Miracle-dz/UniFAR-FTUs huggingface dataset:
“Fading out” - genomic epidemiology of the last persistently infected BVDV cattle in Germany

Bovine viral diarrhea virus (BVDV) is one of the most important cattle pathogens worldwide, causing major economic losses and animal welfare issues. Disease eradication programs have been implemented in several countries, including Germany where an obligatory nationwide control program is in force since 2011. As molecular epidemiology has become an essential tool to understand the transmission dynamics and evolution of BVDV, 5′ untranslated region (UTR) sequences are generated from viruses present in persistently infected animals since the beginning of the BVDV control program. Here, we report the results of the sequence-based subtyping of BVDV strains found from 2018 through 2022 in calves born in Germany. In 2018, 2019 and 2020, BVDV-1d and-1b were the dominant subtypes and cases were spread throughout the area that was not yet officially declared BVDV-free at that time. In addition, BVDV–1a, −1e, −1f and -1h could rarely be detected. From 2021 onwards, subtype 1d clearly took over the dominance, while the other subtypes could be gradually nearly eliminated from the cattle population. The eradication success not only results in a drastic reduction of cases, but also in a marked reduction of strain diversity. Interestingly, before vaccination has been banned in regions and farms with a disease-free status, two live-vaccine virus strains were repeatedly detected in ear tissue samples of newborn calves (n = 14) whose mothers were immunized during gestation. The field-virus sequences are an important basis for molecular tracing and identification of potential relationships between the last outbreaks in the final phase of the German BVDV eradication program, thereby supporting classic epidemiological investigations. Furthermore, the monitoring of the composition of virus subtypes in the cattle population helps to maintain effective diagnostic methods and control measures and is an early warning system for the introduction of new pestiviruses in the naïve cattle population.
Food Safety Aspects of Breeding Maize to Multi-Resistance against the Major (Fusarium graminearum, F. verticillioides, Aspergillus flavus) and Minor Toxigenic Fungi (Fusarium spp.) as Well as to Toxin Accumulation, Trends, and Solutions—A Review

Maize is the crop which is most commonly exposed to toxigenic fungi that produce many toxins that are harmful to humans and animals alike. Preharvest grain yield loss, preharvest toxin contamination (at harvest), and storage loss are estimated to be between 220 and 265 million metric tons. In the past ten years, the preharvest mycotoxin damage was stable or increased mainly in aflatoxin and fumonisins. The presence of multiple toxins is characteristic. The few breeding programs concentrate on one of the three main toxigenic fungi. About 90% of the experiments except AFB1 rarely test toxin contamination. As disease resistance and resistance to toxin contamination often differ in regard to F. graminearum, F. verticillioides, and A. flavus and their toxins, it is not possible to make a food safety evaluation according to symptom severity alone. The inheritance of the resistance is polygenic, often mixed with epistatic and additive effects, but only a minor part of their phenotypic variation can be explained. All tests are made by a single inoculum (pure isolate or mixture). Genotype ranking differs between isolates and according to aggressiveness level; therefore, the reliability of such resistance data is often problematic. Silk channel inoculation often causes lower ear rot severity than we find in kernel resistance tests. These explain the slow progress and raise skepticism towards resistance breeding. On the other hand, during genetic research, several effective putative resistance genes were identified, and some overlapped with known QTLs. QTLs were identified as securing specific or general resistance to different toxicogenic species. Hybrids were identified with good disease and toxin resistance to the three toxigenic species. Resistance and toxin differences were often tenfold or higher, allowing for the introduction of the resistance and resistance to toxin accumulation tests in the variety testing and the evaluation of the food safety risks of the hybrids within 2–3 years. Beyond this, resistance breeding programs and genetic investigations (QTL-analyses, GWAM tests, etc.) can be improved. All other research may use it with success, where artificial inoculation is necessary. The multi-toxin data reveal more toxins than we can treat now. Their control is not solved. As limits for nonregulated toxins can be introduced, or the existing regulations can be made to be stricter, the research should start. We should mention that a higher resistance to F. verticillioides and A. flavus can be very useful to balance the detrimental effect of hotter and dryer seasons on aflatoxin and fumonisin contamination. This is a new aspect to secure food and feed safety under otherwise damaging climatic conditions. The more resistant hybrids are to the three main agents, the more likely we are to reduce the toxin losses mentioned by about 50% or higher.
Lake-habitat use of post-juvenile sea trout over time and space - An acoustic telemetry study in a regulated river

