Miracle-dz/UniFAR-FTUs huggingface dataset:
Poverty Reduction, Growth performance and Governance: Policy implications for Bangladesh

The development narratives on Bangladesh have changed signiJicantly. With sustained growth, Bangladesh S per capita real GDP has nearly trepled since 1975. Life expectancy has risen to nearly 69 years. Bangladesh has successfully overcome its initial image of a famine-prone country unable to feed its population. The intensity ofpoverty in Bangladesh has been arrested to some extent but the social disparity and inequality remained persistently same. There are also strong criticism of not maintaining a comprehensive approach to address the issues of poverty and development. Bangladesh faces enormous challenges in alleviating poverty and achieving high, sustained and equitable economic growth. The country has to grapple with a number of growth retarding factors, such as a record of political uncertainty and systemic governance constraints. This paper intends to analyze the new perspective of governance and its role in poverty alleviation with empirical evidence from Bangladesh.
Chatbot Layanan Akademik Menggunakan K-Nearest Neighbor

Perusahaan atau institusi yang bergerak di bidang pelayanan publik pasti memiliki layanan customer service untuk menjawab pertanyaan dari konsumen. Namun perusahaan atau institusi dengan skala menengah ke bawah seringkali tidak sanggup untuk menyediakan karyawan khusus untuk menangani pekerjaan tersebut, sehingga pekerjaan tersebut dirangkap oleh karyawan di posisi lain. Chatbot dapat digunakan untuk menyelesaikan permasalahan yang berkaitan dengan layanan tanya jawab, khususnya bagi perusahaan atau institusi yang tidak memiliki sumber daya khusus untuk menangani pekerjaan tersebut. Dengan adanya chatbot, pertanyaan-pertanyaan konsumen yang bersifat redundan dapat ditangani secara otomatis. Pada penelitian ini, penulis membangun sistem chatbot untuk layanan tanya jawab seputar kegiatan akademik dengan menggunakan metode K-Nearest Neighbor. Berdasarkan hasil pengujian yang telah dilakukan, sistem dapat memberikan nilai akurasi sebesar 53.48% untuk nilai K = 3.
Testing the Relationship between Financial Inclusion, Institutional Quality and Inclusive Growth for Nigeria

This paper examines the causal relationship between financial inclusion, institutional quality and inclusive growth within a fourvariate ARDL-EC framework and forecast error variance decomposition technique for the period of 2003-2018 using quarterly data in Nigeria. The paper incorporates two variables to capture institutional quality (government effectiveness and regulatory quality) in order to eliminate variable omission bias in which most existing studies are characterised. Those adopted techniques confirm the long-run and bi-causal relationships mainly between financial inclusion and inclusive growth in Nigeria. In addition, bi-directional causal relationships of the outcome of the study are also established between financial inclusion and government effectiveness, likewise between inclusive growth and regulatory quality mainly in the short-run. The results based on the model and empirical outputs suggest that for the authorities of this economy to achieve and sustain equitable growth, fully disciplined policies that can promote and enhance financial inclusion and inclusive growth of the greater proportion of the population should not be managed and handled by loosed hands
Practical Feature Selection for Online Reinforcement Learning and Planning in Relational MDPs

Planning problems with large state spaces and unknown models can be solved by value-based reinforcement learning methods, using function approximation which abstracts states with feature vectors. Sample complexity increases when unnecessary features are selected. Conversely, omitting necessary features results in poor performances. A feature selection algorithm should add all necessary features while avoiding unnecessary ones. We introduce an online feature selection that considers the structure of relational MDPs (RMDPs) to reduce unnecessary features. Generalisation over different planning problems can be achieved by representing the approximated value-function with lifted representations of state variables and actions. Empirical results show that our method is practical for solving large RMDPs with reduced sample complexities and can generalise over different problems.
Eosinophilic Dermatosis of Hematologic Disease: A Case Report

Case Report Eosinophilic dermatosis of hematologic disease (EDH) or insect bite-like reaction is a rare paraneoplastic manifestation mostly described in patients with chronic lymphocytic leukemia. We report a case of a 67-years-old female patient presented to our dermatology department with a recurrent itchy papulo-vesicular lesions located on her face and extremities accompanied with asthenia and weight loss revealing chronic lymphocytic leukaemia. Based on clinical history and histopathologic features, we concluded to the diagnosis of EDH, and the patient received topical corticosteroids and antihistamines in association to chemotherapy achieving an hematological remission. However, the skin lesions recurred. The interest of this report lies in the rarity of this entity and the difficulty of differential diagnosis with lympho-proliferations. In addition, we aim to stress the fact that EDH can reveal the diagnosis of the hematologic malignancy.
Draft genome sequence of the polysaccharide degrading bacterium Cytophagaceae strain SJW1-29

