Miracle-dz/UniFAR-FTUs huggingface dataset:
Marketing Capabilities and Firm Performance of Food and Beverages Firms, Southwest, Nigeria

his study investigated marketing capabilities and firm performance of T Food and Beverages Firms, Southwest, Nigeria. Hence this study examined the effect of marketing capabilities and firm performance of food and beverage firms in Southwest, Nigeria of Food and Beverages Firms, Southwest, Nigeria. This study adopted a cross-sectional study, the population of three leading selected FMCG companies i.e., Nestle Nigeria Plc, Unilever Nigeria Plc and are 642 staff. A sample size of 413 staff was Coca-Cola computed using Taro Yamane formula. The study adopted random sampling technique to select employee in the selected FMCG's firms in Lagos and Ogun States, Nigeria. A validated questionnaire was used to collect data. Findings revealed that marketing capabilities have significant effects on firm performance 2 of food and beverage firms in Southwest, Nigeria (Adj. R = 0.000, F(3,357)= 11.486, p= 0.897). The study recommended that marketing capabilities have a significant but weak effect on firm performance of food and beverages firms in southwest, Nigeria. Management of food and beverages firms should pay special attention to marketing capabilities antecedents to increase firm performance in food and beverages firms in southwest, Nigeria.
Inuence of Activity-Based Entrepreneurship Education on Students' Entrepreneurial Intention to Startup Business After Graduation from Federal College of Education (Tech.), Omoku-Rivers State

his study examined the inuence of activity-based entrepreneurship T education on students' entrepreneurial intention to start up business. Three research questions and hypotheses were posed. A four-point basis response questionnaire whose PPMC r-value was 0.90 was used to receive response from about 62 year-III business education undergraduates. The data collected were analysed using descriptive statistics of mean and cluster. A signicant relationship exists between the extent of business education students' exposure to activity-based entrepreneurship education learning activities and their attitude towards starting self-business and their capacity to start. Hence, business educators who implement entrepreneurship education curriculum require activity-based training.
Impact of Government Expenditure on Agricultural Output in Nigeria (1981-2019)

T he agricultural sector's impact on GDP, food and nutritional supplies, job creation, income and wealth creation, and foreign exchange revenues cannot be overstated. Despite the agricultural sector's enormous contribution to Nigeria's economic growth, it has received less a�ention since the discovery of oil. As a result, this study investigates how government spending on agriculture has aﬀected agricultural output in Nigeria from 1981 to 2019. �e data used for this study was obtained from the Central Bank Statistical Bulletin. Using the Autoregressive Distributed Lag approach, the results revealed the presence of a long-run link between government agricultural expenditure and agricultural output in Nigeria. Government agricultural capital spending has a negative and statistically insigni�cant in�uence on agricultural output in Nigeria in both the short and long run. �e �ndings demonstrate that government recurrent investment in agriculture had a favorable but statistically insigni�cant impact on agricultural output in Nigeria in the short and long run. Agricultural loan guarantee scheme funds had a negative and statistically negligible long-run in�uence on agricultural output while having a positive short-run impact. To that end, the government should strengthen monitoring institutions to guarantee that funds provided to the agricultural sector are utilized wisely and eﬀectively in Nigeria. �e government should promote the consumption of locally grown farm products to limit the number of resources spent on imported agricultural items, which erode consumers' purchasing power owing to imported in�ation.
MIT Open Access Articles UAV Cooperative Control with Stochastic Risk Models

—Risk and reward are fundamental concepts in the cooperative control of unmanned systems. This paper focuses on a constructive relationship between a cooperative planner and a learner in order to mitigate the learning risk while boosting the asymptotic performance and safety of the behavior. Our framework is an instance of the intelligent cooperative control architecture (iCCA) with a learner initially following a “safe” policy generated by the cooperative planner. The learner incrementally improves this baseline policy through interaction, while avoiding behaviors believed to be “risky”. Natural actor-critic and Sarsa algorithms are used as the learning methods in the iCCA framework, while the consensus-based bundle algorithm (CBBA) is implemented as the baseline cooperative planning algorithm. This paper extends previous work toward the coupling of learning and cooperative control strategies in real-time stochastic domains in two ways: (1) the risk analysis module supports stochastic risk models, and (2) learning schemes that do not store the policy as a separate entity are integrated with the cooperative planner extending the applicability of iCCA framework. The performance of the resulting approaches are demonstrated through simulation of limited fuel UAVs in a stochastic task assignment problem. Results show an 8% reduction in risk, while improving the performance up to 30% and maintaining a computational load well within the requirements of real-time implementation.
Behavior of Pile Subject to Excavation-Induced Soil Movement

