Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards A Model-Based Multi-Perspective Valuation Method for Smart Grid Initiatives: Foundations, Open Issues, and a Research Outlook

Information Technology (IT) is increasingly used in the electricity grid to cope with its multiple challenges, leading to its transformation into a so-called “smart grid”. While there exist various technically feasible pilot smart grid initiatives, a subsequent assessment of their “value” is a non-trivial task given the notion of value in smart grid projects. The notion of value usually encompasses, among others, readily quantiﬁable beneﬁts as well as qualitative ones, of diﬀerent types (economic, social, environmental), which must be assessed for single actors as well as for a network of actors. To support this assessment, several smart grid valuation methods have been proposed, and subsequently adopted in practice. Although those methods are actively used, a question appears to what extent they address all important factors relevant for smart grid valuation. To answer this question, in this technical report, we carry out a literature analysis aiming at (1) identifying existing valuation methods and the steps they propose, (2) identifying important valuation considerations, and (3) confronting these considerations with artifacts proposed by the existing valuation methods to identify open issues that should be tackled. Based on the conducted analysis, we identify, among others, the following main deﬁciencies: (1) only a limited scope of concerns relevant to valuation is covered, particularly a systematic consideration of stakeholders goals, value exchange scenarios, and IT infrastructure is lacking; and (2) a lack of instruments dedicated to fostering accessibility of valuation, in terms of establishing a shared understanding, communicating results, or actively involving diﬀerent stakeholders in the process. The ﬁndings reported here correspond to the ﬁrst stage of a larger project aiming at the development of a modeling method for the multi-perspective valuation of smart grid initiatives.
Computational Notebooks in Public Repositories

: A computational notebook – most prominently a Jupyter notebook – is a special kind of document that encompasses data, text, calculations, visualizations. Public repositories – most prominently GitHub – make them available. The number of notebooks is growing almost exponentially as more and more software developers, data scientists and machine learning students, teachers and engineers share their notebooks publicly. They use these repositories not only to store own notebooks but to find solutions to their specific problems at hand. The open exchange of computational narratives in Jupyter notebooks is an overwhelming success story. In this paper we ask the question of how does the use and spread of publicly available notebooks affect the quality of code and its embedding in a computational narrative. Drawing on empirical studies and our own experiences in the creation of digital material to support machine learning education and our observation of students ’ use of notebooks we comment on the quality. Our findings include that we cannot just reuse the concrete quality criteria that are in use for software in general. Much rather we must integrate the competing demands in creating a linear computational narrative, thus adapting programming style and design patterns to the data science context.
INFLUENCE OF SOCIOECONOMIC FACTORS ON WOMEN FARMERS’ ACCESS TO AGRICULTURAL INFORMATION IN MADAGALI LOCAL GOVERNMENT AREA OF ADAMAWA STATE, NIGERIA

The study was carried out to analyze the influence of socio-economic factors on women farmer’s access to agricultural information in Madagali Local Government Area of Adamawa State, Nigeria. The study sought to describe the socio-economic characteristics of rural women farmers and identity the sources of agricultural information available to them, examine the types of agricultural information accessed by them and identity the constraints to access information. Primary data was obtained through purposive and simple random sampling techniques using 180 respondents. Data were analyzed using descriptive statistic logit regression and Likert type rating scale. The findings revealed that age, educational level, extension contact, and societal affiliation are significant in influencing the level of access to agricultural information by the rural women farmers. Poor extension contacts, illiteracy, poverty, crowded household chores and shyness to access information were also identified as some of the constraints to accessing information. It is therefore recommended that there should be close co-ordination between agricultural extension agents of Adamawa state Agricultural Development Programme (AADP), Ministry of Information, private agencies, and international donor agencies for effective delivery of agricultural information among rural women farmers. Multiple sources of information such as face to face prints and deployment of Information and Communication Technology to deliver information to rural women farmers should be encouraged. Recruitment and training of more female extension agents should be encouraged to raise the number of women extension workers.
Word Sense Disambiguation : The Case for Combinations of Knowledge Sources , by Mark

