Miracle-dz/UniFAR-FTUs huggingface dataset:
An analysis of the determinants of failure processes in UK SMEs

PurposeThis paper has two purposes. First, it evaluates the extent to which different failure processes are present in failed UK SMEs, by considering non-financial metrics including director characteristics, in addition to the financial ones. Second, it analyses the determinants of the transition to failure in relation to the different failure processes that have been identified.Design/methodology/approachThe study is based on a sample of failed UK SMEs. The data covers financial ratios, board characteristics, the macroeconomic environment, sectoral details and regional information. First, failure processes are identified using a combination of factor analysis and cluster analysis. Second, the determinants of firms' transition to failure for the whole sample and in the individual failure clusters are analysed using panel data analysis.FindingsFour different firm failure processes were identified. Director characteristics differ between firm failure processes. We find evidence that director characteristics including director age and board gender structure, affect the transition to failure of UK SMEs. We also find that different factors affect the different failure processes.Originality/valueThe paper is the first to analyse the reasons for failure of UK SMEs in the firm failure process context by considering non-financial metrics such as the characteristics of the firms' directors. In addition the paper also identifies a number of different determinants that affect the various failure processes. This finding is important because it suggests that policies designed to reduce the incidence of firm failure should take account of the different failure processes.
Fecal Calprotectin, CRP and Leucocytes in IBD Patients: Comparison of Biomarkers With Biopsy Results

Abstract Background This study aimed to compare fecal calprotectin (FC) levels with other commonly used parameters as part of patient care during evaluation for inflammatory bowel disease (IBD). Methods We recruited adult IBD patients with ulcerative colitis (UC) and Crohn’s disease (CD) and compared the results of the patient’s biopsy results (i.e., inflamed versus noninflamed) for six sites (i.e., ileum, ascending colon, transverse colon, descending colon, sigmoid colon, rectum) with concentrations of C-reactive protein (CRP), total leucocytes and fecal calprotectin (FC). Results We found that FC was significantly elevated in a concentration-dependent manner that correlated with the number of active inflammation sites reported in biopsy. Although CRP and leucocyte measurements trended upwards in line with inflammation reported from biopsy, the results were highly variable and highlighted poor reliability of these biomarkers for indicating IBD inflammation. Conclusions These results strongly suggest that FC correlates best with biopsy reports and is a superior marker than CRP and leucocytes.
Real-Time Localization Approach for Maize Cores at Seedling Stage Based on Machine Vision

To realize quick localization of plant maize, a new real-time localization approach is proposed for maize cores at the seedling stage, which can meet the basic demands for localization and quantitative fertilization in precision agriculture and reduce environmental pollution and the use of chemical fertilizers. In the first stage, by taking pictures of maize at the seedling stage in a field with a monocular camera, the maize is segmented from the weed background of the picture. And then the three most-effective methods (i.e., minimum cross entropy, ISODATA, and the Otsu algorithm) are found from six common segmentation algorithms after comparing the accuracy rate of extracting maize and the time efficiency of segmentation. In the second stage, plant core from segmented maize image is recognized, and localized, based on different brightness of the rest part of maize core and plant. Then the geometric center of maize core is considered as localization point. the best effect of extracting maize core was found from the minimum cross entropy method based on gray level. According to experimental validation using many field pictures, under weedy conditions on sunny days, the proposed method has a minimum recognition rate of 88.37% for maize cores and is more robust at excluding weeds.
Assessment of quality indicators of the automatic control system influence of accident interference

This work concentrates the analysis of the system of automatic control of the directive diagram of the moving active electronically scanned array with a limited number of transceiver modules. The analysis revealed a number of shortcomings that lead to a significant increase in standard deviations, quadratic integral estimates, and an increase in transient time. The identified disadvantages lead to a decrease in the efficiency of the antenna system, an increase in the error rate at the reception, the inability of the system to react to disturbances applied to any point of the system in the event of a mismatch of a given signal/noise level. In accordance with the analysis, the mathematical model of the automatic control system of the directional diagram of the moving active electronically scanned array was considered, considering this a new method of estimating the quality indicators of the automatic control diagram of the directional diagram of the active electronically scanned array in a random setting and disturbing action was developed. The difference between the proposed method and the existing method is in the construction of an automatic control system with differential coupling equivalent to the combination due to the introduction of derivatives of the random setting action of the open compensation connection.
Trailing TRAIL Resistance for Targeted Cancer Therapy

