Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of Genetic Markers for AmpC, AAC, and RNR3 Genes in Potentially Present Pathogens Organisms in Fecal Sludge

The issue of sanitation and water pollution due to fecal waste has become a serious concern in Indonesia, particularly after it was revealed that approximately 70% of the community's drinking water sources are contaminated with human feces. Determining safe waste management requirements necessitates indicators confirming the contamination-free nature of the waste management methods. Pathogen testing indicators for fecal waste are highly diverse. The current standard testing is the culture-based method for microorganisms and microscopy observation for helminths. However, molecular detection tools for these pathogens can give higher sensitivity and specificity in a relatively shorter time of technical processing. In this research, we designed primers for molecular-based diagnostics on three pathogens exhibiting extreme survival capabilities under various environmental conditions. The species-coupled genes are AmpC for Escherichia coli, AAC for Mycobacterium tuberculosis, and RNR3 for Ascaris lumbricoides. The design of molecular-based biomarkers and their specificity tests were conducted using web-based bioinformatics programs to prevent unintended dimers. Ultimately, primers were validated by conventional gradient PCR on available positive controls and a sample from processed fecal sludge. The PCR validation test showed that the designed primers were validated to amplify the intended target with the right size without unspecific bands on the positive controls. Meanwhile, the AAC gene for E. coli was detected in the sample from the fecal sludge.
The value of geological data, information and knowledge in producing landslide susceptibility maps.

Στο άρθρο αυτό eπιχeιρeίται να δοθeί μια συνοπτική παρουσίαση της αξίας που έχeι η διαχeίριση της γeωλογικής πληροφορίας σe μeλέτeς διeρeύνησης κατολισθητικών φαινομένων και του τρόπου μe τον οποίο αυτή αποτυπώνeται σe χάρτeς κατολισθητικής eπιδeκτικότητας. Συγκeκριμένα, ορίζονται οι έννοιeς, δeδομένα, πληροφορία, γνώση, και παρουσιάζeται η διαδικασία μeτατροπής των δeδομένων σe πληροφορία και της πληροφορίας σe γνώση, eνώ eπιχeιρeίται και μια συνοπτική πeριγραφή των κατολισθητικών φαινομένων και των τeχνικών που διαχeιρίζονται τα δeδομένα και τις προκύπτουσeς πληροφορίeς.
Factors Associated With Food Insecurity Among a Community-Based Sample of Older Adults in a North Florida County

Food insecurity impacts the lives of 7.6 million U.S. adults aged 60 and older and is linked to numerous life challenges. This study examined the nature of food insecurity among community-based participants ≥65 years in a north Florida county and conceptualized food insecurity as encompassing the lack of food and individual adaptability. Thus, food insecurity was measured using three dependent variables: (1) worrying that food would run out, (2) cutting meal size or skipping meals, and (3) food not lasting. Logistic regression revealed that older participants, those with better-perceived health status, and those who were confident that they could find solutions to their problems had lower odds of reporting food insecurity. However, respondents who lived in low-income, low-access zip codes and those who received food assistance were more likely to report food insecurity. To improve outcomes and reduce healthcare disparities, solutions to food insecurity must vary in focus and approach.
Improved Loss Function for Mass Segmentation in Mammography Images Using Density and Mass Size

Mass segmentation is one of the fundamental tasks used when identifying breast cancer due to the comprehensive information it provides, including the location, size, and border of the masses. Despite significant improvement in the performance of the task, certain properties of the data, such as pixel class imbalance and the diverse appearance and sizes of masses, remain challenging. Recently, there has been a surge in articles proposing to address pixel class imbalance through the formulation of the loss function. While demonstrating an enhancement in performance, they mostly fail to address the problem comprehensively. In this paper, we propose a new perspective on the calculation of the loss that enables the binary segmentation loss to incorporate the sample-level information and region-level losses in a hybrid loss setting. We propose two variations of the loss to include mass size and density in the loss calculation. Also, we introduce a single loss variant using the idea of utilizing mass size and density to enhance focal loss. We tested the proposed method on benchmark datasets: CBIS-DDSM and INbreast. Our approach outperformed the baseline and state-of-the-art methods on both datasets.
A Comprehensive Study on the Effect of Plasticizers on the Characteristics of Polymer Inclusion Membranes (PIMs): Exploring Butyl Stearate as a Promising Alternative

