Miracle-dz/UniFAR-FTUs huggingface dataset:
Lightweight Detection Method for X-ray Security Inspection with Occlusion

Identifying the classes and locations of prohibited items is the target of security inspection. However, X-ray security inspection images with insufficient feature extraction, imbalance between easy and hard samples, and occlusion lead to poor detection accuracy. To address the above problems, an object-detection method based on YOLOv8 is proposed. Firstly, an ASFF (adaptive spatial feature fusion) and a weighted feature concatenation algorithm are introduced to fully extract the scale features from input images. In this way, the model can learn further details in training. Secondly, CoordAtt (coordinate attention module), which belongs to the hybrid attention mechanism, is embedded to enhance the learning of features of interest. Then, the slide loss function is introduced to balance the simple samples and the difficult samples. Finally, Soft-NMS (non-maximum suppression) is introduced to resist the conditions containing occlusion. The experimental result shows that mAP (mean average precision) achieves 90.2%, 90.5%, 79.1%, and 91.4% on the Easy, Hard, and Hidden sets of the PIDray and SIXray public test set, respectively. Contrasted with original model, the mAP of our proposed YOLOv8n model increased by 2.7%, 3.1%, 9.3%, and 2.4%, respectively. Furthermore, the parameter count of the modified YOLOv8n model is roughly only 3 million.
RNGU-NET: a novel efficient approach in Segmenting Tuberculosis using chest X-Ray images

Tuberculosis affects various tissues, including the lungs, kidneys, and brain. According to the medical report published by the World Health Organization (WHO) in 2020, approximately ten million people have been infected with tuberculosis. U-NET, a preferred method for detecting tuberculosis-like cases, is a convolutional neural network developed for segmentation in biomedical image processing. The proposed RNGU-NET architecture is a new segmentation technique combining the ResNet, Non-Local Block, and Gate Attention Block architectures. In the RNGU-NET design, the encoder phase is strengthened with ResNet, and the decoder phase incorporates the Gate Attention Block. The key innovation lies in the proposed Local Non-Local Block architecture, overcoming the bottleneck issue in U-Net models. In this study, the effectiveness of the proposed model in tuberculosis segmentation is compared to the U-NET, U-NET+ResNet, and RNGU-NET algorithms using the Shenzhen dataset. According to the results, the RNGU-NET architecture achieves the highest accuracy rate of 98.56%, Dice coefficient of 97.21%, and Jaccard index of 96.87% in tuberculosis segmentation. Conversely, the U-NET model exhibits the lowest accuracy and Jaccard index scores, while U-NET+ResNet has the poorest Dice coefficient. These findings underscore the success of the proposed RNGU-NET method in tuberculosis segmentation.
Prevalence of Systemic Hypertension and Control of Systolic Blood Pressure in a Cohort of 14 Dogs with Adrenal-Dependent Hypercortisolism during the First Year of Trilostane Treatment or after Adrenalectomy

Simple Summary Cushing’s syndrome is a common disease in middle-aged and old dogs, characterized by steroid overproduction by the adrenal glands. This steroid excess can be caused by an adrenal tumor (adrenal dependent hypercortisolism) and is associated with systemic hypertension. In people with this disease, it is known that hypertension can be difficult to manage and, sometimes, several drugs are necessary to treat it. However, there are no studies focused on the changes in the blood pressure during treatment in dogs with adrenal-dependent hypercortisolism. In this study, 14 dogs with this disease were followed during the first year of medical treatment or during 1 year after surgery to remove the adrenal tumor (adrenalectomy), and the changes in their blood pressure were evaluated. We observed that blood pressure in medically treated dogs decreased during the study period using, in most cases, a single antihypertensive drug. Also, in those dogs surgically treated, blood pressure normalized three months after surgery, and in one case, antihypertensive medications could be reduced. Thus, when adrenalectomy is performed, it is important to carefully address blood pressure after the procedure as these dogs might require reductions in their antihypertensive treatment. Abstract Hypercortisolism in dogs is frequently associated with systemic hypertension (SH). However, there are no studies evaluating the changes in systolic blood pressure (SBP) in dogs with adrenal-dependent hypercortisolism (ADH) during trilostane treatment or after adrenalectomy and their response to antihypertensive treatments. For this reason, the objectives of this study were to evaluate the changes in SBP in dogs with ADH during the first year of trilostane treatment or after adrenalectomy, the relation with clinical control of hypercortisolism and certain laboratory parameters, and the response to antihypertensive drugs. Fourteen dogs newly diagnosed with ADH were prospectively included and evaluated at diagnosis (T0) and 1, 3, 6, and 12 months after (T1, T3, T6, and T12, respectively). Dogs were classified as hypertensive (HT; SBP ≥ 160 mmHg) and non-hypertensive. In HT dogs, benazepril was considered as the first-line drug, and, if necessary, amlodipine was prescribed. The prevalence of SH at T0 was 79%, and it was reduced to 25% at T12. Blood pressure (BP) was not associated with disease control or selected laboratory parameters at any endpoint. Only 22% of dogs with SH needed more than one drug to normalize their SBP. In all dogs surgically treated that were HT at T0, BP normalized at T3.
ATTA: Adversarial Task-transferable Attacks on Autonomous Driving Systems