Introduction A central aspect of natural language processing (NLP) systems is the analysis of word meaning in context. As humans we are faced with this problem every time we travel to any country of which we do not speak the local language. Given an appropriate dictionary and the context of the uncommon words used, we will be more or less able to figure out their intended meaning. Machines obviously are faced with a similar problem in processing any (! ) human text or speech input. NLP systems (such as those involving information extraction, question answering, machine translation, etc.) also need to capture the intended meaning of the words in their input stream as part of building up more complex meaning representations. As many words may potentially express several different meanings (or senses) the system needs to make a decision on which one(s) to select that are most appropriate given a particular context. Through time there have been a large number of different methods developed for the process of word sense disambiguation (WSD). As described aptly by Yorick Wilks in the Foreword to Stevenson s book, the first wave of methods that were largely based on knowledge representation and logical inference came to an end when more data-intensive methods began to be explored. This second wave of methods is also the starting point for this book, which discusses the first approaches to WSD based on machine-readable dictionaries (MRDs) and large text collections (corpora). Most prominent among these is the work by Lesk on dictionary definitions and by Yarowsky on large-scale corpora. (Lesk, 1986) pioneered the use of dictionary information in WSD by determining the overlap between words in the definitions of ambiguous words in the dictionary and context words surrounding these ambiguous words in a given text. A relatively large overlap between context and a particular definition indicates that most likely the corresponding sense of the word is intended here. (Yarowsky, 1992) took this idea one step further by including additional evidence from corpora and training machine learning algorithms on this data. The work described in Stevensons book stands largely in this tradition. The book is based on the authors PhD thesis in which he investigated the relative influence of different knowledge sources in WSD. The definition of " knowledge sources " is largely defined by the contents of the MRD version of the LDOCE (Longman Dictionary of Contemporary English) dictionary, which …
SELF MICROEMULSIFYING DRUG DELIVERY SYSTEM : A METHOD FOR ENHANCEMENT OF BIOAVAILABILITY

Oral route is the easiest and most convenient route of drug administration, being non invasive and cost effective, thereby leading worldwide drug delivery market. But major problem encountered in oral formulations (as estimated more than 50 % of oral formulations are found to be poorly aqueous soluble), is low bioavailability, giving rise to further problems like, high inter and intra subject variability, lack of dose uniformity and finally leading to therapeutic failure. The challenging task is to increase the bioavailability of drugs. Number of technological strategies are investigated and reported in literature for improving bioavailability like solid dispersions, cyclodextrins, micronization etc. But Self-microemulsifying Drug Delivery System (SMEDDS) have gained exposure for their ability to increase solubility and bioavailability of poorly aqueous soluble drugs with reduction in dose and also drugs are protected from hostile environment in gut. SMEDDS are isotropic mixture of oil, surfactant, drug and sometimes containing cosurfactant and administered orally which on mild agitation with GI fluids forms o/w microemulsion. This review gives complete overview of SMEDDS but special attention has been paid to formulation design, evaluation and little emphasis on application of SMEDDS. INTRODUCTION: Poor aqueous solubility of lipophilic drugs creates problems in formulation as well as in oral administration. Various approaches have been developed to resolve poor aqueous solubility of lipophilic drugs. As oral route for drug administration is most commonly used among all the routes of administration due to its convenience, noninvasiveness and cost effectiveness it become necessary that drug should have some aqueous as well as some lipid solubility for their absorption. Whenever a drug is administered by oral route it undergoes many steps like solubilisation followed by permeation to produce the desired effect. After oral administration drug solubilises first due to aqueous solubility then undergoes permeation through membrane due to lipid solubility. This solubilization is difficult for drugs which have poor aqueous solubility thus act as the rate limiting step for absorption from gastrointestinal tract. Due to poor aqueous solubility of drug their efficacy also hindered leading to low absorption after oral administration. A part of administered dose of such drug absorbed and reaches to therapeutic site and the remaining part produce toxicity or side effects due to imbalance in biodistribution. For the therapeutic delivery of poorly aqueous soluble active moieties, lipid based formulations are introduced. Various formulation approaches such as micronization, solid dispersions and complexation with cyclodextrin have been used but these approaches have some disadvantages 1, . Advanced approaches include incorporation of active moiety into inert lipid vehicles 3 like oils , surfactant dispersions 5, 6 and selfmicroemulsifying delivery system 7, 8 emulsions 9, 10 and Correspondence to Author:
Growth of the Lesser Himalayan Duplex and rapid fluvial incision modulate landscape morphology in tectonically-active Kishtwar Window in NW Himalayan interiors

The Kishtwar Window (KW) of the NW Himalaya exposes the north-western termination of the orogen-parallel anticlinal stack of thrust nappes, known as the Lesser Himalayan Duplex. However, its exact tectonic deformation pattern, geographic extent and activity are still debated. Here we combine morphometric analyses with structural data, field evidence and chronological constraints to describe the spatial pattern of internal deformation of the duplex. We agree with previous findings that the variations in the geometry of the basal décollement, the Main Himalayan Thrust (MHT) is important; however, the observed topography and neotectonic deformation can be explained only with additional internal faulting within the duplex. We recognize two significant steep stream segments/ knickzones, one in the center of the window, and a second one along its western margin, which we relate to fault-ramps emerging from the MHT. The larger of the knickzones corresponds tohighlyfractured and folded rocks at the base of the steep stream segment suggesting internal deformation of the duplex, possibly linked to surface-breaking thrust fault-ramp at the core of the duplex. The second steepened knickzone coincides with the western margin of the window and is identified by a narrow channel through a comparatively weaker bedrock gorge. Luminescence dating of sediments overlying the bedrock strath provides the upper limit of terrace abandonment. We deduced a minimum of 3.1-3.5 mm/y fluvial bedrock incision on the MHT-fault ramp which is in overall agreement with long-term exhumation rates from the KW. Summarizing our findings, we favor a structural and active tectonic control on the growth of the duplex even over geomorphic timescales.
Fluorometric optical sensor arrays for the detection of urinary bladder cancer specific volatile organic compounds in the urine of patients with frank hematuria

