Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Surface Water Resource Availability under the Impact of Climate Change in the Dhidhessa Sub-Basin, Ethiopia

Climate change, with its reaching implications, has become a popular topic in recent years. Among the many aspects of climate change, one of the most pressing concerns has been identified as the impact on the terrestrial water cycle, which has a direct impact on human settlement and ecosystems. The paper begins by reviewing previous studies, and then identifies their flaws and future research directions. The effects of climate change on surface water resources in the Dhidhessa Sub-basin, Abbay Basin, Ethiopia, were studied as practices. For future potential climate change, the results of global climate models (GCMs) and high-resolution regional climate models (RCMs) from multiple climate models were combined with data from Representative Concentration Pathways (RCPs) prepared by the Intergovernmental Panel on Climate Change from the CCAFS Data Distribution Center web page. To evaluate the impacts on water resources, various distributed hydrologic models based on local underlying surfaces were developed. The future potential climate change of the Dhidhessa Sub-basin Province was evaluated by integrating RCP outputs, whereas the climate change of the Dhidhessa River was directly derived from the results of different RCP. Dhidhessa stream flow will decrease in the future compared to the baseline era. The predictions of future discharge (stream flow) were based on climate scenarios data from 1991 to 2020 and for the future with two time windows, 2044 (2030–2059) and 2084 (2070–2099), on a monthly time-step after bias correction to both precipitation and temperature in the future climate described in the under each RCP. According to model results, the quantity of surface water resources in the Dhidhessa river region will decrease over the next 100 years, the percent decrease in mean annual stream flow by 10%, in 2044, and 6.3% in 2084, respectively, making the impact of temperature increase on runoff greater than that of precipitation. The distribution of runoff would be more even across years but more uneven across years in the long-term window, implying a higher possibility of drought and flooding. In general, this study discovered that any effect on this river that results in a decrease in flow will have a direct impact on the area’s ongoing water resource development and socioeconomic development.
Deep Learning for Vessel Trajectory Prediction Using Clustered AIS Data

Accurate vessel track prediction is key for maritime traffic control and management. Accurate prediction results can enable collision avoidance, in addition to being suitable for planning routes in advance, shortening the sailing distance, and improving navigation efficiency. Vessel track prediction using automatic identification system (AIS) data has attracted extensive attention in the maritime traffic community. In this study, a combining density-based spatial clustering of applications with noise (DBSCAN)-based long short-term memory (LSTM) model (denoted as DLSTM) was developed for vessel prediction. DBSCAN was used to cluster vessel tracks, and LSTM was then used for training and prediction. The performance of the DLSTM model was compared with that of support vector regression, recurrent neural network, and conventional LSTM models. The results revealed that the proposed DLSTM model outperformed these models by approximately 2–8%. The proposed model is able to provide a better prediction performance of vessel tracks, which can subsequently improve the efficiency and safety of maritime traffic control.
Dimension reduction based adaptive dynamic programming for optimal control of discrete-time nonlinear control-affine systems

Dynamic programming based methods have been widely used in solving discrete-time nonlinear constrained optimal control problems. However, applying these methods in real-time is challenging because a large amount of memory is needed and the associated computational cost is high. Here, a search space dimension reduction strategy is proposed for a class of nonlinear discrete-time systems that are control-affine and invertible. Specifically, a bio-inspired motion rule is combined with inverse dynamics to reduce the value iteration search space to one dimension. The corresponding suboptimal control algorithm is developed and its optimality is analysed. An adaptation rule is developed to estimate uncertainties and improve the base policy. The closed-loop system is proven to be asymptotically stable. The advantages of the algorithm including much smaller computational cost and significantly reduced memory usage are demonstrated with two simulation examples.
Analysis of Incorporation of Ion-Bombarded Nickel Ions with Silicon Nanocrystals for Microphotonic Devices