Apoptosis is an orchestrated cell death that occurs in physiological condition. The loss of balance between cell division and cell death leads to pathological condition such as cancer [1]. Despite remarkable advances in the understanding the cancer biology and the development of novel diagnostic and therapeutic strategies, cancer still remains one of the major causes of death [2]. The lack of specificity of the current cancer therapy sparked an urgency to unravel a targeted cancer therapy. Tumour necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL), a member of TNF cytokine superfamily is a promising anti-cancer agent due to its selective targeting on TRAIL-R1 (DR4) and TRAIL-R2 (DR5) expressed by the cancer cells, sparing the normal cells [3].
Syphilis: A Tricky Disease that may Pose Some Diagnostic Challenges - A Case Report

This article reports a case of secondary stage syphilis involving the oral mucosa and the skin (the palms). The lesion’s clinical aspects of both sites could possibly be misdiagnosed for some common inflammatory diseases, among them oral lichenoid contact lesion or drug reaction. As a standard procedure, the differential diagnosis required to rule out syphilis. The treponemal and anti-treponemal tests confirmed the diagnosis of syphilis. The patient was successfully treated, but, unfortunately, his partners from sexual encounters were left unaccounted for. People who contract syphilis and are left untreated jeopardize society. This is the main reason why syphilis cannot be easily controlled from spreading.
Model of family health empowerment preventing stroke in Puskesmas Ulee Kareng Banda Aceh

Stroke is a clinical sign that develops from the Focal brain with symptoms that occur for a day or more and can cause death for no apparent reason other than vascular. Stroke has become the leading cause of death in almost all hospitals in Indonesia and in Aceh is the number one death factor. The purpose of this study is to empower families to get a stroke prevention model and have the effect of that model for lowering blood pressure, cholesterol and blood sugar. Participants in this study were hypertension sufferers with a total of 32 participants at the Ulee Kareng Health Center in Banda Aceh. The study was conducted from February 2017 to December 2018, using the Participatory Action Research (PAR) and T-Test methods. The results of research through PAR studies found stroke prevention models and differences in blood pressure, cholesterol and blood sugar decreased after the study. It can be concluded that the effect of the stroke prevention model was found to reduce the risk of stroke. Recommendations: Strengthening and family motivation is very influential to reduce the risk of stroke.
Facebook or fail-book: Exploring “community” in a virtual community of practice

Abstract Creating collaborative working and learning experiences has long been at the forefront of computer-assisted language learning research. It is in this context that, in recent years, the integration of social networking sites and Web 2.0 in learning settings has surged, generating new opportunities to establish and explore virtual communities of practice (VCoPs). However, despite the number of studies on the concept, research remains inconclusive on how learners develop a sense of community in a VCoP, and what effect this may have on interaction and learning. This research project proposes to use social network analysis, part of graph theory, to explore the configuration of a set of VCoPs, and presents an empirical approach to determine how interaction in such communities takes shape. The present paper studies the concept of “community” in two VCoPs on Facebook. Participants (Group 1: N = 123, Group 2: N = 34) in both VCoPs are enrolled in English as a foreign language courses at two Belgian institutions of higher education. Social network analysis is used to show how both learner groups establish and develop a network of peers, and how different participants in those groups adopt different roles. Participation matrices reveal that interaction mainly revolves around a number of active key figures and that certain factors such as the incorporation of online and offline assignments and the inclusion of a teacher online result in varying levels of success when establishing collaborative dialogue within the VCoPs. Recommendations are formulated to inform and improve future practice.
Electric cars: Are they solution to reduce CO2 emission?

Reducing CO2 emission is one of the major environmental challenges for transportation. One way to solve this problem is to replace old cars that use fossil fuels (petrol, diesel) with new electric cars. In this paper, the existing model for calculating well-to-wheels CO2 emission during the life cycle of the car (fossil fuel car and electric car) is upgraded. The developed model is used for comparing optimal lifetime and optimal car? s kilometers driven during a lifetime in the replacement process of a fossil fuel car with a new electric car. We find that reducing CO2 emission depends on the type of fossil fuel, and the weight of fossil fuel cars and electric cars. Changing petrol fossil fuel cars with lower weight electric cars have the greatest potential for reducing CO2 emission. However, the introduction of electric cars does not achieve a significant reduction of CO2 emission in countries where electricity is primarily produced in thermal power plants, i. e. in countries with a high emission factor of electricity production.
Average Neural Face Embeddings for Gender Recognition

