Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptation to Climate Change and Variability and Its Implications for Household Nutrition in Kenya

Climate change and variability are affecting weather patterns and causing seasonal shifts with serious repercussions for households and communities in Kenya. The livelihoods of the majority of Kenyans are therefore threatened due to the potential adverse impacts of climate change, such as declining production and productivity, which could lead to food insecurity. To mitigate the negative impacts of climate change and variability, farmers need to adopt different strategies, such as new crop varieties, crop and livestock diversification, and water-harvesting technologies. These climate change adaptation strategies are expected to influence the level of food production (hence food security) in the country, and therefore their linkages with food security in Kenya need to be studied. It is against this background that this study was undertaken to assess factors influencing climate change adaptation and the implications of adaptation for nutrition, measured in kilocalories (Kcal) produced. To accomplish this task, an endogenous switching regression model is applied to household survey data of 708 households from 38 counties in Kenya. The results demonstrate that mean temperature does not influence Kcal production but increased precipitation can negatively or positively influence Kcal production, depending on whether it rains during harvest, land preparation or crop growing periods. Households living in areas with different soil types are likely to produce varying quantities of Kcal depending on the soil type. This requires intervention in improving soil fertility, alongside adopting crop enterprises suitable for these areas. In addition, older and more experienced farmers will produce more nutrition compared to younger farmers with little farming experience. Finally, it is shown that farmers who adapted to climate change produced 1,305,414 Kcal against 564,789 Kcal for households that did not adapt. The treatment effects results show that farm households that actually adapted would have produced about 996,224 Kcal less (that is, about 23.7% less) if they had not adapted. By contrast, if farmers who did not adapt had adapted, they would have produced about 773,879 Kcal more (that is, about 27.01% more). Thus, adaptation to climate change significantly increases production of nutrition.
Pomogranite disease detection and classification

In country like India, agriculture is the backbone of the overall GDP. Horticulture has become one of the important source of economy for the country and even the farmers. Formers will face much losses because of the not identifying the diseases at early stage. Relying on pure naked-eye observation to detect and classify diseases can be expensive for various plant diseases such as Pomegranate. It poses a great threat to the agricultural sector by reducing the life of the plants. In Agriculture field also image processing plays a very important role in identifying any disease of the plant or in grading of the quality of the fruit. Identification of the plant diseases is the key to preventing the losses in the yield and quantity of the agricultural product. The studies of the plant diseases mean the studies of visually observable patterns seen on the plant. Health monitoring and disease detection on plant is very critical for sustainable agriculture. It is very difficult to monitor the plant diseases manually. In this paper, we have implemented the methods for the detection of Pomegranate plant diseases using the images of the leaves.
Robust Frequency Divider for Power System Online Monitoring and Control

Accurate local bus frequency is essential for power system frequency regulation provided by distributed energy sources, flexible loads, and among others. This paper proposes a robust frequency divider (RFD) for online bus frequency estimation. Our RFD is independent of the load models, and the knowledge of swing equation parameters, transmission line parameters, and local Phasor Measurement Unit (PMU) measurements at each generator terminal bus is sufficient. In addition, it is able to handle several types of data quality issues, such as measurement noise, gross measurement errors, cyberattacks, and measurement losses. Furthermore, the proposed RFD contains the decentralized estimation of local generator rotor speeds and the centralized bus frequency estimation, which resembles the structure of the decentralized/hierarchical control scheme. This enables RFD for very large-scale system applications. Specifically, we decouple each generator from the rest of the system by treating metered real power injection as inputs and the frequency measurements provided by PMU as outputs; then a robust unscented Kalman filter based dynamic state estimator is proposed for local generator rotor speed estimation; finally, these rotor speeds are transmitted to control center for bus frequency estimation. Numerical results carried out on the IEEE 39-bus and 145-bus systems demonstrate the effectiveness and robustness of the proposed method.
Performance analysis of VSI based standalone PV generation system connected to induction motor

Renewable energy sources like wind & solar can be regarded as the acceptable alternative for conventional energy sources. The standalone photovoltaic system basically used to provide the electricity to the remote areas. This study illustrates the performance analysis of 3-phase induction motor working as a load with PV array is connected. In this paper input voltage of the inverter is a step-up by dc/dc boost converter. Designed boost converter with MPPT boosts the voltage that is developed by the PV array to a specific required value that can run satisfactorily the 3-phase induction motor. The inverter transforms the DC voltage to the AC that is controlled with the help of SPWM-VSI techniques, as the inverter output voltage is not pure sinusoidal so LC-filter is used to obtain the proper sine waveform. Thus output voltage of Inverter can be used to operate the 3-phase induction motor at different loading. The acceptable results are procured for the given loads and the load voltage is found to be steady under varying load setting.
Increased Fatty Acid Oxidation in Differentiated Proximal Tubular Cells Surviving a Reversible Episode of Acute Kidney Injury

