Miracle-dz/UniFAR-FTUs huggingface dataset:
Internationalization challenges for SMEs: evidence and theoretical extension

Purpose The paper aims to examine new research on the internationalization of small- and medium-sized enterprises (SMEs) in Pacific Island Nation country Fiji. Design/methodology/approach A multiple case qualitative method was used which adopted a purposeful sampling methodology through semi-structured interviews to test propositions and present preliminary findings. Findings The authors find that, SME internationalization in Fiji is driven by management competence (MC) and entrepreneurial orientation (EO) and is hindered by the unfavourable institutional environment. The authors then develop a conceptual model and propositions to further explore these enablers and the inhibitors of Fiji SME internationalization. The authors’ findings have important implications for managers in improving their firms’ international performance. Originality/value This is a pioneering effort to evaluate the relationship between the factors of EO, MC and institutional distance and their impact on the international performance of SMEs. This paper contributes to the existing literature on international entrepreneurship through the examination of SMEs’ internationalization activities in Fiji.
Speech Augmentation via Speaker-Specific Noise in Unseen Environment

Speech augmentation is a common and effective strategy to avoid overfitting and improve on the robustness of an emotion recognition model. In this paper, we investigate for the first time the intrinsic attributes in a speech signal using the multi-resolution analysis theory and the Hilbert-Huang Spectrum, with the goal of developing a robust speech augmentation approach from raw speech data. Specifically, speech decomposition in a double tree complex wavelet transform domain is realized, to obtain sub-speech signals; then, the Hilbert Spectrum using Hilbert-Huang Transform is calculated for each sub-band to capture the noise content in unseen environments with the voice restriction to 100−4000 Hz; finally, the speechspecific noise that varies with the speaker individual, scenarios, environment, and voice recording equipment, can be reconstructed from the top two high-frequency sub-bands to enhance the raw signal. Our proposed speech augmentation is demonstrated using five robust machine learning architectures based on the RAVDESS database, achieving up to 9.3 % higher accuracy compared to the performance on raw data for an emotion recognition task.
The pandit : traditional scholarship in India

In January 1999, the distinguished scholar Pandit Dr Parameswara Aithal retired from his position at Heidelberg University. To mark this occasion, Professor Axel Michaels organised a symposium on the institution of the Pandit and the future of traditional Sanskrit scholarship in India and the West. Pt. Aithal, an internationally esteemed expert in Dharmashastra and manuscriptology, was born in Kota (Karnataka). He received his early Sanskrit education in the traditional method at home and became a staff member of the Adyar Library and Reserch Centre, Chennai, in 1962. In 1968, he joined the South Asia Institute, Heidelberg University, as a Sanskrit lecturer where he stayed for about thirty years. The present volume contains the learned papers of the conference which cover a wide range of topics: the pandit as a private scholar, university teacher, public intellectual or legal adviser; traditional ways of Sanskrit teaching and learning, especially the methods of memorisation and transfer of traditional knowledge; the relevance of traditional Sanskrit grammar for the learning of Sanskrit; the prestige of Sanskrit and the social standing of pandits; the special guru-shishya-relationship; the relationship between pandit and professor in academic systems; life histories of some well-known pandits such as Krishnashastri Chiplunkar, Hazari Prasad Dvivedi, Gopinath Kaviraj, V S Apte and others --the role of Tantrik pandits. The contributors of this Festschrifts are friends and colleagues of Pandit Aithal.
Modeling and Robust Control of Heterogeneous Vehicle Platoons on Curved Roads Subject to Disturbances and Delays

This paper presents an integrated platoon control framework for heterogeneous vehicles on curved roads with varying slopes, aerodynamic drag, and wireless communication delays. First, a linear heterogeneous vehicle platoon model with decoupled longitudinal and lateral dynamics is built based on nonlinear feedback linearization and arc-length parametric transformation of an arbitrary curved road. The external disturbances are also considered, including the up-down road slopes, wind and equivalent time-delays caused by the wireless communication delay and discrete data in onboard sensors. Second, to achieve stable platoon control on a curved road, the platoon uses the state-feedback control method in the longitudinal direction while each vehicle tracks the centerline of the curved road to realize lateral control. Longitudinally, an $ H_\infty$ platoon controller is designed based on the Lyapunov-Krasovskii functional to ensure the inner-vehicle and string stability of the platoon, which suffers from parameter uncertainty, and external disturbances. Additionally, the $ \mathcal {L}_2$ string stability is defined to guarantee that the perturbations do not grow unbounded as they propagate through the platoon. Simulation results indicate that the proposed robust controller achieves proper platoon intervehicle spacing in both the longitudinal and lateral directions.
Predictors of quality of life in individuals with end stage renal disease