29, isolated from the Seomjin River in Korea, was performed using the PacBio platform. The draft genome was composed of 7,065,248 bp with a G + C content of 50.7%. Genome annotation revealed that the genome comprised 5,684 protein-coding genes, 9 rRNA genes, 41 tRNA genes, 2 ncRNA genes, and 273 pseudo genes. Genome analysis revealed that the strain SJW1-29 harbors several carbohydrate active enzymes, which are provides insights for understanding the polysaccharide degradation system of the strain at the genome level.
Evaluating Performance of OMG DDS in Kubernetes Container Deployment (Industry Track)

OMG’s Data Distribution Service (DDS) is an open, real-time publish/subscribe middleware standard, which has been widely adopted in many latency-sensitive and mission-critical industrial IoT applications. However, deploying and managing large-scale distributed DDS applications is tedious and laborious. As a successful container orchestration platform for distributed applications in the cloud, Kubernetes (k8s) is a promising solution for DDS-based systems. However, the feasibility of running DDS applications in a k8s environment, and the overhead of different k8s virtualization network architectures on DDS application performance has not been systematically studied. To address this, we compare the performance of DDS applications with several k8s network solutions using a comprehensive set of experiments we designed for a DDS benchmark application. Our experimental results reveal that: (1) the overhead of container virtualization is trivial for DDS applications; (2) the overhead imposed by virtual networks is not significant and there is not much performance difference between the experimented virtual networking solutions; (3) WeaveNet is useful for DDS discovery because it supports IP multicast, but its multicast performance is considerably lower than the host network.
Outcome of SARS-CoV-2 in pregnancy and newborns – is there a new kid in the TORCH block?

Objective. This study aimed to perform a systematic review of existing literature to assess the outcomes of pregnancy in women with COVID-19 infection and their newborns while estimating the possibility of vertical transmission. Materials and methods. We conducted a systematic literature research using Pubmed and Google Scholar covering the period from December 2019 to 20th of November 2020. The review was conducted in accordance with PRISMA guidelines. Outcomes. We included 16 studies – systematic reviews and meta-analyses published between May 2020 and November 2020 – which focused on perinatal outcomes of pregnant women with COVID-19 and 7 case reports of neonates with congenital transmission of COVID-19. Overall, the rate of COVID-19 cases in neonates of COVID-19 positive mothers was 3% with 95% CI [1.86, 4.24]). The preterm birth rate was 16.4% with 95% CI [10.5, 22.3] and the rate of stillbirths and foetal deaths was 1.4% (11 studies, 0 to 4.8%). From the 7 newborns with proved vertical transmission, majority were born preterm, with good birth weight and APGAR score and heterogenous symptoms; 4 developed severe symptoms. Overall progress and evolution for both mother and newborn was good. Conclusions. COVID-19 impact on pregnancy outcome is similar to general population in regard to preterm rate and stillbirth rate. Vertical transmission is possible and it seems to occur in about 3% of cases. Overall maternal and perinatal outcome is favourable and clinical presentation of in utero transmission of SARSCoV-2 in newborns is heterogenous.
GC×GC-HRTOFMS for Cadaveric Odor Analysis: A Forensic Case Study

Objectives: Odor analysis is still highly controversial in the legal system regardless of its foundation in well-established gas chromatography – mass spectrometry (GC-MS) techniques. Despite extensive research characterizing decomposition odor, it has been disputed in a recent court case as being too untested (1). The literature depicts a different story whereby GC-MS analysis of decomposition odor is rapidly becoming outdated and replaced by comprehensive two-dimensional gas chromatography – mass spectrometry (GC×GC-MS). It has been demonstrated that GC×GC coupled with high-resolution time-of-flight mass spectrometry (HRTOFMS) is a valuable tool for the analysis of volatile organic compounds (VOCs) from decomposing cadavers (2). In this study, soil and adipocere samples from a forensic case were recovered at a site were a decomposing body was found. The goals were to accurately profile decomposition odor from case samples using GC×GC, establish the start of a long-term case study, and understand future challenges in real case scenarios.
Agent-based Investigation of the Impact of Low Rates of Influenza on Next Season Influenza Infections

