Miracle-dz/UniFAR-FTUs huggingface dataset:
Hepatic arterial infusion chemotherapy and trastuzumab in gastric cancer with liver metastases: a case report

Background Gastric cancer is a common cancer worldwide and is responsible for over one million new cases in 2020 and an estimated 769,000 deaths, ranking fifth for incidence and fourth for mortality globally. Incidence rates are highest in Eastern Asia and Eastern Europe. Gastric cancer is highly heterogeneous and progresses rapidly. The prognosis of gastric cancer with liver metastases is poor, and clinical treatment remains challenging. Human epidermal growth factor receptor 2 (HER2) positivity is correlated to a bad prognosis for gastric cancer. Trastuzumab combined with systemic chemotherapy is the preferred treatment for HER2-positive advanced gastric cancer. However, intravenous chemotherapy has severe systemic toxicity, which reduces the local drug concentration and tumor uptake rate, and the effect is unsatisfactory. Case summary We reported a 66-year-old patient with HER2-positive advanced gastric cancer with jaundice due to multiple liver metastases, after 6 cycles of trastuzumab combined with hepatic arterial infusion chemotherapy (HAIC), the tumor retracted significantly, the jaundice subsided, and the patient recovered well. The patient achieved disease control with an intensive regimen followed by less toxic maintenance therapy. Trastuzumab combined with capecitabine maintenance therapy followed up for more than 16 months. Conclusion HAIC plus trastuzumab may be a tolerable treatment option for patients with severe liver metastases from HER2-positive gastric cancer to achieve local control and prolong survival.
Surrogate-Assisted Cooperative Lion Swarm Optimization Algorithm for High-Dimensional Feature Selection

With the development of information science, a large amount of data has poured into people's lives. As one of the effective means of extracting massive data, feature selection has been concerned by a large number of scholars. Feature selection is an NP-hard problem, and one of the traditional methods is to use optimization algorithms to search. However, this traditional method faces serious challenges with the increase of feature- dimensional data. This is mainly because as the feature dimension becomes larger, the search space of the optimization algorithm will increase exponentially, which will seriously degrade the search performance. Previous studies have shown that evolutionary algorithms assisted by surrogate models can solve high-dimensional feature selection well. Following this research line of thought, this paper proposes a surrogate-assisted cooperative lion swarm optimization algorithm for high- dimensional feature selection, which combines co-evolution and surrogate assistance with the lion swarm optimization algorithm to improve the accuracy of high-dimensional feature selection problems. Experiments show that the algorithm can show excellent performance in feature selection problems up to 6000 dimensions.
Textural Restoration of Broiler Breast Fillets with Spaghetti Meat Myopathy, Using Two Alginate Gels Systems

The effects of salt-sensitive alginate (“A”) and a two-component salt-tolerant alginate system (“B”) used at a 0.5% or 1.0% level were evaluated in normal breast (NB) chicken fillets and in spaghetti meat (SM) fillets. Minced raw and cooked SM samples showed higher cooking loss (p < 0.05) and lower penetration force compared to NB meat. Both alginate systems significantly raised the penetration force in raw samples and decreased cooking loss (p < 0.05). Adding 1% of “A” or 0.5% “B” to SM, without salt, resulted in a similar penetration force as the cooked NB meat, while 1% “B” with salt resulted in a higher penetration force. Excluding salt from SM samples while adding alginate “A” or “B” improved texture profiles, but not to the same level as using NB without additives. Overall, salt, together with alginate “B”, improved the texture of SM to that of normal meat without myopathy.
Artifact Removal in Long-Range Single Photon LiDAR via Waveforms-Guided Depth Image Estimation

