Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth and flow cytometric monitoring of bacteria in drinking water

Bacteria are omnipresent, also in our drinking water. This is unavoidable but should not be a reason to worry. It is better to understand them, to be able to control and predict their behavior. In a first section of this research, fundamental factors affecting bacterial presence in drinking water were studied. Transparent exopolymer particles were monitored as a possible biofilm promoter, but their importance in Flemish drinking waters appeared to be limited. In addition, the factors governing growth or survival of intruding bacteria in drinking water were studied. It appeared that next to the available nutrients, the present indigenous microbial community was crucial. Routine monitoring of bacteria in drinking water asks for performant tools. Therefore, the second section optimized the use of flow cytometry as a high-throughput monitoring tool and it was shown that bacterial analysis could be done fast and precise. A third and final section was conducted in close collaboration with drinking water industry and searched for additional applications for flow cytometry, deviating from routine monitoring. The tool was successfully applied for providing fast information during rinsing of major supply pipes and for a quick screening of bacterial growth in a local drinking water network.
The Effects of Peer-to-Peer (P2P) Lending on Competition, Discrimination, and Financial Stability

Using loan application and origination data reported by the largest peer-to-peer (P2P) lender, Lending Club, I test whether P2P lending expands access to credit for households and small businesses, whether its lending criteria has a disparate impact on communities based on race, and how competition with P2P lenders may make banks’ loan portfolios riskier. I find strong support for the expansion of credit by P2P lending by mitigating lack of competition due to a concentrated banking market. I find some support for expansion of credit by overcoming discrimination in terms of approvals for applicants in areas with more black residents. However, I also find striking evidence of the P2P lender assigning lower loan ratings (higher interest rates) to approved borrowers living in areas with more black residents. I also find that competition from P2P lenders could leave a riskier pool of potential borrowers for banks, thus threatening financial stability. An important control in these tests are the average credit attributes aggregated over the same areas in which bank structure, income, and demographic variables are constructed.
Weak convergence and empirical processes

1 Review of metric topology 3 1.1 Metric spaces . 3 1.2 Open and closed sets . 4 1.3 Continuity . 4 1.4 Limit points and accumulation points . 5 1.5 Denseness . 6 1.6 Convergence, Cauchy sequences and completeness . 6 1.7 Compactness . 7 1.8 Connectedness . 8
The company perspective of product variety: a conceptual model

In economics research questions are often discussed in isolation, thereby forgetting the bigger picture, e.g. regarding product variety, and consumer needs and demands on a product. In this paper, we integrate miscellaneous aspects and establish a conceptual model of changing product variety from a company´s perspective using qualitative reasoning. We use a set of selected publications that gives a contemporary overview of this economic domain and how parts of the system are interconnected. The formalization and visualization of domain knowledge is expected to dissolve discrepancies and misinterpretations in meaning, since it empowers people involved in decision processes to enter in dialog and discussion more easily. The development of causal relationships turned out to be demanding, perhaps also because in the literature there is a lack of answers to some questions. However, that is also a benefit of our research: developing mechanisms that explain how these phenomena may work. The question of how the relevant parts of the system behave if a trigger from the outside comes (or the absence of a trigger) is helpful for thinking about business processes.
OPTIMIZATION UNDER UNCERTAINTIES USING THE CONTINUOUS ADJOINT METHOD AND POLYNOMIAL CHAOS EXPANSION

Uncertainties associated with either the operating conditions and/or manufacturing imperfections frequently affect the results of design/optimization methods in various engineering fields. This paper deals with optimization under uncertainties related to the flow conditions and is based on the non-intrusive Polynomial Chaos Expansion (PCE). In previous work by the same group of authors, the non–intrusive PCE was combined with evolutionary algorithms [1, 2]; in contrast, in this work, the optimization is performed by a gradient–based algorithm. The role of PCE is to compute the first and second statistical moments of the quantity of interest. Working, though, with a gradient–based method, the gradient of these statistical moments with respect to the design variables must be computed too and this is made possibly by implementing the continuous adjoint technique. This paper presents optimizations under uncertainties of a) a heat transfer system, namely a lid–driven cavity with one blowing and one suction jet for the maximization of the heat extracted through the upper moving wall by computing the optimal locations of the jets, with uncertainties related to their operating conditions and b) a car model aiming at minimum drag, in which the design variables are the control points of a volumetric B–Splines lattice and the uncertain variable is the freestream velocity. A.G. Liatsikouras et al
Karyotype Differentiation in Newly Discovered Members of the Drosophila obscura Species Group from Yunnan , China