Background/Aims: Fatty acid oxidation (FAO), the main source of energy produced by tubular epithelial cells in the kidney, was found to be defective in tubulo-interstitial samples dissected out in kidney biopsies from patients with chronic kidney disease (CKD). Experimental data indicated that this decrease was a strong determinant of renal fibrogenesis, hence a focus for therapeutic interventions. Nevertheless, whether persistently differentiated renal tubules, surviving in a pro-fibrotic environment, also suffer from a decrease in FAO, is currently unknown. Methods: To address this question, we isolated proximal tubules captured ex vivo on the basis of the expression of an intact brush border antigen (Prominin-1) in C57BL6/J mice subjected to a controlled, two-hit model of renal fibrosis (reversible ischemic acute kidney injury (AKI) or sham surgery, followed by angiotensin 2 administration). A transcriptomic high throughput sequencing was performed on total mRNA from these cells, and on whole kidneys. Results: In contrast to mice subjected to sham surgery, mice with a history of AKI displayed histologically more renal fibrosis when exposed to angiotensin 2. High throughput RNA sequencing, principal component analysis and clustering showed marked consistency within experimental groups. As expected, FAO transcripts were decreased in whole fibrotic kidneys. Surprisingly, however, up- rather than down-regulation of metabolic pathways (oxidative phosphorylation, fatty acid metabolism, glycolysis, and PPAR signalling pathway) was a hallmark of the differentiated tubules captured from fibrotic kidneys. Immunofluorescence co-staining analysis confirmed that the expression of FAO enzymes was dependent of tubular trophicity. Conclusions: These data suggest that in differentiated proximal tubules energetic hyperactivity is promoted concurrently with organ fibrogenesis.
Brief Announcement: Sustainable Blockchains through Proof of eXercise

Cryptocurrency and blockchain technologies are recently gaining wide adoption since the introduction of Bitcoin, being distributed, authority-free, and secure. Proof of Work (PoW) is at the heart of blockchain's security, asset generation, and maintenance. Although simple and secure, a hash-based PoW like Bitcoin's puzzle is often referred to as "useless'', and the used intensive computations are considered "waste'' of energy. A myriad of Proof of "something'' alternatives have been proposed to mitigate energy consumption; however, they either introduced new security threats and limitations, or the "work'' remained far from being really "useful''. In this work, we introduce Proof of eXercise (PoX): a sustainable alternative to PoW where an eXercise is a real world matrix-based scientific computation problem. We provide a novel study of the properties of Bitcoin's PoW, the challenges of a more "rational'' solution as PoX, and we suggest a comprehensive approach for PoX.
Energy Storage From Aggregate Deferrable Demand: Fundamental Trade-Offs and Scheduling Policies

We investigate the ability of a collection of deferrable energy loads to behave as a battery; that is, to absorb and release energy in a controllable fashion up to fixed and predetermined limits on volume, charge rate, and discharge rate. We derive explicit bounds on the battery capacity that can be offered, and show that there is a fundamental tradeoff between the abilities of collective load to absorb and release energy at high aggregate rates. Finally, we introduce a new class of dynamic priority-driven feedback policies that balance these abilities, and characterize the batteries that these policies can emulate.
Evaluation of the Quality of Care among Hospitalized Adult Patients with Community-Acquired Pneumonia in Korea

Pneumonia is an important cause of morbidity and mortality. Since 2014, the Health Insurance Review and Assessment Service (HIRA) has assessed the overall quality of care among hospitalized adult patients with community-acquired pneumonia (CAP) provided by all medical institutions in Korea. A committee of the Korea Academy of Tuberculosis and Respiratory Diseases developed the hospital inpatient quality measures set for CAP consisting of eight core measures and five monitoring measures. The composite measure score was calculated. The medical records of hospitalized adult patients ages 18 years or more with CAP from October to December 2014 were evaluated. The data of 523 hospitals (42 tertiary hospitals [8.0%], 256 general hospitals [49%], and 225 hospitals [43.0%]) and 15,432 cases (tertiary hospitals, 1,673 cases [10.8%]; general hospitals, 8,803 cases [57.1%]; hospitals, 4,956 cases [32.1%]) were analyzed. We found large variations among institutions in terms of performance of care measures for CAP. For the composite measure score, the mean value was 66.7 (tertiary hospitals, 98.5; general hospitals, 79.2; hospitals, 43.8). Despite significant differences in measure scores between tertiary, general hospitals and hospitals, no significant differences were found in mortality between hospitals. Further studies are needed to determine the care measures appropriate for CAP.
Comparative analysis of postural control in individuals with and without injuries on knee anterior cruciate ligament