Single-photon light detection and ranging (LiDAR) has widespread applications due to the ultra-high sensitivity of the single-photon detector. However, the reconstruction has been plagued by multiple types of noise caused by crosstalk, dark counts, and background light. Artifacts produced by crosstalk are particularly difficult to distinguish directly from the signal for single photon avalanche diode (SPAD) array detector. This work proposes a waveforms-guided depth image estimation method to remove the signal artifacts effectively. Experiments show that a region of interest recognition ratio of 1.02 is achieved at 4.2 km. The study demonstrates that this waveform-guided method has excellent potential for accurate target recognition in a long range.
Cell-Free DNA Genomic Profiling and Its Clinical Implementation in Advanced Prostate Cancer

Simple Summary Prostate cancer (PCa) accounts for the second-highest mortality rate in cancer-associated deaths. Liquid biopsy has great potential to tailor treatment choices in advanced PCa. In this study, we evaluated the utility and diagnostic potential of a custom-designed NGS cfDNA panel based on the AmpliSeq HD Technology in advanced PCa. cfDNA somatic mutations were detected in the majority (71%) of examined advanced PCa patients. The most frequently mutated genes in the PCa cohort of 68 patients (40 metastatic castration-resistant and 28 metastatic hormone-naive PCa) were: TP53, FOXA1, SPOP, PTEN, AR, CTNNB1, RB1, and PIK3CA. AR amplifications were detected in 31% of mCRPC patients. This approach appears to be a straightforward and cost-effective method for detecting clinically relevant somatic mutations in cfDNA to aid in clinical decision-making. Abstract Most men with prostate cancer (PCa), despite potentially curable localized disease at initial diagnosis, progress to metastatic disease. Despite numerous treatment options, choosing the optimal treatment for individual patients remains challenging. Biomarkers guiding treatment sequences in an advanced setting are lacking. To estimate the diagnostic potential of liquid biopsies in guiding personalized treatment of PCa, we evaluated the utility of a custom-targeted next-generation sequencing (NGS) panel based on the AmpliSeq HD Technology. Ultra-deep sequencing on plasma circulating free DNA (cfDNA) samples of 40 metastatic castration-resistant PCa (mCRPC) and 28 metastatic hormone-naive PCa (mCSPC) was performed. CfDNA somatic mutations were detected in 48/68 (71%) patients. Of those 68 patients, 42 had matched tumor and cfDNA samples. In 21/42 (50%) patients, mutations from the primary tumor tissue were detected in the plasma cfDNA. In 7/42 (17%) patients, mutations found in the primary tumor were not detected in the cfDNA. Mutations from primary tumors were detected in all tested mCRPC patients (17/17), but only in 4/11 with mCSPC. AR amplifications were detected in 12/39 (31%) mCRPC patients. These results indicate that our targeted NGS approach has high sensitivity and specificity for detecting clinically relevant mutations in PCa.
Evaluation method for co-frequency interference between satellites

In recent years, with the development of inter satellite network technology and the flourishing of commercial micro satellites, the number of satellites in orbit has increased sharply, and the problem of frequency interference between satellites and constellations is particularly prominent. Due to the use of the same frequency band in similar satellite services as agreed by the International Telecommunication Union, the issue of co frequency interference between geostationary orbit satellites and non geostationary orbit satellites, as well as between different non geostationary orbit satellites, is becoming increasingly prominent due to real-time changes in relative positions. This article takes the Beidou Navigation Constellation as an example and proposes an interference evaluation method for calculating and evaluating inter satellite co frequency interference through modeling analysis.
Registered Nurse Competencies and the Implementation of Self-Registered Nurse Competencies and the Implementation of Self-Care Interventions Among Surgical Patients with Type Two Care Interventions Among Surgical Patients with Type Two Diabetes: A Quality Improvement Project Diabetes: A Quality Impr

