Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Financial Deepening Cause Liquidity Problems for Banks? Evidence from Nigeria

Attempt to facilitate economic growth makes the Central Banks to formulate monetary policies that seek to deepen the provision of financial resources to target sectors. Since Banks are the main channels through which monetary policies are executed, we attempted to examine whether financial deepening cause liquidity problem among Nigerian banks in this study. We employed time series analytical techniques to analyze selected financial deepening indicators and data for banking system liquidity between 1981 and 2019. The financial deepening variables used include of broad money to the gross domestic product (GDP) ratio; credit to private sector to the GDP ratio; ratio of commercial banks liabilities to the GDP; financial sector contribution to the GDP and ratio of market capitalization to the GDP. On the other hand, the liquidity of the banking system is proxy by its loan/deposit ratio for the period under study. We estimated the statistical properties of the variables examined and conducted some pre-estimation tests (stationarity and co-integration) to ascertain choice estimation techniques. We used a vector error correction mechanism to investigate long and short-run effects of financial deepening on Nigerian banking system liquidity. Both the long run vector autoregressive (VAR) and the short run and vector error correction (VEC) models results showed that there is a positive but statistically insignificant relationship between banking system liquidity and financial deepening variables. In addition, the results of the Granger causality between the dependent and independent variables revealed that there exists no causal relationship between the liquidity of the banking system and financial deepening. These findings imply that financial deepening did not impair banks’ liquidity position in Nigeria during the years under review. The study concluded that financial deepening does not cause liquidity problem for banks in Nigeria; rather, if well managed, can have positive effect on it. In the light of this, the study recommends that banks should re-strategize in the implementation of financial deepening policies that are liquidity friendly and that the Central Bank of Nigeria, should formulate policies that will not only focus on credit and loan beneficiaries, but also on the banks.
Family Foundations To promote parent mental health and family functioning during the COVID-19 pandemic in Australia: A mixed methods evaluation

ABSTRACT Evidence-based family-based interventions targeting parent mental health and partner conflict during community-wide crises such as the COVID-19 pandemic are scarce. Family Foundations (FF), a 10-week couple/parent-based intervention targeting parent mental health, conflict and co-parenting was delivered via video-conferencing during the COVID-19 pandemic. This study aimed to: (1) explore parents’ and clinicians’ experiences and perceived benefits of FF, and (2) assess pre–post intervention changes in parent mental health, interparental conflict and co-parenting behaviour. A mixed methods evaluation was conducted with 62 families with young children experiencing parent mental health difficulties and/or parental conflict. Qualitative interviews with parents and FF clinicians were conducted, and intervention outcomes were assessed using mother-report surveys. Maternal stress and anxiety symptoms decreased and co-parenting support and parenting warmth increased following FF. Parents expressed high satisfaction with FF despite the perceived limited cultural and family structure diversity in the videos. Although some activities were modified and clinicians were more directive in their style of delivery, FF was implemented with fidelity. Importantly, telehealth delivery made FF accessible to meet the needs of families during the pandemic when in-person services were not available. These findings will inform further development and evaluation of telehealth FF during community-wide crises such as the COVID-19 pandemic.
Regeneration ability of wheat (Triticum aestivum L.) embryos after bombardment with a particle gun

The plant regeneration ability of the spring wheat variety Cadenza from the UK and the winter variety Mv Emese from Hungary was studied over the course of two years. The calli were regenerated with 10 hours illumination in the first year and 14 hours illumination in the second, and the external environment was not completely excluded, light being admitted through a window. The level of plant regeneration was evaluated 7-8 weeks after the isolation of the scutella. Both genotypes exhibited considerable fluctuation in plant regeneration over the two years, but no significant difference was observed in the mean plant regeneration ability of Mv Emese and Cadenza as a function of the two illumination periods
Water use and supply concerns for utility-scale solar projects in the Southwestern United States.

As large utility-scale solar photovoltaic (PV) and concentrating solar power (CSP) facilities are currently being built and planned for locations in the U.S. with the greatest solar resource potential, an understanding of water use for construction and operations is needed as siting tends to target locations with low natural rainfall and where most existing freshwater is already appropriated. Using methods outlined by the Bureau of Land Management (BLM) to determine water used in designated solar energy zones (SEZs) for construction and operations & maintenance, an estimate of water used over the lifetime at the solar power plant is determined and applied to each watershed in six Southwestern states. Results indicate that that PV systems overall use little water, though construction usage is high compared to O&M water use over the lifetime of the facility. Also noted is a transition being made from wet cooled to dry cooled CSP facilities that will significantly reduce operational water use at these facilities. Using these water use factors, estimates of future water demand for current and planned solar development was made. In efforts to determine where water could be a limiting factor in solar energy development, water availability, cost, and projected future competing demandsmore » were mapped for the six Southwestern states. Ten watersheds, 9 in California, and one in New Mexico were identified as being of particular concern because of limited water availability. « less
Exploring the Risky Travel Area and Behavior of Car-hailing Service