Introduction Interventions to curb the spread of SARS-CoV-2 during the 2020-21 influenza season essentially eliminated influenza during that season. Given waning antibody titers over time, future residual population immunity against influenza will be reduced. The implication for the subsequent 2021-22 influenza season is unknown. Methods We used an agent-based model of influenza implemented in the FRED (Framework for Reconstructing Epidemiological Dynamics) simulation platform to estimate cases and hospitalization over two succeeding influenza seasons. The model uses a synthetic population to represent an actual population, and individual interactions in workplaces, school, households and neighborhoods. The impact of reduced residual immunity was estimated as a consequence of increased protective measures (e.g., social distancing and school closure) in the first season. The impact was contrasted by the level of similarity (cross-immunity) between influenza strains over the seasons. Results When the second season strains were dissimilar to the first season (have a low level of cross immunity), a low first season has limited impact on second season cases. When a high level of cross-immunity exists between strains in the 2 seasons, the first season has a much greater impact on the second season. In both cases this is modified by the transmissibility of strains in the 2 seasons. In the context of the 2021-22 season, the worst case scenario is a highly transmissible strain causing increased cases and hospitalizations over average influenza seasons, with a possible significant increase in cases in some scenarios. The most likely overall scenario for 2021-22 is a more modest increase in flu cases over an average season. Discussion Given the light 2020-21 season, we found that a large, compensatory second season might occur in 2021-22, depending on cross-immunity from past infection and transmissibility of strains. Furthermore, we found that enhanced vaccine coverage could reduce this high, compensatory season. Young children may be especially at risk in 2021-22 since very young children were unlikely to have had any exposure to infection and most immunity in that age group would be from vaccination, which wanes quickly.
Chemical Reaction Reference Resolution in Patents

Many new chemical compounds are reported each year in patent documents, leading to increasing demand for methods for automatic information extraction of chemical compounds and reactions from patents. Chemical patents often detail a number of similar compounds that have a common substructure and can be synthesized in analogous ways, and therefore contain many references connecting descriptions of similar chemical reactions, to avoid redundancy in describing common reaction conditions. This leads to the problem of reaction reference resolution , where, given a reaction description, we need to identify links to other reaction descriptions it refers to. In this paper, we formally introduce the task and propose baseline methods to address it in analogy with co-reference resolution. To evaluate the performance, we create a large-scale silver-standard dataset based on a commercial database of chemical reactions. The experimental results show that the approach based on a state-of-the-art co-reference resolution method struggles to outperform a simple heuristic in detecting reference links, demonstrating the difficulty of the proposed task and its fundamentally different nature to co-reference resolution.
Análisis de la utilidad del Bastón Blanco Inteligente UAEM

The aim of this research is to test the usefulness of the UAEM Smart White Cane prototype with ultrasonic sensors (alarm and vibration triggers) and GPS system (Global Positioning System) for visually impaired users. The technology included in the UAEM Smart White Cane provides the visually impaired user with several advantages to expand their mobility safely and improving their quality of life. But the proper use requires specialized training to help the user obtain the utility that the prototype promises. To prove the benefits, an exploratory study was used to analyze the training and consumption experiences of 20 adult participants with severe visual impairment and blindness. The statistical analysis was descriptive where the users' satisfaction with the physical characteristics and benefits obtained by the prototype was observed. As a result, it was observed an association between
Diet of Leptodactylus spixi (Anura: Leptodactylidae) from a cacao plantation in southern Bahia, Brazil

We studied the diet of Leptodactylus spixi from a cacao plantation in southern Bahia, Brazil. A total of 109 frogs were manually collected between December 2006 and October 2007 and analysed using a stomach flushing method. Of these, 69 stomachs revealed 168 prey items. Acarina, Orthoptera and Formicidae were the most abundant items, while Orthoptera, Diplopoda and Hemiptera were the most important in terms of frequency of occurrence. With more than 50% of total prey volume and the highest Index of Relative Importance, Orthoptera was considered the dominating prey category for this species in the studied area. The comparison between available potential prey in the environment and diet revealed that L. spixi fed on most present invertebrates. Electivity values were highest for orthopterans, gastropods and dermapterans. We conclude that L. spixi can be considered a “sitand-wait” predator and also a generalist consuming what is available in the environment.
REABILITAÇÃO ORAL ATRAVÉS DO PROTOCOLO DE

Endosseus titanium implants represent an important progress in dentistry. These implants allow edentulous patients rehabilitation by the use of Bränemark protocol. An appropriate and integrated treatment plan, as well the techniques used in each clinical stage, are essencial to the long-term sucesses. There is a high prevalence of edentulous in Brazil. Therefore, this case report aim to cause a discussion about the implant rehabilitation in a 65 years-old female patient whom was rehabilitated with a Bränemark protocol using 6 implants in the upper jaw and 5 in the lower jaw. This patient sought treatment in the State University of Maringá and was referred to the services of the Periodontics and Prosthodontics Residences. She asked for a better smile, but also she wanted to improve her chewing skills and phonation. At the end of this case, it might be concluded that Bränemark protocol is a practicable option since the technique is performed correctly leading great functional and aesthetics outcomes.
Safe Driving via Expert Guided Policy Optimization