Nanotechnology is playing a greater role in biomedical engineering. Microphotonic technology is on another side, having faster growth with more requirements. The nanocrystals are a part of nanotechnology which uses silicon for manufacturing. These silicon nanocrystals have the optical property mostly used in microphotonic devices. Silicon nanocrystals are of biocompatibility with less toxicity. Therefore, the advancement in the silicon nanocrystal helps develop more microphotonic devices for biological purposes. One critical factor of silicon nanocrystal is the surface defects or surface imperfections. Surface passivation is the method employed for rectifying this disadvantage of silicon nanocrystal. Another major thing is that silicon nanocrystals are size dependent. So proper variation on the surface is required for yielding high performance of the nanocrystal. After characterizing the surface of the silicon nanocrystal, ion bombardment can occur. Nickel is a lustrous white chemical element which is less reactive when it is of a smaller size. So ion bombardment of nickel ion on the surface of the silicon nanocrystal can be done to improvise the performance of the microphotonic devices. Nearly there is an excess of 20 a.u. of photoluminescence intensity yielded. The relative fluorescence is also increased by 150 a.u. This research work enhanced the silicon nanocrystal using ion bombardment of nickel ion, which increased energy traps resulting in more intensities.
Towards building active defense for software applications

Over the last few years, cyber attacks have become increasingly sophisticated. In an effort to defend themselves, corporations often look to machine learning, aiming to use the large amount of data collected on cyber attacks and software systems to defend systems at scale. Within the field of machine learning in cybersecurity, PDF malware is a popular target of study, as the difficulty of classifying malicious files makes it a continuously effective method of attack. The obstacles are many: Datasets change over time as attackers change their behavior, and the deployment of a malware detection system in a resource-constrained environment has minimum throughput requirements, meaning that an accurate but time-consuming classifier cannot be deployed. Recent work has also shown how automated malicious file creation methods are being used to evade classification. Motivated by these challenges, we propose an active defender system to adapt to evasive PDF malware in a resource-constrained environment. We observe this system to improve the f1 score from 0.17535 to 0.4562 over five stages of receiving PDF files that the system considers unlabeled. Furthermore, average classification time per file is low across all 5 stages, and is reduced from an average of 1.16908 seconds per file to 1.09649 seconds per file. Beyond classifying malware, we provide a general active defender framework that can be used to deploy decision systems for a variety of resource-constrained adversarial problems. Thesis Supervisor: Kalyan Veeramchaneni Title: Principle Research Scientist
On the homomorphisms between the generalized Verma modules arising from conformally invariant systems

It is shown by Barchini, Kable, and Zierau that conformally invariant systems of differential operators yield explicit homomorphisms between certain generalized Verma modules. In this paper we determine whether or not the homomorphisms arising from such systems of first and second order differential operators associated to maximal parabolic subalgebras of quasi-Heisenberg type are standard.
Diagnostic Potential of Circulating Tumor Cells, Urinary MicroRNA, and Urinary Cell-Free DNA for Bladder Cancer: A Review

Early detection of primary bladder cancer (BCa) is vital, because stage and grade have been generally accepted not only as categorical but also as prognostic factors in patients with BCa. The widely accepted screening methods for BCa, cystoscopy and urine cytology, have unsatisfactory diagnostic accuracy, with high rates of false negatives, especially for flat-type BCa with cystoscopy and for low-risk disease with urine cytology. Currently, liquid biopsy has attracted much attention as being compensatory for that limited diagnostic power. In this review, we survey the literature on liquid biopsy for the detection of BCa, focusing on circulating tumor cells (CTCs), urinary cell-free DNA (ucfDNA), and urinary microRNA (umiRNA). In diagnostic terms, CTCs and umiRNA are determined by quantitative analysis, and ucfDNA relies on finding genetic and epigenetic changes. The ideal biomarkers should be highly sensitive in detecting BCa. Currently, CTCs produce an unfavorable result; however, umiRNA and ucfDNA, especially when analyzed using a panel of genes, produce promising results. However, given the small cohort size in most studies, no conclusions can yet be drawn about liquid biopsy’s immediate application to clinical practice. Further large studies to validate the diagnostic value of liquid biopsy for clinical use are mandatory.
CCD Photometry of Variable Stars in the Galactic Open Cluster NGC 7419