Background: Type 2 Diabetes is a chronic disease that requires a holistic approach, an in-depth understanding of self-care, education comprehension, and an effective relationship between healthcare professionals and the individual patient (Saeed et al., 2018). Due to a variety of factors such as increased nurse-to-patient ratios, inconsistent education methods, and limited confidence levels among registered nurses, important treatment measures and discussion of one’s T2DM diagnoses are often not addressed. Initiatives to improve education methods and nursing confidence levels will create more effective treatment measures and discharge education. Local Problem: Registered nurses spend minimal time educating patients on the severity of their disease and how to prevent further complications. A point-of-care education model was utilized to understand nursing barriers that prevent them from offering optimal T2DM education. The desired outcome of this intervention was to have registered nurses incorporate concrete diabetic education into individual patient care. Methods: The project used a plan-do-study-act (PDSA) strategy to gather information relating to post-surgical management of T2DM. A seven-question survey generated data on the top reasons why education was not initiated among patients. Intervention: Following data collection, a point-of-care discussion model was utilized so that nurses could privately discuss personal barriers to patient education. Qualitative data was shared which emphasized areas that nurses can improve upon and implement into daily education methods. The goal was to increase nursing competency levels during routine patient care and upon discharge. Results: Data showed that 72% of registered nurses said they were not comfortable talking about self-care interventions with patients diagnosed with T2DM.
Are Measures of Patrollability Affected by Tessellating Shape

A grid-based thematic map is a spatial analysis tool that can be used to identify crime patterns, aiding law enforcement agencies in identifying problem areas within their jurisdictions and allocating resources to address them. Grids used to create these maps are comprised of shapes that tessellate (i.e., squares, hexagons, triangles). Square grids are used most often in crime hot spot mapping, but little is known whether the choice of tessellating shape affects performance metrics used to assess prospective hot spot forecasts. Using a purposive sample of known crime locations in St. Petersburg, Florida, the current study investigated whether tessellating shape used in grid-based thematic maps affects one particular performance metric: patrollability. Findings were mixed, showing that the effect tessellating shape has on grid-based thematic maps varies by type of crime and on which patrollability metric is used to assess forecasting performance. Results are discussed in terms of their impact on practioners' use of crime hot spot mapping in law enforcement and on future research.
Detectability of change in winter precipitation within mountain landscapes: Spatial patterns and uncertainty

Detecting long‐term change in seasonal precipitation using ground observations is dependent on the representativity of the point measurement to the surrounding landscape. In mountainous regions, representativity can be poor and lead to large uncertainties in precipitation estimates at high elevations or in areas where observations are sparse. If the uncertainty in the estimate is large compared to the long‐term shifts in precipitation, then the change will likely go undetected. In this analysis, we examine the minimum detectable change across mountainous terrain in western Montana, USA. We ask the question: What is the minimum amount of change that is necessary to be detected using our best estimates of precipitation in complex terrain? We evaluate the spatial uncertainty in the precipitation estimates by conditioning historic regional climate model simulations to ground observations using Bayesian inference. By using this uncertainty as a null hypothesis, we test for detectability across the study region. To provide context for the detectability calculations, we look at a range of future scenarios from the Coupled Model Intercomparison Project 5 (CMIP5) multimodel ensemble downscaled to 4 km resolution using the MACAv2‐METDATA data set. When using the ensemble averages we find that approximately 65% of the significant increases in winter precipitation go undetected at midelevations. At high elevation, approximately 75% of significant increases in winter precipitation are undetectable. Areas where change can be detected are largely controlled by topographic features. Elevation and aspect are key characteristics that determine whether or not changes in winter precipitation can be detected. Furthermore, we find that undetected increases in winter precipitation at high elevation will likely remain as snow under climate change scenarios. Therefore, there is potential for these areas to offset snowpack loss at lower elevations and confound the effects of climate change on water resources.
Population distribution and breeding practices of livestock in different districts of Bangladesh