This study investigated the influence of various plasticizers commonly used in the manufacture of polymer inclusion membranes (PIMs), such as 2-nitrophenyl octyl ether (NPOE), phthalates, adipates, and sebacates on the mechanical, thermal, and transport properties of membranes. Additionally, butyl stearate (BTS), chosen for its non-toxic nature compared to phthalates and its cost-effectiveness relative to adipates and sebacates, was evaluated as a plasticizer in PIMs for the first time. All plasticizers were incorporated in PIMs made of either cellulose triacetate (CTA) or poly(vinyl chloride) (PVC) as the base polymers and the task-specific ionic liquid trioctylmethylammonium thiosalicylate (TOMATS) as the carrier. The plasticizers were found to significantly affect the characteristics of membrane hydrophilicity, mechanical flexibility, and thermal stability. Transport experiments using Hg(II) as a model target ion revealed that, for CTA-based PIMs, the plasticizer did not significantly affect transport efficiency. However, for PVC-based PIMs, BTS exhibited better efficiency when compared to NPOE. These findings highlight the potential of BTS as an attractive alternative to currently used plasticizers in PVC-based PIM formulations.
Diagnostic performance of GcfDNA in kidney allograft rejection: a meta-analysis

In this comprehensive meta-analysis, our objective was to evaluate the diagnostic utility of graft-derived cell-free DNA (GcfDNA) in kidney allograft rejection and explore associated factors. We conducted a thorough search of PubMed, Embase, and the Cochrane Library databases, spanning from their inception to September 2022. Statistical analysis was executed utilizing Stata 15, Meta-DiSc 1.4, and Review Manager 5.4 software. The combined pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristics (SROC) curve from the synthesis of findings across ten studies were as follows: 0.75 (0.67–0.81), 0.78 (0.72–0.83), 3.36 (2.89–4.35), 0.32 (0.24–0.44), 8.77 (4.34–17.74), and 0.83 (0.80–0.86), respectively. Among the ten studies primarily focused on GcfDNA’s diagnostic potential for antibody-mediated rejection (ABMR), the optimal cut-off threshold demonstrated substantial diagnostic efficacy, with pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, DOR, and area under the summary receiver operating characteristics curve values of 0.83 (0.74–0.89), 0.75 (0.70–0.80), 3.37 (2.64–4.30), 0.23 (0.15–0.36), 14.65 (7.94–27.03), and 0.85 (0.82–0.88), respectively. These results underscore the high diagnostic accuracy of GcfDNA in detecting rejection. Furthermore, the optimal cut-off threshold proves effective in diagnosing ABMR, while a 1% threshold remains a robust diagnostic criterion for rejection. Notably, for ABMR diagnosis, droplet digital PCR digital droplet polymerase chain reaction emerges as a superior method in terms of accuracy when compared to other techniques. Nonetheless, further research is warranted to substantiate these findings.
MoCA Domain-Specific Pattern of Cognitive Impairment in Stroke Patients Attending Intensive Inpatient Rehabilitation: A Prospective Study

A domain-specific perspective to cognitive functioning in stroke patients may predict their cognitive recovery over time and target stroke rehabilitation intervention. However, data about domain-specific cognitive impairment after stroke are still scarce. This study prospectively investigated the domain-specific pattern of cognitive impairments, using the classification proposed by the Montreal Cognitive Assessment (MoCA), in a cohort of 49 stroke patients at admission (T0), discharge (T1), and six-month follow-up (T2) from subacute intensive rehabilitation. The predictive value of T0 cognitive domains cognitive impairment at T1 and T2 was also investigated. Patients’ cognitive functioning at T0, T1, and T2 was assessed through the MoCA domains for executive functioning, attention, language, visuospatial, orientation, and memory. Different evolutionary trends of cognitive domain impairments emerged across time-points. Patients’ impairments in all domains decreased from T0 to T1. Attention and executive impairments decreased from T0 to T2 (42.9% and 26.5% to 10.2% and 18.4%, respectively). Conversely, altered visuospatial, language, and orientation increased between T1 and T2 (16.3%, 36.7%, and 40.8%, respectively). Additionally, patients’ global cognitive functioning at T1 was predicted by the language and executive domains in a subacute phase (p = 0.031 and p = 0.001, respectively), while in the long term, only attention (p = 0.043) and executive (p = 0.019) domains intervened. Overall, these results confirm the importance of a domain-specific approach to target cognitive recovery across time in stroke patients.
Atrial Fibrillation Detection with Single-Lead Electrocardiogram Based on Temporal Convolutional Network–ResNet