We present results of a CCD variability search in the field of the young open cluster NGC 7419. This cluster contains a large number of Be stars and almost all of them turned out to be variable. They show mostly irregular variations on different time-scales with ranges up to 0.4 mag in the I C band. The most interesting result is the discovery of short-period variability in some of the Be stars.
Thermomagnetic-Responsive Self-Folding Microgrippers for Improving Minimally Invasive Surgical Techniques and Biopsies

Traditional open surgery complications are typically due to trauma caused by accessing the procedural site rather than the procedure itself. Minimally invasive surgery allows for fewer complications as microdevices operate through small incisions or natural orifices. However, current minimally invasive tools typically have restricted maneuverability, accessibility, and positional control of microdevices. Thermomagnetic-responsive microgrippers are microscopic multi-fingered devices that respond to temperature changes due to the presence of thermal-responsive polymers. Polymeric devices, made of poly(N-isopropylacrylamide-co-acrylic acid) (pNIPAM-AAc) and polypropylene fumarate (PPF), self-fold due to swelling and contracting of the hydrogel layer. In comparison, soft metallic devices feature a pre-stressed metal bilayer and polymer hinges that soften with increased temperature. Both types of microdevices can self-actuate when exposed to the elevated temperature of a cancerous tumor region, allowing for direct targeting for biopsies. Microgrippers can also be doped to become magnetically responsive, allowing for direction without tethers and the retrieval of microdevices containing excised tissue. The smaller size of stimuli-responsive microgrippers allows for their movement through hard-to-reach areas within the body and the successful extraction of intact cells, RNA and DNA. This review discusses the mechanisms of thermal- and magnetic-responsive microdevices and recent advances in microgripper technology to improve minimally invasive surgical techniques.
Intermodal Four-Wave Mixing Process in Strain-Induced Birefringent Multimode Optical Fibers

Our study investigated the partially degenerate intermodal four-wave mixing (IM-FWM) process in nonlinear multimode optical fibers with strain-induced birefringence. The difference in the refractive index along the two orthogonal directions was due to the photoelastic effect that occurred when the fiber under test (FUT) was subjected to uniformly applied diameter stress caused by winding on a cylinder of a given diameter. Our work analyzed how the nonlinear frequency conversion and the output modal field profiles depended on the degree of birefringence in FUT. The experimental results significantly affected the order of the excited moduli in fiber sections characterized by different amounts of birefringence. We also checked the efficiency of the FWM process for different polarizations of the pump beam to determine those for which the FWM process was most effective for the 532 nm sub-nanosecond pulses. More than 30% conversion efficiency was obtained for the FUTs with a length of tens of centimeters.
Validation of vital sign measurement by nanosecond pulse near-field sensing and the conductive silver paste printed textile technique

Vital sign monitoring is fundamental in daily patient care. Wearable technology has become an important tool in personalized medicine; however, there is a tradeoff problem between accuracy and comfort caused by the elastic textile used. Our study sought to examine the accuracy of heart rate (HR) and breathing rate (BR) monitoring as measured by iSmartweaR, a novel wearable and wireless sensor that uses the laser Doppler technique, with special focus on sex and different static postures. A total of 30 male and 23 female patients, including 23 patients with cardiovascular diseases and 30 healthy participants, were recruited. The HR and BR were measured with iSmartweaR and the gold standard method (CardioSoft and MasterScreen™ CPX) simultaneously in three static postures (supine rest, right lateral decubitus, and left lateral decubitus). The mean errors of HR and BR between iSmartweaR and the gold standard method were close to zero (0.55 and 0.71, respectively). The standard deviations of the HR error and BR error were 0.59 and 0.67, respectively. Disease, posture, sex, and measurement time did not cause clinically significant measurement errors. The overall percentage of missing data was 7.01%. The use of iSmartweaR was valid across different sexes and static postures. It is real-time, continuous and manpower-saving, and can be applied in patient care.
Conceptual clarity and empirical testability: Commentary on Knauff and Gazzo Castañeda (2023)