The objectives of this study were to determine the farmers’ socio-economic characteristics, livestock population dynamics, and breeding practices followed by the farmers. Out of 1487 farmers, a major proportion (53.12%) of farmers was middle-aged. Most of the farmers (71.22%) were associated with agricultural activities and had low income per month (52.32%). Livestock keeping patterns of farmers were cattle, goats, buffalo, and combinations of these animals. Female animals were inferred to be more prevalent in different districts (cow 85.08%, doe 81.29%) than males (bull 14.92%, buck 18.71%). In case of cattle and goats, the highest number of farmers maintained a medium size herd, whereas buffalo farmers had a large herd size. In terms of breeding practices, the majority of the farmers (75.55%) performed artificial insemination (AI) in cattle and found it convenient to service their cows. When considering buffalo, and goat, the majority of the farmers (94.12% and 98.50%, respectively) practiced natural services. The findings also demonstrated that the majority of the farmers (73.8% and 82%, respectively) raised crossbreed cattle and buffalo, while just a tiny portion (26.18% and 18%, respectively) raised indigenous breeds. However, this situation was vice versa in case of goat. For choice of the breed according to the farmers, 39.17% of farmers preferred Black Bengal goat, 60.83% preferred cross breed. This study represents a comprehensive overview of livestock status and existing breeding practices employed by the farmers in different districts of Bangladesh, which may be utilized to implement relevant livestock improvement programs in Bangladesh. Asian Australas. J. Biosci. Biotechnol. 2023, 8(3), 38-48
Automatic Vehicle License Plate Recognition Using Lightweight Deep Learning Approach

Intelligent transportation systems rely heavily on automatic vehicle license plate recognition (AVLPR). This system is required for traffic control, electronic toll collection, and access to parking lots. Due to the complexity and structure of license plate design for each country, especially in Arabic countries, license plate recognition is one of the most difficult recognition problems. Using image processing and deep learning (DL) techniques, the proposed AVLPR system is applied to new Iraqi license plates (LPs). We proposed a Lightweight Convolution Neural Network (LWCNN) in this study. It has four convolutional blocks, each with a batch of Max-pooling and Dropout layers, as well as a Flatten layer and two Dense layers. This architecture is simple, fast, and dependable, with promising classification accuracy that could propel the field forward. The proposed algorithm achieved 98% detection accuracy for the standard new PLs style and 85% training accuracy for digits dataset.
Faulting of the Roman aqueduct of Venafrum (southern Italy): Methods of investigation, results, and seismotectonic implications

We present evidence of surface faulting of a poorly known first-century B.C. aqueduct in central-southern Italy. Data were acquired by means of geological, geophysical, and geodetical surveys along the surficial trace of a primary active fault (Aquae Iuliae fault). The ~30-km-long Venafrum aqueduct presents a net vertical offset of almost 4 m at the intersection with this normal fault. This fact reveals the occurrence of repeated faulting of the Roman water supply after its construction, i.e., during large historical earthquakes, the last being one of the most violent events to happen in Italy during the Middle Ages (September 1349, Mw = 6.6). We tentatively associate the remaining offset of the aqueduct to other poorly characterized earthquakes in the area, which were not previously associated with any active fault. It is a well-known fact that the recognition of ancient earthquakes on archaeological relics is a matter of debate in archaeoseismology, being difficult at all times—and often impossible—to ascertain whether the damage observed should be related to seismic shaking or other *paolo.galli@protezionecivile.it Galli, P.A. C. , Giocoli, A. , Naso, J.A. , Piscitelli, S. , Rizzo, E. , Capini, S. , and Scaroina, L. , 2010, Faulting of the Roman aqueduct of Venafrum (southern Italy): Methods of investigation, results, and seismotectonic implications, in Sintubin, M. , Stewart, I.S. , Niemi, T.M. , and Altunel, E. , eds., Ancient Earthquakes: Geological Society of America Special Paper 471, p. 233–242, doi: 10.1130/2010.2471(19). For permission to copy, contact editing@geosociety.org. © 2010 The Geological Society of America. All rights reserved.
Image of Self Compassion on Space Officers at Eltari Airport