Deep learning (DL) based perception models have enabled the possibility of current autonomous driving systems (ADS). However, various studies have pointed out that the DL models inside the ADS perception modules are vulnerable to adversarial attacks which can easily manipulate these DL models’ predictions. In this paper, we propose a more practical adversarial attack against the ADS perception module. Particularly, instead of targeting one of the DL models inside the ADS perception module, we propose to use one universal patch to mislead multiple DL models inside the ADS perception module simultaneously which leads to a higher chance of system-wide malfunction. We achieve such a goal by attacking the attention of DL models as a higher level of feature representation rather than traditional gradient-based attacks. We successfully generate a universal patch containing malicious perturbations that can attract multiple victim DL models’ attention to further induce their prediction errors. We verify our attack with extensive experiments on a typical ADS perception module structure with five famous datasets and also physical world scenes1.1We release our code at https://github.com/qingjiesjtu/ATTA
Soil fungal community is more sensitive than bacterial community to modified materials application in saline–alkali land of Hetao Plain

Soil salinization has become a major challenge that severely threatens crop growth and influences the productivity of agriculture. It is urgent to develop effective management measures to improve saline–alkali soil. Thus, in this study, soil properties, microbial communities, and function under desulfurization gypsum (DE), soil amendment (SA), farm manure (FA), and co-application of desulfurization gypsum, soil amendment, and farm manure (TA) in a field experiment were examined by high-throughput sequencing. The results showed that the application of modified materials is an effective approach in improving saline–alkali soil, especially TA treatment significantly increased the content of available phosphorus (AP), available potassium (AK), soil organic matter (SOM), and alkaline hydrolysis nitrogen (AHN) and decreased pH, bulk density (BD), and electrical conductivity (EC). The application of modified materials resulted in notable enhancement in fungal diversity and altered the composition and structure of the fungal community. Conversely, the effect on the bacterial community was comparatively minor, with changes limited to the structure of the community. Regarding the fungal community composition, Ascomycota, Mortierellomycota, and Basidiomycota emerged as the dominant phyla across all treatments. At each taxonomic level, the community composition exhibited significant variations in response to different modified materials, resulting in divergent soil quality. The TA treatment led to a decrease in Mortierellomycota and an increase in Ascomycota, potentially enhancing the ability to decompose organic matter and facilitate soil nutrient cycling. Additionally, the sensitivity of fungal biomarkers to modified materials surpassed that of the bacterial community. The impact of modified materials on soil microbial communities primarily stemmed from alterations in soil EC, AP, AK, and SOM. FUNGuild analysis indicated that the saprotroph trophic mode group was the dominant component, and the application of modified materials notably increased the symbiotroph group. PICRUSt analysis revealed that metabolism was the most prevalent functional module observed at pathway level 1. Overall, the application of modified materials led to a decrease in soil EC and an increase in nutrient levels, resulting in more significant alterations in the soil fungal community, but it did not dramatically change the soil bacterial community. Our study provides new insights into the application of modified materials in increasing soil nutrients and altering soil microbial communities and functions and provides a better approach for improving saline–alkali soil of Hetao Plain.
Sequencing, Analysis and Organization of the Complete Genome of a Novel Baculovirus Calliteara abietis Nucleopolyhedrovirus (CaabNPV)