The KUSTUS project is financed by the Sogn og Fjordane County Municipality, ECO Energi AS, Ostfold Energi AS, Marine Harvest Norway, County Governor in Sogn og Fjordane, ErcoSeafood AS, Firda Sjofarmer AS, Marine Harvest Norway AS, Osland Havbruk AS, SulefiskAS, Luster kommune, Ardal kommune, Laerdal elveierlag.
Feature Extraction of Elderly Signals based on Bicoherence Estimation for Automated Medical Diagnosis System

Physiological changes in the vocal fold due to aging may change the pitch of the voice and the elderly signal can be automatically distinguished from the normal signal through various analyses. In case of most smart biomedical devices, the elderly voices have been neglected due to optimization which does not take into account the elderly. The objective of this study is to find the parameters that can distinguish the elderly signal. This paper suggests the mean of normalized skewness, the mean of normalized kurtosis, the ratio of the normalized skewness and kurtosis (RSK), and maximum bicoherence (MB) based on the linear predictive coding (LPC) residual. The parameters are based on the higher-order statistics (HOS) of the time and frequency domain. The mean of normalized skewness and MB parameter were useful and meaningful in an analysis between normal and elderly signals because they showed p-values <. 05. In particular, it was believed that MB was very significant for the classification between two signals. And the mean of normalized skewness, RSK, and MB were significant for the objective classification among normal, female elderly, and male elderly signals. In most cases, MB is specially performs better statistically than do the other parameters. To improve the performance of speech interface in automated medical diagnosis system, an analysis of elderly signal is of great interest. These results will contribute to provide an easy access means for the elderly. Future investigations will incorporate multiple classification methods to implement more reliable detector for automated medical diagnosis system.
Novel Framework for Quality Control in Vibration Monitoring of CNC Machining

Vibrations are a common issue in the machining and metal-cutting sector, in which the spindle vibration is primarily responsible for the poor surface quality of workpieces. The consequences range from the need to manually finish the metal surfaces, resulting in time-consuming and costly operations, to high scrap rates, with the corresponding waste of time and resources. The main problem of conventional solutions is that they address the suppression of machine vibrations separately from the quality control process. In this novel proposed framework, we combine advanced vibration-monitoring methods with the AI-driven prediction of the quality indicators to address this problem, increasing the quality, productivity, and efficiency of the process. The evaluation shows that the number of rejected parts, time devoted to reworking and manual finishing, and costs are reduced considerably. The framework adopts a generalized methodology to tackle the condition monitoring and quality control processes. This allows for a broader adaptation of the solutions in different CNC machines with unique setups and configurations, a challenge that other data-driven approaches in the literature have found difficult to overcome.
USING UNMANNED AERIAL SYSTEMS (UAS) AND PHOTOGRAMMETRY TO REMOTELY ASSESS LANDSLIDE EVENTS IN NEAR REAL-TIME

OF THESIS USING UNMANNED AERIAL SYSTEMS AND PHOTOGRAMMETRY TO REMOTELY ASSESS LANDSLIDE EVENTS IN NEAR REAL-TIME Commercially available unmanned aerial systems (UAS) and photogrammetry software have undergone rapid advancements in recent years. However, the use of UAS and photogrammetry techniques for monitoring surface landform deformation has not been adopted for the most part due to complicated workflows and complex UAS systems. This study demonstrates the ability to monitor landslides in near-real time with commercia lly available UAS and photogrammetry software using direct georeferencing and coregistration techniques. The results of this research were then assessed to develop an optimal workflow for the rapid assessment of surface deformations with direct georeferenced UAS obtained imagery and photogrammetry software.
Washed Out: Policy and Practical Considerations Affecting Return after Hurricane Katrina and Superstorm Sandy

