Miracle-dz/UniFAR-FTUs huggingface dataset:
From Waste to Energy; Comparative Assessment of Heat Values of Biomass Briquettes and Fuel Wood for Bio-fuel Utilization and Strategic Waste Management in Ethiopia

:- Organic wastes accumulation and disposal is always creating an environmental crisis. Hence, there is a shortfall of proper management of these wastes. Changing these biomass wastes in to another important product like briquettes is advantageous. Beside this, too much energy Ethiopia consumes comes from sources that are likely to be out of stock in the near future. The traditional way of collecting fuel wood has been going on for long time resulting in the depletion of the forest. The use of biomass as a fuel, however, requires knowledge of its heating performance. This study is therefore aimed to evaluate the heating value of biomass briquettes and conventional fire wood. Briquette from four selected solid wastes (Bagasses, Waste paper, Fruits peels and saw dust) were developed and the heat value of the briquette was compared with eucalyptus fuel wood. Energy evaluation test of briquettes and fuel wood was made using the Parr Isoperibol bomb calorimeter. Results of the investigation showed that, mean value of the bulk density of the selected samples of briquettes and fuel wood are 2.94 g/cm3 and 6.1457 g/cm3 respectively. Average moisture content of biomass briquettes is 3.06% while average moisture content of fuel wood is 7.5%. Mean heat value of briquettes and fuel wood is 16.27kj/g and 20.439kj/g respectively. It is proved that although fuel wood gave the slightly higher average heat value than briquettes, they have similar heat value at 95% level of significance. It is therefore concluded that briquettes with higher calorific value which could make excellent fuel can be produced from biomass solid wastes. Generally, briquettes have adequate thermal calorific values and therefore can substitute the utilization of conventional types of fuels.
Allocation of Fetal Heart Tones During Non-stop Monitoring of Pregnant Women

Annotation – The article is to study the system of non-stop daily monitoring of the state of the maternal and the fetal circulatory systems using acoustic sensors. After preliminary preparation of the phonocardiogram heart tones of the fetus and the pregnant woman were extracted using Shannon energy. The obtained data was separated, followed by calculation of the heart beats. As a result, software algorithms for calculating heart beats at a particular time (30 seconds to 6 hours) have been developed and implemented. The measurement error ranges from 1 to 6 beats per minute. The accuracy of the software and algorithmic support was estimated by comparing the results obtained during parallel cardiotocography, taken as the reference method.
Empirical Research of Credit Risk for the Public Company Using EDF Model

This paper employs the method of Numerical Calculation and gets the solution by computer programming.The paper testifies the solution using the method of Numerical Calculation is the sole solution.And we use EDF model to conduct an empirical research to the credit risk of the public companies.We show that EDF model doesn't provide a wrong message to the good-performance companies.But the results show that the asset's market value and equity's market value of those high-risk companies are overvalued.
Critical point equation and closed conformal vector fields

In this article, we study the critical points of the total scalar curvature functional restricted to the space of metrics with constant scalar curvature of unitary volume, for simplicity, CPE metrics. Here, we prove that a CPE metric admitting a non‐trivial closed conformal vector field must be isometric to a round sphere metric, which provides a partial answer to the CPE conjecture.
A Microbial‐Explicit Soil Organic Carbon Decomposition Model (MESDM): Development and Testing at a Semiarid Grassland Site

Explicit representations of microbial processes in soil organic carbon (SOC) decomposition models have received increasing attention, because soil heterotrophic respiration remains one of the greatest uncertainties in climate‐carbon feedbacks projected by Earth system models (ESMs). Microbial‐explicit models have been developed and applied in site‐ and global‐scale studies. These models, however, lack the ability to represent microbial respiration responses to drying‐wetting cycles, and few of them have been incorporated in land surface models (LSMs) and validated against field observations. In this study, we developed a multi‐layer, microbial‐explicit soil organic carbon decomposition model (MESDM), based on two main assumptions that (a) extracellular enzymes remain active at dry reaction microsites, and (b) microbes at wet microsites are active or potentially active, while microbes at the dry microsites are dormant, by dividing the soil volume into wet and dry zones. MESDM with O2 and CO2 gas transport models was coupled with Noah‐MP LSM and tested against half‐hourly field observations at a semiarid grassland site in the southwest US characterized by pulsed precipitation. The results show MESDM can reproduce the observed soil respiration pulses of various sizes in response to discrete precipitation events (Birch effect) and thus improve the simulation of net ecosystem exchange. Here, both microbial accessibility to accumulated dissolved organic carbon and reactivation of dormant microbes at the dry microsites upon rewetting are critical to reproducing the Birch effect. This study improves our understanding of and ability to simulate complex soil carbon dynamics that experience drying‐wetting cycle in climate‐carbon feedbacks.
Expeditionary Oblong Mezzanine