When learning common skills like driving, beginners usually have domain experts standing by to ensure the safety of the learning process. We formulate such learning scheme under the Expert-in-the-loop Reinforcement Learning where a guardian is introduced to safeguard the exploration of the learning agent. While allowing the sufficient exploration in the uncertain environment, the guardian intervenes under dangerous situations and demonstrates the correct actions to avoid potential accidents. Thus ERL enables both exploration and expert's partial demonstration as two training sources. Following such a setting, we develop a novel Expert Guided Policy Optimization (EGPO) method which integrates the guardian in the loop of reinforcement learning. The guardian is composed of an expert policy to generate demonstration and a switch function to decide when to intervene. Particularly, a constrained optimization technique is used to tackle the trivial solution that the agent deliberately behaves dangerously to deceive the expert into taking over. Offline RL technique is further used to learn from the partial demonstration generated by the expert. Safe driving experiments show that our method achieves superior training and test-time safety, outperforms baselines with a substantial margin in sample efficiency, and preserves the generalizabiliy to unseen environments in test-time. Demo video and source code are available at: https://decisionforce.github. io/EGPO/
Variation of the Interplanetary Shocks in the Inner Heliosphere

Observations of the solar wind plasma and interplanetary magnetic field in the ecliptic plane by the Voyager 1 and 2 spacecraft are utilized to study the variation of the interplanetary shocks (with magnetosonic Mach number >1) encountered in the inner heliosphere, between ∼1 and ∼15 au from the Sun. The overwhelming majority (∼76%) of the shocks are fast forward (FF) moving at an average shock speed (V sh) of ∼458 km s−1 away from the Sun, and only ∼24% are fast reverse (FR) shocks with an average V sh of ∼323 km s−1 toward the Sun. About ∼89% of the shocks are quasi-perpendicular with an average shock angle (θ Bn) of ∼72° relative to the ambient magnetic field, and only ∼11% are quasi-parallel with an average θ Bn of ∼32°. While the interplanetary coronal mass ejections are the major (∼89%) driver of the FF shocks, a significant part (∼41%) of the FR shocks are associated with the corotating interaction regions. The shock occurrence rate, with a peak at the heliocentric distance (R h ) of ∼5 au, exhibits a clear decrease with the increasing R h . While the shock strength and propagation angle do not exhibit any systematic change with R h , V sh increases with the increasing R h at a rate of ∼11 km s−1 au−1.
Lithium ion rechargeable battery

This invention provides a high-output lithium ion rechargeable battery that can realize high capacitance and, at the same time, can maintain a high discharge voltage and can realize the repetition of large current charge/discharge. The lithium ion rechargeable battery comprises a group of electrodes and a lithium salt-containing nonaqueous electrolyte in which the group of electrodes are immersed. The group of electrodes are formed by stacking or winding a negative electrode material layer containing a material, which can occlude and release a lithium ion, and a positive electrode material layer containing a lithium-containing metal oxide through a synthetic resin separator. The lithium ion rechargeable battery is characterized in that the positive electrode material layer comprises a fluoridized lithium-containing metal oxide as a main component and the separator contains a hydrophilic group. Preferably, the positive electrode material layer comprises a main component of LiNixCoyMnzO2 wherein 0.4 <= x <=1, 0 <= y <= 0.2, 0 <= z <= 0.2, and x + y + z = 1.
Using Eye-Tracking to Account for Attribute Non-Attendance in Choice Experiments

This study uses eye-tracking measures to account for attribute non-attendance (ANA) in choice experiments. Using the case of sustainability labelling on coffee, we demonstrate various approaches to account for ANA based on number of fixation count cut-offs, definitions for detecting ignored attributes, and methods for modelling ANA. Some of the sustainability attributes identified through eye-tracking measures as being ‘visually ignored’ were truly ignored while in none of the tested approaches price was truly ignored. The adequacy of eyetracking as a visual ANA measure might thus depend on the attribute. Further, there are inconsistencies in identifying non-attenders using visual ANA and the coefficient of variation. Based on our results, we cannot conclude that eye-tracking always adequately identifies ANA. However, we identified several major challenges that can assist in further optimizing the use of eye-tracking in the context of ANA.
Towards Generating Effective Plans in Zero-sum Games by Estimating Strategy of an Adversary

In a nutshell, zero-sum games represent scenarios where two agents compete for the same goals such that each goal can be achieved by at most one of the agents. The goals are, for example, collecting limited resources or transporting passengers from their given location of origin to a required destination. To achieve the goals, the agent might generate a plan. Plan generation, however, has to take possible actions of the adversary into consideration. In this paper, considering planning in zero-sum games, we propose a heuristic approach for estimating strategies of the adversary, more speciﬁcally distribution of possible application times of its actions interfering with some of the agent’s actions. The agent’s actions in question have to be applied before those of the adversary, whose estimated times hence represent their deadlines. Missing the deadlines can be represented by action cost, so generated plans can be optimised for minimum total action cost. We empirically evaluate our approach by comparing it to the baseline approach (plan generation without taking adversary into account) and to the state-of-the-art approach leveraging the Double Oracle algorithm for computing adversary strategies.