The destructive impacts of Hurricane Katrina and Superstorm Sandy displaced large numbers of people. While some families were able to return home soon after the disasters, others struggled to do so and remained displaced for extended periods of time. Although much attention has been paid to the immediate response to natural disasters, research on policies and practices regarding long-term return migration has been largely overlooked. This article presents an overview of recent literature that addresses factors affecting displaced individualsi¯ decision to return home or relocate following these two disasters. It discusses five major factors influencing individual and household decisions regarding whether to return home, relocate, or remain in limbo if unable to achieve either. These include: (1) habitability of homes; (2) affordability of housing; (3) financial burdens; (4) slow restoration of public services and facilities; and (5) sense of place and identity. The article then assesses the types of policies that have been used with varying goalsiapromoting, discouraging, and, in some cases, prohibiting return. It presents four examples of policy tools that have influenced post-disaster return or relocation after Hurricane Katrina and Superstorm Sandy: (1) tax policies; (2) buyouts; (3) changes to building codes; and (4) revisions to the U.S. National Flood Insurance Program. The article concludes that a better understanding of factors affecting displaced persons can help policymakers meet their objectives of encouraging or inhibiting return to a specific site after a disaster.
State-Aware Deep Item Response Theory using student facial features

This paper introduces a novel approach to Item Response Theory (IRT) by incorporating deep learning to analyze student facial expressions to enhance the prediction and understanding of student responses to test items. This research is based on the assertion that students' facial expressions offer crucial insights into their cognitive and affective states during testing, subsequently influencing their item responses. The proposed State-Aware Deep Item Response Theory (SAD-IRT) model introduces a new parameter, the student state parameter, which can be viewed as a relative subjective difficulty parameter. It is latent-regressed from students' facial features while solving test items using state-of-the-art deep learning techniques. In an experiment with 20 students, SAD-IRT boosted prediction performance in students' responses compared to prior models without the student state parameter, including standard IRT and its deep neural network implementation, while maintaining consistent predictions of student ability and item difficulty parameters. The research further illustrates the model's early prediction ability in predicting the student's response result before the student answered. This study holds substantial implications for educational assessment, laying the groundwork for more personalized and effective learning and assessment strategies that consider students' emotional and cognitive states.
Foramen Magnum and Dental Osteometry of Balami, Uda, and Yankasa Breeds of Sheep

The increasing demand for animal protein, particularly meat, requires a thoughtful approach to selecting the type of meat-producing animal to achieve maximum yields. This is crucial to maintain food security. This study aimed to evaluate and compare some skull osteometries. A total of 60 each of Balami, Uda, and Yankasa sheep (30 adult males and 30 adult females) were used in this study. The skulls were macerated using a hot water technique. Then 7 parameters were measured using a digital Vernier caliper. The obtained data were analyzed using ANOVA (p < 0.05). The result of this study was that the mean foramen magnum height (FMH) was highest, medium, and lowest in the Balami (2.1 ± 0.1 cm), Uda (1.9 ± 0.1 cm), and Yankasa (1.8 ± 0.0 cm) breeds, respectively, and vice versa in the foramen magnum index (FMI). The foramen magnum width (FMW) was similar in Balami and Uda but higher than in Yankasa (1.8 ± 0.1 cm). The FMH, FMW, and FMI were similar within sexes of the same breeds in Balami, Uda, and Yankasa. The mean dental length (DL), oral palatal length (OPL), and length of the upper molar row (LUM) were highest and lowest in Balami and Yankasa, respectively, while the mean length of the upper premolar row (LUP) was highest and lowest in Balami and Uda, respectively. The (DL), (OPL), (LUM), and (LUP) were higher in males than females in Balami and vice versa in Uda and Yankasa. In conclusion, craniometric values, including foramen magnum and dental osteometry, of indigenous Nigerian sheep breeds were used to compare them to other breeds and among themselves. It could also guide oral surgery and assist in identifying sheep breeds through comparative study.
Revisiting extreme storms of the past 100 years for future safety of large water management infrastructures

