Miracle-dz/UniFAR-FTUs huggingface dataset:
TO FORMAL FINANCE IN KENYAN MANUFACTURING

The descriptive analysis shows that access to formal credit significantly varies across firm size and firm status. The required collateral is often several times the borrowed amount. However, whether security is asked for to some degree appears to depend on the ability to offer it. Multivariate analysis reveals that factors affecting the credit decision include firm status, firm size, ethnicity, the ability to pledge collateral, and to some extent the proximity between lenders and borrowers. The results suggest that dominating segments of the manufacturing sector, namely small firms, do not receive the much needed financial support necessary to enable manufacturing growth.
Constructions and Properties of Linear Locally Repairable Codes

In this paper, locally repairable codes with all-symbol locality are studied. Methods to modify already existing codes are presented. It is also shown that, with high probability, a random matrix with a few extra columns guaranteeing the locality property is a generator matrix for a locally repairable code with a good minimum distance. The proof of the result provides a constructive method to find locally repairable codes. Finally, constructions of three infinite classes of optimal vector-linear locally repairable codes over a small alphabet independent of the code size are given.
Efficient distinction of road surface conditions using surveillance camera images in night time

Knowing the road surface condition is one of the most important topics at contributes to the safety of pedestrians and car drivers. It is increasingly becoming necessary to distinguish road surface condition at night-time, as most of the previously methods only focus on daytime conditions. In this paper, we propose a distinction method of road surface conditions by using only video information acquired from a visible surveillance video camera. The main feature of this method is to simply use passing car's headlights as the lighting source. As a result, we were able to distinguish road surface conditions such as dry or wet with high accuracy.
Landscape identity, before and after a forest fire

Abstract Our identity is tied to where we are and how we engage with the landscapes in which we find ourselves. But what happens if the landscape which we use for our everyday life is drastically altered by a catastrophic upheaval, for example, when forest fires ravage the landscape? In this paper, interviews with individuals affected by the largest forest fire in modern Swedish history are used to exemplify our conceptualisation of how landscape identity is impacted by dramatic change. We address the phases of stability, change and progression in relation to the case. Finally, we propose that landscape identity can be utilised as a central concept for engaging with the social aspects of the impact of forest fires.
Vidas al Revés /Upside-Down Lives: Educational Challenges Faced by Transnational Children of Return Mexican Families

ABSTRACT Drastic immigration policies and economic conditions have resulted in unparalleled return rates to Mexico. Deported parents are faced with the difficult choice of leaving US-born children behind or taking them to their country of origin, where many face significant educational, cultural, and linguistic barriers. This study focuses on six families and the challenges they have faced living with undocumented status in the US, re-adjusting to life in Mexico, and the educational challenges faced by their children in both countries.
A molecular identification protocol for roots of boreal forest tree species

Premise of the study: Roots play a key role in many ecological processes, yet our ability to identify species from bulk root samples is limited. Molecular tools may be used to identify species from root samples, but they have not yet been developed for most systems. Here we present a PCR-based method previously used to identify roots of grassland species, modified for use in boreal forests. Methods: We used repeatable interspecific size differences in fluorescent amplified fragment length polymorphisms of three noncoding chloroplast DNA regions to identify seven woody species common to boreal forests in Alberta, Canada. Results: Abies balsamea, Alnus crispa, Betula papyrifera, Pinus contorta, and Populus tremuloides were identifiable to species, while Picea glauca and Picea mariana were identifiable to genus. In mixtures of known composition of foliar DNA, species were identified with 98% accuracy using one region. Mixed root samples of unknown composition were identified with 100% accuracy; four species were identified using one region, while three species were identified using two regions. Discussion: This methodology is accurate, efficient, and inexpensive, and thus a valuable approach for ecological studies of roots. Furthermore, this method has now been validated for both grassland and boreal forest systems, and thus may also have applications in any plant community.
Ergonomics of thumb-based pointing while holding tablets

Interaction in mobile computing mainly relies on selecting targets by touch. A large body of work showed the effect of target size and target distance on selection time. Recent work on hand-held devices suggests that size and distance are not the only factors that affect selection time. In this paper, we investigate target selection performance of the thumb when interacting with grasping hands (see Figure 1). In the first study, we show that the relative direction of the target has a significant effect on selection time. In the second study we show that the direction of movement also has a significant effect. The results extend our knowledge about pointing on hand-held devices and can be used to improve transfer functions of mobile GUIs.
Coalition Structure Generation based on Distributed Constraint Optimization

