Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Analyses of Impressions Related to the Customer’s Experience while Attending Restaurants Located in Vlore, Albania

Studies on customer’s experience are important to better understand what is offered and to define what should be improved. The purpose of this study is to measure and observe customer’s satisfaction from the quality of services received from restaurants located in Vlore, Albania. Data is gathered through an online survey which was filled 700 times. Descriptive analysis, Cronbach’s alpha, chi-square test, Cramer’s measure of association, Spearman’s rho correlation coefficient, and generalized linear model are used throughout the analysis. Findings showed that the overall level of customer’s satisfaction was neutral with 37:6  5% followed by satisfied ones with 27:9  5%. There was statistical evidence of a frail relationship at the 1% level of significance between the overall level of satisfaction and gender, employment, monthly income, bill accuracy, fairness of the prices, speed in service, the patience to bring the bill, clear communication, and politeness of the host staff. Further, there was evidence of a negative relationship at the 5% level between the overall level of satisfaction and employment, monthly income and fairness of the price. 66:18% of the variation of the overall level of satisfaction was explained by age, gender, employment, monthly income, patience to bring the bill, bill accuracy, and variety in menu, warm and fresh served foods. The best model predicts 62:25% of the overall satisfaction. These results help restaurant businesses, and whoever wants to invest in this sector, to better understand customer’s satisfaction about service quality and to pinpoint aspects that can be improved.
Production theory under price uncertainty for firms with disappointment aversion

This paper studies the production theory of the competitive firm under price uncertainty by adopting four of the most well-established models of disappointment aversion. Our results show that a disappointment-averse firm will generally produce less than a risk-averse firm. Further, the disappointment-averse firm's optimal output level will surely decrease with an increase in the disappointment coefficients. Moreover, the optimal outputs among the four disappointment-averse models are not the same. As a real case example, we apply our models to determine the optimal building heights for new buildings in Punta del Este, Uruguay. In this example, our disappointment averse models' predictions are very close to the observed heights of these new projects.
BCL2 expression in ductal carcinoma of breast and its association with other clinicopathologic variables

Breast cancer has now become the most common cancer among Indian females exceeding cervical cancer. Age adjusted incidence rate as high as 25.8 per 100,000 women and mortality 12.7 per 100,000 women. Trends of breast cancer now in India are increasing incidence at younger age group, late stage of presentation, aggressive cancers in the young. Bcl 2-a protooncogene identified in 1984. The protein is found mainly in the periphery of mitochondria, on the perinuclear membrane, and in the endoplasmic reticulum. In our study bcl2 expression in different histologic types of breast carcinoma and correlates we read about its expression with other clinico pathologic variables such as tumour size, histological grade, lymph node status, hormone receptor status and Nottingham prognostic index. :In this study 23.3% (7 out of 30) of the cases showed positivity for bcl2 expression of which all cases were strongly positive. Bcl2 expression was found in 45.5% grade I well differentiated ductal carcinoma,14.3% of Grade II Moderately differentiated ductal carcinomas, all cases of mucinous carcinoma of breast(p-<0.025) Bcl2 and ER/PR status found to have a statistically significant direct correlation with p value<0.004. Hence Bcl2 antagonism in these ER+ tumors might increase the effectiveness of these predominately proapoptotic treatment even more than it does from combination with endocrine therapies. Further development of bcl2 inhibitors has been explored and small molecule inhibitors such as ABT-737 AND ABT-199 have been recently introduced. Emerging evidence also suggests the usefulness of this type of theraphy in breast cancer. © 2020 Published by Innovative Publication. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by/4.0/)
Network Weight Estimation for Binary-Valued Observation Models

This paper studies the estimation of network weights for a class of systems with binary-valued observations. In these systems only quantized observations are available for the network estimation. Furthermore, system states are coupled with observations, and the quantization parts are unknown inherent components, which hinder the design of inputs and quantizers. In order to deal with the temporal dependency of observations and achieve the recursive estimation of network weights, a deterministic objective function is constructed based on the likelihood function by extending the dimension of observations and applying ergodic properties of Markov chains. By imposing an independent Gaussian assumption on disturbances, we show that the function is strictly concave and has a unique maximum identical to the true parameter vector, so in this way the estimation problem is transformed to an optimization problem. A recursive algorithm based on stochastic approximation techniques is proposed to solve this problem, and the strong consistency of the algorithm is established. Our recursive algorithm can be applied to online tasks like real-time decision-making and surveillance for networked systems. This work also provides a new scheme for the identification of systems with quantized observations.
Data-driven Neural Architecture Learning For Financial Time-series Forecasting