This paper presents the results of centrifuge model tests on unstrutted deep excavation in dense sand and its influence on an adjacent single pile foundation behind the retaining wall. It is found that, in the case of a stable wall, the induced pile bending moment and deflection decrease exponentially with increasing distance between the pile and the wall. Pile head boundary condition plays an important role in affecting the pile responses due to an adjacent excavation. In the case of retaining wall collapse, the failure pattern of the soil behind the wall features a slip plane projecting from near the wall toe to the ground surface. Soil within the failure zone demonstrates large lateral movement and induces significant bending moment and deflection on pile located within the zone. Soil movement and pile responses outside this zone are noted to be significantly less. A comparison between the experimental results and the theoretical predictions by an existing numerical method shows good agreement, provided that appropriate assumptions are made on the soil parameters and conditions, especially in the case of retaining wall collapse.
The �iR gene contributes to the virulence of S. marcescens in a Drosophila intestinal infection model

Serratia marcescens is an opportunistic bacterium that infects a wide range of hosts including humans. It is a potent pathogen in a septic injury model of Drosophila melanogaster as five bacteria directly injected in the body cavity of the fly kill the host within a day. In contrast, flies do not succumb to ingested bacteria for days even though some bacteria traverse the intestinal barrier into the hemolymph within a couple of hours. The mechanisms by which S. marcescens attacks enterocytes and damages the intestinal epithelium remain uncharacterized. To better understand intestinal infections, we performed a genetic screen for loss of virulence of ingested S. marcescens in which we identified FliR, a structural component of the flagellum, as a virulence factor. Next, we compared the virulence of two flagellum mutants fliR and flhD using two Serratia strains. Both genes are required for S. marcescens to escape the gut lumen into the hemocoel indicating that the flagellum plays an important role for the passage of bacteria through the intestinal barrier. In contrast, fliR but not flhD is needed to severely damage the intestinal epithelium and ultimately kill the host. Our results therefore suggest a flagellum-independent role for fliR in bacterial virulence.
Splice Expression Variation Analysis (SEVA) for Differential Gene Isoform Usage in Cancer

Alternative splicing events (ASE) cause expression of a variable repertoire of potential protein products that are critical to carcinogenesis. Current methods to detect ASEs in tumor samples compare mean expression of gene isoforms relative to that of normal samples. However, these comparisons may not account for heterogeneous gene isoform usage in tumors. Therefore, we introduce Splice Expression Variability Analysis (SEVA) to detect differential splice variation, which accounts for tumor heterogeneity. This algorithm compares the degree of variability of junction expression profiles within a population of normal samples relative to that in tumor samples using a rank-based multivariate statistic that models the biological structure of ASEs. Simulated data show that SEVA is more robust to tumor heterogeneity and its candidates are more independent of differential expression than EBSeq and DiffSplice. SEVA analysis of head and neck tumors identified differential gene isoform usage robust in cross-study validation. Moreover, SEVA finds approximately hundreds of splice variant candidates, manageable for experimental validation in contrast to the thousands of candidates found with EBSeq or DiffSplice. Based on performance in both simulated
Comparative Pharmacokinetics and Bioequivalence of Two 50 mg Atenolol Tablet Formulations in Healthy Korean Male Volunteers

The objective of this study was to compare the pharmacokinetics and bioequivalence of 50 mg atenolol test drug manufactured by Hana Pharmaceuticals (Seoul, Korea; Hana Atenolol ® ) with 50 mg atenolol reference drug manufactured by Hyundai Pharmaceuticals (Seoul, Korea; Tenor-min ® ) in 24 healthy Korean male volunteers
Effectiveness of herb-partitioned moxibustion combined with electroacupuncture on polycystic ovary syndrome in patients with symptom pattern of kidney deficiency and phlegm-dampne.