Forming effective coalitions is a major research challenge in AI and multi-agent systems (MAS). Coalition Structure generation (CSG) involves partitioning a set of agents into coalitions so that social surplus (the sum of the rewards of all coalitions) is maximized. A partition is called a Coalition Structure (CS). In traditional works, the value of a coalition is given by a black box function called a characteristic function. In this paper, we propose a novel formalization of CSG, i.e., we assume the value of a characteristic function is given by an optimal solution of a distributed constraint optimization problem (DCOP) among the agents of a coalition. A DCOP is a popular approach for modeling cooperative agents, since it is quite general and can formalize various application problems in MAS. At first glance, one might assume that the computational costs required in this approach would be too expensive, since we need to solve an NP-hard problem just to obtain the value of a single coalition. To optimally solve a CSG, we might need to solve n-th power of 2 DCOP problem instances, where n is the number of agents. However, quite surprisingly, we show that an approximation algorithm, whose computational cost is about the same as solving just one DCOP, can find a CS with quality guarantees. More specifically, we develop an algorithm with parameter k that can find a CS whose social surplus is at least max(k/(w*+1), 2k/n) of the optimal CS, where w* is the tree width of a constraint graph. When k=1, the complexity of this algorithm is about the same as solving just one DCOP. These results illustrate that the locality of interactions among agents, which is explicitly modeled in the DCOP formalization, is quite useful in developing an efficient CSG algorithm with quality guarantees.
Facilitating efficient Mars terrain image classification with fuzzy-rough feature selection

This paper presents an application study of exploiting fuzzy-rough feature selection (FRFS) techniques in aid of efficient and accurate Mars terrain image classification. The employment of FRFS allows the induction of low-dimensionality feature sets from sample descriptions of feature vectors of a much higher dimensionality. Supported with comparative studies, the work demonstrates that FRFS helps to enhance both the effectiveness and the efficiency of conventional classification systems such as multi-layer perceptrons and K-nearest neighbors, by minimizing redundant and noisy features. This is of particular significance for on-board image classification in future Mars rover missions.
TurtleEditor: An Ontology-Aware Web-Editor for Collaborative Ontology Development

Inspired by the shift of vocabulary development projects towards repository hosting services such as GitHub, we noticed the lack of ontology-aware editors that can be easily connected to these repositories. This motivated us to build a web client optimized for the communication with external repositories and including specific functionalities to ease the participation in collaborative ontology development efforts also for non-expert contributors. This paper describes TurtleEditor, an open-source web editor, which can load files from, and commit changes to a central repository and offers features such as syntax highlighting, syntax checking, auto-completion and a SPARQL endpoint to query the ontology.
Combining classifiers based on confidence values

The paper describes our investigation into the neural gas (NG) network algorithm and the hierarchical overlapped architecture (HONG) which we have built by retaining the essence of the original NG algorithm. By defining an implicit ranking scheme, the NG algorithm was made to run faster in its sequential implementation. Each HONG network generated multiple classifications for every sample data presented as confidence values. These confidence values were combined to obtain the final classification of the HONG architecture. Three HONG networks based on three different feature sets with global and structural features were also trained to obtain better classification on conflicting handwritten data. An excellent recognition rate for the NIST SD3 database was consequently obtained.
Measuring Surprise in Recommender Systems

A lot of current research on recommender systems focuses on objectives that go beyond the accuracy of the recommendations; for instance, ensuring that the list of recommended items is diverse. In this work we explore a particular beyond-accuracy objective — serendipity. We follow the idea of measuring item serendipity by its distance from items previously experienced by the user and propose two ways to measure item surprise, which constitutes the core component of serendipitous recommendations. Through offline experiments we compare three state-ofthe-art recommendation algorithms in terms of their ability to generate surprising recommendations. For one of the suggested metrics, the results validate the intuition that a matrix factorization approach generates the most accurate but also the least surprising recommendations, while a userbased neighbourhood approach performs best in terms of surprise. Furthermore, our analysis of the influence of the size of the user’s profile on surprise metric values indicates that some information may be lost when averaging item distance values.
Selected sequence-pair: an efficient decodable packing representation in linear time using sequence-pair

In this paper, we propose "selected sequence-pair" (SSP), a sequence-pair (seq-pair) with the limited number of subsequences called adjacent crosses. Its features are: (1) The smallest packing based on a given SSP can be obtained in O(n) time, where n is the number of rectangles. (2) An arbitrary packing can be represented by SSP. (3) The total representation number of SSP of size n is not more than that of rectangular dissection of the same size with n-/spl lfloor//spl radic/(4n-1)/spl rfloor/ empty rooms (the necessary number of empty rooms to represent an arbitrary packing). To realize these features of SSP, we propose an algorithm to enumerate all adjacent crosses on a seq-pair in linear time of n + k (k is the number of adjacent crosses). Also we apply a conventional method to convert a seq-pair without adjacent crosses to an equivalent Q-sequence, representation of rectangular dissection, in O(n + k) time. A move operation to obtain an adjacent solution efficiently is proposed to perturb SSP for Simulated Annealing (SA). From experimental results, we confirmed the proposed method was carried out in linear time and was more efficient than the conventional method when SSP size got bigger.
Effects of Ice Crystal Fall Speed on the Simulations of Convective Cloud Systems