1. Physical therapist, student in the Course on Improvements in Locomotive Apparatus Biomechanics, from the Professional Refinement Program, Qualification and Development Nucleus – HC-FMUSP. 2. Doctor orthopaedics, PhD assistant and vice-head of the Laboratory of Biomechanics of the Orthopaedics and Traumatology Institute, HC-FMUSP. 3. Health technologist, expert in Biomechanics and coordinator of the mechanics department of the Laboratory of Biomechanics, Orthopaedics and Traumatology Institute, HCFMUSP. 4. Physiatrist of the Laboratory of Motion Studies, Orthopaedics and Traumatology Institute, HC-FMUSP. 5. Physiatrist, Full Professor at FMUSP. 6. Physical therapist, student in the Course on Improvements in Physical Therapy in Orthopaedics, from the Professional Refinement Program, Qualification and Development Nucleus, HC-FMUSP.
LcwtNet: Lifting complex wavelet layers for constructing a compact DNN model

In this paper, a new compact deep neural network (DNN) architecture based on lifting complex wavelets is proposed. The proposed DNN architecture (LcwtNet) is composed of multiple layers in addition to a CNN architecture. Complex wavelet and lifting wavelet layers are introduced as the lower layers of LcwtNet, which can reduce the number of parameters while maintaining high performance similar to that of CNN models. In simulations, the effectiveness of LcwtNet is demonstrated by several test results using the MNIST dataset.
Improving Government Response to Citizen Requests Online

The Mexican constitution guarantees its citizens the right to submit individual requests to the government. Public officials are obligated to read and respond to citizen requests in a timely manner. Each request goes through three processing steps during which human employees read, analyze, and route requests to the appropriate federal agency depending on its content. The Mexican government recently created a centralized online submission system. In the year following the release of the online system, the number of submitted requests doubled. With limited resources to manually process each request, the Sistema Atención Ciudadana (SAC) office in charge of handling requests has struggled to keep up with the increasing volume, resulting in longer processing time. Our goal is to build a machine learning system to process requests in order to allow the government to respond to citizen requests more efficiently. We develop models to help at each stage: to accept or reject incoming requests, distinguish between technical support questions to a help desk and substantive requests to the SAC, and send substantive requests to the appropriate federal agency. Given the office's needs, our system can automatically accept or reject 85% of all requests, automatically send 39% of requests to a technical helpdesk or to the SAC, and automatically routes 49% of all requests to the most appropriate federal agency. These models each operate at a different step in the manual request sorting process. Incorporation of our models into the request system would save the office of the president 3.8 man hours per day accepting and rejecting requests, 3.1 man hours per day deciding whether requests should go to the helpdesk, and 4.8 man hours per day routing requests to federal agencies. Together, this would allow the government to process 24.4% more petitions, allowing them to better address citizen needs with limited resources.
NON-LOCALLY CENTRALIZED SPARSE REPRESENTATION FOR IMAGE SUPER-RESOLUTION WITH SPATIAL INFORMATION FILTERING

Sparse representation models code an image patch as a linear combination of a few atoms chosen out from an over-complete dictionary, and they have shown promising results in various image restoration applications. However, due to the degradation of the observed image (e.g., noisy, blurred, and/or down-sampled), the sparse representations by conventional models may not be accurate enough for a faithful reconstruction of the original image. To improve the performance of sparse representation-based image restoration, in this paper the concept of sparse coding noise is introduced, and the goal of image restoration turns to how to suppress the sparse coding noise. To this end, we exploit the image nonlocal self-similarity to obtain good estimates of the sparse coding coefficients of the original image, and then centralize the sparse coding coefficients of the observed image to those estimates. The so-called nonlocally centralized sparse representation (NCSR) model is as simple as the standard sparse representation model, while our extensive experiments on various types of image restoration problems, including denoising, deblurring and super-resolution, validate the generality and state-of-the-art performance of the proposed NCSR algorithm.
A domain-specific language for supporting event log extraction from ERP systems

Process mining techniques provide capabilities for discovering the real business process flows from data, and compare expected and actual behaviors. Actual behaviors, in many cases, are obtained from Enterprise Resource Planning (ERP) systems and other enterprise information systems transaction logs. These transaction logs provide valuable insight into the companies' business processes. They traditionally hold a large amount of data in a set of conceptual documents related to each other through one-to-many and many-to-many relations, where information changes occur in transactions. Underlying data model gives rise to complex interactions between multiple data objects without a clear notion of a unique case identifier in an isolated process. However, enterprise process mining techniques can be applied only to event logs containing event data related to one notion of process instances. Within ERP systems, such event logs are not explicitly given and substantial domain knowledge is required to select the right data from multiple tables in relational databases. In order to respond to this need, in this paper we present an abstract syntax of domain-specific language (DSL) for facilitating the extraction of an appropriate dataset from ERP systems by domain experts, and its conversion into event log based on XES IEEE standard. It is developed specifically to describe behavior over complex data from ERP systems in terms of multiple interacting artifacts. The goal is to align the data and process perspectives, supporting extraction of complex ambiguous cases, affected by data convergence and data divergence problems. The basic concepts of the language as well as principles are discussed in depth in this paper.
Game theoretic belief approach in project selection problem