OBJECTIVE To observe the effect of herb-partitioned moxibustion combined with electroacupuncture on polycystic ovary syndrome (PCOS) in patients with symptom pattern of kidney deficiency and phlegm-dampness. METHODS Totally 62 PCOS patients who met the inclusion criteria were randomly divided into intervention group and control group. In the intervention group, acupoints were subjected to (43 ± 1) ℃ herb-partitioned moxibustion and electroacupuncture treatment. In the control group, acupoints were subjected to (37 ± 1) ℃ herb-partitioned moxibustion and sham electroacupuncture treatment. Treatment was provided 3 times per week for 12 weeks, and the treatment was stopped during menstruation. After the treatment, the clinical efficacy, the Traditional Chinese Medicine (TCM) symptom pattern score, basal body temperature (BBT) levels, menstrual cycle, and related sex hormone levels of the two groups were evaluated. RESULTS Sixty patients were eventually included in the study (30 in the intervention group and 30 in the control group). There were not obvious between-group differences in the baseline efficacy parameters (all P > 0.05). (a) After treatment, the two groups have improved in terms of clinical efficacy, TCM symptom pattern score, menstrual cycle and, BBT (P < 0.01, < 0.05), and the intervention group was better than the control group (P < 0.01, < 0.05). (b) In the intervention group, the estradiol (E2) and P450 aromatase (P450arom) levels were increased (all P < 0.05), the testosterone (T) level was decreased (P < 0.05), and the luteotropic hormone (LH) and anti-Müllerian hormone (AMH) levels were significantly decreased (P < 0.01). In the control group, E2 level was increased (P < 0.05), and LH level was decreased (P < 0.05). After treatment, the T, LH, and AMH levels of the intervention group were decreased compared with those of the control group (all P < 0.05), and the P450arom level was increased (P < 0.05). CONCLUSIONS Herb-partitioned moxibustion combined with electroacupuncture can effectively improve the related clinical symptoms of PCOS patients with kidney deficiency and phlegm-dampness. Herb-partitioned moxibustion combined with electroacupuncture may inhibit the overexpression of AMH to increase the expression level of P450arom in ovarian granulosa cells, thereby reconstructing the dependence of follicular development on FSH, and finally improving abnormal follicular development and hyperandrogenism in PCOS patients with kidney deficiency and phlegmdampness. TRIAL REGISTRATION NUMBER ChiCTR1900024182.
Hippocampal Resting-State Functional Connectivity Forecasts Hippocampal Resting-State Functional Connectivity Forecasts Individual Posttraumatic Stress Disorder Symptoms: A Data-Individual Posttraumatic Stress Disorder Symptoms: A Data-Driven Approach Driven Approach

knowledge that employs a multivariate, machine-learning analytic approach to the question of hippocampal-rsFC and PTSD prediction. Results provide further rationale for not restricting the study of the biological underpinnings of PTSD to limbic structures. Given the multitudinous role of the hippocampus in both memory formation and fear regulation, in addition to the constellation of PTSD symptoms spanning domains of memory alterations and altered arousal, results support the conclusion that hippocampal distributed connectivity across the brain may be consequential for understanding PTSD prognosis in trauma survivors.
The Relationship between Collective Self-Esteem and Volunteer Engagement: The Mediating Role of Basic Psychological Need Satisfaction

: The present study aimed to investigate the contribution of collective self-esteem (CSE) on volunteer engagement and the mediating role of basic psychological need satisfaction among volunteers. Offline survey with self-reported questionnaires was completed by 799 college students who had been involved in voluntary service. Results showed that volunteers’ CSE were positively correlated with volunteer engagement. Furthermore, satisfaction of basic psychological needs mediated the relationship between CSE and volunteer engagement and the indirect effect accounted for 24.3% of the total effect. Findings suggested that the promotion of volunteers’ CSE could satisfy their basic psychological need, which in turn motivated college students to be more engaged in volunteer activities.
Multifrequency News and Stock Returns ∗