Baculoviridae, a virus family characterized by a single large double stranded DNA, encompasses the majority of viral bioinsecticides, representing a highly promising and environmentally friendly pesticide approach to insect control. This study focuses on the characterization of a baculovirus isolated from larvae of Calliteara abietis (Erebidae, Lymantriidae) collected in Mongolian pinaceae forests. This new isolate was called Calliteara abietis nucleopolyhedrovirus (CaabNPV). CaabNPV exhibits an irregular polyhedron shape, and significant variation in the diameter of its occlusion bodies (OBs) was observed. Nucleotide distance calculations confirmed CaabNPV as a novel baculovirus. The CaabNPV genome spans 177,161 bp with a G+C content of 45.12% and harbors 150 potential open reading frames (ORFs), including 38 core genes. A comprehensive genomic analysis categorizes CaabNPV within Group II alphabaculovirus, revealing a close phylogenetic relationship with Alphabaculovirus orleucostigmae (OrleNPV). Additionally, repeat sequence analysis identified three highly repetitive sequences consisting of 112 bp repeat units, known as homologous regions (hrs). This research contributes valuable insights into CaabNPV’s phylogenetic placement, genomic structure, and its potential applications in insect biocontrol.
Bounds on the Free Distance of Periodically Time-Varying SC-LDPC Codes

Time-invariant spatially coupled low-density parity-check (TI-SC-LDPC) codes can be obtained by unwrapping quasi-cyclic (QC) LDPC block codes. This results in a free distance that is lower bounded by the minimum distance of the underlying QC-LDPC block codes. By introducing some variability in the syndrome former matrix, time-varying (TV) SC-LDPC codes are obtained, which trade an improved error correction performance for an increased decoding memory requirement and decoding complexity. A family of codes able to combine the advantages of TI-SC-LDPC codes with those of TV-SC-LDPC codes is that of periodically time-varying (PTV) SC-LDPC codes, based on a finite and periodic variation of the syndrome former matrix. In this paper we focus on such codes, and derive new upper bounds on the free distance of PTV-SC-LDPC code ensembles as well as on specific codes. By using these bounds, we show that PTV-SC-LDPC codes can achieve important improvements in the free distance over TI-SC-LDPC codes even using a very small period of variability, which corresponds to a minimal increase in memory and complexity. We also validate the new upper bounds through numerical experiments and assess the error correction performance of the corresponding codes through Monte Carlo simulations.
Is Acute Lower Back Pain Associated with Heart Rate Variability Changes? A Protocol for Systematic Reviews

Acute lower back pain (ALBP) is an extremely common musculoskeletal problem. ALBP consists of a sudden onset of short-duration pain in the lower back. However, repeated attacks can make the pain chronic. It can be measured through a self-report scale as well as through physical and physiological evaluations. Heart Rate Variability (HRV) has been used to evaluate the body’s response to pain. However, to the best of our knowledge, no clear consensus has been reached regarding the relationship between both variables and on an optimal protocol for ALBP evaluation based on HRV. The objective of this review is to analyze the relationship and effectiveness of HRV as an instrument for measuring ALBP. Furthermore, we consider the influence of different types of interventions in this relationship. The protocol of this review was previously recorded in the International Prospective Register of Systematic Reviews (number CRD42023437160). The PRISMA guidelines for systematic reviews and PubMed, WOS and Scopus databases are employed. Studies with samples of adults with ALBP are included. This study sets out a systematic review protocol to help identify the relationship between HRV and ALBP. Understanding this relationship could help in designing early detection or action protocols that alleviate ALBP.
Construction of a prognostic prediction model in liver cancer based on genes involved in integrin cell surface interactions pathway by multi-omics screening