Self-compassion is an attitude of having concern and kindness towards oneself when faced with various difficulties in life. In the field of work, which has the function and duty to regulate the smooth operation of civil aviation, pretending space employees are required not to make the slightest mistake. So employees need to have self-compassion themselves. This study uses a qualitative method, with the techniques of observation, interviews, and documentation. The participants were 8 employees of the temple space. In general, participants in this study tend to have good self-compassion. This is illustrated by the ability of self-kindness, mindfulness, and common humanity, as well as low self-judgment, isolation, and over-identification by participants at this time.
The Complex Interplay between the Gut Microbiome and Osteoarthritis: A Systematic Review on Potential Correlations and Therapeutic Approaches

The objective of this review is to systematically analyze the potential correlation between gut microbiota and osteoarthritis (OA) as well as to evaluate the feasibility of microbiota-targeted therapies for treating OA. Studies conducted from October 2013 to October 2023 were identified via a search on electronic databases such as PubMed, Web of Science, and Scopus, following established PRISMA statement standards. Two reviewers independently screened, assessed, and extracted relevant data, and then they graded the studies using the ROBINS I tool for non-randomized interventions studies and SYRCLE’s risk-of-bias tool for animal studies. A search through 370 studies yielded 38 studies (24 preclinical and 14 clinical) that were included. In vivo research has predominantly concentrated on modifying the gut microbiota microenvironment, using dietary supplements, probiotics, and prebiotics to modify the OA status. Lactobacilli are the most thoroughly examined with Lactobacillus acidophilus found to effectively reduce cartilage damage, inflammatory factors, and pain. Additionally, Lactobacillus M5 inhibits the development of OA by preventing high-fat diet (HFD)-induced obesity and protecting cartilage from damage. Although there are limited clinical studies, certain compositions of intestinal microbiota may be associated with onset and progression of OA, while others are linked to pain reduction in OA patients. Based on preclinical studies, there is evidence to suggest that the gut microbiota could play a significant role in the development and progression of OA. However, due to the scarcity of clinical studies, the exact mechanism linking the gut microbiota and OA remains unclear. Further research is necessary to evaluate specific gut microbiota compositions, potential pathogens, and their corresponding signaling pathways that contribute to the onset and progression of OA. This will help to validate the potential of targeting gut microbiota for treating OA patients.
User Behavior Prediction Based on Oil Consumption Data

Accurate prediction of user behavior has important application value in various fields. By understanding and predicting user behavior, businesses can make informed decisions and optimize their marketing strategies. In order to be able to accurately predict user purchase behavior, we propose a new user behavior prediction method. Firstly, the user consumption amount and consumption times are preprocessed, secondly, we use random forest (RF) for feature screening, and use long short-term memory network (LSTM) to construct a user behavior prediction model. Finally, we use the sparrow search algorithm(SSA) to optimize the hyperparameters of the model. Experimental results show that our RF-SSA-LSTM model can make accurate predictions of user behavior.
Towards a better definition of the Anisian/Ladinian boundary: New biostratigraphic data and correlations of boundary sections from the Southern Alps

Stratigraphic sections of basinal «Buchenstein Beds» in the northwestern Dolomites and eastern Lombardy are correlated on the basis of the distribution of macrofossils (ammonoids, Daonellas) and volcaniclastic layers. In Lombardy, these strata are bracketed by other Middle Triassic basinal sediments (Prezzo Lst., «Wengen Beds»), and the entire succession hosts a clear macrofossil (ammonoids, Daonellas) record ranging from the Late Anisian to the Late Ladinian. In the Anisian/Ladinian boundary interval this record appears to be relatively coherent when compared to equivalent standard sections in the western Tethys area. It allows the full integration of rich faunas from isolated localities in coeval platform carbonates (Latemar and Cernera) and intra-platform deposits (Monte San Giorgio)