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Infrared thermal imaging presents significant potential in various domains. However, the widespread development of this technology is hindered by the high cost associated with acquiring high-quality thermal imaging sensors. To overcome this challenge, super-resolution techniques have emerged as a viable solution for extracting valuable information from low-resolution thermal images. While generative adversarial networks (GANs) have been widely adopted for thermal imaging super-resolution, their performance is limited by the inherent lack of detail in low-resolution training images, resulting in reduced fidelity and accuracy in generating high-resolution reconstructions. To tackle this challenge, this letter introduces FEGAN, a novel approach that enhances the performance of GANs by incorporating a feature-oriented enhanced (FE) mechanism within the generative network (GN). The FE plays a pivotal role in extracting high-frequency texture and edge details from low-resolution inputs and reconstructing them into enhanced images. This process substantially improves textures and edges within the training set of thermal images. Furthermore, refinements have been applied to both the GN and the discriminative network (DN) to enhance feature extraction efficiency. The experimental findings unequivocally demonstrate the superior performance of FEGAN compared to state-of-the-art methods. FEGAN achieves impressive performance metrics, including PSNR of 27.18, SSIM of 0.6523, FSIM of 0.5500, and LPIPS of 0.1221, highlighting its remarkable capabilities in the realm of thermal image super-resolution.

Efficient construction of ubiquitous carbon–carbon bonds between two electrophiles has garnered interest in recent decades, particularly if it is mediated by nonprecious, first-row transition metals. Reductive coupling has advantages over traditional cross-coupling by obviating the need for stoichiometric air- and moisture-sensitive organometallic reagents. By harnessing transition metal-catalyzed reductive coupling as a powerful tool, intricate molecular architectures can be readily assembled through the installation of two C–C bonds across π systems (alkenes/alkynes) via reaction with two appropriate electrophiles. Despite advances in reductive alkene difunctionalization, there remains significant potential for the discovery of novel reaction pathways. In this regard, development of reductive protocols that enable the union of challenging alkyl/alkynyl electrophiles in high regio- and chemoselectivity remains a highly sought-after goal.

Driver drowsiness is a major factor that leads to traffic accidents and loss of life. A popular drowsiness detection (DD) method is based on machine learning (ML) and monitoring electroencephalogram (EEG) signals from the scalp. However, the setup is usually bulky and too obtrusive for use in daily life. In addition, the data processing unit is usually placed in large hardware such as cloud servers and personal computers that receive the EEG signal from wearable sensors wirelessly. This results in a cumbersome system that lacks mobility and suffers high latency and power consumption because of wireless connection. The behind-the-ear (BTE) EEG is a novel approach that promises a more convenient and practical solution than scalp-EEG. Recent advances in tiny ML (TinyML) mean that on-device ML-based driver DD (DDD) could also be realized to avoid the limitations mentioned above. This article presents the design of a novel BTE EEG-based DDD system that uses a wearable headband device and runs built-in neural network (NN) models. The device collects EEG signals from four proposed BTE locations that are then preprocessed. Welch’s method is applied to extract the relative power spectral density (rPSD) ratio of three EEG bands (theta, alpha, and beta). Two NN models [multilayer perceptron (MLP) and convolutional NN (CNN)] were trained and compared to a support vector machine (SVM) before deployment in the embedded device. Then, a benchmark test was performed to evaluate the on-device performances of these models. The test results established the practicality and feasibility of the proposed system for on-device DDD.