: This study outlines a simple ﬂuorometric optical sensor system for the sensitive, real time measurement of volatile organic compounds (VOCs) as biomarkers of urinary bladder cancer in patients presenting with frank hematuria and conﬁrmed to have the disease on histopathology. Arrays of 24 sensor points based on ﬂuorescence VOC sensitive materials were made. Urine samples of 38 consecutive patients with pathologically conﬁrmed bladder tumours and 41 age and gender matched healthy controls were recruited and analysed using this sensor array. This system correctly classiﬁed 68 out of 79 urine samples with 84.21% sensitivity and 87.80% speciﬁcity; the system also achieved 66.67% sensitivity and 75.00% speciﬁcity for classiﬁcation of high-grade and low-grade bladder cancer patients. This study showed promising results in the detection of urinary bladder cancer as well as to classify high grade versus low grade bladder cancers.
PROBABILISTIC TSUNAMI LOSS ESTIMATION USING MOMENTUM FLUX-BASED TSUNAMI FRAGILITY FUNCTIONS

Inundation depth and flow velocity are typical tsunami hazard intensity measures (IM) and can represent the impact of tsunami waves in terms of hydrostatic force and hydrodynamic force, respectively. However, neither of them can solely represent the influence of actual tsunami forces, since tsunami loading is a complex process of multiple types of fluid forces acting on structures. Momentum flux, which is defined as a function of both inundation depth and flow velocity, is considered as a more suitable IM to reflect the tsunami impact, particularly for dominant hydrodynamic forces. To date, not many tsunami fragility functions have been developed using momentum flux. Thus, it is not yet known how the use of momentum flux improves the tsunami damage assessment and the tsunami loss estimation. From a statistical perspective, the consideration of momentum flux does not improve the tsunami fragility model significantly compared to the consideration of flow velocity. This study aims at evaluating the features of three tsunami hazard indicators, i.e. inundation depth, flow velocity, and momentum flux, for probabilistic tsunami loss estimation. Focusing on Sendai and Onagawa in Miyagi Prefecture, Japan, as representative location for plain and ria coast, respectively, the evaluation of three sets of tsunami loss estimation results indicates that the use of momentum flux as IM generates larger tsunami loss for Sendai, whereas does not make a significant difference for Onagawa when momentum flux is used.
The Positive Impact From Group Counselling With Cognitive Behaviour (GC-CB) To Stress About Cyberbullying Conditions

Technology has now served as a means of cyberbullying. Cyberbullying represents harassment done at any time and in any place. A victim of cyberbullying may undergo a sequence of emotional effects such as anxiety, stress, depression, or even suicidal intention. The present study aimed to confirm the effectiveness of cognitive behavior group counseling with cognitive restructuring and selfinstruction technique in reducing university students’ stress due to cyberbullying. To this end, factorial experimental design was implemented. The participants of the study were 20 private university students in Yogyakarta, Indonesia. The data were collected using Social Anxiety Scale. In analyzing the data, repeated measure ANAVA was applied. The result of the study indicated that cognitive behavior group counseling with cognitive restructuring and self-instruction technique was effective in reducing the stress of cyberbullying victims. The study also revealed that self-instruction was more effective in reducing stress, compared to cognitive structuring. Regarding gender, female students exhibited a more significant decrease in stress than male students did.
Governance Risk and the Cross-Section of Stock Returns

This paper develops a framework for studying the impact of time-varying agency conflicts on the cost of equity. Investors infer agency costs coming from these conflicts by observing a firm’s governance policy. They dislike stocks of firms with higher agency costs in bad times, because conflicts are more costly in these periods. I empirically test the model with two commonly used measures of corporate governance and study the implications for U.S. firms from 1990 to 2006. A higher index level implies more power to insiders and is interpreted as leading to more costs by shareholders. I find that firms with a higher index in bad compared to good times have a higher cost of equity, even after controlling for prominent market factors, firm-specific financial and operating variables and also replacing the indices by their IVs.
Bank Regulation, Investment, and Capital Requirements Under Adverse Selection