Background: Liver cancer is a common malignant tumor with an increasing incidence in recent years. We aimed to develop a model by integrating clinical information and multi-omics profiles of genes to predict survival of patients with liver cancer. Methods: The multi-omics data were integrated to identify liver cancer survival-associated signal pathways. Then, a prognostic risk score model was established based on key genes in a specific pathway, followed by the analysis of the relationship between the risk score and clinical features as well as molecular and immunologic characterization of the key genes included in the prediction model. The function experiments were performed to further elucidate the undergoing molecular mechanism. Results: Totally, 4 pathways associated with liver cancer patients’ survival were identified. In the pathway of integrin cell surface interactions, low expression of COMP and SPP1, and low CNVs level of COL4A2 and ITGAV were significantly related to prognosis. Based on above 4 genes, the risk score model for prognosis was established. Risk score, ITGAV and SPP1 were the most significantly positively related to activated dendritic cell. COL4A2 and COMP were the most significantly positively associated with Type 1 T helper cell and regulatory T cell, respectively. The nomogram (involved T stage and risk score) may better predict short-term survival. The cell assay showed that overexpression of ITGAV promoted tumorigenesis. Conclusion: The risk score model constructed with four genes (COMP, SPP1, COL4A2, and ITGAV) may be used to predict survival in liver cancer patients.
A Review on Influence Dissemination in Social Networks

Influence dissemination research is a key issue in information dissemination in social networks. Due to the practical significance of influence analysis in marketing, advertising, personalized recommendation, and public opinion monitoring, researchers have investigated the problem from different perspectives and proposed solutions. In this paper, we review the influence propagation in social networks and conclude that the existing research uses three main approaches, network topology analysis, greedy algorithms, and heuristic algorithms. Also, according to the purpose of the research, we divided the existing literature into three categories, individual influence analysis, community mining, and influence maximization. Finally, based on state-of-the-art research, we unveil current weaknesses and future research directions.
Gut Symptoms, Gut Dysbiosis and Gut-Derived Toxins in ALS

Many pathogenetic mechanisms have been proposed for amyotrophic lateral sclerosis (ALS). Recently, there have been emerging suggestions of a possible role for the gut microbiota. Gut microbiota have a range of functions and could influence ALS by several mechanisms. Here, we review the possible role of gut-derived neurotoxins/excitotoxins. We review the evidence of gut symptoms and gut dysbiosis in ALS. We then examine a possible role for gut-derived toxins by reviewing the evidence that these molecules are toxic to the central nervous system, evidence of their association with ALS, the existence of biochemical pathways by which these molecules could be produced by the gut microbiota and existence of mechanisms of transport from the gut to the blood and brain. We then present evidence that there are increased levels of these toxins in the blood of some ALS patients. We review the effects of therapies that attempt to alter the gut microbiota or ameliorate the biochemical effects of gut toxins. It is possible that gut dysbiosis contributes to elevated levels of toxins and that these could potentially contribute to ALS pathogenesis, but more work is required.
PALEOECOLOGY OF THE GADDIS SITE IN THE UPPER CRETACEOUS AGUJA FORMATION, TERLINGUA, TEXAS

Abstract Diverse faunas at the Gaddis site near Terlingua, Texas are present at four stratigraphic levels along a hill in the Upper Cretaceous Aguja Formation providing a rich fossil record of the transition from an aquatic environment to dry land while recording exceptional events such as predation and wildfires. Given evidence for minimal transport the microvertebrates, macrovertebrates, coprolites, and plants may be reliably utilized for paleoecological analysis. Paleoenvironments shift upsection from nearshore marine, through tidal channel, to swamp, and, finally, to well-vegetated dry land. The faunas change from a basal layer of oysters with shark teeth to a microvertebrate assemblage just above logs with Teredolites borings and pristine leaves. Above the microvertebrates are diverse macrovertebrates including numerous dinosaurs associated with leaves, logs, and scrambling vines. The macrovertebrate layer is a rich assemblage of herbivorous and carnivorous dinosaurs, crocodiles, turtles, and rare pterosaurs. Several skeletal elements exhibit signs of predation that include punctures and gouges that precisely match crocodile and theropod teeth also recovered at the site. Abundant plant material that includes charred vines and logs is likely evidence of wildfires having ranged across the area. The preponderance of young dinosaur remains may support a wildfire scenario. An exposed surface with 24 coprolites, two hadrosaur vertebrae, logs, and in situ stumps caps the section. The larger coprolites are likely dinosaurian. Most contain plant materials while one contains a bone fragments suggesting the presence of herbivorous and carnivorous dinosaurs on the same surface, an occurrence that echoes herbivore/carnivore interactions in the underlying bonebed.
GPR55 Inactivation Diminishes Splenic Responses and Improves Neurological Outcomes in the Mouse Ischemia/Reperfusion Stroke Model