Falling is one of the primary causes of firefighter casualties. Therefore, early fall detection, followed by reliable and timely notification, is vital to ensure the survival of firefighters. However, due to complex and diverse firefighting scenarios, current fall detection systems (FDSs) are inadequate, especially in terms of accuracy and real-time applications. Hence, in this study, a wearable pre-impact FDS (PIFDS) for firefighters is proposed. We also evaluated the feasibility of using machine learning (ML) and ensemble learning (EL) methods deployed on the edge node to simultaneously improve the real-time performance and accuracy. Moving thresholding method is introduced to overcome the class-imbalanced issue due to fewer samples acquired during the pre-impact (PI) phase. Based on 14 firefighters’ data collection, the experimental results revealed that a Decision Tree classifier with optimized parameters (DT-ED4) outperformed other ML and EL methods in a tradeoff between processing time and accuracy. The results also showed that our system can detect falls before the impact with an average lead time of 447.9 ms, sensitivity of 95.10%, and specificity of 97.99%. The system’s heterogeneous IoT network architecture facilitated remote monitoring and alerts that enabled the incident commander (IC) to execute the rescue mission immediately upon notification. This study enhances the practicability of PIFDS and extends the application range of PIFDS from healthcare to firefighting.

The popularity of nature-based tourism revolves around tourist experiences. Tourism, as an experiential good has the potential to impact on tourists’ awareness, appreciation, and actions concerning the environment and wildlife. User preferences and valuations of nature and wildlife may change because of the experience. Exploring user valuations of environmental goods before and after the experience is, however, an area that has been given little attention in the literature. We use discrete choice experiments (DCEs) to evaluate tourists’ preferences and valuations for nature, wildlife and related services before and after experiencing a nature tour. The results demonstrate how the unfamiliarity of the good consumed (in this case fauna and flora in a hitherto unseen natural environment) affect the non-use valuations of consumers. We find that tourists’ valuations for nature and wildlife significantly improve after experiencing the nature tour.

Schools devote considerable attention in identifying and implementing evidence-based prevention programmes to enhance student development and functioning. A major challenge faced is with organising the theory, research and practice of the implementation and dissemination process. This poses even greater challenges to schools because these are complex systems and rarely implement programmes singly to meet the varied needs of their students. Beyond establishing efficacy, there is little documentation about how these programmes have been adapted for diverse student populations. We utilised the Prevention System Support component of Wandersman et al.’s (Am J Community Psychol 41:171–181, 2008) Interactive Systems Framework for Dissemination and Implementation to systematically elicit key general and programme-specific capacity builders that promote the implementation of school prevention programmes in Singapore schools. SWOT analysis completed by 308 school programme leaders yielded five organisational-level general capacity builders and two programme-specific factors related to teacher training and technical support. Fewer opportunities and threats present as challenges to strengthening school capacity to deliver programmes effectively. Implications arising from the analysis were discussed.

Negative emotional responses are a growing problem among drivers, particularly in countries with heavy traffic, and may lead to serious accidents on the road. Measuring stress- and fatigue-induced emotional responses by means of a wireless, wearable system would be useful for potentially averting roadway tragedies. The focus of this study was to develop and verify an emotional response-monitoring paradigm for drivers, derived from electromyography signals of the upper trapezius muscle, photoplethysmography signals of the earlobe, as well as inertial motion sensing of the head movement. The relevant sensors were connected to a microcontroller unit equipped with a Bluetooth-enabled low-energy module, which allows the transmission of those sensor readings to a mobile device in real time. A mobile device application was then used to extract the data from the sensors and to determine the driver's current emotion status, via a trained support vector machine (SVM). The emotional response paradigm, tested in ten subjects, consisted of 10 min baseline, 5 min prestimulus, and 5 min poststimulus measurements. Emotional responses were categorized into three classes: relaxed, stressed, and fatigued. The analysis integrated a total of 36 features to train the SVM model, and the final stimulus results revealed a high accuracy rate (99.52%). The proposed wearable system could be applied to an intelligent driver's safety alert system, to use those emotional responses to prevent accidents affecting themselves and/or other innocent victims.