Forecasting based on financial time-series is a challenging task since most real-world data exhibits nonstationary property and nonlinear dependencies. In addition, different data modalities often embed different nonlinear relationships which are difficult to capture by human-designed models. To tackle the supervised learning task in financial time-series prediction, we propose the application of a recently formulated algorithm that adaptively learns a mapping function, realized by a heterogeneous neural architecture composing of Generalized Operational Perceptron, given a set of labeled data. With a modified objective function, the proposed algorithm can accommodate the frequently observed imbalanced data distribution problem. Experiments on a large-scale Limit Order Book dataset demonstrate that the proposed algorithm outperforms related algorithms, including tensor-based methods which have access to a broader set of input information.
One-Way Substitution Newsboy Problem under Retailer’s Budget Constraint

One-way substitution means that when low-end brand goods are sold out, high-end brand goods can be offered to consumers as substitute goods, but not the opposite. In realistic economic activity, “shortage of funds” is a common practical problem for the retailer in making order decision. This paper proposes a nonlinear optimization model with the retailer’s budget to study the optimal order quantities and substitution discount for two one-way substitution products under a stochastic demand scenario, and the objective is to maximize the retailer’s revenue. We solve the model mainly according to the Karush–Kuhn–Tucker (KKT) theorem and present the conditions of optimal decisions. Finally, through the numerical study, we analyze the influence of the budget constraint and other parameters on the optimal solutions.
Management of perioperative volume therapy – monitoring and pitfalls

Over 300 million surgical procedures are performed every year worldwide. Anesthesiologists play an important role in the perioperative process by assessing the overall risk of surgery and aim to reduce the risk of complications. Perioperative hemodynamic and volume management can help to improve outcomes in perioperative patients. There has been ongoing discussion about goal-directed therapy. However, there is a consensus that fluid overload and severe fluid depletion in the perioperative period are harmful and can lead to adverse outcomes. This article provides an overview of how to evaluate the fluid responsiveness of patients, details which parameters could be used, and what limitations should be noted.
EPIDEMIC INDIVIDUAL-BASED MODELS APPLIED IN RANDOM AND SCALE-FREE NETWORKS

This work proposes a version of the Individual-Based Model (IBM) that converges, on average, to the result of the SIR (Susceptible-Infected-Recovered) model, and studies the eﬀect of this IBM in two types of networks: random and scale-free. A numerical computational case study is considered, using large scale networks implemented by an eﬃcient framework. Statistical tests are performed to show the similarities and diﬀerences between the network models and the deterministic model taken as a baseline. Simulation results verify that diﬀerent network topologies alter the behavior of the epidemic propagation in the following aspects: temporal evolution, basal reproducibility and the number of infected in the ﬁnal.
Multichannel Sparse Blind Deconvolution on the Sphere

Multichannel blind deconvolution is the problem of recovering an unknown signal f and multiple unknown channels xi from convolutional measurements yi = xi ⊛ f (i = 1, 2, …, N). We consider the case where the xi’s are sparse, and convolution with f is invertible. Our nonconvex optimization formulation solves for a filter h on the unit sphere that produces sparse output yi ⊛ h. Under some technical assumptions, we show that all local minima of the objective function correspond to the inverse filter of f up to an inherent sign and shift ambiguity, and all saddle points have strictly negative curvatures. This geometric structure allows successful recovery of f and xi using a simple manifold gradient descent algorithm with random initialization. Our theoretical findings are complemented by numerical experiments, which demonstrate superior performance of the proposed approach over the previous methods.
Humor and the Creative Use of English Expressions in the Speech of University Students: A Case From Jordan

The present study examines the use of English lexical insertions to create humor by Jordanian university students. The data of the study are collected from spontaneous tape-recorded conversations from 62 participants of both males and females, representing different age groups (from 18–23 years old) and belonging to different specializations (e.g., engineering, pharmacy, mathematics, business, and English). The recorded conversations are qualitatively analyzed applying Auer’s sequential approach to code-switching to attain a local interpretation of lexical insertions for humor effect from English into Jordanian Arabic (JA). The findings of the study reveal that Jordanian university students exploit their bilingual repertoire to create humor by playfully and innovatively switching to English. This is shown to take place by unexpected switching points, a switching that flouts Arabic syntactic constraints, a violation of code-switching constraints, incongruity and incompatibility of translating Arabic culture-bound expressions to English, and imposing Arabic word formation templates to English insertions. Specifically, five patterns of code-switching of humor are found, namely, switching around the interrogative, playful affixation, phonological playfulness, haphazard calquing, and the imposition of Arabic morphological rules on English lexical insertions. The study argues that humorous insertions are in fact a marker of solidarity and an in-group membership. Humorous insertions are also shown not to contribute to the content of the message or the pragmatic meaning. Bilingual university students (of Arabic and English) purposefully make use of an additional linguistic resource to mock certain propositions.
On Multi-Armed Bandit Designs for Phase I Clinical Trials