观察了新近发现于我国云南的果蝇属暗果蝇种组( Drosophila obscura species group ) 种类 D1luguensis 、D1 dianensis 和D1limingi 的有丝分裂中期核型, 并将3 个种的核型与各自的近缘种类进行了比较。 D1luguensis 具2n = 12 条染色体, 包括3 对中央着丝粒(V 形) 染色体、2 对近端着丝粒(棒状) 染色体以及1 对微小(点状) 染色体。 其中X 和Y染色体均为中央着丝粒染色体。 D1 dianensis 和D1limingi 具2n = 10 条染 色体, 包括1 对大的V 形常染色体, 1 对小的V 形常染色体, 2 对J 形(亚中着丝粒型) 常染色体和1 对点状染 色体。 其中X 染色体为J 形, Y染色体为短棒状。 基于核型比较的结果以及D1sinobscura 亚组地理分布的资料, 结合种间系统发育关系研究结果, 认为D1 luguensis 可能保留了该亚组祖先种类的核型。 D1sinobscura 的核型(2n = 12 : 2V , 1J , 2R , 1D) 可能由一个pre2“sinobscura2hubeiensis”谱系的一个分支通过臂间倒位演化而来, 而D1 hubeiensis 的核型(2n = 10 : 4V , 1D) 可能由该谱系的另一分支通过着丝粒融合(2 对近端着丝粒常染色 体的融合) 而形成。 推测在D1 dianensis 和近缘欧洲种D1subsilvestris (2n = 12 : 3V , 2R , 1D) 间、D1limingi 和 东亚近缘种D1tsukubaensis (2n = 12 : 3V , 2R , 1D) 间的物种分化过程中, 可能有相似的染色体变异类型发生。
Elevated Serum Levels of CEA in Egyptian Female Breast Cancer Patients as Standing Tumor Biomarker

Tumor markers are substances produced by the tumors or by other cells of the body in response to cancer or certain benign conditions. Although most of these markers are made by the normal cells as well as by cancer cells, they are produced at much higher levels in cancerous conditions. These markers are used to evaluate the patient's response to treatment and to detect the presence of metastasis or recurrence. Breast cancer is one of the most common malignancies in females worldwide. The Carcinoembryonic antigen CEA is tumor marker that is often expressed in people with breast cancer. It plays a crucial role in diagnosis, monitoring response to therapy, early detection of metastasis and determination of recurrence in patients with breast cancer. KeywordsBreast cancer, Carcinoembryonic antigen, Diagnosis, Screening, Tumor marker ——————————  ——————————
Impact of AnonStalk (Anonymous Stalking) on users of Social Media: a Case Study

In the period that we are living, there is a massive exchange of information, while the communication has drastically changed as more and more people using the social networks. Using this kind of technology undoubtedly leads to exposure of personal information on the part of users, enabling the use of Open-Source Intelligence (OSINT) techniques in order to obtained sensitive data from not authorised users. Separating the medium itself from how it is used by users, we consider how possible it is for a malicious user (intruder) to extract personal data in an automated method, and use them against an unsuspicious user of social media. By this way users can be deceived as well as the user’s followers by watching different data from the real one as the attacker has the chance to modify them. Moreover, the exposed users lose any sense of privacy as they become victims, penetrating to their personal information. The paper describes the architecture and implementation of a method that collects data anonymously from Twitter and Instagram using Twitter REST API and “geoJSON” along with “Instagram Real-Time API” and “Genymotion”. After the collection and the processing of data, the output is representing in a graphical map that can be easily accessible and provide all the information to the attacker. In terms of anonymity we followed various procedures that a malicious user could follow in order to hide his tracks and create accounts in both platforms that can be used in the implemented application. The results show that the intruder can retrieve sensitive personal data (user location via tweets / instas from smartphone). In addition, the ability to map the activity could allow a malicious user to track an unsuspecting person’s activity and predict their future locations. This research also revealed that anyone with basic knowledge of computer becomes anonymous intruder of our personal life, causing fear and horror to those that are unsheltered.
Neuroprosthesis: A Step Towards Complete Control Over Prosthetic Limbs