Decision making problem is co-related to quality and availability of the information. In this paper, an innovative algorithm has been proposed to help decision support system under imperfect and fuzzy information provided by unreliable and conflicting source of information. Belief function calculation is used as an effective mathematical tool to deal with uncertainty in the decision making procedure. In this paper, a new concept, called as Systematic derivation of mass function coined with game theoretic calculation of best response is applied to handle quantification evidence preference from different multiple criteria. As an example, project selection problem with fuzzy information has been taken to demonstrate the concept.
Morphology and mechanical properties of nanocrystalline cellulose reinforced chitosan based nanocomposite

Chitosan/cellulose nanocrystals (Ch-CN) composites were prepared with different contents of CN. Chitosan/cellulose nanocrystals films were obtained by casting of dispersions while the composition of films was varied from 5-20 wt. % of CN. Changes in the morphology of the systems were studied by SEM. The covalent linkage between CN and Ch was confirmed by FTIR spectroscopy. While and X-ray diffraction studies confirmed the appearance of crystalline structure for the nanocomposite films which makes it more rigid. The overall mechanical properties of Ch are significantly improved due to the homogeneous dispersion of CN and the strong interfacial interactions resulting from hydrogen bonding between Ch chains and CN in addition to the biocompatibility of both Ch and CN materials.
Quad‐Based Fourier Transform for Efficient Diffraction Synthesis

Far‐field diffraction can be evaluated using the Discrete Fourier Transform (DFT) in image space but it is costly due to its dense sampling. We propose a technique based on a closed‐form solution of the continuous Fourier transform for simple vector primitives (quads) and propose a hierarchical and progressive evaluation to achieve real‐time performance. Our method is able to simulate diffraction effects in optical systems and can handle varying visibility due to dynamic light sources. Furthermore, it seamlessly extends to near‐field diffraction. We show the benefit of our solution in various applications, including realistic real‐time glare and bloom rendering.
2 Keystroke Dynamics Algorithms

In this review paper we present a comprehensive survey of research efforts in the past couple of decades on keystroke dynamics biometrics. We review the literature in light of various feature extraction, feature matching and classification methods for keystroke dynamics. We also discuss recent trends in keystroke dynamics research, including its use in mobile environments, as a soft biometrics, and its fusion with other biometric modalities. We further address the evaluation of keystroke biometric systems, including traditional and new performance metrics, and list publicly available keystroke datasets for performance benchmarks to promote synergy in the research community.
The combined and interactive effects of zinc, temperature, and phosphorus on the structure and functioning of a freshwater community

Ecotoxicological studies mainly consist of single‐species experiments evaluating the effects of a single stressor. However, under natural conditions aquatic communities are exposed to a mixture of stressors. The present study aimed to identify how the toxicity of zinc (Zn) is affected by increased temperature and increased phosphorus (P) supply and how these interactions vary among species, functional groups, and community structure and function. Aquatic microcosms were subjected to 3 Zn concentrations (background, no Zn added, and 75 and 300 μg Zn/L), 2 temperatures (16–19 and 21–24 °C), and 2 different P additions (low, 0.02, and high, 0.4 mg P L−1 wk−1) for 5 wk using a full factorial design. During the study, consistent interactions between Zn and temperature were only rarely found at the species level (4%), but were frequently found at the functional group level (36%), for community structure (100%) and for community function (100%; such as dissolved organic carbon concentrations and total chlorophyll). The majority of the Zn × temperature interactions were observed at 300 μg Zn/L and generally indicated a smaller effect of Zn at higher temperature. Furthermore, no clear indication was found that high P addition by itself significantly affected the overall effects of Zn on the community at any level of organization. Interestingly, though, 90% of all the Zn × temperature interactions observed at the species, group, and community composition level were found under high P addition. Collectively, the results of our study with the model chemical Zn suggest that temperature and phosphorus loading to freshwater systems should be accounted for in risk assessment, because these factors may modify the effects of chemicals on the structure and functioning of aquatic communities, especially at higher levels of biological organization. Environ Toxicol Chem 2018;37:2413–2427. © 2018 SETAC