Abstract : This research explores how advanced collaboration tools might improve current operational environments within military and government organizations. Currently, military and government organizations collaborate via in-person communications and brief situational awareness using static and time-late information by sharing PowerPoint presentations. Two emerging technologies, the Emergency Operations Center in a Box (EOC in a Box) and Oblong Mezzanine, offer innovative methods to create a collaborative assessment environment, even in disadvantaged intermittent latency (DIL) environments. EOC in a Box offers rapid communications and networking infrastructure, and can be setup within hours of initial need. Oblong Mezzanine offers an advanced collaboration environment as seen in the movies Minority Report and Iron Man 3, where gestural accommodations enable new forms of collaboration with high definition graphics. Development in 2014 showed that these two capabilities could be married to create a rapidly deployable expeditionary capability to support nuanced and high-end collaboration, command and control, and data investigation. The purpose of this thesis is to determine if the Oblong Mezzanine coupled with the EOC in a Box technology is useful in an emergent situation. This thesis examines Mezzanine-to-Mezzanine and Mezzanine-to-other collaborative appliances in low bandwidth and austere environments.
The Forensic Challenger - A Digital Forensic E-Learning Platform

E-learning is becoming an increasingly popular form of education. The ability to teach many students at once, and the students possibility to learn material at their own pace have been very successful. Knowing how digital forensics investigations are performed is becoming a necessity in many fields. The society’s dependency on computers, and the massive increase in computing power and data storage, causes the society to require more expertise and efficient methods to handle digital forensics investigations. The use of e-learning can greatly benefit this situation, as more people can be aware of the correct procedures and key elements to digital forensics. The challenge is to efficiently teach these methods through an e-learning platform. By using the Hyper Interactive Presentation (HIP) platform, this thesis provided a proof of concept platform of an e-learning solution for digital forensics investigations,"The Forensic Challenger"(TFC), to improve teaching digital forensics. This thesis outlines the technical development of the platform. The results of the trial experiment with two groups of first year information security bachelor students. One group of 5 students used TFC platform, and the other group of 4 students used a simulation version of the existing platform used in the forensics lab. When we compared the groups in terms of motivation, and time spent, the TFC group indicated higher motivation and spent less time solving the task in the assignment.
Dissecting the nuclear import of SnRNPs via the Sm core pathway.

by USHA NARAYANAN The fundamental unit of human life is the cell and proper functioning of a myriad of cellular pathways ensures its vitality. One of the central processes in the cell is pre-mRNA splicing. Here, mRNA transcripts are generated from precursor mRNAs by the spliceosome which is comprised of mature snRNPs. The maturation pathway of snRNPs starts with snRNA transcripts and culminates in fully functional snRNPs. This life cycle of snRNPs is intricate and spans the nuclear and cytoplasmic compartments of the eukaryotic cell. The entry of the snRNPs into the nucleus is particularly fascinating and is facilitated by large pore complexes integral to the nuclear membrane that recognize and respond to specific signals and factors on the snRNPs. Efficient snRNP import is facilitated by a specific bipartite signal composed of RNA and protein. Earlier studies have demonstrated that the protein component of this signal is both necessary and sufficient for basal snRNP import in somatic cells yet, it remains unknown. Gaining insight on various aspects of snRNP biogenesis has implications for combating a
Improved Approaches to Discover Weighted and High Utility Itemsets

Extracting knowledge from large amounts of data has been an important research ﬁeld for the past three decades. Data mining is one such area that deals with the investigation of frameworks and algorithms to extract different kinds of knowledge from large databases. Pattern mining is one of the data mining tasks, which deals with developing frameworks and algorithms for extracting interesting patterns (or itemsets) from large databases. In the literature, several pattern mining techniques have been employed to mine different kinds of patterns such as frequent patterns, coverage patterns, periodic patterns, weighted patterns, utility patterns, etc. In this thesis, we investigate improved approaches for mining weighted and high utility itemsets. As a ﬁrst contribution, we have proposed an improved approach to mine Weighted Frequent Itemsets (WFIs) from spatio-temporal databases. The WFI framework allows the users to set weights to the items present in the database based on their importance and discovers all itemsets whose weighted sum in a transactional database is no less than the user-speciﬁed minimum weighted sum ( minW S ) value. The existing works in the literature have focused on ﬁnding WFIs in a transactional database and did not consider the spatial characteristics of the items within the data. The spatial characteristics of an item imply the geographical location of an item. We have proposed an improved WFI Mining (WFIM) approach for spatio-temporal databases by introducing the notion of neighborhood itemset , which is deﬁned by considering the spatial characteristics of the items. An itemset is called a neighborhood itemset if the distance between each pair of items is no more than the user-speciﬁed maximum distance ( maxDist ) value. By adding the notion of neighborhood itemset to WFIM, we have proposed a new model, which we call Weighted Frequent Neighborhood Itemset Mining (WFNIM), to mine Weighted Frequent Neighborhood Itemsets (WFNIs) from spatiotemporal data. The generated WFNIs do not satisfy the anti-monotonic property. To extract WFNIs efﬁciently, we have proposed new pruning measures by exploiting the spatial nature of items to effectively reduce the search space and the computational cost of ﬁnding the desired patterns. A new pattern-growth algorithm has been presented to ﬁnd all WFNIs from a
Consent in the Age of AR: Investigating The Comfort With Displaying Personal Information in Augmented Reality