The paper proposes an alternative to Bionic Prosthetics, which can be advancement in the field of Neuroprosthetics, using the user’s brain wave. It uses WBCI and organic opto-electronic muscle contracting sensor to interface the brain with the basic bionic arm making the mobility of amputees easier. This paper also proposes the usage and importance of “phantom limb syndrome” for replicating sensations and for creating an interface between both brain and technology. [4]
Building Innovation Capabilities in Farmer Organizations

Organizational capabilities for innovation encompass the abilities of the organization’s members (such as specialized knowledge, creativity, and task commitment) and the organization’s key characteristics (such as culture, governance, communications and learning routines, and resources). Interventions to build organizational capabilities for innovation involve building the individual and collective capabilities themselves and making the enabling environment more supportive of innovation. Instruments for capacity building have included fostering interactions among actors in the AIS, creating venture capital funds, consolidating innovation brokers, strengthening the policy framework for innovation, and setting up training and mentoring programs and multistakeholder platforms. The environment for innovation improves when governments and donors facilitate dialogues to develop consensual innovation policies, create market and social opportunities for innovation, facilitate access to crucial inputs, strengthen flows of commercial and technical information, offer public institutions incentives to interact with farmer organizations, and promote a legal environment that supports farmer organizations and encourages decentralization to empower local farmer organizations. The most innovative farmer organizations have a federated structure, i.e., are composed of small, linked farmer groups, thus combining the best features of large organizations and small groups. In designing projects to develop farmer organ izations that can innovate, practitioners should select organizations that can learn; avoid overly strict criteria for participation; avoid requiring organizations to become formal entities; identify the networks in which the farmer organization participates, because its partners can indicate its own innovativeness; use external consultants and innovation brokers to design training programs; and develop a monitoring and evaluation system that promotes exploration and learning.
A comparative, correlate analysis and projection of global and regional life expectancy, healthy life expectancy, and their GAP: 1995-2025

Background Life expectancy (LE) and healthy life expectancy (HALE) are indicators measuring the national health level. GAP is the difference between them. This study systematically analyzed and projected LE, HALE, and GAP across global regions from 1995 to 2025. Methods We obtained the data of 195 countries/regions on their LE, HALE, and influencing factors from 1995 to 2017. We compared the overall changes of LE, HALE, and GAP. Multiple linear regression analysis examined relationships among LE, HALE, GAP, and the associated factors. Using the Autoregressive Integrated Moving Average (ARIMA) model, we projected trends in LE, HALE, and GAP for 2017-2025. Results During 1995-2017, LE, HALE, and their GAP in 195 countries/regions in the world showed overall increasing trends. Global average LE increased from 66.20 to 72.98 years, HALE from 57.59 to 63.25 years, and GAP from 8.62 to 9.72 years. LE and HALE in North America, Europe, and Australia were generally higher, while Africa had the lowest rates. Females' LE, HALE, and GAP were all higher than males’, but females' growth rates of LE and HALE were lower. Different factors were included to project LE, HALE, and GAP, respectively, and prediction results showed that approximately 18% of the 195 countries/regions might achieve improved LE and HALE and lower GAP. Conclusions LE, HALE will likely continue to increase in most of countries and regions worldwide in the future and GAP will further expand. While striving to improve LE and HALE, more attention needs be made to reduce GAP and improve quality of life.
Higer-order commutators of parametrized Marcinkewicz integrals on Herz spaces with variable exponent