We study the problem of finding the optimal dosage in a phase I clinical trial through the multi-armed bandit lens. We advocate the use of the Thompson Sampling principle, a flexible algorithm that can accommodate different types of monotonicity assumptions on the toxicity and efficacy of the doses. For the simplest version of Thompson Sampling, based on a uniform prior distribution for each dose, we provide finite-time upper bounds on the number of sub-optimal dose selections, which is unprecedented for dose finding algorithms. Through a large simulation study, we then show that Thompson Sampling based on more sophisticated prior distributions outperform state-of-the-art dose identification algorithms in different types of phase I clinical trials.
The Use of Microalgae for Coupling Wastewater Treatment With CO2 Biofixation

Production and emission of CO2 from different sources have caused significant changes in the climate, which is the major concern related to global warming. Among other CO2 removal approaches, microalgae can efficiently remove CO2 through the rapid production of algal biomass. In addition, microalgae have the potential to be used in wastewater treatment. Although, wastewater treatment and CO2 removal by microalgae have been studied separately for a long time, there is no detailed information available on combining both processes. In this review article, microalgae-based CO2 biofixation, various microalgae cultivation systems,¯ and microalgae-derived wastewater treatment are separately discussed, followed by the concept of integration of CO2 biofixation process and wastewater treatment. In each section, details of energy efficiency and differences across microalgae species are also given.
A review of collective robotic construction

Collective robotic construction concerns multirobot systems that modify their environment according to high-level user-specified goals. The increasing need for safe, inexpensive, and sustainable construction, combined with novel technological enablers, has made large-scale construction by robot teams an active research area. Collective robotic construction (CRC) specifically concerns embodied, autonomous, multirobot systems that modify a shared environment according to high-level user-specified goals. CRC tightly integrates architectural design, the construction process, mechanisms, and control to achieve scalability and adaptability. This review gives a comprehensive overview of research trends, open questions, and performance metrics.
Diagnosis-Free Self-Healing Scheme for Open-Circuit Faults in Dual Three-Phase PMSM Drives

Aiming at tolerating common electric faults of multiphase motor drives comprehensively and minimizing the adverse impacts from the remedial scheme itself, a diagnosis-free self-healing scheme is put forward for the open-circuit faults of dual three-phase permanent-magnet synchronous motor (PMSM) drives. First, the self-healing mechanisms of dual three-phase PMSM drives are analyzed in detail. On the basis of theoretical analysis, the repressed self-healing capability of the dual three-phase PMSM drives is fully released by optimizing the current references on harmonic subspace. Since the diagnosis process is not required in the proposed self-healing scheme, the misdiagnosis problem and the prolonged damage caused by the additional time cost of diagnosis can be fundamentally avoided. The proposed self-healing scheme can be generally applied to open-switch faults, single open-phase faults, and multiple open-phase faults in the multiphase motor drives. No change is required for the machine model, modulation strategy, or control framework under different open-circuit faults. Thus, the complex transition strategies among different fault-tolerant control methods for different faults can be avoided, and the adverse impacts from the remedial scheme itself can be minimized. Experimental verification is presented to prove the validity of the proposed self-healing scheme.
A mutation in the semaphorin signalling pathway and its consequences in prostate cancer

Prostate cancer kills over 10,000 men every year in the UK, mainly as a consequence of the spread of the disease to other sites in the body. It is important to understand what controls the spread of prostate cancer cells, as this may lead to treatments that either slow down or prevent metastasis, and perhaps result in the cure of some of the advanced prostate cancers. Semaphorins act as chemotactic cues for axon guidance and cell movement, via their transmembrane receptors, plexins. It has been found that semaphorins and their receptors are overexpressed in some human prostate cancer cell lines. These cell lines have been screened for mutations in genes in the semaphorin signalling pathway. 13 somatic missense mutations in the cytoplasmic domain of the Plexin B1 gene have been identified in clinical samples of primary and metastatic prostate cancers. One of the mutations C5662T was predicted to result in a substitution of a Proline to a Serine. The aim of this research is to determine if the mutation C5662T in the Plexin B1 gene alters cell behaviour and contributes to prostate cancer progression. This thesis describes the method of constructing an expression vector containing the mutation and transfecting the mutation into COS7 cells to produce stable and transient clones. The effect of the mutation on cell collapse was examined. It was possible to show that Plexin B1 is involved in cell collapse and that Rnd1 is required for this process and this effect is independent of its ligand Semaphorin 4D (Sema4D). Although no functional difference between the wild type Plexin B1 and the mutant (C5662T) was observed, the rate of cell collapse may be important and more work will be needed to define whether this is a mutation that alters prostate cancer cell behaviour.
A Mathematical Analysis of Zika Virus Transmission with Optimal Control Strategies