Adaptation has become a key priority in dealing with climate change issues. However, successful implementation of climate change adaptation entails substantial financial investment. This study examines differences in Nepalese farming households’ willingness to contribute to the implementation of adaptation programs across monetary and non-monetary modes of payments. To this end, we undertake discrete choice experiments with monetary payment and labor contributions as the payment vehicles. We find that farmers are interested in participating in and financially supporting the implementation of climate change adaptation initiatives that increase the availability of climate-adaptive crop varieties, improve soil quality, expand irrigation and build farmers’ capacity in terms of climate-adaptive farming. Factors influencing farmers’ participation in adaptation programs include age, income, access to extension services, size of land holdings, number of farm parcels, climate change perception and climate change experience. Furthermore, the findings reveal significant heterogeneity in the farmers’ preferences across three agro-ecological regions in Nepal. Our findings also strengthen the methodological validity of the results of the choice experiment, which indicated that farmers are willing to pay significantly more when asked to make a payment in terms of a labor contribution compared to a monetary payment for the implementation of adaptation programs. Overall, the findings of this study justify the relevance of implementing agricultural adaptation programs in Nepal.

Food security is a global challenge. With rising world population and demand for food being compounded by resource and arable land constraints, raising the efficiency of food production and use has become increasingly important. While much of the research on food security is focused on farm efficiency and productivity, most neglect post-harvest (PH) handling which is critical in determining the availability of food. In this study, we employ the network Data Envelopment Analysis (DEA) model to evaluate the PH efficiency of milling, using data from Kenya’s rice processing industry. The results show lower efficiency scores when using a network DEA model, which reflects its greater discriminatory power when compared to the standard DEA approach. The study also quantified sources of productive efficiency using a fractional regression model and identified storage space and distance to market as having an impact on drying efficiency; while experience, age of mill, servicing and energy type influenced milling efficiency. The results suggest that policy makers should focus on investing in drying technologies and storage facilities to improve drying efficiency. To improve milling efficiency, policy recommendations include enhancing millers’ access to better technologies, investing in reliable sources of energy and providing PH handling workshops to reduce PH losses.

The National Cancer Institute is the only referral centre in Malaysia that provides 68Ga-DOTA-peptide imaging. The purpose of this study is to determine the impact of 68Ga-DOTA-peptide PET/CT on the management of gastrointestinal neuroendocrine tumours (GI-NET). A cross-sectional study was performed to review the impact of 68Ga-DOTA-peptide (68Ga-DOTATATE or 68Ga-DOTATOC) PET/CT on patients with biopsy-proven GI-NET between January 2011 and December 2015. Suspected NET was excluded. Demographic data, tumoral characteristics, change of disease stage, pre-PET intended management and post-PET management were evaluated. Over a 5-year period, 82 studies of 68Ga-DOTA-peptide PET/CT were performed on 44 GI-NET patients. The most common primary site was the rectum (50.0%) followed by the small bowel, stomach and colon. Using WHO 2010 grading, 40.9% of patients had low-grade (G1) tumour, 22.7% intermediate (G2) and 4.5% high (G3). Of ten patients scheduled for pre-operative staging, 68Ga-DOTA-peptide PET/CT only led to therapeutic change in three patients. Furthermore, false-negative results of 68Ga-DOTA-peptide PET/CT were reported in one patient after surgical confirmation. However, therapeutic changes were seen in 20/36 patients (55.6%) scheduled for post-surgical restaging or assessment of somatostatin analogue (SSA) eligibility. When 68Ga-DOTA-peptide PET/CT was used for monitoring disease progress during systemic treatment (sandostatin, chemotherapy, everolimus and PRRT) in metastatic disease, impact on management modification was seen in 19/36 patients (52.8%), of which 84.2% had inter-modality change (switch to everolimus, chemotherapy or PRRT) and 15.8% had intra-modality change (increased SSA dosage). 68Ga-DOTA-peptide PET/CT has a significant impact on management decisions in GI-NET patients as it can provide additional information on occult metastasis/equivocal lesions and supply the clinician an opportunity to select patients for targeted therapy.

