Miracle-dz/UniFAR-FTUs huggingface dataset:
Corporate Social Responsibility (CSR) Employee Outcomes in the Aviation Industry during the COVID19 Pandemic Era. A Conceptual Framework

Purpose – By drawing on conservation of resources,social identity and attachment theories, this paper investigates the impact of corporate social responsibility (CSR) initiatives on work engagement, covid‐induced perceived job insecurity and organizational citizenship behavior (OCB). The mediating role of organizational pride and trust is also explored. Relevance – The pandemic has caused an unimaginable collapse of air passenger and cargo volumes, sweeping job cuts and huge financial losses for aviation. Employees in the aviation industry have been afflicted by the pandemic but also decipher CSR and are part of the road towards recovery combined with responsible business practices. Methodology – An integrative literature review method was adopted. A range of literature review relevant to the concept and the materialization of CSR, both generally and specifically in the aviation industry, is explored. A conceptual model linking CSR to certain employee outcomes is then proposed and discussed. Findings – The paper offers insights into the ways CSR initiatives may impact employees in the aviation industry at the emotional, attitudinal and behavioral level during the pandemic. It is proposed that when companies undertake CSR activities, employees develop higher levels of organizational trust and pride particularly reinforced by empathetic leadership and employee CSR participation. Those emotions, in turn, lead to more engaged employees with reduced feelings of job insecurity. An improvement in employees’ OCB is considered to be the end result. Practical implications – This study is helpful for companies within the aviation industry, during the pandemic and post‐pandemic era, to plan and implement CSR activities in such a way that could positively affect employee outcomes.
Impacts of Climate Change and Hydropower Development on the Community Livelihoods in Sondu Miriu River Basin, Kenya

Hydropower is sustainable and environmentally friendly source of energy worldwide. Driven by streamflow, it is vulnerable to climate change and land use change. The hydropower production from the two-existing run-of-river hydropower projects on the Sondu Miriu river are vulnerable to rainfall variability and requires proper understanding of the climate change trends and policies to support sustainable hydropower development and put in place strategies for building resilience for the local communities. The main objective of this paper was to examine the impacts of both the climate change and the hydropower development projects on the livelihoods of the community living within the Sondu Miriu River basin. Participatory methodologies involving administration of questionnaires at household level and focus group discussions with the local leaders and actors were applied to determine the impacts of climate change and the hydropower development on the community livelihoods within the basin. The socioeconomic status of the basin indicates that majority of the households (>59%) are poor and earn below 8 US dollars per day. The employment rate is extremely low with only 22% in formal employment. About 49% of the households still use wood fuel and charcoal as energy sources which is a threat to catchment conservation. Strengthening community resilience to climate change impacts is one of the benefits to be derived from the hydropower projects by supporting appropriate adaptation strategies within the existing policy framework.
An Empirical Method for Decomposing the Contributions of Land and Building Values
 to Housing Value

This paper develops an empirical method that uses two separate housing related components to estimate housing value: land and building. The artificial neural network (ANN) technique is used to iteratively solve for two hedonic models simultaneously by minimizing the difference in the observed total value and the sum of the estimated land and building values. This method enables one to objectively separate housing value into land and building components. Using actual sales transaction data from Taipei City, we estimate the land value as a share of the total housing value. The results show that the land value accounts for a higher share with older properties. The share of the land value of low-rise buildings tends to be higher than that of high-rise buildings. The share of the land value can deviate by 20 percentage points between more or less expensive housing communities within Taipei City.
Language and Topic Choice among Prolific and Non-Prolific Posters on an Arabic-English Website

 Abstract—Mahjoob.com is a popular Jordan-based website featuring dozens of discussion forums in both English and Arabic. This paper explores the language and topic choices among the 1,261 posters that authored posts on mahjoob.com during a 14-month period. The results indicate that the top 10 prolific posters (i.e. those who have posted more than 1000 messages) have very different language and topic preferences to the rest of the posters. Prolific posters prefer to post using Arabic and to contribute to humor-related forums whereas non-prolific posters prefer to post in 3arabizi, a mixture of Arabic and English written in Latin script, and to a lesser extent, in English. These non-prolific posters tend to post to a variety of other topical forums besides the humour-related forums.
Mining Willing-to-Pay Behavior Patterns from Payment Datasets