Social Media (SM) has shown that we adapt our communication and disclosure behaviors to available technological opportunities. Head-mounted Augmented Reality (AR) will soon allow to effortlessly display the information we disclosed not isolated from our physical presence (e.g., on a smartphone) but visually attached to the human body. In this work, we explore how the medium (AR vs. Smartphone), our role (being augmented vs. augmenting), and characteristics of information types (e.g., level of intimacy, self-disclosed vs. non-self-disclosed) impact the users’ comfort when displaying personal information. Conducting an online survey (N=148), we found that AR technology and being augmented negatively impacted this comfort. Additionally, we report that AR mitigated the effects of information characteristics compared to those they had on smartphones. In light of our results, we discuss that information augmentation should be built on consent and openness, focusing more on the comfort of the augmented rather than the technological possibilities.
Mining Change Rules

Changes in data happen frequently, and discovering how the changes interrelate can reveal information about the data and the transactions on them. In this paper, we define change rules as recurring patterns in database changes. Change rules embody valuable metadata and reveal semantic as well as functional relationships between versions of data. We can use change rules to discover formerly unknown relationships, anticipate data changes and explore anomalies if changes do not occur as expected. Wepropose the CR-Miner algorithm, which dispenses the manual formulation of rules to uncover this hidden knowledge in a generic and domain-independent way. Given a dataset together with its past versions, we efficiently discover change rules and rank them according to their potential for a manual review. The experimental results confirm that our method finds change rules efficiently in big data: On a subset of Wikipedia infoboxes encompassing data from four years and different categories, we discover 4456 change rules. Rules between changes from 48706 tables of open-government data observed over the period of one year can be discovered within 33minutes, and rules between about 2.5million Wikipedia infoboxes from 153 templates within 77minutes.
Design and Development of a Low Cost Grain Flour Blender

One of the major solutions to reduce the consumption of wheat flour in the country is to introduce flour mixtures blended with rice flour and other locally produced grain flour to the market and flour based food processors, since it has a great demand even now. Blending equipment are essential to produce flour mixtures with uniformly distributed particles. Flour blending machines are available in the international market, but they are very expensive and those are not at an affordable price to purchase even for medium scale flour producers. Therefore, a low cost grain flour blender was designed and developed to introduce for flour producers. Developed grain flour blender was tested by blending rice flour with wheat flour to the ratio of 3:7 which is generally used for preparing bread. It was found that the minimum blending time required for giving a uniform mixture was 3 minutes when the equipment was operated at 51 rpm. Capacity of the blender was 50 kg per batch and it was operated by a 3 hp electric motor. When the developed flour blender is compared with the available blending machines in the international market with same capacity, it was found that the developed flour blender reduces the blending time and the initial cost of the machine is reduced by 5 times while the flour blending cost is reduced by 25%. ENGINEER, Vol. 48, No.03, pp. 27-34 2015
Downscaling of GOES-16's Land Surface Temperature Product Using Epitomes

Land surface temperature (LST) is an environmental variable derived from thermal infrared (TIR) imagery. Satellite platforms are a good source of TIR imagery because of their ability to provide widespread and frequent coverage of the Earth’s surface. It is common that a single satellite remote sensing platform is able to provide images with good spatial resolution or temporal resolution but not both. LST is an important parameter for studies on the urban heat island (UHI) effect. These studies are limited by the spatial or temporal resolutions of available LST products. This thesis presents an algorithm to estimate land surface temperature with high spatial and high temporal resolutions by downscaling GOES16’s LST product. This is done by extending an epitomic representations methodology, previously used to create high-resolution land cover maps, to land surface temperature data. An LST product with high spatial and high temporal resolutions will benefit UHI studies as well as any users of LST data. The accuracy and precision of our downscaled LST products are in line with the targets set by the GOES-16 satellite’s LST product of 2.5 K for accuracy and 2.3 K for precision.
The in uence of risk perceptions on close contact frequency during the SARS-CoV-2 pandemic