Flavivirus infections by Zika and dengue virus impose a significant global healthcare threat with no US Food and Drug Administration (FDA)-approved vaccination or specific antiviral treatment available. Here, we present the discovery of an anti-flaviviral natural product named cavinafungin. Cavinafungin is a potent and selectively active compound against Zika and all four dengue virus serotypes. Unbiased, genome-wide genomic profiling in human cells using a novel CRISPR/Cas9 protocol identified the endoplasmic-reticulum-localized signal peptidase as the efficacy target of cavinafungin. Orthogonal profiling in S. cerevisiaefollowed by the selection of resistant mutants pinpointed the catalytic subunit of the signal peptidase SEC11 as the evolutionary conserved target. Biochemical analysis confirmed a rapid block of signal sequence cleavage of both host and viral proteins by cavinafungin. This study provides an effective compound against the eukaryotic signal peptidase and independent confirmation of the recently identified critical role of the signal peptidase in the replicative cycle of flaviviruses.

Recently, there has been an interest in potential of antioxidant film incorporated with natural extract. The film was produced by using chitosan in the presence of pomelo (Citrus grandis) peel extract. In this study, there were 3 different effects of parameter that had been screened by using 2-Level Factorial which were concentrations of chitosan, pomelo peel extract and glycerol. Meanwhile, the response that had been investigated which was Total Phenolic Content (TPC). The data were analyzed by using ANOVA to screen the parameters affecting the antioxidant activity of films. Factor B (concentration of pomelo peel extract) and AC (interaction between the concentration of chiotosan and glycerol) were significant parameters in this studied. Meanwhile, FTIR spectra of antioxidant film revealed that there were interaction between functional groups of chitosan with pomelo peel extract with presence of aromatic ring C=C stretch at wavelength of 1555.3 cm-1 and 1410.7 cm-1. These results suggested that chitosan films containing pomelo peel extract have potential as the antioxidant thin film, which can be used for development of antioxidant food packaging materials.

Sign language has served as a communication medium between the Deaf community and society. Nonetheless, the practice of sign language is not common in Chinese society, along with a lack of professional sign language interpreters. Most existing studies on sign language recognition have only considered basic, simple, and static handshapes, which have not been practically implemented as real-world applications. To resolve the shortage of sign language interpreters, a sign language recognition application that interprets the sign language is required. Thus, the aim of this study was to develop and evaluate a sign language recognition framework using multi-modalities approach and spatio-temporal features that include dynamic handshapes. The proposed framework consists of three main parts, namely handshape recognition, movement tracking, and sign recognition. In this study, the use of hand skeletal data as features was also investigated, which were input to a bi-directional long short-term memory (Bi-LSTM) model for sign recognition. The proposed model was evaluated on a continuous Chinese sign language (CSL) dataset of 8 subjects with 1200 sample videos covering 100 signs. The experimental results demonstrated a true recognition rate of 98.75%, outperforming most of the state-of-the-art alternatives used for sign language recognition. The proposed sign recognition application can be deployed in public service sectors such as banks, hospitals, and police stations.

In neuroendocrine liver metastases of unknown primary, a multimodality approach is usually adopted and consists of transabdominal ultrasound, endoscopic ultrasound (EUS), computed tomography (CT), magnetic resonance imaging (MRI), nuclear medicine techniques, endoscopy and exploratory surgery. The purpose of the study is to evaluate the diagnostic value of 68Ga-DOTATATE positron emission tomography (PET)/CT as part of a multimodality approach in neuroendocrine liver metastases of unknown primary. Six patients (M:F = 5:1, age range 28–56 years) with immunohistochemically proven neuroendocrine liver metastases but inconclusive initial CT work-up were retrospectively analysed. Clinical finding, histopathology, comparative imaging and follow-up were used to validate the results when ethically justified. 68Ga-DOTATATE PET/CT identified the primary tumour in five out of six (83.3 %) patients: pancreas (n= 4) and stomach (n= 1). Out of three patients with indeterminate primary on initial CT, two patients were confirmed by 68Ga-DOTATATE PET/CT. Absence of uptake in indeterminate primary of one patient was later confirmed negative by histopathology. In another three patients with undetected primary on initial CT, primary site was demonstrated in all patients with unsuspected metastases in two patients on 68Ga-DOTATATE PET/ CT. No further work-up was done to confirm the primary in patients with distant metastases. Change of management was observed in three out of six (50 %) patients. Our small study indicates that 68Ga-DOTATATE PET/CT is a promising diagnostic option in the multimodality approach to neuroendocrine liver metastases of unknown primary origin.

