bluuebunny/crossref_metadata_2025_split huggingface dataset:
Octopus arm ‘slap’ in situ: A syntactic analysis of a complex motor action
Authors: Alupay Jean , Mather Jennifer , Iskarous Khalil 
Published: February 2023

Abstract
An octopus, Abdopus sp., can use rotation and translation of its hydrostatic arms, and combine these kinematic behaviors serially and in parallel, on different arms, to ‘slap’ at fish in the wild. Different motor programs may be used in multiple arms producing complex actions. The movements analyzed in this work show how complex the movements of the octopus, in situ, can be, furthering knowledge of this animal’s behavior, as well as furthering understanding of the structure of animal motor control. Stiffening of the flexible muscular hydrostatic arms was found to be important to both primitives of translation and rotation. By combining these kinematic primitives, the octopus is able to maintain flexibility while controlling only a few factors, or degrees of freedom, a concept we term ‘flexible rigidity’. The slapping action of the octopus of interest, Abdopus sp., therefore, gives support for Flash and Hochner’s embodied organization view of motor behavior, as well as their idea that motor primitives can combine syntactically to form a complex action. Our results suggest that the octopus’s ability to use sensory feedback from the position of a moving fish target, along with the feed-forward motor primitives, allows for the building of complex actions at dynamic equilibrium with the environment. Overall, these findings lead to a more realistic view of how a complex behavior allows an animal to coordinate with its environment.
Unsupervised machine learning and image recognition model application in English part-of-speech feature learning Under the open platform environment
Authors: Yang Liu 
Published: February 2023

Abstract
The traditional English part-of-speech analysis model fails to meet people’s actual needs due to the fact that the accuracy and other parameters are not up to standard. Facing large-scale English text data, quickly and accurately obtaining the key information needed and improv-ing the efficiency and accuracy of clustering have always been the focus of attention. However, the inherent characteristics of English text make it impossible to accurately calculate the traditional feature weight calculation method, and it’s part of speech is difficult to recognize. Moreover, in order to obtain a structure closer to the real data, this paper fuses the norm graph and the k-nearest neighbor graph, proposes a new composition framework, and combines it with two common propagation algorithms to complete the classification task. In addition, in order to obtain the improvement effect of the algorithm, the algorithm is tested on the English text classification corpus data set of the natural language processing open platform, and a control experiment is set to analyze the model performance. Finally, this article combines mathematical statistics to process data and draw corresponding charts.
Research on campus network security protection system framework based on cloud data and intrusion detection algorithm
Authors: Shaorong Wang , Guiling Long 
Published: February 2023

Abstract

The continuous progress of society has created conditions for the widespread use of information technology. People rely more and more on information technology and the Internet. People can use the Internet to retrieve relevant information to meet their work needs, but the widespread use of the Internet is also accompanied by network security issues. The existence of network security problems will affect people's work to varying degrees. Network security management departments use intrusion detection technology and set firewalls to improve the security of people's personal information on the Internet, prevent viruses and some criminals from stealing people's important information through the Internet, causing adverse effects on the Internet environment. In the daily management of the school, the extensive use of the campus network can not only facilitate students' daily study and life, but also improve the efficiency of school management. Ensuring the network security of campus network is an important work to ensure the campus management and students' study and life. The four parts of network security work include setting firewall, encrypting cloud data, using intrusion detection technology, and recovering data. Intrusion detection technology is extremely important for the development of network security work, which can help people actively find vulnerabilities in networks and systems, identify possible behaviors that may invade systems and networks, and give early warning or automatically close intrusion channels. There are various types of cloud data, so cloud database plays an extremely important role in the development of various fields. This paper uses intrusion detection algorithms to design the campus network security protection system, which provides security for the use of the campus network.
Brain Tumor Type Identification from MR Images using Texture Features and Machine Learning Techniques
Authors: Dewan Jaya , Thepade Sudeep , Deshmukh Pradnya , Deshmukh Sharvari , Katpale Pooja , Gandole Kartik 
Published: February 2023