This paper studies the optimal design of bank capital regulations when capital markets are subject to adverse selection. In this setting, the regulator faces a trade-off between enhancing financial stability and inducing investment in socially valuable projects. We show how the implementation of capital requirements can eliminate the information frictions that make raising capital costly by inducing banks to reveal their private information to the market. Importantly, under this approach the regulator faces an entirely different objective and trade-off when compared to setting capital requirements that do not reveal bank information. We solve for the optimal regulations which induce information revelation via recapitalization programs when the banking sector is weak and pool the banks' private information via uniform capital requirements otherwise. Optimal capital requirements are linked to the securities issued to meet them, demonstrating potential welfare gains from allowing less informationally sensitive securities (e.g. contingent convertible bonds) to qualify as bank capital. (JEL D82, G21, G28)
Maturity Clienteles and Corporate Bond Maturities

Abstract The average maturity of newly issued corporate bonds has declined substantially over the past 40 years, and the traditional determinants of debt maturity fail to explain this decline fully. We show that the changing composition of investors in the corporate bond market influences bond maturities. The results of a Granger causality test, an instrumental variable approach, and a natural experiment suggest that a decline in the insurance companies’ – which prefer long-term bonds – ownership share in the corporate bond market explains a significant part of the unexplained maturity decline. These findings illustrate how investor preferences can have real effects on corporations.
Deep Transfer Learning based COVID-19 Detection in Cough, Breath and Speech using Bottleneck Features

We present an experimental investigation into the automatic detection of COVID-19 from coughs, breaths and speech as this type of screening is non-contact, does not require specialist medical expertise or laboratory facilities and can easily be deployed on inexpensive consumer hardware. Smartphone recordings of cough, breath and speech from subjects around the globe are used for classiﬁcation by seven standard machine learning classiﬁers using leave-p -out cross-validation to provide a promising baseline performance. Then, a diverse dataset of 10.29 hours of cough, sneeze, speech and noise audio recordings are used to pre-train a CNN, LSTM and Resnet50 classi-ﬁer and ﬁne tuned the model to enhance the performance even further. We have also extracted the bottleneck features from these pre-trained models by removing the ﬁnal-two layers and used them as an input to the LR, SVM, MLP and KNN classi-ﬁers to detect COVID-19 signature. The highest AUC of 0.98 was achieved using a transfer learning based Resnet50 architecture on coughs from Coswara dataset. The highest AUC of 0.94 and 0.92 was achieved from an SVM run on the bottle-neck features extracted from the breaths from Coswara dataset and speech recordings from ComParE dataset. We conclude that among all vocal audio, coughs carry the strongest COVID-19 signature followed by breath and speech and using transfer learning improves the classiﬁer performance with higher AUC and lower variance across the cross-validation folds. Although these signatures are not perceivable by human ear, machine learning based COVID-19 detection is possible from vocal audio recorded via smartphone.
EXPLORING THE NEXUS OF ENTREPRENEURIAL ORIENTATION AND MARKET ORIENTATION ON BUSINESS PERFORMANCE AND THE ROLE OF INNOVATION AMONG THE MSMES IN SRI LANKA

This paper is aimed to investigate the impact of entrepreneurial orientation (EO) and market orientation (MO) business performance (BP) and to explore the role of innovation (IN) to enhance the business performance of the micro small and medium enterprises (MSMEs) in Sri Lanka. The sample size of 441 owners/mangers of MSMEs. Survey methodology was implemented for this study. Hypotheses are tested using SmartPLS. Findings suggests that significant positive relationship exist between the relationship of EO and BP, MO and BP, EOINBP, MO-IN-BP. Findings also reveal that innovation is complementary mediator on the relationship of EO and BP, and of MO and BP. This study focus on EO and MO. There are other variables under the strategic orientation and that need to be incorporated for further studies. EO and MO are important factors to determine the business performance of micro small and medium enterprises. When innovation is added between the relationship of EO and BP, and of MO and BP, innovation is mediating the relationships. Hence, MSMEs can focus on more the innovation and it will help them to enjoy the competitive advantage. The study of this nature has not been done in the Sri Lankan context with MSMEs in Sri Lanka. This study provides unique contribution to the existing literature.
Intention-to-Treat Comparisons in Randomized Trials

Intention-to-treat (ITT) comparisons have a central place in reporting on randomized controlled trials, though there are typically additional analyses of interest such as those making adjustments for nonadherence. In our ITT reporting of results from the Women’s Health Initiative (WHI) randomized trials we have relied primarily on highly flexible hazard ratio (Cox) regression methods. However, these methods, especially the proportional hazards special case, have been criticized for being difficult to interpret and frequently oversimplified, and for not being consistent with modern causality theories using potential outcomes. Here we address these topics and extend our use of hazard rate methods for ITT comparisons in the WHI trials.