15 Human behaviour is known to be crucial in the propagation of infectious diseases through 16 respiratory or close-contact routes like the current SARS-CoV-2 virus. Intervention measures 17 implemented to curb the spread of the virus mainly aim at limiting the number of close contacts, 18 until vaccine roll-out is complete. Our main objective was to assess the relationships between 19 SARS-CoV-2 perceptions and social contact behaviour in Belgium. Understanding these 20 relationships is crucial to maximize interventions’ effectiveness, e.g. by tailoring public health 21 communication campaigns. In this study, we surveyed a representative sample of adults in 22 Belgium in two longitudinal surveys (8 waves of survey 1 in April 2020 to August 2020, and 11 23 waves of survey 2 in November 2020 to April 2021). Generalized linear mixed effects models were 24 used to analyse the two surveys. Participants with low and neutral perceptions on perceived 25 severity made a significantly higher number of social contacts as compared to participants with 26 high levels of perceived severity after controlling for other variables. Furthermore, participants 27
“It Basically Started Using Me:” An Observational Study of Password Manager Usage

There is limited information regarding how users employ password managers in the wild and why they use them in that manner. To address this knowledge gap, we conduct observational interviews with 32 password manager users. Using grounded theory, we identify four theories describing the processes and rationale behind participants’ usage of password managers. We find that many users simultaneously use both a browser-based and a third-party manager, using each as a backup for the other, with this new paradigm having intriguing usability and security implications. Users also eschew generated passwords because these passwords are challenging to enter and remember when the manager is unavailable, necessitating new generators that create easy-to-enter and remember passwords. Additionally, the credential audits provided by most managers overwhelm users, limiting their utility and indicating a need for more proactive and streamlined notification systems. We also discuss mobile usage, adoption and promotion, and other related topics.
Entrepreneurial Passion and Social Entrepreneurial Intent: The Mediating Role of Entrepreneurial Self-Efficacy in Public Universities in Ghana

Entrepreneurship makes a huge contribution to any country's economy by providing jobs, instilling innovation, and creativity, and fostering exceptional social development. Scholars have recognized the value of entrepreneurship education since it has a significant impact on students by instilling a feeling of entrepreneurship in them. Entrepreneurial passion refers to the good and intense sensations a person gets from participating in activities related to their role as an entrepreneur. The primary goal of this research is to determine the impact of entrepreneurial passion on social entrepreneurial intent, as well as the role of entrepreneurial self-efficacy as a mediating factor. The study developed a mediation model to further research on the relationship between entrepreneurial passion and entrepreneurial intention. The study also investigated if entrepreneurial self-efficacy plays a role in this relationship. This study's philosophical viewpoint is positivism, and the research design is descriptive and explanatory. The study relied on primary data collected using questionnaires. The study adopted a quantitative approach and to analyze the data obtained from a sample of 200 (graduate students). The study revealed that entrepreneurial passion has a positive impact on entrepreneurial intention and self-efficacy. Second, using entrepreneurial self-efficacy as a mediator, the indirect effect of entrepreneurial passion on entrepreneurial intention was significant and positive. It is therefore recommended that more emphasis be paid to Entrepreneurial Self-Efficacy when attempting to build or increase Social Entrepreneurial Intent through Entrepreneurial Passion.
Competing technologies and the struggle towards a new dominant design: the emergence of the hybrid vehicle at the expense of the Fuel Cell Vehicle?

Once in a while, a radical breakthrough technology emerges that has a devastating impact on established industries. In comparison to existing technologies, such disruptive innovations deliver a dramatic leap in performance, and incumbent firms tend to respond either by ignoring the new technology or by trying to improve the performance of the established technology (the so-called sailing ship effect); as a result, they often perish (Christensen 1997; Utterback 1994). Established industry’s reaction to the emergence of possible disruptive technologies is an intensively studied phenomenon in innovation studies (Tushman and Anderson 1986; Henderson and Clark 1990). Due to the unexpected nature of these events, they are often studied ex post. While disruptive and radical technologies are highly imaginative, most technological progress has been made through incremental improvements in the available technology, products and processes (see, for example, Neij 1997). This difference is clearly demonstrated in the recent debates on transitions to more sustainable sociotechnical systems (Geels 2002; Kemp 1994; Schot et al. 1994). Although there is consensus over