Abstract
The detection of brain tumors using Magnetic Resonance Images(MRI) is difficult for contemporary medical imaging research. Basically, a brain tumor is an expansion of aberrant brain cells that expand erratically and seemingly uncontrolled. Meningioma, Glioma, and Pituitary are the three kinds of tumors that are most frequently seen. Early identification is essential for the successful treatment of brain tumors. With the development of medical imaging, doctors now employ a variety of imaging methods, such as fMRI, EEG, etc., to diagnose brain tumors. These imaging methods can help clinicians establish a precise diagnosis and create a treatment strategy by providing details on the location, size, and shape of brain tumors. Feature extraction and classification are two steps in the categorization of brain tumors. Two traditional manual feature extraction methods were frequently utilized in certain earlier research to extract details like the intensity and texture of images of brain tumors. This work employs the 'GLCM(Grey Level Co-occurrence Matrix)' approach for feature extraction. The generated feature set is provided to machine learning(ML) algorithms, including 'K-Nearest Neighbours(KNN), Support Vector Machine(SVM), Decision Tree(DT), Naive Bayes(NB), Logistic Regression(LR), Naive Bayes(NB), and Random Forest(RF)'. According to experimental results, random forest yields a maximum accuracy of 91.04%. The proposed methodology helps to classify the different brain tumor classes like glioma, meningioma, pituitary, or else no tumor.
Simple Preparation of bagasse pith cellulose nanofibers and precise controlling their morphology
Authors: Zhou Yan , Qiao Yu , Guan Qingqing , Zhou Huajing , He Liang 
Published: February 2023

Abstract
As one of the main by-products of the sugar industry, bagasse is widely used in pulp and paper industry because of its rich cellulose and a small amount of lignin. However, in addition to fiber cells, bagasse also contains about 30% soft, short pulp. And high silicon content in sugarcane pith will cause difficulty in black liquor recovery. Therefore, in the process of pulping and papermaking, pulp is often removed first. Obviously, this measure violates the principle of making full use of biomass resources. Under the premise of ensuring the efficient use of resources, the study of new technologies that are more environmentally friendly is an important measure to achieve the efficient use of sugarcane pulp waste. It is also highly consistent with the National Development and Reform Commission’s “14th Five-Year Plan” circular economy development plan on the “high-value utilization of agricultural and forestry biomass resources.” Based on this, this paper mainly studied the preparation of nanocellulose by low-temperature ethanol-oxygen-alkali technology of sugarcane pulp, and flexibly regulated the morphology of nanocellulose by changing the ratio of alcohol to water. The semi-liquefaction process behavior was analyzed from solid-liquid ratio, alkali pre-extraction and alcohol-water ratio. The physicochemical properties of nanocellulose and residue were analyzed by SEM, XRD and FTIR to capture the process of cellulose depolymerization. The results show that when the solid-liquid ratio is 1:8 and the alkali concentration is 60 g/L, the semi-liquefaction process of ethanol-oxygen-alkali system and the alkali pre-extraction effect are the best. The results of FTIR spectroscopy showed that with the increase of ethanol concentration, the structure of semi-liquefied solid was effectively destroyed, resulting in the degradation of lignin macromolecules and the significant increase of cellulose content. XRD analysis showed that the highest crystallinity of semi-liquefied solid was 68.75%. In addition, with the increase of ethanol concentration, the structure of the fibers gradually formed a uniformly distributed block structure. After the ultrasonic pretreatment process, the irregular aggregate fibers and block fibers were subjected to strong impact force to form granular fibers. After alkali extraction pretreatment, cellulose completed the transformation from irregular and large aggregates to small and uniformly distributed granular nanocellulose. In this paper, for the first time, the morphology of nanocellulose into flower-like, rod-like, spherical and ultrafine particles was simply and controllable regulated by ethanol-mediated method. By capturing the fibers with different morphologies in the process of cellulose depolymerization, the mechanism of preparing nanofibers from bagasse pith cellulose was inferred to achieve precise regulation of the morphology of cellulose nanofibers.
TRIM21 mediates the synergistic effect of Olaparib and Sorafenib by degrading BRCA1 through ubiquitination in TNBC
Authors: Xin Hong , Huang Ning , Sun Xiaolin , Tong Li , Li Peng , Dong Xinyi , Zhang Xuemei , Duan Jifeng , Sheng Xia 
Published: February 2023