Recent years have witnessed the rapid development of car-hailing services, which provide a convenient approach for connecting passengers and local drivers using their personal vehicles. At the same time, the concern on passenger safety has gradually emerged and attracted more and more attention. While car-hailing service providers have made considerable efforts on developing real-time trajectory tracking systems and alarm mechanisms, most of them only focus on providing rescue-supporting information rather than preventing potential crimes. Recently, the newly available large-scale car-hailing order data have provided an unparalleled chance for researchers to explore the risky travel area and behavior of car-hailing services, which can be used for building an intelligent crime early warning system. To this end, in this article, we propose a Risky Area and Risky Behavior Evaluation System (RARBEs) based on the real-world car-hailing order data. In RARBEs, we first mine massive multi-source urban data and train an effective area risk prediction model, which estimates area risk at the urban block level. Then, we propose a transverse and longitudinal double detection method, which estimates behavior risk based on two aspects, including fraud trajectory recognition and fraud patterns mining. In particular, we creatively propose a bipartite graph-based algorithm to model the implicit relationship between areas and behaviors, which collaboratively adjusts area risk and behavior risk estimation based on random walk regularization. Finally, extensive experiments on multi-source real-world urban data clearly validate the effectiveness and efficiency of our system.
Beginning Ubuntu LTS Server Administration: From Novice to Professional, Second Edition

Beginning Ubuntu LTS Server Administration, Second Edition is the touchstone companion book for anyone implementing Ubuntu LTS Server. Author Sander van Vugt introduces the most recent server edition of Ubuntu Linux, the most popular Linux distribution, to power users, system administrators, and programmers and demonstrates the power and flexibility that the HardyHeron Ubuntu Server Long Term Support Edition offers for small networks and corporate systems alike. This book covers: Installing and configuring Ubuntu to ensure secure installations Virtual Ubuntu and LDAP configuration Full network and web services management What youll learn Administer, install, and configure the 5year HardyHeron Ubuntu Server Long Term Support Edition of the most popular Linux distribution in the world. Use the new installation and GUI tools. Familiarize yourself, whether you are a power user or system administrator, with LDAP administration. Build a network infrastructure with Ubuntu Server. Harden Ubuntu to withstand new security threats. Use virtual services. Who is this book for This book will suit Linux system administrators of all levels. It also lets power users who want to familiarize themselves with network and web services relevant to their work acquire uptodate specialized Ubuntu skills. About the Apress Beginning Series The Beginning series from Apress is the right choice to get the information you need to land that crucial entrylevel job. These books will teach you a standard and important technology from the ground up because they are explicitly designed to take you from novice to professional. Youll start your journey by seeing what you need to knowbut without needless theory and filler. Youll build your skill set by learning how to put together realworld projects step by step. So whether your goal is your next career challenge or a new learning opportunity, the Beginning series from Apress will take you thereit is your trusted guide through unfamiliar territory!
Akt Inhibition as Preconditioning Treatment to Protect Kidney Cells against Anoxia

Lesions issued from the ischemia/reperfusion (I/R) stress are a major challenge in human pathophysiology. Of human organs, the kidney is highly sensitive to I/R because of its high oxygen demand and poor regenerative capacity. Previous studies have shown that targeting the hypusination pathway of eIF5A through GC7 greatly improves ischemic tolerance and can be applied successfully to kidney transplants. The protection process correlates with a metabolic shift from oxidative phosphorylation to glycolysis. Because the protein kinase B Akt is involved in ischemic protective mechanisms and glucose metabolism, we looked for a link between the effects of GC7 and Akt in proximal kidney cells exposed to anoxia or the mitotoxic myxothiazol. We found that GC7 treatment resulted in impaired Akt phosphorylation at the Ser473 and Thr308 sites, so the effects of direct Akt inhibition as a preconditioning protocol on ischemic tolerance were investigated. We evidenced that Akt inhibitors provide huge protection for kidney cells against ischemia and myxothiazol. The pro-survival effect of Akt inhibitors, which is reversible, implied a decrease in mitochondrial ROS production but was not related to metabolic changes or an antioxidant defense increase. Therefore, the inhibition of Akt can be considered as a preconditioning treatment against ischemia.
Ransomware Detection Using the Dynamic Analysis and Machine Learning: A Survey and Research Directions