Historical extreme storm events are widely used to make Probable Maximum Precipitation (PMP) estimates, which form the cornerstone of large water management infrastructure safety. Past studies suggest that extreme precipitation processes can be sensitive to land surface feedback and the planetary warming trend, which makes the future safety of large infrastructures questionable given the projected changes in land cover and temperature in the coming decades. In this study, a numerical modeling framework was employed to reconstruct 10 extreme storms over CONUS that occurred during the past 100 years, which are used by the engineering profession for PMP estimation for large infrastructures such as dams. Results show that the correlation in daily rainfall for such reconstruction can range between 0.4 and 0.7, while the correlation for maximum 3‐day accumulation (a standard period used in infrastructure design) is always above 0.5 for post‐1948 storms. This suggests that current numerical modeling and reanalysis data allow us to reconstruct big storms after 1948 with acceptable accuracy. For storms prior to 1948, however, reconstruction of storms shows inconsistency with observations. Our study indicates that numerical modeling and data may not have advanced to a sufficient level to understand how such old storms (pre‐1948) may behave in future warming and land cover conditions. However, the infrastructure community can certainly rely on the use of model reconstructed extreme storms of the 1948‐present period to reassess safety of our large water infrastructures under assumed changes in temperature and land cover.
KARAKTERISTIK FUNGSIONAL DAN UJI HEDONIK KUKIS KETAWA BERBAHAN DASAR TEPUNG GANDUM UTUH LOKAL

Laughing Cookies are a traditional snack made from local whole wheat flour (Gaul). Cookie dough added with kimpul flour is one of the innovative efforts to process the abundant kimpul commodity in Cukilan Village, Semarang Regency, Central Java. This study aimed to determine the panelists' functional characteristics and level of preference for the laugh cookies made from local whole wheat flour. The laugh cookies are made with three formulations, namely A (1:0), B (1:1), and C (1:2) (Gaul flour: kimpul flour ratio). The results of the hedonic test with the parameters texture, color, aroma, taste, and overall showed that the fifty panelists liked formulations A, B, and C, respectively, with a score of 3.7-3.8 respectively (neutral – somewhat like); 3.1-3.6 (neutral – somewhat like), and 2.9-3.4 (dislike - neutral). Based on the panelists' preference for Formulations A and B, these two formulas were tested for fiber. The crude fiber content in formulations A and B was 42.74% and 46.22%, respectively. Based on the study's results, it can be concluded that the formulation of the laugh cookies has a different effect on the level of preference and crude fiber. The best treatment was formulation A, with the highest preference level and high oil fiber.
Efficacy and Safety of Extracorporeal Shock Wave Lithotripsy (ESWL) in Patients With Infected Ureterohydronephrosis Due to Ureteral Stones Following Double-J Catheter Insertion