In this paper, we formulate and analyze a system of ordinary differential equations of Zika virus disease by considering standard incidence type interaction for the human to human transmission.Primarily, the Zika virus is transmitted to humans through the bite of infected Aedes mosquitoes. This vector-borne disease can be spread through sexual transmission and blood transfusions also. The proposed model is an SEIR type model for the human population and an SEI type model for mosquito populations. The equilibria of the proposed model are found and the basic reproduction number $R_0$ is computed. The local and global stability of the disease is investigated theoretically in detail. The backward bifurcation is presented for $R_0<1$, which suggests that the disease is possible to eliminate from the population. A sensitivity analysis of the parameters of the basic reproduction number for our model is established. Incorporating three types of time-dependent control parameters in the system to reduce the transmission. Electronic devices, insecticide-treated bed nets, and mosquito repulsive lotions are used to reduce mosquito biting rates. Considering that fact, we find the appropriate optimal control strategies to eliminate the virus from the tropical area. To exhibit the optimal control strategies we used the Pontryagin's Maximum Principle. It was noticed that the optimal control gives better result than without the optimal control model. Numerical simulation is presented to support our mathematical findings.
The Power of Garden-Based Curriculum to Promote Scientific and Nature-Friendly Attitudes in Children Through a Cotton Project

ABSTRACT Growing plants is a popular and easy method to facilitate preschoolers’ scientific exploration and positive attitude toward the environment, as it creates an awareness that nature is a magical place to be explored. This study examines a year-long garden-based curriculum in South Korea, specifically a cotton project, and its effects on 4- to 6-year-old children’s (n = 165) scientific and nature-friendly attitudes. Classroom observations and teacher interviews were obtained for qualitative data and scientific attitudes and nature-friendly attitudes were collected for quantitative data. The results indicated that planting cotton and observing the process of its growth provided opportunities for developing a scientific attitude of curiosity and inquiry. In addition, the meaningful direct and concrete experience with the natural environment opened the children’s eyes to the significance of nature and the value of harmony with the natural world, resulting in increased nature-friendly attitudes. The critical roles of the teacher are addressed in implications.
Defence Spending and Unemployment in the USA: Disaggregated Analysis by Gender and Age Groups

Abstract The paper examines the effects of military spending using disaggregated unemployment statistics by gender and age group for the period 1948–2017 in the case of the USA. Findings from quantile regression analysis do not seem to point to any robust evidence supporting the thesis that defence spending quashes unemployment levels. This finding appears to be the case across all groups of unemployed persons. In fact, the results suggest a negative effect on unemployment.
Stress and Depression

Major depressive disorder is a significant contributor to the global burden of disease, and it appears to be a mental disorder that is strongly dependent upon exposure to stressful stimuli. A major concern related to the development of animal models of depression is to capture those variables that explain the much higher incidence of depression in human females compared to males. Several genetically selected animal models have been studied, including the Flinders sensitive strain and the WKY strain. In addition, a strain of rats has been selected that is highly susceptible to the development of learned helplessness. Two especially valuable animal models of depression involve exposure of inbred mice to chronic social defeat stress (CSDS) or to chronic unpredictable mild stress. Results from these animal models point to disruptions in dopamine circuits in the brain as critical for the expression of depressive symptoms.
Abnormal growth hormone secretion : clinical aspects

Cardiac involvement is common in acromegaly, but the prevalence of valvular abnormalities in patients with acromegaly has not been documented, and was topic of the current study. In a prospective study design, 40 consecutive patients with acromegaly and 120 control subjects (matched for age, sex, hypertension, and left ventricular systolic function) were studied. All patients and controls were evaluated using conventional 2D and Doppler echocardiography. Significant valve disease was more prevalent in acromegalics compared to controls: 22% vs 6.7% (p=0.005). Aortic valve regurgitation (more than or equal to trace severity) was present in 30% of patients vs 7% in controls (p<0.001), mitral regurgitation (more than or equal to moderate severity was absent in controls, but present in 5% of acromegalics (p=0.014 vs controls). Binary logistic regression analysis showed a significant impact only for disease duration on valvular disease, with an odds ratio of 1.19 (CI 1.028 (cid:150) 1.376; p=0.019). Acromegaly is associated with an increased prevalence of regurgitant valvular heart disease. This is dependent on the duration of exposure to increased growth hormone concentrations, with a 19% increase in odds per year. This increased prevalence of occult valvular disease implicates that these patients require appropriate follow-up care and monitoring, especially those with inadequate control of GH overproduction.