Ransomware is an ill-famed malware that has received recognition because of its lethal and irrevocable effects on its victims. The irreparable loss caused due to ransomware requires the timely detection of these attacks. Several studies including surveys and reviews are conducted on the evolution, taxonomy, trends, threats, and countermeasures of ransomware. Some of these studies were specifically dedicated to IoT and android platforms. However, there is not a single study in the available literature that addresses the significance of dynamic analysis for the ransomware detection studies for all the targeted platforms. This study also provides the information about the datasets collection from its sources, which were utilized in the ransomware detection studies of the diverse platforms. This study is also distinct in terms of providing a survey about the ransomware detection studies utilizing machine learning, deep learning, and blend of both techniques while capitalizing on the advantages of dynamic analysis for the ransomware detection. The presented work considers the ransomware detection studies conducted from 2019 to 2021. This study provides an ample list of future directions which will pave the way for future research.
Self-Localization of the Autonomous Robot for View-Based Navigation Using Street View Images

Navigation requires self-localization, which GPS typically performs outdoors. However, GPS frequently introduces significant errors in environments where radio reflection occurs, such as in urban areas, which makes precise self-localization occasionally impossible. Meanwhile, a human can use street view images to understand their surroundings and their current location. To implement this, we must solve image matching between the current scene and the images in a street view database. However, because of the wide variations in the field angle, time, and season between images, standard pattern matching by feature is difficult. DeepMatching can precisely match images with various lighting and field angles. Nevertheless, DeepMatching tends to misinterpret street images because it may find unnecessary feature points in the road and sky. This study proposes several methods to reduce misjudgment: (1) gaining image similarity with features such as buildings by excluding the road and sky, and (2) splitting the panoramic image into four directions and matching in each. This study shows the results of each method and summarizes their performance using various images and resolutions.
Handling and Braking Analyses of a Heavy Vehicle with a Cross-Axle Fluidically-Coupled Suspension

The handling and braking responses of a heavy vehicle equipped with a cross-axle fluidically-coupled hydropneumatic suspension concept are investigated. The proposed fluidically-coupled suspension is conceived by diagonally interconnecting different hydraulic fluid chambers of the four suspension struts of the vehicle. The analytical formulations of suspension forces are derived based on fluid flows through the couplings and damping valves. A generalized full-vehicle model is developed and validated to evaluate the handling and braking responses to two critical vehicle maneuvers: (i) braking-in-a-turn; and (ii) split-μ straight-line braking. The responses of the vehicle model with the coupled suspension are compared with those of the uncoupled suspension under various inputs to demonstrate the potential benefits of the proposed cross-axle fluidic coupling of the suspension struts.
Evaluation Quality and Success Implementation of Nganjuk Smart City Mobile Application Using Technology Acceptance Model (TAM) and Delone Mclean Model Approach

Nganjuk Smart City is an android-based mobile application that was created to help Nganjuk citizen obtain public information and services. This research uses Technology Acceptance Model (TAM) and Delone & Mclean in order to determine quality and success implementation condition of Nganjuk Smart City. Data retrieval was conducted by sharing online and offline questionnaires to 175 respondents and used purposive sampling techniques to determine research samples. The result of this research is quality condition implementation of Nganjuk Smart City based on Technology Acceptance Model (TAM) falls into high category and get 71.4% score, while successful condition implementation of Nganjuk Smart City based on Delone & McLean model falls into the high category and get 69.4% score. There are 4 variables and 18 indicators that get improvement recommendations because they get scores lower than the total average scores.
COEVOLUTIONARY PERSPECTIVE OF INDUSTRY-NETWORK DYNAMICS

Abstract The chapter presents a theoretical framework that deals with the basic question of how networks and industries coevolve. We draw upon the structural and relational perspectives of networks to theorize about changes occurring in interfirm networks over time and the coevolutionary linkage of these changes to the industry life cycle. We further extend the widely accepted industry life cycle model by claiming that industry-specific evolutionary patterns impact the structure of the network’s relations, which in turn lead to diversification in the sources of innovation and to variation in the patterns of industrial evolution.
Seismic Moment Tensor Inversion in Anisotropic Media using Deep Neural Networks

We design a deep neural network (DNN) and train it to invert the focal mechanism of microseismic events that occur during a hydraulic fracture treatment of unconventional reservoirs. For the testing, we generate synthetic microseismic events in anisotropic 3D media and consider a realistic dual-well monitoring scenario. We show that for this geometry a trained DNN can successfully retrieve the six independent elements of the moment tensor. We statistically analyze the correlation coefficients and relative errors of the results and demonstrate that the moment tensor can be accurately estimated using the proposed DNN, providing a reliable alternative to other conventional inversion techniques.
Enabling machine learning‐based side‐chaining for improving QoS in blockchain‐powered IoT networks