In recent years, with the rise of artificial intelligence and deep learning, facial recognition technologies have been developed that operate with high accuracy even in adverse conditions. However, extracting demographic information such as gender, age and race from facial features has been a hot research area. In this study, a new Average Neural Face Embeddings (ANFE) method that uses facial vectors of people for gender recognition is presented. Instead of training deep neural network from scratch, a simple, fast and effective solution has been developed that performs a distance calculation between the average gender vectors and the person's face vector. The method proposed as a result of the study carried out provided a high and successful recognition performance with with 96.47% of the males and 99.92% of the females.
Use of Dried Blood Spot Specimens to Monitor Patients with Inherited Metabolic Disorders

Monitoring of patients with inherited metabolic disorders (IMDs) using dried blood spot (DBS) specimens has been routinely used since the inception of newborn screening (NBS) for phenylketonuria in the 1960s. The introduction of flow injection analysis tandem mass spectrometry (FIA–MS/MS) in the 1990s facilitated the expansion of NBS for IMDs. This has led to increased identification of patients who require biochemical monitoring. Monitoring of IMD patients using DBS specimens is widely favoured due to the convenience of collecting blood from a finger prick onto filter paper devices in the patient’s home, which can then be mailed directly to the laboratory. Ideally, analytical methodologies with a short analysis time and high sample throughput are required to enable results to be communicated to patients in a timely manner, allowing prompt therapy adjustment. The development of ultra-performance liquid chromatography (UPLC–MS/MS), means that metabolic laboratories now have the capability to routinely analyse DBS specimens with superior specificity and sensitivity. This advancement in analytical technology has led to the development of numerous assays to detect analytes at low concentrations (pmol/L) in DBS specimens that can be used to monitor IMD patients. In this review, we discuss the pre-analytical, analytical and post-analytical variables that may affect the final test result obtained using DBS specimens used for monitoring of patients with an IMD.
Branding Cultural Products in International Markets: A Study of Hollywood Movies in China

Cultural products are a major component of the world economy and are responsible for a growing share of U.S. exports. The authors examine brand name strategies when cultural products are marketed in foreign countries. Incorporating the unique characteristics of these products, the authors develop a theoretical framework that integrates similarity, which focuses on how the translated brand name relates to the original brand name, and informativeness, which focuses on how the translated brand name reveals product content, to study the impact of brand name translations. The authors analyze Hollywood movies shown in China from 2011 to 2018. The results show that higher similarity leads to higher Chinese box office revenue, and this effect is stronger for movies that perform better in the home market (i.e., the United States). When the translated title is more informative about the movie, the Chinese box office revenue increases. The informativeness effect is stronger for Hollywood movies with greater cultural gap in the Chinese market. Moreover, both similarity and informativeness effects are strongest when the movie is released and reduce over time. This research provides valuable guidance to companies, managers, and policy makers in cultural product industries as well as those in international marketing.
Deep Reinforcement Learning for Dynamic Spectrum Sensing and Aggregation in Multi-Channel Wireless Networks

In this paper, the problem of dynamic spectrum sensing and aggregation is investigated in a wireless network containing <inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> correlated channels, where these channels are occupied or vacant following an unknown joint 2-state Markov model. At each time slot, a single cognitive user with certain bandwidth requirement either stays idle or selects a segment comprising <inline-formula> <tex-math notation="LaTeX">${C}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">${C} < {N}$ </tex-math></inline-formula>) continuous channels to sense. Then, the vacant channels in the selected segment will be aggregated for satisfying the user requirement. The user receives a binary feedback signal indicating whether the transmission is successful or not (i.e., ACK signal) after each transmission, and makes next decision based on the sensing channel states. Here, we aim to find a policy that can maximize the number of successful transmissions without interrupting the primary users (PUs). The problem can be considered as a partially observable Markov decision process (POMDP) due to without full observation of system environment. We implement a Deep Q-Network (DQN) to address the challenge of unknown system dynamics and computational expenses. The performance of DQN, Q-Learning, and the Improvident Policy with known system dynamics is evaluated through simulations. The simulation results show that DQN can achieve near-optimal performance among different system scenarios only based on partial observations and ACK signals.
Investigation of sex hormones on the early diagnosis of schizophrenia