Although strokes are frequent and severe, treatment options are scarce. Plasminogen activators, the only FDA-approved agents for clot treatment (tissue plasminogen activators (tPAs)), are used in a limited patient group. Moreover, there are few approaches for handling the brain’s inflammatory reactions to a stroke. The orphan G protein-coupled receptor 55 (GPR55)’s connection to inflammatory processes has been recently reported; however, its role in stroke remains to be discovered. Post-stroke neuroinflammation involves the central nervous system (CNS)’s resident microglia activation and the infiltration of leukocytes from circulation into the brain. Additionally, splenic responses have been shown to be detrimental to stroke recovery. While lymphocytes enter the brain in small numbers, they regularly emerge as a very influential leukocyte subset that causes secondary inflammatory cerebral damage. However, an understanding of how this limited lymphocyte presence profoundly impacts stroke outcomes remains largely unclear. In this study, a mouse model for transient middle cerebral artery occlusion (tMCAO) was used to mimic ischemia followed by a reperfusion (IS/R) stroke. GPR55 inactivation, with a potent GPR55-specific antagonist, ML-193, starting 6 h after tMCAO or the absence of the GPR55 in mice (GPR55 knock out (GPR55ko)) resulted in a reduced infarction volume, improved neurological outcomes, and decreased splenic responses. The inhibition of GPR55 with ML-193 diminished CD4+T-cell spleen egress and attenuated CD4+T-cell brain infiltration. Additionally, ML-193 treatment resulted in an augmented number of regulatory T cells (Tregs) in the brain post-tMCAO. Our report offers documentation and the functional evaluation of GPR55 in the brain–spleen axis and lays the foundation for refining therapeutics for patients after ischemic attacks.
Jenis-Jenis Belajar Matematika

Belajar adalah sebuah proses mental dari seseorang yang melakukannya. Ini berarti mendeteksi orang belajar atau tidak, bukanlah hal yang mudah. Dua orang sedang membaca buku yang sama secara bersamaan tidak dapat divonis bahwa mereka melakukan kegiatan belajar. Boleh jadi keduanya belajar, salah satunya atau mungkin dari keduanya tak ada yang belajar. Sebelum dijelaskan pengertian belajar matematika maka terlebih dahulu dikemukakan tentang karakteristik matematika. Terdapat enam karakteristik matematika yaitu: obyek kajiannya bersifat abstrak, memilikii simbol yang kosong dari arti, konsisten dalam sistemnya, dibatasi oleh semesta pembicaraan, berpola pikir deduktif, dan bertumpu pada kesepakatan. Selain itu salah satu ciri khas dari matematika adalah memiliki sifat hirarkis. Mengenal karakteristik dan sifat dari matematika akan lebih memudahkan untuk mempelajari matematika.
Integrating Natural Resource Indicators into Procedural Visualisation for Sustainable Urban Green Space Design

Environmental aspects are often not properly integrated or even neglected in urban development planning, which can have rather long-term negative social and economical impacts (GRET-REGAMEY ET AL., 2008). For a more sustainable urban design, planners and decision-makers need to identify and understand the relationships between the natural and the built environment enhancing urban qualities. Further, methods need to be developed, which integrate this information into the urban design process (NASSAUER & OPDAM, 2008). Finally, comprehensive visualizations of the interrelationships between natural resource indicators and societal demanded values and the respectively resulting urban structure are needed for an effective analysis and evaluation by the relevant stakeholders (LANGE & HEHL-LANGE, 2006; OPDAM ET AL., 2002; TERMORSHUIZEN & OPDAM, 2009), which calls for the development of a new approach integrating indicators into visualisation tools (ANDRIENKO ET AL., 2007; WISSEN ET AL., 2008).