It is easy to see that when ρ = 1, and μρ(h) = μ1(h), then (2) is the classical Marcinkiewicz integral μ(h) introduced by Stein in [1]. It has been proved in [1] that if Ω ∈ Lipγ(Sn−1) (0 < γ ≤ 1) and Ω is continuous, then the operator μ(h) is of the type (q, q) for 1 < q ≤ 2 and of the weak type (1, 1). Benedek et al., [2] proved that if Ω ∈ C1(Sn−1), then μ(h) it is of type (q, q) for any 1 < q ≤ ∞. The Lp boundedness of the μ(h) has been studied in [1,3–5]. In 1960, Hörmander [4] introduced the parametrized Marcinkiewicz integral operators proved that if Ω ∈ Lipγ(Sn−1), 0 < γ ≤ 1, then it is of strong type (q, q) for 1 < q ≤ 2. Sakamoto and Yabuta [6] proved the boundedness of the operator μρ(h) on Lq(Rn). Shi and Jiang [7] considered the weighted Lq−boundedness of parametrized Marcinkiewicz integral operator and its higher order commutator. Note that the Littlewood-paley g-function played very important roles in harmonic analysis and the parameterized Marcinkiewick integral is a special case of the Littlewood-paley g-function. Many authors studied properties of μρ(h) on different function spaces, for examples [8–14].
Latent Context Based Soft Actor-Critic

The performance of deep reinforcement learning methods prone to degenerate when applied to tasks requiring relatively longer horizon memory or with highly variable dynamics. In this paper, we utilize the probabilistic latent context variables motivated by recent Meta-RL materials, and propose the Latent Context based Soft Actor-Critic (LC-SAC) approach to address aforementioned issues. The latent context is capable to encode information about both the agent’s previous behaviors and the dynamics of the current undergoing environment, which empirically believed to be beneficial for efficient policy optimization. Experiment results demonstrate that LC-SAC can achieve comparable performance with SAC on a collection of continuous control benchmarks and outperforms SAC in some particular tasks with above two characteristics. Moreover, we also introduce a simple but general procedure to integrate LC-SAC with diverse-quality demonstrations to enable efficient reuse of human prior knowledge, and finally achieve competitive performance with comparatively small number of interactions with environments.
Automated Agricultural FieldAnalysis and Monitoring System Using IOT

— Smarter world is the resultant of the smarter technology. Agriculture was implemented in the nine of sedentary human civilization and it is the backbone of our Indian Economy. But the same traditional techniques like manual field monitoring, water feeding, pest detection, soil testing, etc., we are using for monitoring the field and frequently applying pesticides with or without having the knowledge of quantity to be used to control pests that affect the crops. So it is very important to enhance the agricultural production by making use of technology to overcome the damages being done. Our aim is to provide smart monitoring system using the current technologies like IoT, cloud computing and image processing. To address the above problems the authors of this paper are coming up with a model named “AAFAMS”( Automated Agricultural Field Analysis and Monitoring System Using IOT) which is used not only for monitoring the field but also to suggest the farmers about the moisture content in soil, detecting pest and the type of crop suited for the soil. In AAFAMS, a line follower robot is developed by using a hardware kit called Raspberry pi, which monitors the soil moisture level at every 100m distance using a soil moisture sensor and the information obtained from the sensor will be sent to cloud for storage. A camera will be connected to the AAFAMS which will detect the pests. After complete survey of field AAFAMS retrieves all stored data from
Segregation of Code-Switching Sentences using Rule-Based Technique

Code-switching sentence contains a mixture of two or more languages within a single constructed sentence. Code-switching is a new trend of language that is widely used in open platform such as blogs and social medias. Consequently, code-switching which has become a new challenge to natural language processing (NLP). The challenge is due to the limitation of the existing NLP systems which were designed for mono-lingual system. Therefore, a new NLP system is needed to deal with code-switching sentences. However, system that segregate code-switching sentences from mono-lingual sentences must be developed prior to the code-switching sentences are used in the NLP systems. This paper considers the segregation is essential because firstly the current NLP systems deals only with mono-lingual sentences. Secondly the current NLP systems treats switching words as meaningless thus will lead to inaccurate result. This paper segregates code-switching sentences from mono-lingual sentences using rule-based technique and dictionaries. This paper used the ratio of word presence to segregate the sentences. The rule-based technique performed with accuracy of more than 87.00% for Malay-English code-switching (MY-EN-CS) sentences.
Online Mixed Missing Value Imputation Using Gaussian Copula