Schizophrenia is a severe psychiatric disorder showing cognitive deficits among the early symptoms. Previous studies have reported that sex hormones are related to the cognitive dysfunction in schizophrenia. In this paper, we explore sex hormones as the potential biomarkers in differentiating first-episode schizophrenia patients from healthy controls, and investigate the most discriminative sex-hormone related biomarkers for the diagnosis of schizophrenia at the same time. Specifically, six sex hormones, which are follicle-stimulating hormone, luteinizing hormone, prolactin, estradiol, progesterone and testosterone, were examined as the basic features. Based on these sex hormones, the sex-hormone ratios and log-transformed sex-hormone ratios were computed for feature enhancement. T-test was further used for feature selection. In order to avoid the possible bias on sex hormones caused by female physiological factors, the classification experiment was performed on male participants using random forest. The effectiveness of different feature combination strategies was further studied. Among these strategies, the scheme fusing sex hormones, sex-hormone ratios and log-transformed sex-hormone ratios produced the best classification performance with an accuracy of 80.67%, which is comparable with the results obtained by complex neuroimaging data. Finally, the most discriminative features were further discussed according to the t-test results. Results show that the luteinizing hormone, prolactin, sex-hormone ratios and log-transformed sex-hormone ratios are the most significant features. This work supports the use of sex hormones as potential biomarkers for the diagnosis of schizophrenia. Given the convenient detection of these sex hormones in the routine examination, it could be a more straightforward and cost-saving way for the early diagnosis of schizophrenia patients.
Energy Efficiency-Oriented Resource Allocation for Massive MIMO Systems with Separated Channel Estimation and Feedback

This paper proposes a dynamic resource allocation scheme to maximize the energy efficiency (EE) for Massive MIMO Systems. The imperfect channel estimation (CE) and feedback are explicitly considered in the EE maximization problem, which aim to optimize the power allocation, the antenna subset selection for transmission, and the pilot assignment. Assuming CE error to be bounded for the complex-constrained Cramer–Rao Bound (CRB), theoretical results show that the lower bound is directly proportional to its number of unconstrained parameters. Utilizing this perspective, a separated and bi-directional estimation is developed to achieve both low CRB and low complexity by exploiting channel and noise spatial separation. Exploiting global optimization procedure, the optimal resource allocation can be transformed into a standard convex optimization problem. This allows us to derive an efficient iterative algorithm for obtaining the optimal solution. Numerical results are provided to demonstrate that the outperformance of the proposed algorithms are superior to existing schemes.
Potentially Toxic Elements (PTEs) in Cultivated Soils from Lombardy (Northern Italy): Spatial Distribution, Origin, and Management Implications

This work aims to quantify the contribution of agricultural practices to diffuse pollution in cultivated soils. Two samples (the first from the top layer and the second from a depth of about 100 cm) were retrieved from about 1000 soil profiles and analyzed for their potentially toxic elements (PTEs) content (Cd, Cu, Ni, Pb, Zn, Mn). In addition, we collected dedicated soil profiles for three specific types of land use and agronomic practice, namely vine-, cereal- and rice-growing areas. Baseline concentrations and distribution maps were produced. Statistical data treatment, coupled with the results of the dedicated soil profiles, enabled the identification of precise pollution sources and processes. In cultivated soils, PTEs contents prove to be generally well below the Italian regulatory limits, with the exception of Cu in vineyard soils, due to the long-lasting use of Cu-based pesticides. South of Milan and in other urban areas, we attribute the top soil enrichment in Cd, Cu, Pb, and Zn to industrial activities and urban settlement. Ni sporadically exceeds regulatory standards, but its association with Mn and its depth distribution point to a natural origin, mostly due to the occurrence of serpentine. The project demonstrates that although agriculture, especially in the form of vineyards and of intensive cultivation, certainly contributes to pollution, such contribution is exceeded by that deriving from industry and road traffic.
Oxygen Vacancy Substitution Linked to Ferric Iron in Bridgmanite at 27 GPa

Ferric iron can be incorporated into the crystal structure of bridgmanite by either oxygen vacancy substitution (MgFeO2.5 component) or charge‐coupled substitution (FeFeO3 component) mechanisms. We investigated the concentrations of MgFeO2.5 and FeFeO3 in bridgmanite in the MgO‐SiO2‐Fe2O3 system at 27 GPa and 1700–2300 K using a multianvil apparatus. The FeFeO3 content increases from 1.6 to 7.6 mol. % and from 5.7 to 17.9 mol. % with and without coexistence of (Mg,Fe)O, respectively, with increasing temperature from 1700 to 2300 K. In contrast, the MgFeO2.5 content does not show clear temperature dependence, that is, ~2–3 and < 2 mol. % with and without the coexistence of (Mg,Fe)O, respectively. Therefore, the presence of (Mg,Fe)O enhances the oxygen vacancy substitution for Fe3+ in bridgmanite. It is predicted that Fe3+ is predominantly substituted following the oxygen vacancy mechanism in (Mg,Fe)O‐saturated Al‐free bridgmanite when Fe3+ is below ~0.025 pfu, whereas the charge‐coupled mechanism occurs when Fe3+ > 0.025 pfu.