The objective of this study was to investigate the effects of process variables on size of chitosan-alginate capsules produced through extrusion-dripping method. Chitosan-calcium chloride solution was extruded into sodium alginate to form chitosan-alginate capsules which have a defined inner core and membrane. The results showed that sodium alginate concentration, chitosan concentration, chitosan to calcium chloride concentration ratio, needle diameter, gelation time have significant effect on the diameter and membrane thickness of chitosan-alginate capsules. Under the tested condition, chitosan-alginate capsules with diameter in a range of 3.4 mm to 4.5 mm were produced. The membrane thickness of the capsules increased when the curing time increased from 5 min to 60 min. As the concentration of sodium alginate (0.3-0.9 %w/v) and chitosan (0.4-1.0 %w/v) increased, the diameter of the chitosan-alginate capsules increased. The diameter of chitosan-alginate capsules increased with decreasing the chitosan to calcium chloride concentration ratio (1:0.5-1:1.5).

Delivering high-quality, timely and formative feedback for students’ code-based coursework submissions is a problem faced by Computer Science (CS) educators. Automated Feedback Systems (AFSs) can provide immediate feedback on students’ work, without requiring students to be physically present in the classroom—an increasingly important consideration for education in the context of COVID-19 lockdowns. There are concerns, however, surrounding the quality of the feedback provided by existing AFSs, with many systems simply presenting a score, a binary classification (pass/fail), or a basic error identification (“The program could not run”). Such feedback, with little guidance for how to rectify the problem, raises doubts as to whether or not these systems can stimulate deep engagement with the related knowledge or learning activities. In this paper, we propose TAFFIES, a framework to scaffold the development of AFSs that promote high-quality, tailored feedback for student’s solutions. We tested our framework by applying it to develop an AFS to mark and provide feedback to 160 CS students in an introductory databases class. In contrast to most introductory-level coursework feedback and marking, which typically generate significant student reaction and change requests, our AFS deployment resulted in zero grade challenges. There were also no identified marking errors, or suggested inconsistencies or unfairness. Student feedback on the AFS was universally positive, with comments indicating an AFS-related increase in student motivation. The experience of designing, deploying, and evolving the AFS using TAFFIES is examined through reflective practice, student evaluation, and focus group (involving peer teachers) analysis.

This paper seeks to identify and quantify sources of the lagging productivity in Singapore’s retail sector as reported in the Economic Strategies Committee 2010 report. A two-stage analysis is adopted. In the first stage, the Malmquist productivity index is employed which provides measures of productivity change, technological change and efficiency change. In the second stage, technical efficiency estimates are regressed against explanatory variables based on a truncated regression model. Sources of technical efficiency were attributed to quality of workers while product assortment and competition negatively impacted on efficiency.

Ectopic thyroid or thyroid ectopia is a rare developmental anomaly with the prevalence of 1 per 100,000–300,000 population. Even rarer, such an anomaly manifests as dual thyroid ectopia. To our best knowledge, only one case has been reported on dual thyroid ectopia with Graves’ disease in the English literature. We present here a case of dual thyroid ectopia complicated by Graves’ disease, whereby the diagnosis was rendered through judicious use of various diagnostic modalities coupled with a close clinical follow-up. In this case, therapeutic consideration should be personalized with proper informed consent of the patient.Ectopic thyroid or thyroid ectopia is a rare developmental anomaly with the prevalence of 1 per 100,000–300,000 population. Even rarer, such an anomaly manifests as dual thyroid ectopia. To our best knowledge, only one case has been reported on dual thyroid ectopia with Graves’ disease in the English literature. We present here a case of dual thyroid ectopia complicated by Graves’ disease, whereby the diagnosis was rendered through judicious use of various diagnostic modalities coupled with a close clinical follow-up. In this case, therapeutic consideration should be personalized with proper informed consent of the patient.