Many data science algorithms require complete observations, making missing value imputation an important step in many data processing pipelines. Imputation is also of independent interest for applications such as recommender systems. To address real-world big data problems, imputation algorithms must handle mixed data, containing ordinal, boolean, and continuous variables, and such algorithms must be highly scalable. In this work we develop a semi-parametric online algo-rithm for mixed missing value imputation using a Gaussian Copula. This online algorithm improves on the speed of its ofﬂine counterpart by an order of magnitude, with similar accuracy. The online method can also improve on the ofﬂine method by adapting to a changing data distribution.
Comparison of the Effect of Different Dosages of Celecoxib on Reducing Pain after Cystocele and Rectocele Repair Surgery

This randomized clinical trial was performed on 90 patients undergoing cystocele and rectocele repair under spinal anesthesia. Patients were randomly divided into 3 groups: the first group received 200 mg/day celecoxib, the second group received 400 mg/day celecoxib and the third group was placebo. The pain was measured at 8, 16 and 24 hours after surgery using the VAS (Visual Analogue Scale) method. If the pain score was greater than 5, pethidine 1 mg/kg was prescribed. Pain score at 8, 16 and 24 hours, the need for pethidine, side effects and satisfaction score were recorded during the first 24 hours after surgery.
Closed-Form Formulas for Generalized Cox, Ingersoll and Ross Models-Proceedings AFIR 1999-Tokyo, Japan

This paper gives a closed-form formula for pricing default-free zero-coupon bonds in a generalization of the Cox, Ingersoll and Ross (1985) model, in which the “normal level” of the short rate is an exponentially weighted average of past short rates. The model is further extended to the case in which the initial yield curve can be prescribed exogenously, and a closed-form formula for bond prices is also found.
A study on factors affecting consumers' information retrieval activities: Focusing on outbound tourism consumers in Japan and South Korea

Information is very important for modern consumers, and the factors that have a great influence on product purchasing. Accordingly, elucidating factors affecting the retrieval process of information is an important. This study identifies factors that affect tourism information retrieval activities. First, it was carried out the meta analysis of tourism information, repurchase intention, attitude toward technology, and information utilization. Through the meta analysis, hypothesis model about each factor of information retrieval and repurchase of tourism products was suggested. The hypothesis model was verified by a survey of Korean and Japanese tourists. As a result, it is confirmed the relationship between the above factors. The results of this study are expected to contribute to the development of a tourists’ information usage model in the future.
Multi-criteria analysis involving Pareto-optimal misclassification tradeoffs on imbalanced datasets

On binary classification, the goal of minimizing the false positive and false negative rates creates a conflict, being impossible to optimize both simultaneously. This challenge is even more significant on imbalanced classification datasets since an incorrect choice of the relative relevance of each objective on the optimization can lead to ignoring, or poorly learning the minority class. The proposal of this work takes into account the existing conflict among the learning losses of the classes, and use a deterministic multi-objective optimization method, called MONISE, to create a set of solutions with diverse misclassification tradeoffs among the classes. Since accuracy is no longer a proper criterion for imbalanced datasets, we had to resort to multiple criteria to report the performance: each classifier, proposed or competitors, was selected and reported using the same metrics. We used F1, kappa and g-mean for general evaluation of performance and ${F_\beta }{\mathbf{s}}\left({{F_{1/16}},{F_{1/4}},{F_4}{\text{ and }}{F_{16}}}\right)$ to emulate a shifting decision maker preference from precision to recall; all comparisons were made using a Friedman test with Finner posthoc test. However, when we take into account multiple metrics without any prior knowledge, it may become impossible to pinpoint the best method, since the evaluation criteria may also be in conflict. Again, to solve this, we resorted to a Friedman test with a non-dominated ranking. With this multi-criteria analyses, we conclude that explicitly considering multiple objectives on the optimization can guide to promising results.