Aggregate stock prices are driven by shocks with persistence levels ranging from daily intervals to several decades. To accommodate this, we introduce a parsimonious equilibrium with regime-shifts of heterogeneous durations in dividend news, and estimate specifications with up to 256 states on daily U.S. equity returns. The multifrequency equilibrium has significantly higher likelihood than the classic Campbell and Hentschel (1992) specification, while generating volatility feedback effects 10 to 40 times larger. Furthermore, Bayesian learning about volatility generates a novel tradeoff between skewness and kurtosis as information quality varies, which complements the traditional uncertainty channel (e.g., Veronesi, 1999). Economies with intermediate investor information best match the return data. ∗Calvet: Department of Finance and Economics, HEC School of Management, 78351 Jouy-en-Josas Cedex, France, and NBER, calvet@hec.fr. Fisher: Sauder School of Business, University of British Columbia, 2053 Main Mall, Vancouver, BC Canada V6T 1Z2, adlai.fisher@sauder.ubc. ca. We received helpful comments from Andrew Abel, Michael Brandt, John Campbell, John Geanakoplos, Bruno Solnik, Robert Stambaugh, Amir Yaron, Jessica Wachter, and seminar participants at CREST, Paris I Panthéon-Sorbonne, the Swedish Central Bank, the Wharton School, the UBC Summer Finance Conference, and the 2005 World Congress of the Econometric Society. We are very appreciative of financial support provided for this project by the Agence Nationale de la Recherche, the HEC Foundation, the UBC Bureau of Asset Management, and the Social Sciences and Humanities Research Council of Canada. Multifrequency News and Stock Returns
Conjunction Agreement and the Coordinate Structure Constraint

A long-standing question in syntax is what role linear order plays in a hierarchical grammar. Phenomena that on the surface show sensitivity to linear order have been particularly illuminating. When agreeing with coordinated subjects with different gender features, participles in Bosnian-Croatian-Serbian (BCS), Slovenian, and other languages allow multiple options including agreeing with the linearly closest conjunct. This pattern motivated an analysis where linear order can play a role in a syntactic operation such as agreement (Marušič et al. 2015; Willer-Gold et al. 2016 among others). On the other hand, Murphy & Puškar (2018) show that the pattern can be accounted for without resorting to linear order. This paper provides novel evidence from Coordinate Structure Constraint violating movement in BCS to argue for the non-linear approach. If the argument is on the right track, agreement can be kept within syntax without resorting to PF conditions.
Interpretable machine learning prediction of all-cause mortality

Explainable artificial intelligence provides an opportunity to improve prediction accuracy over standard linear models using "black box" machine learning (ML) models while still revealing insights into a complex outcome such as all-cause mortality. We propose the IMPACT (Interpretable Machine learning Prediction of All-Cause morTality) framework that implements and explains complex, non-linear ML models in epidemiological research, by combining a tree ensemble mortality prediction model and an explainability method. We use 133 variables from NHANES 1999-2014 datasets (number of samples: n = 47,261) to predict all-cause mortality. To explain our model, we extract local (i.e., per-sample) explanations to verify well-studied mortality risk factors and make new discoveries. We present major factors for predicting x-year mortality (x = 1,3,5) across different age groups and their individualized impact on mortality prediction. Moreover, we highlight interactions between risk factors associated with mortality prediction, which leads to findings that linear models do not reveal. We demonstrate that compared with traditional linear models, tree-based models have unique strengths such as: (1) improving prediction power, (2)making no distribution assumptions, (3) capturing non-linear relationships and important thresholds, (4)identifying feature interactions, and (5) detecting different non-linear relationships between models. Given the popularity of complex ML models in prognostic research, combining these models with explainability methods has implications for further applications of ML in medical fields. To our knowledge, this is the first study that combines complex ML models and state-of-the-art feature attributions to explain mortality prediction, which enables us to achieve higher prediction accuracy and gain new insights into the effect of risk factors on mortality.
Relationship of oceanic whitecap coverage to wind speed and wind history