Introduction: Double-J ureteral catheters in patients with ureteral lithiasis undergoing extracorporeal shockwave lithotripsy (ESWL) procedures reduce the efficacy of the procedure or have no effect on the stone-free rate. However, the effect of double-J catheters on the patients in whom they were inserted for infected hydronephrosis is not known. The aim of our study was to evaluate the efficacy and safety of the ESWL procedure in patients with ureteral lithiasis and double-J catheters previously inserted for infected hydronephrosis. Method: We conducted a comparative case-control, match-paired study in a group of patients with ureteral lithiasis treated by ESWL from January 1, 2018, to March 1, 2023, who were divided into two groups according to the presence of the double-J catheter. For each patient with the double-J catheter from the study group, we selected one patient for the control group without the double-J catheter and matched them in terms of size, location of stones, and body mass index (BMI). We analyzed the stone-free rate and complications that occurred in the two groups. Results: Forty patients with ureteral lithiasis and a double-J catheter inserted for infected hydronephrosis were enrolled in the study group. The control group included 40 patients with ureteral stones without double-J catheters. The patients in the two groups were predominantly men with stones located in the lumbar region and on the right side and with a BMI between 25 and 30 kg/m2. The stones had an average size of 0.9+/-0.12mm and 0.89+/-0.15mm, respectively (p=0.624). There was no statistically significant difference in stone-free rate between the two groups after the first session of ESWL (47.5% vs. 52.5%, p=0.502), the second (70% vs. 75%, p = 0.616), and the third session (85% vs. 87.5%, p=0.761). The rate of complications was similar in both groups (7.5% vs. 5%, p=0.761). Conclusions: The presence of double-J catheters inserted in patients with ureteral stones who underwent ESWL for infected hydronephrosis does not affect the stone-free rate of the procedure or the complication rate. The procedure of ESWL in patients with ureteral lithiasis and double-J catheters inserted for infected hydronephrosis is a safe and efficient method that can be recommended as an initial treatment alongside retrograde ureteroscopy.
Double-Difference Tomography Applied to Monitoring of Geologic Carbon Sequestration in the Aneth Oil Field, Utah

Double-difference seismic tomography is performed on a carbon sequestration operation in the Aneth Oil Field in southeast Utah as part of a Department of Energy initiative on monitoring, verification, and accounting of sequestered CO2. A total of 1,211 seismic events were recorded from a borehole array of 22 geophones. Aneth Unit data were divided into four time periods for time-lapse analysis. A low velocity zone spanning the lateral extents of the observable region, likely representing a CO2 plume, is detected when considering voxels containing the highest ray path coverage. A series of synthetic tomography tests simulating different CO2 plume sizes and locations was performed to assist in characterizing velocity changes associated with Aneth Unit data. Inferences about the existence of a CO2 plume should be made by comparing actual data to synthetic data resulting from simulations performed under similar conditions. Considering synthetic simulation similarities and a derivative weight sum analysis, a CO2 plume can be imaged within the Desert Creek reservoir, but the resolution of the CO2 plume is too low for proper monitoring, verification, and accounting of injected CO2. Recommendations, for improving CO2 plume resolution through double difference seismic tomography, are made to increase the ray path distribution throughout the Aneth Unit by varying geophone locations.
Meningkatkan Kemampuan Skill Membaca dan Berfikir Kritis Menghadapi Ancaman AI di Era Digital yang Semakin Modern

Bagi sebagian orang, Kecerdasan Buatan dianggap sebagai ancaman terhadap keberadaan manusia dan peluang kerja. Namun, saya memandang fenomena ini secara berbeda. Bagi sebagian orang, AI akan menempati banyak peluang kerja. Namun, bagi saya, manusia telah dan masih menjadi bagian dari masa depan. Manusia memiliki mekanisme berpikir yang sangat berbeda dibandingkan AI. Jika manusia ingin berada di peta, manusia harus mengembangkan keterampilan yang tidak dapat dicapai oleh AI seperti intuisi dan empati. Berpikir kritis dan belajar adalah kunci untuk mencapai tujuan tersebut. Dalam tulisan ini, saya akan membuktikan pendirian saya berdasarkan metode penelitian yang disebut Systematic Literature Review (SLR). Masih banyak ruang kompetisi bagi manusia ketika berhadapan dengan AI. Yang terpenting adalah manusia harus melihat dan memahami bahwa manusia memiliki kelebihan dibandingkan dengan AI. Kelebihan manusia ketimbang AI ini harus diwujudkan dengan belajar dan membaca kritis. Caranya adalah dengan manusia belajar tanpa harus terbebani mencapai kompetensi tertentu, merefleksikan apa yang manusia pelajari, memandang ilmu dengan empati dan visioner serta kemudian mempersonalisasi ilmu yang telah manusia pelajari agar menjadi bagian dari diri manusia untuk kemudian dapat menggunakan ilmu tersebut untuk kepentingan yang lebih baik di masa depan.