mixed LAB cultures of Lactobacillus acidophilus, Lactobacillus casei, Lactobacillus plantarum, Bifidobacterium bifidum and Bifidobacterium breve. The changes of folic acid characteristics were observed every 8 hours during 0 – 48 hours of fermentation, as well as the change in pH, total acid, soluble protein, and reducing sugar. The identification of folic acid monomers was conducted at the most optimal condition of the fermentation by using LC-MS. The result showed fermentation affect the folic acid content, pH, total acid, reducing sugar and soluble protein of banana juice. During fermentation, pH of the sample decreased with the increasing of total acid. Reducing sugar and soluble protein content tended to fluctuate. Optimal condition for folic acid enhancement was obtained by 32 hours of fermentation with mixed LAB, in which it yielded folic acid 34.07 μg/mL, pH . ,00, total acid 0.51%, reducing sugar 119.17 mg/L, dissolved protein 0.43 mg/mL. Folic acid identification on the optimal condition revealed that it was dominated by compound with a molecular weight of 441.49 Dalton.
EnablesMonitoring of Intratumoral CD8 T-cell Infiltrates in Tumor-Bearing Humanized Mice after T-cell Bispecific Antibody Treatment

The PET-Tracer Zr-Df-IAB22M2C EnablesMonitoring of Intratumoral CD8 T-cell Infiltrates in Tumor-Bearing Humanized Mice after T-cell Bispecific Antibody Treatment A C Christoph M. Griessinger, Tove Olafsen, Alessandro Mascioni, Ziyue Karen Jiang, Charles Zamilpa, Fang Jia, Michael Torgov, Jason M. Romero, Filippo Marchioni, Daulet Satpayev, Chenyu Lee, Green Zhang, Tapan K. Nayak, Mudita Pincha, Maria Amann, Preethi L.B. Mohan, Marine Richard, Valeria G. Nicolini, Johannes Sam, Christina Claus, Claudia Ferrara, Peter Br€ unker, Marina Bacac, Pablo Umana, Dominik R€ uttinger, Ian A. Wilson, Jean Gudas, Christian Klein, and Jean J.L. Tessier
The Adoption of Mobile Health Applications by Patients in Developing Countries: A Systematic Review

Mobile health (m-health) apps adoption in developing countries is a new research area in the healthcare industry. M-health is comparatively recent in information systems, with little attention being paid to it developing countries in the previous years. Applications of the m-health strategies in developing nations are considered one of the best platforms for guaranteeing the citizenry's safety and healthcare security. A systematic review was conducted of m-health apps adoption by patients in developing countries to evaluate the current results. It reviews 22 papers that were published on the topic of m-health adoption in developing countries in academic journals and conferences over the last decade. It identifies the research in terms of research methodologies, theories and models adopted, significant factors identified, limitations and recommendations. Findings show there is a limited contribution to m-health apps adoption in developing countries. Most studies employed TAM and focused on the technological and individual levels; very low intention has been made to health-related factors, levels, and theories. The review presents a broad overview of previous academic studies with a view to future research. Keywords—M-health; mobile health; apps; adoption; review; developing countries
Precision exercise medicine: predicting unfavourable status and development in the 20-m shuttle run test performance in adolescence with machine learning

Objectives To assess the ability to predict individual unfavourable future status and development in the 20m shuttle run test (20MSRT) during adolescence with machine learning (random forest (RF) classifier). Methods Data from a 2-year observational study (2013‒2015, 12.4±1.3 years, n=633, 50% girls), with 48 baseline characteristics (questionnaires (demographics, physical, psychological, social and lifestyle factors), objective measurements (anthropometrics, fitness characteristics, physical activity, body composition and academic scores)) were used to predict: (Task 1) unfavourable future 20MSRT status (identification of individuals in the lowest 20MSRT tertile after 2 years), and (Task 2) unfavourable 20MSRT development (identification of individuals with 20MSRT development in the lowest tertile among adolescents with baseline 20MSRT below median level). Results Prediction performance for future 20MSRT status (Task 1) was (area under the receiver operating characteristic curve, AUC) 83% and 76%, sensitivity 80% and 60%, and specificity 78% and 79% in girls and boys, respectively. Twenty variables showed predictive power in boys, 14 in girls, including fitness characteristics, physical activity, academic scores, adiposity, life enjoyment, parental support, social status in school and perceived fitness. Prediction performance for future development (Task 2) was lower and differed statistically from random level only in girls (AUC 68% and 40% in girls and boys). Conclusion RF classifier predicted future unfavourable status in 20MSRT and identified potential individuals for interventions based on a holistic profile (14‒20 baseline characteristics). The MATLAB script and functions employing the RF classifier of this study are available for future precision exercise medicine research.
DEVELOPING MARKET SENTIMENT INDICATORS FOR COMMODITY PRICE FORECASTING USING MACHINE LEARNING

The objective of this study is to develop a market sentiment model for financial markets using machine learning, and to illustrate these methods using commodity price data. A market sentiment model may capture the fundamental and crowd psychology of the market, through a variable that uses positive and negative words and phrases. The commodity price used is the daily price of the spot crude oil exchange-traded fund (ETF), United States Oil Fund (USO). The forecasting power of the market sentiment model is compared with a traditional autoregressive model. The results showed that the autoregressive models did not have significant forecasting power for the oil data over the time period examined and the addition of the sentiment model did not improve the forecasting power. Machine learning is a relatively new forecasting method. Therefore, further research on this topic is needed before any firm conclusions can be drawn regarding the effectiveness of this approach.
Significance of risk factor analysis and dissection for station 4L lymphatic metastasis in left lung cancer: a systematic review and meta-analysis