The Internet of Things (IoT) makes developers for integrating various collection of device, saving, and processing a huge amount of data, allowing new services for improving several personal and professional activities. But, the privacy problems occur with a large amount of data produced and therefore the solutions on the basis of blockchain with sidechain technology have been developed to overcome these problems.
Determinants of Environmental Sustainability among Tertiary Students During the COVID-19 Pandemic

This study aims to assess the determinants of environmental sustainability among students from a tertiary education institution in Central Luzon, Philippines, during the COVID-19 pandemic. This study used a descriptive-correlational research design with the online survey as the primary data gathering tool. A total of 136 students participated in the online survey using the convenience sampling technique due to restriction protocols implemented by the government authority. For the instrument of the study, the researcher adopted and modified a previous instrument to fit with the study’s objectives. With the help of SPSS 23, the researcher computed and analyzed the gathered data using weighted mean, Pearson-r, and regression analysis as statistical tools. In general, the students were “very aware” of environmental sustainability. In addition, students “often” do waste and recycling activities, consume consciously, and save energy. Furthermore, statistical inferences revealed a weak – moderate positive correlation between waste and recycling activities, conscious consumption, energy-saving awareness, and environmental sustainability. For the determinants, waste and recycling activities and energy-saving awareness provided substantial evidence to influence the students’ environmental sustainability in the study. This study becomes a reference and basis for future research in the field of environmental sustainability.
Morphology and phenology of sexuals and new distribution data on the blind Mediterranean ant Hypoponera abeillei (Hymenoptera, Formicidae)

Hypoponera abeillei is the sole member of the otherwise exclusively Afrotropical abeillei group to occur in the West-Palearctic and since its first description on the basis of two Corsican workers in 1881, it remained little-known. Workers of this species are thought to entirely lack eyes, a rare trait among ants of the region, yet their lifestyle remains undocumented. On the other hand, the male caste has been described from 4 Tunisian specimens in 1921, and queens remained so far undescribed. We present an updated description of the male caste based on 45 specimens and a first description of the queen caste based on 14 specimens. The H. abeillei material we examined comes from Italy, Spain and Malta (mostly originating from coastal localities), and comprises 11 inedit distribution records, including the first findings in the islands of Mallorca, Malta and Sardinia. Moreover, we provide a first phenological overview of the species’ nuptial flights. Our data show that H. abeillei sexuals flight during the summer, mostly in August, and demonstrate that they can easily be distinguished from all the other Hypoponera species inhabiting the Mediterranean region based on their morphology. The remarkable diversity of Mediterranean Hypoponera males and queens suggest that sexuals may have a role in future attempts to understand relationships within this genus, yet the number of species in which sexual castes are documented is still extremely reduced.
Optimum design of power transistor switches

An optimization procedure is developed that completely specifies the one-dimensional design of a double-diffused transistor with only two pieces of input data required--the collector-emitter sustaining voltage and the current gain required when the device is operating in the region of quasi-saturation. A simple but experimentally validated model for predicting h FE versus I C is also developed and used in the optimization procedure. The analysis is intended to apply mainly to the case of high-voltage high-current switching transistors that have a lightly doped collector. Several design examples are given that illustrate the optimization procedure. In the first example it is shown that the emitter area can be minimized, while simultaneously meeting both the H FE and BV CEO specifications. This result is of economic significance, since it results in the minimization of die size, and hence die cost. Other examples are given that illustrate various extensions of the procedure.
RECOVERY OF OIL TRAPPED IN SHIP-WRECKS: THE DIFIS CONCEPT

ABSTRACT A method for the prompt and cost-effective intervention and remediation of tanker wrecks dealing with eventual leaks and recovering the fuel trapped in their tanks, even at considerable depths, is described. The method is of general applicability as long as the trapped pollutant does not dissolve and is of lower density than sea water. It relies on gravity to channel the flow of spilt fuel towards the surface. Instead of channeling the flow directly to the surface, the fuel-water mix is directed to a buffer reservoir/separator some 30–50 m below the sea surface so as not to be affected by rough weather. This is achieved by means of a light, quickly deployable flexible structure that should stay in place until all the tanks of the wreck are emptied and the pollution threat eliminated. The buffer reservoir, into which the spilt fuel is channelled, is provided with standard equipment through which shuttle vessels, weather permitting, can recover the fuel rapidly, using standard off-shore equipment a.