Sea surface images obtained during the 2006 Marine Aerosol Production (MAP) campaign in the North East Atlantic were analysed for values of percentage whitecap coverage (W). Values of W are presented for wind speeds up to circa 23 m s−1. The W data were divided into two overlapping groups and a piecewise, wind‐speed‐only parameterization of W is proposed that is valid for wind speeds between 3.70 m s−1 and 23.09 m s−1. Segregation of data points based upon a 2.5 hour wind history acted to decrease data scatter at wind speeds above approximately 9.25 m s−1. At these wind speeds W values were greater for decreasing wind speeds than for increasing wind speeds. No clear wind history effect was observed at wind speeds below 9.25 m s−1.
REAL TIME PEST DETECTION USING YOLOv5

Depending on the increasing population and nutritional needs, we should develop new methods and systems in agricultural production that take environmental issues into account and ensure efficiency and sustainability. Inappropriate pest control methods can result in 70% of yield loss. The caterpillar is a pest that can be invasive and can damage yield by eating the leaves, shoots, fruit and flower parts of plants and trees. Pesticide spraying is the most preferred pest control method due to its speed of action and scalability. However, due to the increasing environmental and health awareness, less pesticide use is required. One of the important methods of reducing pesticide usage is to spray only the places where they are needed. In order to perform spot spraying, first of all, the location of the pest must be determined. It is possible to detect pests using computer vision methods. In the study, we developed an object detection system to detect the thistle caterpillar ( Vanessa cardui ), which is encountered in Turkey and can cause damage to sunflower cultivation, in real time via video using the YOLOv5 object detection architecture. For this purpose, we used 2416 images taken under different lighting and background conditions. We trained the object detection system in two different ways using transfer learning and learning from scratch methods and compared the results. Results indicate that the system is functional and being able to correctly detect the thistle caterpillar at 65 FPS.
Pollen Dispersal Across the Southern Alps, South Island, New Zealand

The aim of this research was to improve the understanding of modem pollen deposition in central South Island in order to interpret Quaternary pollen profiles. This was accomplished by examining the results from a chain of pollen traps ( exposed for one year), moss polsters collected along a transect from Westland across the Southern Alps to Canterbury (with and without addition of exotic spores to facilitate 'absolute' counting) and three short peat monoliths. The role of topography, vegetation type and weather patterns were also briefly assessed. The results were analysed by means of principal components and cluster analyses to identify the respective contribution of different pollen taxa. The conclusions are: 1. Trap and polster results are broadly comparable. 2. With exceptions, caused by local effects such as fire and contributions by adjacent vegetation and taxa introduced since 1850, the monolith profiles show little change over the period studied. 3. Forest sites in Westland were dominated by pollen of local podocarps (Dacrydium cupressinum, Prumnopitys) and broadleaved angiosperm species (Metrosideros, Quintinia, Weinmannia). Nothofagus fusca type pollen dominates within the beech forest areas, but drops to about 10% a short distance from the forest edge. Poaceae pollen shows low frequencies in forested sites, but dominates in grass/scrubland areas. 4. Sites above the treeline on the Main Divide shows proportionately high counts of exogenous Podocarpaceae pollen. However, the high counts involve no 'real' increase in regional deposition. i LIST OF TABLES Table List 2.1 3.1 3.2 3.3 3.4 3.5 3.6 3.7 4.1 4.2 4.3 4.4 Location of the 43 surface samples. Location of the pollen traps. The number of undamaged traps collected. Seasonal pollen accumulation rates. Yearly pollen accumulation rates. Total annual accumulation rates. Pollen percentage from seasonal accumulation rates. Pollen percentage from annual accumulation rate. The 14 surface samples to which two Lycopodium tablets were added. Pollen source area and deposition components. Local/ extralocal and regional percentage values Two samples using different numbers of marker Lycopodium. ii 4 30 35 36 38 41 42 43 54 70 74 n
Cftr Modulates Wnt/  -Catenin Signaling and Stem Cell Proliferation in Murine Intestine

This study documents the functional activity of Cftr in the active intestinal stem cell population of murine intestine. In the absence of Cftr, stem cell proliferation and Wnt/  - catenin signaling are increased, which is associated with changes in intracellular pH-dependent plasma membrane localization of the Wnt-transducer Disheveled. Increased stem cell proliferation may contribute to gastrointestinal cancer risk in cystic fibrosis.