Abstract
Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive breast cancer with a poor prognosis and a high recurrence rate. Although Olaparib, a poly (ADP-ribose) polymerase (PARP) enzyme inhibitor, was approved for germline BRCA-mutated metastatic breast cancer, chemotherapy remains the mainstay of treatment for cancer patients without BRCA mutation. Tripartite motif containing-21 (TRIM21) is one of the TRIM family members that has been implicated in various types of cancer. This study aimed to investigate the prognostic function of TRIM21. It was found that a low TRIM21 expression level was correlated with a poorer overall survival of TNBC patients. TRIM21 depletion promoted the proliferation of TNBC cells in vivo and in vitro, as well as migratory and invasive capabilities in vitro. Importantly, breast cancer susceptibility gene 1 (BRCA1) was identified as a ubiquitination substrate of TRIM21. It was confirmed that BRCA1 was upregulated after Olaparib treatment, which could explain the relative resistance of TNBC cells without BRCA1 mutation to Olaparib. Moreover, Sorafenib, a standard treatment for hepatocellular carcinoma, increased the sensitivity of TNBC cells to Olaparib through TRIM21-mediated ubiquitination degradation of BRCA1. Thus, a synergic effect of Olaparib and Sorafenib was found in vitroand in vivo. The combined treatment also aggravated DNA damage, cell cycle arrest, and apoptosis of TNBC cells. In summary, the findings verified the synergistic effect of Olaparib and Sorafenib and revealed TRIM21 as a potential target for TNBC therapy.
Surface Grafting of a Zwitterionic Copolymer onto a Cellulose Nanofiber Membrane for Oil/Water Separation
Authors: Son Dongwan , Kim Seungjun , Kim Jinhyeong , Ryu Sujin , Kim Myungwoong , Lee Hoik 
Published: February 2023

Abstract
Numerous oil/water mixtures are produced by industrial processes and residential activity, leading to the need for effective separation technologies for wastewater treatment and environmental remediation. In the present study, we report a cellulose-based nanofiber membrane with exceptional hydrophilicity and oleophobicity that rejects organic solvents and allows the penetration of water, thus avoiding fouling by organic residues, which has been a serious issue for conventional oil/water separation membranes. The cellulose-based nanofiber membrane was fabricated using the electrospinning of cellulose acetate and subsequent deacetylation. The resulting surface hydroxyl groups were utilized to bind with the zwitterionic copolymer poly(sulfobetaine methacrylate-r-glycidyl methacrylate) via a ring-opening reaction with the epoxy groups in the copolymer. The resulting copolymer-grafted cellulose nanofiber membrane allowed the highly selective penetration of the water phase from three different oil/water mixtures. The average filtration efficiency was higher than 98% with outstanding recyclability over at least 20 cycles following decontamination by washing the membrane with water. The proposed material platform expands the potential use of cellulose materials to a wide range of applications, including antifouling, wastewater treatment, oil purification, and the coating of medical devices.
Global Evidence on the Economic Effects of Disease Suppression During COVID-19
Authors: Rothwell Jonathan , Cojocaru Alexandru , Kim Yeon Soo , Sriniva Rajesh 
Published: February 2023

Abstract

Governments around the world attempted to suppress the spread of COVID-19 using restrictions on social and economic activity. This study presents the first global analysis of the welfare impacts of those policies, using Gallup World Poll data from 321,000 randomly selected adults in 117 countries. Using several measures of economic harm, impacted individuals experience a loss in subjective-well-being and are more likely to have low socio-economic status. A one-standard deviation increase in policy stringency predicts a 0.28 standard deviation increase in economic harm, corresponding to a three-percentage point increase in the share of workers experiencing job loss. These results are supported by robustness checks and validation exercises. A decomposition shows that stay-at-home orders and other economic restrictions were strongly associated with economic harm, but other non-pharmaceutical interventions were not. Furthermore, we show that adults with lower socio-economic status were disproportionately harmed in countries with more stringent policies.
Probabilistic Qualitative Localization and Mapping
Authors: Mor Roee , Indelman Vadim 
Published: February 2023