PREDICTORS OF QUALITY OF LIFE IN INDIVIDUALS WITH END STAGE RENAL DISEASE MAY 2008 KRISTEN L. MCDONALD, B.A., POMONA COLLEGE M.A., SAN FRANCISCO STATE UNIVERSITY Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Richard P. Halgin The primary purpose of this study was to examine the role of posttraumatic growth in determining quality of life outcomes for patients with a chronic medical condition. Predictors of quality of life were examined for 65 hemodialysis patients with End Stage Renal Disease, 82% of whom were Caucasian, 14% African American, 3% Hispanic, and 2% Native American. Multiple regression analyses were performed in which depressive symptomatology, posttraumatic growth, gender, interval since diagnosis, nutritional status, optimism, and social support were examined as main effects and moderators. Depressive symptomatology was associated with better quality of life when controlling for other variables. Optimism moderated the relationship between depressive symptomatology and quality of life, such that individuals high in optimism and depressive symptomatology had quality of life scores similar to scores obtained by those reporting few depressive symptoms. Similarly, there was a trend toward posttraumatic growth moderating the relationship between depressive symptomatology and quality of
A Framework to Measure/Assess the Utility of Profiling as a Counterterrorism Tool

The assessment of the usefulness of terrorist profiling is often conflated with an exaggerated presentation of the threat of terrorism as a basis to justify the use of terrorist profiling or an exaggerated impact of terrorist profiling as a basis to criticize its use by law enforcement officers. There is a considerable gap in the literature on terrorist profiling which fails to present a framework that can objectively engage in assessing/measuring the usefulness of terrorist profiling. The continued prevalence of terrorism continues to necessitate the existence of counterterrorism frameworks that allow law enforcement officers deploy pre-emptive control strategies. However, the difficulty posed by the existence of these strategies is whether they can actually be considered capable of assisting law enforcement officers detect, deter, or prosecute those engaged in acts of terrorism or its associated preparatory activities. This article proposes to address this gap by firstly examining previous attempts at analysing the usefulness of terrorist profiling and the different approaches more generally adopted to measure the usefulness of counterterrorism strategies. This discussion is followed by a presentation of a workable framework that can be applied to different manifestations of terrorist profiling to begin considering its usefulness as a counterterrorist tool. This article ultimately concludes that any assessment of terrorist profiling requires an assessment of the processes used to construct profiles separately from the assessment of the application of terrorist profiling in the field with a further layer of assessing considering its broader impact to question its overall usefulness as a counterterrorism tool.
Effect of Pointing Errors on the Performance of Hybrid FSO/RF Networks

The performance of a free space optics (FSO) transmission suffers from the atmospheric turbulence and the attenuation in foggy environment. By employing relay nodes, the error rate and the coverage area of the FSO communication system can be significantly improved. However, the pointing errors, generated because of the building sway, have the potential to eradicate the benefits of the relay-based FSO communication system. The effect of pointing errors in the presence of Gamma Gamma atmospheric fading together with path loss attenuation is considered in this paper. To counteract the adverse affects of the FSO link, a reliable millimeter-wave radio frequency (MMW RF) link is used as a backup. In this context, this paper proposes a cooperative decode-and-forward (DF)-relaying-based hybrid FSO/RF system with maximal-ratio-combining (MRC) at the destination. The system consists of FSO and RF sub-systems, where FSO sub-system has the priority to transmit and RF sub-system serves as a back up when the FSO sub-system is in outage. The exact and asymptotic outage probability and average symbol error rate (SER) expressions for the proposed system are derived in closed-form and the diversity order is determined. The effect of pointing errors on the system performance is analyzed extensively. The optimum values of transmit beam waist and radius of receiver aperture are determined. The theoretical results, which are validated by Monte-Carlo simulations, show that the proposed cooperative hybrid FSO/RF system drastically improves the system performance compared to single hop (SH) hybrid FSO/RF and cooperative FSO systems especially for large pointing errors scenario.
A Conic Approach to the Implementation of Reduced-Form Allocation Rules

We examine the implementation of reduced-form allocation rules in mechanism design problems. To handle the problem, we adopt a conic approach which uses a lift-and-project method to construct a projection cone and find its finite generators. This results in a set of implementable reduced forms for implementation. We then characterize projection cones for several typical mechanism design problems including single-item auctions, bilateral trade, compromise, and multiple-item auctions with group capacity constraints. We find that the implementation condition in general has a linear characterization by a class of sign functions, which is larger and richer than the well-known class of characteristic functions found by Border. These results admit meaningful economic interpretations.
Extracting heavy metal stress indicators from remote sensing imagery using WOFOST model and wavelet packet decomposition algorithm