Cloud resolving models are considered one of the best tools that can simulate cloud systems and their growth over time. Within cloud systems, there are many different parameters involving moisture and ice that can have major effects on the overall system. Thus the ice crystal fall speed, is analyzed to see how it affects the cloud system. We hypothesize that cloud systems will increase in size and grow deeper when ice crystal fall speeds are slower, and inversely that cloud systems will decrease in size and become more shallow when ice crystal fall speeds are faster. Observed large-scale forcing was obtained using data from the DYNAMO (Dynamics of the Madden-Julien Oscillation) experiment over the Indian Ocean. A Clark-Hall cloud resolving model was then run with the forcing to compare the model simulation against observations. Two different cloud simulations were run with faster and slower ice fall speeds to compare to the original control test. Shortwave and longwave radiation and mixing ratio plots were used to analyze the size of the clouds in relation to ice crystal fall speeds. Results show that the cloud model was also able to simulate cloud systems and their characteristics without much bias. They also show that cloud systems are larger with slower ice fall speeds and smaller with faster ice fall speeds. ______________________________________________________________________________
A theoretical assessment of solution quality in evolutionary algorithms for the knapsack problem

Evolutionary algorithms are well suited for solving the knapsack problem. Some empirical studies claim that evolutionary algorithms can produce good solutions to the 0-1 knapsack problem. Nonetheless, few rigorous investigations address the quality of solutions that evolutionary algorithms may produce for the knapsack problem. This paper focuses on a theoretical investigation of three types of (N+1) evolutionary algorithms that exploit bitwise mutation, truncation selection, plus different repair methods for the 0-1 knapsack problem. It assesses the solution quality in terms of the approximation ratio. Our work indicates that the solution produced by both pure strategy and mixed strategy evolutionary algorithms is arbitrarily bad. Nevertheless, an evolutionary algorithm using helper objectives may produce 1/2-approximation solutions to the 0-1 knapsack problem.
Congestion-aware scheduling for NoC-based reconfigurable systems

Network-on-Chip (NoC) is becoming a promising communication architecture in place of dedicated interconnections and shared buses for embedded systems. Nevertheless, it has also created new design issue such as communication congestion and power consumption. A major factor leading to communication congestion is mapping of application tasks to NoC. Latency, throughput, and overall execution time are all affected by task mapping. As a solution, an efficient run-time Congestion-Aware Scheduling (CWS) is proposed for NoC-based reconfigurable systems, which predicts traffic pattern based on the link utilization. The proposed algorithm alleviates the overall congestion, instead of only improving the current packet blocking situation. Our experiment results have demonstrated that compared to other existing congestion-aware algorithm, the proposed CWS algorithm can reduce the average communication latency by 66%, increase the average throughput by 32%, reduce the energy consumption by 23%, and decrease the overall execution by 32%.
Evaluation of Risk for Complex Systems Using Attack Surface

Many approaches for security assessment were recently proposed. In particular, attack graphs and attack surface gained a lot of attention. Nevertheless, these approaches suffer from several drawbacks. For example, attack graph operates only with known vulnerabilities and it is unclear how attack surface (metric) contributes to the risk picture for a complex system. We introduce a novel formal approach for modelling cyber attacks and evaluating of security of complex systems. Our formalisation unites attack surface and attack graph approaches and establishes an explicit link between these approaches and security risk assessment. In this way we are able to exploit the advantages of these three security evaluation approaches in a common framework overcoming many shortcomings of using these approaches separately.
Differences in ICT Adoption in Comparable Developing Countries: An Exploratory Study of Four Nations

This study compares ICT adoptions of four developing nations: Zimbabwe to Albania and Namibia to Venezuela. Each pair of countries has similar gross domestic product but different ICT adoption level. Using qualitative, non-conventional analysis of comparing a pair of countries based on country-specific factors, the findings reveal that the difference in ICT adoption of two similar such countries may be attributed to such factors as poor infrastructure, income inequality, and adult illiteracy. Cultural factors, governance and GDP growth rate are shown as possible reasons for the two African nations to perform differently than their counterparts in the adoption of PCs and Internet. This study further reveals that the impact of a given factor depends on the type of ICT in question in these nations. For example, in Zimbabwe, poor infrastructure may adversely affect the adoption of telephone but has no impact on Internet adoption.
Gastric Function in Children with Oesophageal Atresia and Tracheoesophageal Fistula