The customer base is the most valuable resource to E-commerce companies. A comprehensive understanding of customers’ preferences and behavior is crucial to developing good marketing strategies, in order to achieve optimal customer lifetime values (CLVs). For example, by exploring customer behavior patterns, given a marketing plan with a limited budget, a set of potential customers is able to be identified to maximize profit. In other words, personalized campaigns at the right time and in the right place can be treated as the last stage of consumption. Moreover, effective future purchase estimation and recommendation help guide the customer to the up-selling stage. The proposed willing-to-pay prediction model (W2P) exploits the transaction data to predict customer payment behavior based on a probabilistic graphical model, which provides semantic explanation of the estimated results and deals with the sparsity of payment data from each customer. Existing work in this domain ranks the customers by their probabilities of purchase in different conditions. However, the customer with the highest purchase probability does not necessarily spend the most. Therefore, we propose a CLV maximization algorithm based on the prediction results. In addition, we improve the model by behavioral segmentation wherein we group the customers by payment behaviors to reduce the size of the offline models and enhance the accuracy for low-frequency customers. The experiment results show that our model outperforms the state-of-the-art methods in purchase behavior prediction.
Reward contingency gates selective cholinergic suppression of amygdala neurons

Basal forebrain cholinergic neurons modulate how organisms process and respond to environmental stimuli through impacts on arousal, attention, and memory. It is unknown, however, whether basal forebrain cholinergic neurons are directly involved in conditioned behavior, independent of secondary roles in the processing of external stimuli. Using fluorescent imaging, we found that cholinergic neurons are active during behavioral responding for a reward – even in prior to reward delivery and in the absence of discrete stimuli. Photostimulation of basal forebrain cholinergic neurons, or their terminals in the basolateral amygdala (BLA), selectively promoted conditioned responding (licking), but not unconditioned behavior nor innate motor outputs. In vivo electrophysiological recordings during cholinergic photostimulation revealed reward-contingency-dependent suppression of BLA neural activity, but not prefrontal cortex (PFC). Finally, ex vivo experiments demonstrated that photostimulation of cholinergic terminals suppressed BLA projection neuron activity via monosynaptic muscarinic-receptor-signaling, while also facilitating firing in GABAergic interneurons. Taken together, we show that the neural and behavioral effects of basal forebrain cholinergic activation are modulated by reward contingency in a target-specific manner.
Micro-glassblowing Paradigm for Realization of Rate Integrating Gyroscopes

Author(s): Senkal, Doruk | Advisor(s): Shkel, Andrei M | Abstract: This Ph.D. dissertation reports novel fabrication processes and architectures for implementation of Rate Integrating Gyroscopes at micro-scale. Majority of the focus is directed towards development of a surface tension and pressure driven micro-glassblowing paradigm, which is envisioned to serve as an enabling mechanism for wafer-scale fabrication of 3-D micro-wineglass gyroscopes. New 2-D silicon Micro Rate Integrating Gyroscope (MRIG) architectures are also explored to bridge the gap between conventional micro-machining techniques and micro-glassblowing processes, and to serve as a test platform for various MRIG control strategies. Closed loop Whole Angle operation of these 2-D silicon MRIG architectures is presented to identify some of the control challenges associated with MRIG control, such as energy pumping and suppression of errors caused by structural imperfections.The main contribution of the thesis is the development of a high temperature (1700 °C) micro-glassblowing process for fabrication of highly symmetric and low internal dissipation 3-D fused silica wineglass resonators. Owing to the "self-healing'" properties of surface tension and pressure driven micro-glassblowing paradigm, and the low internal loss fused silica material, quality factors above 1 million and frequency splits less than 1 Hz have been demonstrated. In addition to a multi-purpose test-bed for micro-wineglass characterization, in-situ electrode structures with sub 10 micron capacitive gaps are reported for electrostatic transduction.In order to streamline the realization of MRIG control strategies, two new Si-MEMS MRIG architectures were also developed as a part of this thesis: Toroidal Ring Gyroscope (TRG) and Dual Foucault Pendulum (DFP) Gyroscope. Toroidal Ring Gyroscope consists of an outer anchor, concentric ring suspension system, and inner electrode assembly. Q-factors above 100,000 were obtained with this architecture at a compact size of 1760 micron. First demonstration of a parametrically driven MRIG is also reported as a part of this work, showing better than 20 ppm scale factor stability at 360 °/s rate input. Dual Foucault Pendulum (DFP) architecture is a conventionally machined lumped mass Micro Rate Integrating Gyroscope implemented using in-house silicon-on-insulator technology. It is believed that this two mass DFP architecture is the minimal realization of a dynamically balanced, lumped mass MRIG.Finally, a custom, multi-purpose FPGA/DSP based control system was developed to demonstrate interchangeable rate and rate integrating mechanization of micro-scale gyroscope architectures developed in this thesis. Continuous Rate Integrating Gyroscope operation is demonstrated, by electronically compensating structural imperfections via control loops, such as Phase Locked Loop (PLL), Amplitude Gain Control (AGC), quadrature null loop, and closed-loop parametric drive.
State Estimation Technique for VRLA Batteries for Automotive Applications