Growing evidence suggests that the presence of a subpopulation of hypoxic non-replicating, phenotypically drug-tolerant mycobacteria is responsible for the prolonged duration of tuberculosis treatment. The discovery of new antitubercular agents active against this subpopulation may help in developing new strategies to shorten the time of tuberculosis therapy. Recently, the maintenance of a low level of bacterial respiration was shown to be a point of metabolic vulnerability in Mycobacterium tuberculosis. Here, we describe the development of a hypoxic model to identify compounds targeting mycobacterial respiratory functions and ATP homeostasis in whole mycobacteria. The model was adapted to 1,536-well plate format and successfully used to screen over 600,000 compounds. Approximately 800 compounds were confirmed to reduce intracellular ATP levels in a dose-dependent manner in Mycobacterium bovisBCG. One hundred and forty non-cytotoxic compounds with activity against hypoxic non-replicating M. tuberculosiswere further validated. The resulting collection of compounds that disrupt ATP homeostasis in M. tuberculosisrepresents a valuable resource to decipher the biology of persistent mycobacteria.

The motivation of the study stems from the results reported in the Excellence in Research for Australia (ERA) 2010 report. The report showed that only 12 universities performed research at or above international standards, of which, the Group of Eight (G8) universities filled the top eight spots. While performance of universities was based on number of research outputs, total amount of research income and other quantitative indicators, the measure of efficiency or productivity was not considered. The objectives of this paper are twofold. First, to provide a review of the research performance of 37 Australian universities using the data envelopment analysis (DEA) bootstrap approach of Simar and Wilson (2007). Second, to determine sources of productivity drivers by regressing the efficiency scores against a set of environmental variables.

The motivation of this paper stems from the growing concern of heavy pesticide use in developing countries such as Sri Lanka. Its excessive use affects the environment, the economy and farmers’ health and yet farmers still seem unaware of its ill-effects. More worrying is the lack of appropriate government efforts to address this problem. If neglected, heavy use of pesticide eventually renders land useless, reduces future farm output and productivity and can severely affect farmers’ health. This paper investigates pesticide use in agriculture and its impact on farm level technical efficiency using a metafrontier framework with stochastic frontier analysis. Data are collected through surveys of two groups of farmers in Sri Lanka. The first (described as the ‘non-hospitalized farmers’) are farmers who perceive that their ill-health is due to exposure to pesticides and obtained treatment but are not hospitalized. The second group (described as the ‘hospitalized farmers’) are farmers whose ill-health has been diagnosed by doctors and have been treated in hospital for exposure to pesticides. The results show that farmers overuse pesticides because of higher expectations of future returns which has led to an increase in inefficiency and remains unknown to the farmers. Determinants of inefficiency supports the argument that pesticide induced health problems reduce the health capital, while increasing farm level inefficiency.

This paper presents a pilot study of benefits derived from information and communications technology (ICT) adoption and use in medical practices in regional Australia. The study involved 122 regional medical practitioners. The results show that like the more general small business sector, the perception of certain benefits is associated with the size of the practice (in terms of employee levels) and/or the gender of the respondent practitioner. The data also showed that the level of skill of certain software used within the practice was significantly associated with the level of perceived benefit derived from ICT adoption and use.