Abstract Knauff and Gazzo Castañeda (2022) criticise the use of the term “new paradigm” in the psychology of reasoning and raise important issues about how to advance research in the field. In this commentary I argue that for the latter it would be helpful to clarify further the concepts that reasoning theories rely on, and to strengthen the links between the theories and the empirical observations that would and would not be compatible with them.
Stabilizing Geo-Spatial Splines with Helperpoints – How to Estimate Smooth Price Surfaces when there are Data Gaps

This paper examines how to overcome an essential disadvantage of polynomial spline behavior: over-shooting of estimated spline functions in areas with poor data support. We introduce a new method that avoids the spline overshooting problem by placing helper points in data-gap areas before estimating the spline surface. We estimate helper point values via the Random Forest algorithm. Helper points force the algorithm to put a cost on deviating from reasonable local values in these areas. We show that our method can prevent spline overshooting where data are missing, can improve predictions in areas where data are scarce, but does not distort the spline surface in areas where data are plentiful. Our method also has a positive knock-on e ﬀ ect in that it reduces the need for high (global) penalisation values and thus improves the spline’s response to changes in actual prices in regions with more data. Our method is particularly suited to the estimation of property price gradients, as property data are inherently unevenly distributed in space. We illustrate that our method can signiﬁcantly improve the estimation of regional house price gradients using data for new apartment transactions in Vienna, Austria. To the best of our knowledge, our method is new - not only to the ﬁeld of Real Estate Economics - but also to the spline literature.
ANÁLISE DAS PERDAS DE CAULE, FOLHAS E FRUTOS DE HORTALIÇAS FRESCAS COMERCIALIZADAS NA REDE VAREJISTA DE AREIA (PB)

It was conducted a survey of the losses of onion, lettuce, cilantro, cabbage, eggplant, cucumber and okra at fresh market in Areia (PB) in order to provide information that may assist the sector specific actions to reduce losses of vegetables fresh retail site and increase profitability in business activity. It was used a questionnaire consisting of 40 questions, which included socio-economic aspects, production, commercialization and marketing of storage. Respondents were divided into three groups: group I fairground producers of vegetables that sells directly in free market, group II consists of fairground not producers of vegetables, but that the purchase of third parties weekly and group III consists of traders owners of retail chains. It was found that the sprouting of onion bulbs; mass loss, color and texture in lettuce, cilantro and kale; ripening and loss of color and texture in eggplant, cucumber and okra; friction and mechanical injuries caused by damage insects and pathogens were responsible for the most significant losses in these vegetables. It is important to adopt good manufacturing practices, handling, hygiene, packaging and exhibition of vegetables after harvest in order to minimize losses in the marketing of vegetables in Areia (PB). Losses pre and post-harvest by offering variation in market behavior, generate serious economic and social consequences.
New Insights into Boron Essentiality in Humans and Animals

Boron (B) is considered a prebiotic chemical element with a role in both the origin and evolution of life, as well as an essential micronutrient for some bacteria, plants, fungi, and algae. B has beneficial effects on the biological functions of humans and animals, such as reproduction, growth, calcium metabolism, bone formation, energy metabolism, immunity, and brain function. Naturally organic B (NOB) species may become promising novel prebiotic candidates. NOB-containing compounds have been shown to be essential for the symbiosis between organisms from different kingdoms. New insights into the key role of NOB species in the symbiosis between human/animal hosts and their microbiota will influence the use of natural B-based colon-targeting nutraceuticals. The mechanism of action (MoA) of NOB species is related to the B signaling molecule (autoinducer-2-borate (AI-2B)) as well as the fortification of the colonic mucus gel layer with NOB species from B-rich prebiotic diets. Both the microbiota and the colonic mucus gel layer can become NOB targets. This paper reviews the evidence supporting the essentiality of the NOB species in the symbiosis between the microbiota and the human/animal hosts, with the stated aim of highlighting the MoA and targets of these species.
Eye-balling and heart girth models for live weight estimation of highly admixed Sudani Shorthorn Zebu Cattle for Precise Production and Veterinary Services