Atrial fibrillation, one of the most common persistent cardiac arrhythmias globally, is known for its rapid and irregular atrial rhythms. This study integrates the temporal convolutional network (TCN) and residual network (ResNet) frameworks to effectively classify atrial fibrillation in single-lead ECGs, thereby enhancing the application of neural networks in this field. Our model demonstrated significant success in detecting atrial fibrillation, with experimental results showing an accuracy rate of 97% and an F1 score of 87%. These figures indicate the model’s exceptional performance in identifying both majority and minority classes, reflecting its balanced and accurate classification capability. This research offers new perspectives and tools for diagnosis and treatment in cardiology, grounded in advanced neural network technology.
Herbaceous layer cover and biomass in a young versus a mature stand of a central Appalachian hardwood forest

GILLIAM, F. S. AND N. L. TURRILL (Department of Biological Sciences, Marshall University, Huntington, WV 25755). Herbaceous layer cover and biomass in a young versus a mature stand of a central Appalachian hardwood forest. Bull. Torrey Bot. Club 120: 445-450. 1993. -This study examined herb layer vegetation (all vascular plants c 1 m in height) of two montane watersheds of different stand ages in the Femow Experimental Forest, in north-central West Virginia (WS3, -20 yr; WS4, >80 yr). Mean herb layer cover was 19.3 and 26.4% for WS3 and WS4, respectively. Herb layer biomass was significantly (P < 0.00 1) correlated with herb cover for both watersheds. Mean herb layer biomass was 8.1 and 11.6 g/m2 for WS3 and WS4, respectively. Herb cover responded positively to elevation on both watersheds. Within WS3, herb cover was only weakly correlated with canopy characteristics, but was positively correlated with soil pH, organic matter, sand content, cation exchange capacity, Ca, K, Mg, and N03-N. Within WS4, herb cover was negatively correlated with understory basal area and density, but not significantly correlated with any soil variables except Ca. From these data we suggest a hypothesis that in early forest succession in these ecosystems, early herb layer development is influenced greatly by allogenic factors (such as soil fertility) but that autogenic factors, such as canopy closure, become more important as the stand matures and becomes more stratified.
Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Tarif Pajak Penghasilan Di Oenity

Thel Oelnity tax consulting officel is onel of thel companiels that havel a lot of data on goods, data-data, and transaction data elvelry day. In gelnelral, thel Oelnity tax consulting officel only usels this data for relporting purposels only. Tax transaction data collelcteld and storeld can providel uselful knowleldgel for company managelmelnt in carrying out elfforts rellateld to tax increlasels, for elxamplel in telrms of deltelrmining tax financel stratelgiels and supporting delcisions for thel company. Consumelrs who apply for thel procelss of deltelrmining incomel tax ratels usually havel relasons why thely choosel a tax data calculation systelm from a tax consultant rathelr than managing it thelmsellvels. Belcausel tax consultants can providel what thely want, such as convelnielncel, accuracy, speleld, and nelatnelss of incomel tax calculations. Many consumelrs complain about thel incomel tax ratel calculation systelm, whelrel thel layout, making it difficult for consumelrs to gelt thel final tax relsults thely neleld, will also spelnd quitel a long timel just to find thel total incomel tax ratel. Thel Apriori algorithm is onel of thel most frelquelntly useld typels of data analysis in thel world of data procelssing. This analysis procelss is to analyzel thel numbelr of businelssels and thel amount of consumelr incomel by finding associations beltweleln lists of taxels that must bel paid. Thel Apriori algorithm is useld to arrangel itelm layouts and group itelms. From thel relsults of systelm implelmelntation, it was concludeld that using thel Apriori Algorithm melthod can hellp thel procelss of finding incomel tax ratels for elach consumelr data.
Role of climate changes for wind gap formation in a young, actively growing mountain range