Delamination and crack were considered as significant failures in electronic packaging. For these circumstances, Modified Crack Closure Integral method was tested and applied to determine crack growth rate and for the purpose to understand failures. TQFP package was successfully verified by using the method. A PBGA package was modeled for thermal distribution and moisture concentration in order to calculate vapor pressure acted on crack. The energy release rate was the main concern among fracture parameters, which had been proven fully related with vapor pressure and crack length ratio in popcorn cracking.

The purpose of this paper is to discuss the relevance of folk therapies or traditional medicine to counselling in Singapore. It addresses the meanings of the indigenous psychotherapies and then the rationales for understanding them. Three popular Chinese indigenous psychotherapies have been selected for discussion in terms of their aetiology and treatment beliefs about emotional problems: traditional Chinese medicine, dang-ki (Chinese shamanism), and feng-shui (Chinese geomancy). Findings from an empirical study are briefly presented to show that Chinese Singaporean clients hold eclectic belief systems encompassing both beliefs derived from thse indigenous psychotherapies and those from Western psychotherapies (e.g. psychodynamic and behavioural therapies). Two cases are presented to illustrate the application of these indigenous psychotherapies in counselling practice.

Upconversion emission has been obtained from Er-focused ion-beam (FIB) implanted GaN. Visible green emission at the 522- and 546-nm range were excited with infrared (IR) laser sources at either 840 or 1000 nm, or with both lasers simultaneously. By implanting closely spaced patterns with the FIB, we demonstrated the concept of storing data in Er-implanted GaN. Information stored as data bits consists of patterns of implanted locations as logic 1 and unimplanted locations as logic 0. The photon upconversion process in Er ions is utilized to read the stored information. This process makes use of the IR lasers to excite visible emission. The integrated upconversion emission power was measured to be ∼40 pW when pumped by a 840-nm laser at 265 mW and by a 1000-nm laser at 208 mW. Patterns as small as 0.5 µm were implanted and read. Three-dimensional optical memory based on rare-earth-doped semiconductors could in theory approach a storage capacity of 10^12 bits/cm^3.

By the use of the yeast two‐hybrid screen we have identified two proteins that interacted with UCH37: S14, which is a subunit of PA700 and a novel protein, UIP1 (UCH37 interacting protein 1). The interaction of UCH37 with S14 or UIP1 was confirmed by in vitro binding assay and in vivo co‐immunoprecipitation analysis. The C‐terminal extension of UCH37 is essential for interaction with S14 or UIP1 as shown by the yeast two‐hybrid assay and the in vitro binding assay. Furthermore, UIP1 blocked the interaction between UCH37 and S14 in vitro.

By the use of the yeast two-hybrid screen we have identified two proteins that interacted with UCH37: S14, which is a subunit of PA700 and a novel protein, UIP1 (UCH37 interacting protein 1). The interaction of UCH37 with S14 or UIP1 was confirmed by in vitro binding assay and in vivo co-immunoprecipitation analysis. The C-terminal extension of UCH37 is essential for interaction with S14 or UIP1 as shown by the yeast two-hybrid assay and the in vitro binding assay. Furthermore, UIP1 blocked the interaction between UCH37 and S14 in vitro.

In this paper we examine regulatory issues relating to electronic money. The discussion proceeds along three main lines. First, the focus of attention on the potential risks to the financial system is typically on the systemic risk arising from the payments system. Since issuers of electronic money automatically become part of the payments system we consider if the arguments relating to systemic risk originating in the payments system apply in the case of electronic money. Second, we examine the sharp divergence in regulatory approaches between the US and the EU, and suggest that a useful way of reconciling this divergence is to note the existence of a tradeoff between the efficiency of the financial system and the amount of risk assumed by the public sector. This means that there is not necessarily a “correct” answer to the desirability of regulation. Third, technological advances and financial innovations have made it easier for firms to engage in regulatory arbitrage. Competitive pressures may have encouraged financial centres to engage in competitive deregulation, resulting in a less than socially optimal level of regulation overall. It is therefore important that national authorities coordinate and harmonise their regulatory policies.