Background The effect of 4L lymph node dissection on the prognosis of left lung cancer is currently controversial. Therefore, a meta-analysis was conducted to compare the difference in prognosis between the dissection group and the non-dissection group, and assess the independent risk factors for 4L lymphatic metastasis. Methods A systematic literature retrieval from PubMed, Embase and CNKI was conducted to identify relevant studies up to October, 5, 2020. The data concerning the overall survival (OS) rate, disease-free survival (DFS) rate, and risk factors for 4L lymphatic metastasis were extracted and analyzed. Results L10 lymphatic metastasis was an independent risk factor for positive L4 lymph node result (Z=4.89, P<0.05). The probability of positive L4 with positive L10 was 5.11 times of that with negative L10. L5 lymphatic metastasis was an independent risk factor for positive L4 lymph node result (Z=3.92, P<0.05). The probability of positive L4 with positive L5 was 3.92 times of that with negative L5. L7 lymphatic metastasis was not an independent risk factor for positive L4 lymph node result. Positive L4 lymph node decreased the survival rate of relevant patients while L4 lymph node dissection increased the survival rate of relevant patients (Z=2.81, P<0.05 or Z=4.18, P<0.05). Positive L4 lymph node reduced the DFS time of relevant patients while L4 lymph node dissection prolonged the DFS time of relevant patients (P<0.05, Z=2.72). Conclusions If the intraoperative pathological examination indicates positive station 10L lymph node, station 4L lymph node will be dissected, which may be a good choice at present. Positive L4 lymph node may reduce the survival time and DFS time of relevant patients while dissection of positive station 4L lymph node may prolong the survival time and DFS time of relevant patients. The intraoperative rapid frozen section pathological examination of station 10L lymph node may be a good choice.
Effect of clinical mastitis on lactation curves of Murrah buffaloes

India accounts 18.5% of the world milk production and ranked first in milk production. Buffaloes (Bubalus bubalis) produce 54% of total milk production of India. However, mastitis remains the most expensive production disease of the buffaloes. The present study was based on the lactation records of Murrah buffaloes maintained at Cattle and Buffalo Breeding Farm of LPM Section, ICAR-Indian veterinary research institute, Izatnagar over a period of 10 years (2005–2014). The aim of present study was to find best fitted lactation model explaining the lactation behaviour of Murrah buffaloes in healthy and mastitis condition. The data consisted of 80068 daily test day milk yield records of 296 Murrah buffaloes. Different standard lactation curve models such as Ali and Schaeffer (1987), Cobby and Le Du (1978), Sikka (1950), Mitscherlich × Exponential (Rook et al. 1993), Mixed log (Guo and Swalve 1995), Wilmink (1987) and Wood (1967) models were fitted by Proc NLIN Procedure of SAS 9.3. The goodness of fit was judged by the high value of R2 adj and low value of MSPE, AIC and BIC. Durbin-Watson test was used to test autocorrelation and Shapiro-Wilk’s test and Kolmogorov Smirnov test was used to test the normality of the residuals. Based on the analysis of the data Ali and Schaeffer model was the best fitted model to explain the lactation behaviour of the healthy as well as mastitic Murrah buffaloes.
THE REFLECTION ON THE NECESSITY OF LEARNING THEORIES IN TEACHING

The article discusses the necessity of learning theories in teaching. It refers to three learning theories such as constructivism, behaviorism and cognitivism. It describes the role of learning theories in teaching. The article gives a comprehensive and clear idea of necessity of using learning theories. This article will be useful for teachers who are in constant search of effective methods of teaching that motivate students, reveal their potential, independent thinking and other skills.
Benjamin Kane's Area Paper

The development of “intelligent” dialogue assistants and conversational agents, capable of being transferred from one domain to another with minimal engineering necessary, has been consistently high on the priority queue of AI research. Nonetheless, progress towards this achievement has been slow and incremental, with the problem remaining one of the many unsolved puzzles of the field. One crucial subproblem that must first be addressed is the development of an underlying dialogue manager capable of seamlessly coordinating several interacting elements: the interpretations of utterances that the system hears, the system’s own desires and beliefs, and other external events that happen in the world. Furthermore, the system must perform this coordination in a way that is robust to unexpected events and that is not inherently tied to any particular task much like human dialogue participants are capable of. This paper surveys various theoretical tools that have been proposed to model the way that humans and systems can interpret and produce dialogue from plans to schemas as well as a selection of notable dialogue manager implementations that in some way contribute to the goal of developing a fully general dialogue system. Furthermore, it introduces preliminary steps towards the creation of a novel dialogue manager that relies on dialogue schemas (symbolic representations of prototypical sequences of events in a dialogue), and deep understanding using a type-coherent, expressive logical form resembling surface English.
Anomaly Detection with Spiking Neural Networks

In recent years, there has been a revolution in Machine Learning (ML) techniques that can be attributed to the large increase in computational power, mainly harnessing the efficiency for matrix multiplication and convolution granted by Graphical Processing Units (GPUs). The most widespread of these techniques was the Artificial Neural Network (ANN), whose architectural principles were inspired by information processing and distributed communication in biological systems. Even though ANNs were created to mimic brain-like calculations, facilitating communication between artificial neurons and performing calculations inside these neurons, neuroscientists were quick to point out that biological systems perform completely differently from those proposed by any current type of ANN. As such, Artificial Intelligence (AI) has not reached the truly limitless potential that was once promised. Neuromorphic hardware and Spiking Neural Networks (SNNs) [1], which behave like the human brain, aim to fix this problem, bridging the gap between artificial and biological intelligence. The inherent strengths of these SNNs would be extremely useful at the Large Hadron Collider (LHC) with their need for fast inference and accurate data-processing of petabytes of time-series events.