Wind gaps in actively growing mountain ranges are unique geomorphological features testifying to the competition between tectonics and fluvial incision. Although it is clear that these landforms reflect the defeat of rivers during sustained rock uplift, the role of climate changes in their formation has never been explored. Here, we use a coupled tectonics–landscape evolution model to show that temporal changes in precipitation rate exert an important control on wind gap formation. In models with a constant precipitation rate, rivers flowing across a growing range are either defeated at an early stage or they abandon their valleys very late, if at all. If precipitation varies, wind gaps form mostly c. 100–200 ka after a transition to drier conditions because of sediment aggradation upstream of the range. Our results suggest that the Pliocene–Quaternary aridification of Central Asia contributed to wind gap formation in active mountain ranges in the foreland of northeastern Tibet.
Quasi-Yagi Antenna Array With Modified Folded Dipole Driver for mmWave 5G Cellular Devices

A novel quasi-Yagi antenna is proposed for millimeter-wave (mmWave) 5G cellular handsets operating in the 28 GHz band. The proposed antenna is designed to be compact through modification of the planar folded dipole topology so that it can be mounted inside a compact mobile terminal. A vertically stacked structure utilizing a multilayer printed circuit board (PCB) and via holes is applied to the antenna topology to minimize the antenna lateral width while maintaining the characteristics of the planar folded dipole antenna. A single antenna yields a $-$10 dB bandwidth for a return loss of 12.3% (26.3 to 29.75 GHz) and a gain of 5.51 dBi at 28 GHz. The change in beam patterns due to the chassis effect when four-element linear arrays are inserted into the upper and side edge inside the terminal is analyzed.
Seed treatment with chitosan synergizes plant growth promoting ability of Pseudomonas aeruginosa-P17 in sorghum (Sorhum bicolor L.)

Inoculation of crop plants with PGPR has in a large number of investigations resulted in increased plant growth and yield both in the greenhouse and in the field. This plant growth promoting effect of bacteria could be due to net result of synergistic effect of various pgpr traits that they exert in the rhizosphere region of the plant. Four (04) bacterial strain of fluorescent Pseudomonas spp. viz. P1, P17, P22 and P28 were identified previously for their plant growth promoting nature and abiotic stress tolerance and selected further to assess their chitinolytic activity and growth promotion on sorghum in combination with chitosans of low and high degree of acetylation. It was found that P1 has no chitin degrading nature and rest of the three strains have this property. When studied for their ability to grow in presence of chitosans of DA 1.6, 11, 35 and 56% all the strains showed growth in presence of chitosans. Seed bacterization of sorghum seeds with 04 bacterial strains in the presence and absence of chitosans (both low and high DA) and assessment of plant growth promotion after 15 days of sowing showed that P17+DA 56% chitosan combination showed higher growth of seedlings in plant growth chamber with highest root length of 25.9 cm, highest shoot length of 32.1 cm and dry mass of 132.7 mg/ plant. In P17+DA 56% chitosan treated seedlings various defence enzymes and PR-proteins were found to be present in highest quantities as compared to P1 and un-inoculated controls. Since this strain showed highest growth promotion of sorghum seedlings chitin-chitosan modifying enzyme (CCME) of this strain was partially characterized using different proteomic tools and techniques. CCME of P17 had one active polypeptide with a Pi in the range of 3.0-4.0. The digestion pattern of acetylated and deacetylated chitosans showed that P17 enzyme has endochitinase activity. Substrate specificity assay showed that the enzyme had more specificity towards highly acetylated chitosans. Two dimensional PAGE and MS analysis of the protein revealed similarities of this enzyme with protein of Pseudomonas aeruginosa chitinase PA01 strain of GenBank. In conclusion, the study established the option of opening new possibilities for developing bacterial-chitosan (P17+DA 56% chitosan) product for plant growth promotion and induced systemic resistance in sorghum.
Smith ScholarWorks Smith ScholarWorks