The state-of-charge (SOC) and state-of-health (SOH) estimation of batteries play important roles in managing batteries for automotive applications. However, an accurate state estimation of a battery is difficult to achieve because of certain factors, such as measurement noise, highly nonlinear characteristics, strong hysteresis phenomenon, and diffusion effect of batteries. In certain vehicular applications, such as idle stop–start systems (ISSs), significant errors in SOC/SOH estimation may lead to a failure in restarting a combustion engine after the shut-off period of the engine when the vehicle is at rest, such as at a traffic light. In this paper, a dual extended Kalman filter algorithm with a dynamic equivalent circuit model of a lead–acid battery is proposed to deal with this problem. The proposed algorithm adopts a battery model by taking into account the hysteresis phenomenon, diffusion effect, and parameter variations for accurate state estimations of the battery. The validity of the proposed algorithm is verified through experiments by using an absorbed glass mat valve-regulated lead–acid battery and a battery sensor cable for commercial ISS vehicles.
Perception of Dynamic Point Light Facial Expression

This study uses point light displays both to investigate the roles of global and local motion analyses in the perception of dynamic facial expressions and to measure the information threshold for reliable recognition of emotions. We videotaped the faces of actors wearing black makeup with white dots while they dynamically produced each of 6 basic Darwin/Ekman emotional expressions. The number of point lights was varied to systematically manipulate amount of information available. For all but one of the expressions, discriminability (d′) increased approximately linearly with number of point lights, with most remaining largely discriminable with as few as only 6 point lights. This finding supports reliance on global motion patterns produced by facial muscles. However, discriminability for the happy expression was notably higher and largely unaffected by number of point lights and thus appears to rely on characteristic local motion, probably the unique upward curvature of the mouth. The findings indicate that recognition of facial expression is not a unitary process and that different expressions may be conveyed by different perceptual information, but in general, basic facial emotional expressions typically remain largely discriminable with as few as 6 dynamic point lights.
Process thinking and the family business

Time in family businesses plays a crucial role, connecting past, present and future in a non-linear flux. Despite the centrality of time to change and the becoming of organisations, and of family businesses in particular, currently the research in this field primarily relies on variance theory. In this chapter, I aim to show the potential for process thinking and sensemaking in family business research to investigate how dynamic phenomena evolve over time. After having briefly introduced the process approach and its development, I review how it has been used in the family business field to cope with a wide range of phenomena as social capital, business failure and portfolio entrepreneurship. Family business is an idiosyncratic context for implementing process studies due to the relevance of time and of social actors’ interaction. Process thinking may provide us with a better understanding of already studied phenomena analysed from a different perspective while also enabling the investigation of new areas evolving in time.
Analyst forecasts: sales and profit margins

Sales and profit margins are two popular earnings components discussed in the media. We study properties of one-year-ahead analyst forecasts of these two components. As sales are in dollar amounts and profit margin is a ratio, we propose robust statistical methods to assess and contrast their forecast properties. We find that four performance properties associated with earnings forecasts—optimism, relative accuracy with respect to benchmark model forecasts, forecast suboptimality, and serial correlation of forecast errors—apply to both sales and profit margins. Sales forecasts, in general, perform better than profit margin forecasts. Further evidence also shows that sales forecasts perform better than profit margin forecasts in terms of how their forecast errors explain earnings forecast errors and how realized surprises affect adjustments of the respective forecasts. We also find that a better information environment, surrogated by size, improves sales forecasts more than profit margin forecasts. All of these findings suggest that forecasting profit margins is inherently more difficult than forecasting sales.
Power Management Techniques for Micropower Energy Scavenging

Advances in semi-conductor technology have led to the reduction in size and power consumption of microelectronic circuits. With the miniaturization and increased efficiency of these circuits there are more potential applications for wireless sensor networks and portable electronic equipment. These applications include structural integrity and environment monitoring such as aircraft wing health monitoring and forest fire and natural disaster detection. Biomedical devices have also benefited from the improved size and performance of microelectronics. This thesis studies power management techniques to enable efficient energy scavenging at micropower input power levels from a number of power sources. These sources range from temperature gradients, radio frequency (RF) radiation, solar power, and mechanical vibrations. The scavenged energy is used to improve the performance and distribution of wireless sensors and devices by supplementing or potentially replacing the local power supply of the sensor or device. The major focus of this thesis is to combine source characterization, power management theory, detailed power loss analysis, and ultra-low power circuit design to maximize the extraction of energy from source and deliver it to the wireless sensor or device. The resistor emulation techniques from power factor correction (PFC) are leveraged to load an RF rectifying antenna (rectenna) such that maximum power point tracking (MPPT) of the rectenna is achieved naturally. An application specific integrated circuit (ASIC) is developed to implement this technique after experimental verification with commercially available discrete circuitry. Experimental results show efficient energy scavenging at power levels below 2 microwatts. In addition to resistor emulation, synchronous electric charge extraction (SECE) for energy scavenging from piezoelectric generators is also investigated. The presented techniques allow for the scavenging of usable power for sensors at power levels significantly lower than previous research.
On the Application of Cognitive Compatibility to Aircraft Systems Design and Evaluation