Heavy metal pollution of crops seriously endangers food security and indirectly threatens human health. Direct measures in the fields and laboratories through on-site sample collection, testing, and analysis are time-consuming and labor intensive, thereby prohibiting their applications in large-scale monitoring. Remote sensing techniques provide an alternative means through examining above-ground vegetation status, e.g. leaf area index (LAI). Heavy metals, however, are typically accumulated in the root of crops, which may also be affected by a large number of external environmental factors besides heavy metals. The objective of this paper, therefore, is to identify heavy metal stress indicators of crops through integrating LAI extraction from remote sensing imagery, weight of rice roots (WRT) estimation by the World Food Study (WOFOST) model, and heavy metal stress indicator identification with the wavelet packet decomposition (WPD) method. First, LAI was retrieved from the HJ CCD data over three continuous years through constructing a relationship between LAI and normalized difference vegetation index (NDVI). Next, dry weight of rice roots (WRT) curves over these three continuous years were estimated using the WOFOST model with multi-temporal LAIs are inputs. Finally, a component (e.g. cfs 14) was identified to represent the heavy metal pollution status with the Wavelet Packet Decomposition (WPD) of the WRT curves of these three years. Validation results suggest that the identified component can successfully represent different levels of heavy metal stress.
Current Status of Treatment of Radiation Injury in the United States

Abstract : A radiation or nuclear incident would likely result in vast numbers of patients, many of whom would require novel therapy. Although the number of radiation victims in the United States (USA) has been limited, we base our doctrine for treating radiation injuries on i) historical data, ii) animal research, and iii) human results derived from present medical treatment such as the care provided to cancer patients undergoing radiation therapy or chemotherapy. The medical management of radiation injury is complex. Radiation injury may include the acute radiation syndrome (ARS), external and internal contamination, and cutaneous injury. Human and animal data have shown that optimal medical care can raise the nominal lethal dose of radiation by 50% or more. The currently recommended treatment of the ARS in the USA involves supportive care, early use of cytokines, and judicious use of antibiotics. Supportive care for any significant radiation injury also would require the use of intravenous fluids, antiemetics, antidiarrheals, pain medications, and blood product support. The role for cytokines will be described in some detail. The role for stem cell transplantation is controversial as no survival benefit has been demonstrated for this modality. The U.S. Food and Drug Administration (FDA) has published clear guidelines for the use of potassium iodide (KI) to block uptake of radioactive iodine. Treatment of internal contamination requires identification of the radioactive isotope and then appropriate individual programs of treatment. The FDA recently has approved the use of diethylenetriaminepentaacetate (DTPA) for the treatment of internal contamination with plutonium, americium and curium. The FDA also recently approved the use of ferric ferrocyanide (Prussian Blue) for the treatment of internal contamination by radioactive cesium or thallium.
Development and assessment of na elearning course on senology for radiographers: a stratified randomised control trial

Breast cancer is a serious public health problem, and screening is a critical tool to combat the mortality rate of the disease. Mammography technique is considered the best imaging examination for this screening and the radiographer plays a crucial role in this process. For this, the radiographer must be properly prepared and should therefore be subject to specific training and continuing education. Therefore, there should be training programmes, and eLearning has been revealed a useful tool and an alternative to the traditional education method. The objectives of this work include the knowledge promotion and understanding of all aspects related to the breast illness and patient care required to radiographers. To achieve this, we proposed to develop an easy-touse course in eLearning environment and assess about its efficacy, effectiveness and the users’ satisfaction, according to evaluation levels 1 and 2 from Kirkpatrick’s framework. A randomised controlled trial was performed with radiographers and radiology students, using as instruments individual satisfaction questionnaires and pre and post-knowledge tests for further comparisons, respectively. Intention-to-treat and per-protocol analysis were considered in the statistical analysis. As result, a total of 54 participants were included in the intervention group (20 students and 34 radiographers) and 53 in the control group (19 students and 34 radiographers). The intention-to-treat analysis showed a mean improvement of 21 percentual points (pp) in the intervention group, compared with 4 pp in the control group (p<0.001). Radiographers clearly improved with the intervention (23pp vs 4pp.; p=0.004). Although the effect was not clear in students (18pp vs 5pp; p=0.098), we found differences in post-test results between intervention and control (88% vs 63%; p=0.003) whereas such difference was absent in pre-test (63% vs 63%; p=0.106). Therefore, an additional per-protocol analysis was applied to reduce the influence of lost to follow-up individuals, which resulted in a higher effect (26pp vs 2pp; p<0.001),
An Improved Goodness of Pronunciation (GoP) Measure for Pronunciation Evaluation with DNN-HMM System Considering HMM Transition Probabilities