Cattle production is a key pillar of food security in Africa. The majority of African cattle are highly admixed with unknown breed composition. Accurate estimation of the live weight (LW) of these cattle would improve the precision of feeding, veterinary services, and pricing resulting in an improvement in profitability. This study assessed estimating LW of admixed Sudani zebu cattle using eyeballing and heart girth (HG) models. Live weight and HG of 432 Baggara cattle, an admixed Sudani breed, were measured. Three models (a simple linear, a simple linear with box-cox transformed LW, and a quadratic) were generated using 382 heads and validated using 50 heads. A published model (LW (kg) = 3.54*HG (cm) - 322.63) was validated using the data of this study. The error of LW estimation by a breeder and five cattlemen were recorded. All constructed models had high R2 (0.725 - 0.728). However, the 95th percentile of the prediction error of the constructed and published models was higher than 20%. The 95th percentile of LW estimation error of all participants was high (>20%). Accordingly, HG models and eyeballing are not suitable methods to determine the LW of highly admixed zebu cattle for production, veterinary, and marketing purposes as they are prone to a high rate of error.
The overlooked contribution of a fish bypass channel to the density and diversity of macroinvertebrate drift in a heavily modified river system

The freshwater biodiversity decline affects all trophic levels, prompting restoration efforts. While habitat restoration for fish is well‐studied, habitat restoration to benefit other sensitive taxa such as Ephemeroptera, Plecoptera, and Trichoptera (EPT) remains poor. Consequently, this study investigated the habitat function of a man‐made nature‐like bypass system for EPT taxa in a highly modified alpine river with several drift feeding fishes. Spatially and temporally distributed drift samples were used to test the hypotheses that the bypass (a) enhances the density of drifting individuals compared to the main river and (b) diversifies drift assemblages compared to the main river. Mean drift density of EPT taxa was lowest in the main stem of the river close to the inlet of the bypass (38.24 Ind./100m3) and significantly increased toward the downstream direction of the bypass, near the outflow (61.49 Ind./100m3). In addition, drift assemblages significantly changed from the main stem to the bypass and the number of EPT taxa detected more than doubled (main stem: 16 genera; last site in the bypass: 33 genera), indicating that the bypass can provide a macroinvertebrate source to the main stem. Seasonal and diel drift patterns were similar to those observed in natural streams, underpinning the finding that nature‐like bypass systems can feature an EPT community similar to natural rivers. This study aligns with a growing body of evidence on the habitat function of nature‐like bypass systems for aquatic taxa and highlights the importance of this restoration measure beyond the aspect of solely restoring habitat connectivity.
A Robust and Low Computational Cost Pitch Estimation Method

Pitch estimation is widely used in speech and audio signal processing. However, the current methods of modeling harmonic structure used for pitch estimation cannot always match the harmonic distribution of actual signals. Due to the structure of vocal tract, the acoustic nature of musical equipment, and the spectrum leakage issue, speech and audio signals’ harmonic frequencies often slightly deviate from the integer multiple of the pitch. This paper starts with the summation of residual harmonics (SRH) method and makes two main modifications. First, the spectral peak position constraint of strict integer multiple is modified to allow slight deviation, which benefits capturing harmonics. Second, a main pitch segment extension scheme with low computational cost feature is proposed to utilize the smooth prior of pitch more efficiently. Besides, the pitch segment extension scheme is also integrated into the SRH method’s voiced/unvoiced decision to reduce short-term errors. Accuracy comparison experiments with ten pitch estimation methods show that the proposed method has better overall accuracy and robustness. Time cost experiments show that the time cost of the proposed method reduces to around 1/8 of the state-of-the-art fast NLS method on the experimental computer.