Much research has been performed examining various aspects of the relationship between displays and controls in the aircraft cockpit as well as other, related contexts. Yet, the applicability of this work to the design or evaluation of modern aircraft systems is still limited. One reason for this limitation is the disproportionate focus on the physical (spatial) aspects of display-control relationships, often referred to as stimulus-response (S-R) compatibility, relative to the cognitive or perceptual aspects. Another reason for the limited applicability of this research to applied systems design is the lack of computer-aided models and automated tools which incorporate the established principles and guidelines. It is argued here that in order to optimize both the design process and design result of future cockpit interfaces, models of cognitive compatibility must be developed and incorporated into computer-based design and evaluation tools.
EFFECT OF DIET AND EXERCISE-INDUCE WEIGHT LOSS ON LEVEL OF RESISTIN IN PATIENT WITH OBESITY

Мета дослідження. Метою цього дослідження було визначити вплив дієти та фізичного навантаження на рівень резистину і оцінити взаємозв'язок резистину зі змінами ваги. Матеріали та методи. До цього дослідження було включено 133 особи із надмірною вагою/ ожирінням (73 чоловіки та 60 жінок) віком від 29 до 57 років. Кожен пацієнт проходив клінічну оцінку під час консультації (з виміром маси тіла та зростання), біологічні тести. Усі учасники утрималися від будь-якої важкої фізичної активності за 48 годин до вимірювань та були рандомізовані в одну з трьох груп (фізичне навантаження та/або дієта) та контрольну групу. Результати. Зі 133 пацієнтів у групі фізичного навантаження (ФН) було 39 пацієнтів, 34 суб'єктів – у групі дієтотерапії (Д), 30 – у комплексній групі (ДФН) та 30 – у контрольній групі. Застосування дієти та фізичних вправ сприяло статистично значимим змінам у масі тіла порівняно з контролем. Статистично значущі зміни рівня резистину спостерігалися у пацієнтів із групи ДФН. Статистично значущі зміни у рівні глюкози були зареєстровані у пацієнтів із Д-групи (P < 0,05). Рівні інсуліну (P = 0,076) та резистину (P = 0,137) мали тенденцію до зниження групи ФН, але статистично достовірних відмінностей встановлено не було. Однофакторний регресійний аналіз показав, що зміни резистину були взаємопов'язані зі співвідношенням обсяг талії (ОТ) та обсяг стегна (ОС) та з інсуліном. Регресійний аналіз виявив статистично значущі взаємозв'язки між змінами резистину та інсуліну (r = 0,363, R2 = 0,174, P = 0,038) та співвідношенням ОТ/ОС (r = 0,408, R2 = 0,158, p = 0,018). Висновки. У пацієнтів із комплексної групи з фізичним навантаженням та дієтотерапією демонстрували статистичне значуще зниження маси тіла, рівня резистину та резистентності до інсуліну. Резистин статистично значно корелює з рівнем інсуліну, але не з індексом HOMA. Регресійний аналіз виявив статистично значущі взаємозв'язки між змінами резистину та інсуліну (r = 0,363, R2 = 0,174, P = 0,038) та співвідношенням ОТ/ОС (r = 0,408, R2 = 0,158, p = 0,018).
End-to-end network measurement and its applications in peer-to-peer networks

End-to-end measurements between Internet hosts are important in understanding network characteristics and enhancing the performance of applications. In this thesis, we investigate various end-to-end measurement techniques to characterize network performance. A general end-to-end measurement framework, which summarizes the current research efforts and highlights the insights into the measurement practice, is proposed. We first investigate the end-to-end available bandwidth measurement problem through the use of an active probing stream. Based on the probing load, bandwidth probing methods can be classified into two categories: queueing model-based versus selfcongestion probing. In the queueing model-based approach, we studied two probing sequences with different inter-arrival time distributions: Poisson and periodic. The study of the departure process of the probing stream leads to analyze M1 + M2/GIi/1 and D + M/GIi/1 using the exact queueing analysis and the approximation methods. Of particular interest to our investigation, is the squared coefficient of variation (SCV) of the inter-departure process of the probing stream. In a real measurement system, given the measured SCV of the probing stream, the model is inverted to infer the load of the cross traffic on an end-to-end path. In the self-congestion approach, we propose a unified self-congestion probing framework for bandwidth measurement. The self-congestion probing for available bandwidth measurement and TCP congestion control can be treated as special cases of this