Goodness of pronunciation (GoP) is typically formulated with Gaussian mixture model-hidden Markov model (GMM-HMM) based acoustic models considering HMM state transition probabilities (STPs) and GMM likelihoods of context dependent phonemes. On the other hand, deep neural network (DNN)HMM based acoustic models employed sub-phonemic (senone) posteriors instead of GMM likelihoods along with STPs. However, each senone is shared across many states; thus, there is no one-to-one correspondence between them. In order to circumvent this, most of the existing works have proposed modifications to the GoP formulation considering only posteriors neglecting the STPs. In this work, we derive a formulation for the GoP and it results in the formulation involving both senone posteriors and STPs. Further, we illustrate the steps to implement the proposed GoP formulation in Kaldi, a state-of-the-art automatic speech recognition toolkit. Experiments are conducted on English data collected from Indian speakers using acoustic models trained with native English data from LibriSpeech and Fisher-English corpora. The highest improvement in the correlation coefficient between the scores from the formulations and the expert ratings is found to be 14.89% (relative) better with the proposed approach compared to the best of the existing formulations that don’t include STPs.
Impact of Molybdenum Compounds as Anticancer Agents

The aim of this mini review was to report the molybdenum compound intervention to control cancer disease. The intervention explains its roles and progress from inorganic molybdenum compounds via organomolybdenum complexes to its nanoparticles to control oesophageal cancer and breast cancer as case studies. Main contributions of molybdenum compounds as anticancer agents could be observed in their nanofibrous support with suitable physicochemical properties, combination therapy, and biosensors (biomarkers). Recent areas in anticancer drug design, which entail the uses of selected targets, were also surveyed and proposed.
Tight framelets on graphs for multiscale data analysis

In this paper, we discuss the construction and applications of decimated tight framelets on graphs. Based on graph clustering algorithms, a coarse-grained chain of graphs can be constructed where a suitable orthonormal eigenpair can be deduced. Decimated tight framelets can then be constructed based on the orthonormal eigen-pair. Moreover, such tight framelets are associated with filter banks with which fast framelet transform algorithms can be realized. An explicit toy example of decimated tight framelets on a graph is provided.
Cellar Temperature Affects Brettanomyces bruxellensis Population and Volatile Phenols Production in Aging Bordeaux Wines

Brettanomyces bruxellensis is a spoilage yeast particularly dreaded in red wines, where it produces volatile phenols with sensory properties that lead to wine spoilage. The development of this yeast often occurs during wine aging, especially during the summer. We show that in the Bordeaux region, the temperatures of some cellars rise significantly in July, August, and September. This greatly increases the growth rate of B. bruxellensis strains in both permissive and more unfavorable wines. Therefore, although temperature does not affect the specific formation rate of ethyl phenol, raising the wine temperature from 2 to 6°C makes volatile phenols appear both earlier and faster, regardless of the wine or the yeast strain present. Closer control of active yeast populations and closer monitoring of aging wines is thus essential in the summer, particularly in cellars with poor temperature regulation.
Four Essays in the Law and Economics of Novel Technologies

Novel technologies have changed and continue to change modern life. While providing enormous benefits to society, novel technologies often involve unknown risks. When these risks fall on other agents, as is often the case, the problem of risk externalities emerges. Liability is a ubiquitous and heavily researched instrument for regulating risk externalities and the instrument on which this dissertation focuses. There are two parts to this dissertation. The first part examines the relationship between liability rules and novel technologies from a general perspective. The second part concentrates on a specific novel technology, solar geoengineering. The first part focuses on the interaction between learning about novel risks and liability regulation. While the analysis of liability rules is usually undertaken in static settings, novel technologies create a dynamic relationship between liability regimes and the technologies they govern. Risks emerging from novel technologies are uncertain and poorly understood. Liability regimes infl uence if and how novel technologies are adopted, shaping the incentives for the potential use of novel technologies. Consequently, a dynamic interaction arises between how liability regimes govern novel technologies and the learning that takes place about novel technologies' potential risks. The first part's main contribution is the introduction of a learning mechanism operating at the post-market stage that provides an economic rationale for the widespread use of exemptions for harm arising from novel risks found in the US, the EU and beyond. The second part of this dissertation investigates the relationship between liability and solar geoengineering. Potential risks from solar geoengineering are a widespread and serious concern, making governance an overarching topic in the solar geoengineering literature. Liability regimes, specifically, have received considerable attention in the debate. The second part first examines the challenge of causation in climate litigation in an interdisciplinary research effort, taking into account the incentive structure of evidence production in a climate liability trial and its repercussions for overcoming the challenge of causation. It then provides an analytical model of solar geoengineering liability, considering the unique solar geoengineering incentive structure. Lastly, the second part extends the literature on assessing regional differences emerging from solar geoengineering, by considering climate preferences diverging from historic climate conditions. In that, it sheds further light on structural dimensions of regional solar geoengineering disagreement, contributing to the understanding of the solar geoengineering governance problem more generally.