Requirements engineering (RE) has established itself as a core software engineering discipline. It is well acknowledged that good RE leads to higher quality software and considerably reduces the risk of failure or budget-overspending of software development projects. It is of vital importance to train future software engineers in RE and educate future requirements engineers to adequately manage requirements in various projects. To this date, there exists no central concept of what RE education shall comprise. To lay a foundation, we report on a systematic literature review of the field and provide a systematic map describing the current state of RE education. Doing so allows us to describe how the educational landscape has changed over the last decade. Results show that only a few established author collaborations exist and that RE education research is predominantly published in venues other than the top RE research venues (i.e., in venues other than the RE conference and journal). Key trends in RE instruction of the past decade include involvement of real or realistic stakeholders, teaching predominantly elicitation as an RE activity, and increasing student factors such as motivation or communication skills. Finally, we discuss open opportunities in RE education, such as training for security requirements and supply chain risk management, as well as developing a pedagogical foundation grounded in evidence of effective instructional approaches.
Identification and Separation of Turbulence Echo From the Multipeaked VHF Radar Spectra During Precipitation

This paper describes an automated data processing algorithm to identify the turbulence echo in the multipeaked very high-frequency radar spectra, generally observed during the precipitation. Although a few multipeak-picking algorithms exist, they identify the turbulence echo from the clutter and noise, but they do not distinguish turbulence and precipitation echoes. The present algorithm identifies the turbulence echo from multiple peaks based on several criteria, such as the significance of the echoes, separation between the echoes within a sliding window, and a reference turbulence echo. A new method [symmetric method (SM)] is introduced to estimate the moments after proper identification of the turbulence echo, in fact, half portion of the echo. Comparison of the moments estimated by the SM and dual-frequency method (another popular method for the extraction of moments from multipeaked spectra) with those obtained by the routine single-peak detection algorithm reveals large discrepancies, particularly in convective cores and in and above the radar bright band region. In these regions, the error in moments by the traditional single-peak-picking algorithm is found to be substantial. Performance evaluation of these two methods has also been carried out against simulated spectra. The analysis reveals that the error in obtaining moments by the SM and dual-frequency method is less than 15%, except for a few cases. Also, the error in moments by the SM is, in general, smaller than by the dual-frequency method.
A study of concept similarity in Wikidata

Robust estimation of concept similarity is crucial for applications of AI in the commercial, biomedical, and publishing domains, among others. While the related task of word similarity has been extensively studied, resulting in a wide range of methods, estimating concept similarity between nodes in Wikidata has not been considered so far. In light of the adoption of Wikidata for increasingly complex tasks that rely on similarity, and its unique size, breadth, and crowdsourcing nature, we propose that conceptual similarity should be revisited for the case of Wikidata. In this paper, we study a wide range of representative similarity methods for Wikidata, organized into three categories, and leverage background information for knowledge injection via retrofitting. We measure the impact of retrofitting with different weighted subsets from Wikidata and ProBase. Experiments on three benchmarks show that the best performance is achieved by pairing language models with rich information, whereas the impact of injecting knowledge is most positive on methods that originally do not consider comprehensive information. The performance of retrofitting is conditioned on the selection of high-quality similarity knowledge. A key limitation of this study, similar to prior work lies in the limited size and scope of the similarity benchmarks. While Wikidata provides an unprecedented possibility for a representative evaluation of concept similarity, effectively doing so remains a key challenge.
COMPARISON OF FIFTY-SEVEN YEAR CALIFORNIA REANALYSIS DOWNSCALING AT 10 KILOMETERS (CaRD10) WITH NORTH AMERICAN REGIONAL REANALYSIS

v Executive Summary 1 1.0 Introduction 3 2.0 Difference in Large-scale Analysis 6 3.0 Trends 7 3.1. Near-Surface Temperature 7 3.2. 500-hPa Height 8 3.3. Precipitation 11 4.0 Synoptic Events 11 4.1. Catalina Eddy 11 4.2. Coastally Trapped Wind Reversal 12 4.3. Santa Ana Winds 13 5.0 Water Budgets 14 6.0 Summary and Conclusions 19 7.0 References 22