Oesophageal atresia and tracheoesophageal fistula (OA–TOF) are a multifaceted condition which affects patients throughout their lives. Even though it is one of the most common gastrointestinal malformations, most of the current studies focus on gastro-oesophageal reflux disease, anastomotic strictures, and feeding difficulties. However, there is increasing evidence that a proportion of patients with OA–TOF also have abnormal gastric function. This review aims to provide a comprehensive understanding of studies of gastric function in patients with OA–TOF. The etiology of this abnormality has been hypothesized to be congenital and/or acquired. Several modalities are currently available for the investigation of gastric function, each of them trying to answer specific clinical questions. This review summarizes the studies that have looked at gastric function in the OA–TOF cohort with gastric emptying studies (gastric emptying scintigraphy and 13C octanoic breath test), gastric manometry, electrogastrography, and oral glucose tolerance test. However, these modalities are limited due to poor age-specific normative values and heterogeneous methodologies used. The evaluation of symptoms in this cohort is crucial, modalities for abnormal gastric function are also described. With appropriate investigations and symptoms questionnaires, treatment strategies can be implemented to correct abnormal gastric function and thereby improve the outcomes and quality of life of patients with OA–TOF. This review highlights the need for large international multicentre collaborative studies and high-quality prospective randomized controlled trials to improve our understanding of gastric function in this cohort.
The Impact of Diabetes Mellitus on Renal Cell Carcinoma Prognosis

AbstractPrevious studies that investigated the relationship between DM and survival in renal cell carcinoma (RCC) patients reported inconsistent findings. Hence, we conducted a meta-analysis to obtain a more precise evaluation of the prognostic significance of DM in RCC. A systematic review was conducted with PubMed, Embase, and Web of Science to identify relevant articles that evaluated the effect of DM on RCC patients. Based on the inclusion and quality assessment criteria, 18 studies were eligible for the meta-analysis. Pooled hazard ratios (HR) and corresponding 95% confidence intervals (CI) for overall survival (OS), cancer-specific survival (CSS), and recurrence-free survival (RFS) were calculated by standard meta-analysis techniques. The results suggested that DM was associated with poor OS (HR 1.56, 95% CI, 1.35–1.81, P < 0.001), poor CSS (HR 2.03, 95% CI, 1.37–3.01, P < 0.001), and poor RFS (HR 1.73, 95% CI, 1.25–2.39, P = 0.012). In addition, for patients with localized RCC, patients with clear cell RCC, or patients receiving nephrectomy, DM was associated with both poor OS and CSS by subgroup analyses. Our study revealed that there was a significant negative impact of DM on OS, CSS, and RFS in RCC patients. Therefore, more attention should be paid to RCC patients with preexisting DM because of their poor prognosis.
CPW-fed slot antenna with fractal tuning stub for wideband circular polarization

Based on the use of the fractal tuning stub and slot radiator, a wideband circularly polarized coplanar waveguide (CPW)-fed slot antenna with fractal tuning stub is presented. The fractal tuning stub has been designed to enhance widely the impedance bandwidth. Moreover, in order to achieve the extended axial ratio bandwidth, the slot radiator is etched and verified on the upper slot. The proposed antenna attains an overlapped bandwidth (axial ration ≤ 3 dB and return loss ≤ 10 dB) of 45% (2.25–3.57 GHz) in measurement.
Application of the Audio Recorded Cognitive Screen and its relation to functioning in schizophrenia

Objective This study investigated the ability of the Audio Recorded Cognitive Screen (ARCS) to detect cognitive deficit in individuals with schizophrenia, relative to the Mini Mental State Examination (MMSE) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and explored the associations between the ARCS and functional outcomes. We hypothesised that the ARCS would be able to better discriminate between individuals with schizophrenia and healthy controls than the MMSE, and that ARCS performance would be correlated with measures of social and vocational functioning. Methods The participants were 19 community-dwelling individuals with schizophrenia or schizoaffective disorder and 19 healthy controls recruited from the Australian Schizophrenia Research Bank (ASRB). Participants completed the ARCS, MMSE, and self-report measures of social and vocational functioning. Clinical and diagnostic data stored by the ASRB were also utilised. Results The schizophrenia group performed worse than the control group on the ARCS, with memory, t(36)=2.49, p=0.02, 95% CI [−1.84, −18.79] and fluency, t(36)=2.40, p=0.02, 95% CI [−1.87, −22.24] domains being the main discriminating measures. The RBANS also discriminated between the two groups, and ARCS and RBANS total scores were moderately to strongly correlated. There was no difference between the two groups on the MMSE after controlling for demographic variables. ARCS performance was associated with employment status [χ2(1)=7.16, p=0.007]. Conclusion The ARCS may be sensitive to the cognitive deficits in outpatients with schizophrenia and an indicator of functional outcomes in this population.