Abstract

Simultaneous localization and mapping (SLAM) are essential in numerous robotics applications, such as autonomous navigation. Traditional SLAM approaches infer the metric state of the robot along with a metric mapof the environment. While existing algorithms exhibit good results, they are still sensitive to measurement noise,sensor quality, and data association and are still computationally expensive. Alternatively, some navigation andmapping missions can be achieved using only qualitative geometric information, an approach known as qualitativespatial reasoning (QSR). We contribute a novel probabilistic qualitative localization and mapping approach in thiswork. We infer both the qualitative map and the qualitative state of the camera poses (localization). For the firsttime, we also incorporate qualitative probabilistic constraints between camera poses (motion model), improvingcomputation time and performance. Furthermore, we take advantage of qualitative inference properties to achievevery fast approximated algorithms with good performance. In addition, we show how to propagate probabilisticinformation between nodes in the qualitative map, which improves estimation performance and enables inferenceof unseen map nodes - an important building block for qualitative active planning. We also conduct a study thatshows how well we can estimate unseen nodes. Our method particularly appeals to scenarios with few salientlandmarks and low-quality sensors. We evaluate our approach in simulation and on a real-world dataset and showits superior performance and low complexity compared to the state-of-the-art. Our analysis also indicates goodprospects for using qualitative navigation and planning in real-world scenarios.
Double counting of clients using services in Iran: implications for assessing the reach of harm reduction programs
Authors: Tavakoli Fatemeh , Mcfarland Willi , Ghalekhani Nima , Khezri Mehrdad , Haghdoost Ali Akbar , Gouya Mohammad Mehdi , Mahboobi Marzieh , Hosseionpour Ali Mohammad , Komasi Ali , Ghorbanian Mehdi , Moghadam Nasim Nasiri , Taghipour Maryam , Sharifi Hamid 
Published: February 2023

Abstract
Background: Many people with high-risk sexual or injection behaviors use harm reduction services with different identities and therefore counted more than once in client databases. This practice results in inaccurate statistics on the number of clients served and therefore the effective reach of these services. This study aimed to determine the levels of double counting of clients of harm reduction services, including needle and syringe programs, condom distribution, HIV testing and counseling, and methadone maintenance in five cities in Iran.
Methods: Between September and March 2020, our study included 1,630 clients, 115 staff of harm reduction centers, and 30 experts in the field of harm reduction in five cities in Iran. Clients of harm reduction services were asked about using harm reduction services multiple times at the same center or at different centers in the last year under different identities. Estimates of double counting derived from client responses were validated by panels of center staff and experts in harm reduction.
Results: Synthesizing data from clients, staff, and experts, the final estimates of double counting of clients using harm reduction services were: HIV testing 10% (95% confidence interval [CI] 0-15), needle and syringe programs 17% (95% CI 8.5-20), condom distribution programs 13% (95% CI 3-19), HIV/STI counseling 10% (95% CI 0-16), and methadone maintenance 7% (95% CI 2-10).
Conclusion: Double counting of clients in harm reduction services in Iran is considerable. Data on clients reach by harm reduction services need to be corrected for double counting to improve program planning, client population size estimation, and efficient resource allocation.
Failure analysis and prediction of roof instability in end face under repeated mining using early warning system
Authors: Li Fei , Kong Dezhong , Li Qiang , Shang Yuqi , Cheng Zhanbo , He Liuquan 
Published: February 2023

Abstract
The overlying strata of the lower coal seam is easy to be collapsed causing the roof caving accident at the end face of the mining working face under repeated mining in close-distance coal seams. In order to predict the roof instability of the end face, the mechanical model of the granular arch structure is established in this study to further analyze its main influencing factors. The results show that the mining height of the working face, the advancing speed, the distance of coal seams, the tip-to-face distance, the strength of the surrounding rock and the support setting the load of the support are the main influencing factors on the roof caving of the end face. Subsequently, the prediction model of roof instability in the end face under repeated mining is constructed through the radial basis function neural network (RBFNN) and the above main influencing factors are regarded as input layer indexes. Meanwhile, the roof subsidence, coal wall deformation and support load are determined as the output layer indexes. The predicted results are closer to the results of sample tests. Finally, the early warning system, including monitoring and early warning, data query, emergency management, user management, and system settings, is designed to monitor roof conditions of the end face and timely warn the roof accidents. The field application proves that the system has good practical value, which is of great significance to prevent the end face roof disaster under repeated mining.
Management and outcomes of periviable neonates born at 22 weeks of gestation: a single-center experience in Japan
Authors: Motojima Yukiko , Nishimura Eri , Kabe Kazuhiko , Namba Fumihiko 
Published: February 2023

Abstract
OBJECTIVE: We aimed to present the active management and outcomes of infants born at 22 weeks of gestation.
STUDY DESIGN: This retrospective observational study presented the resuscitation methods, management during hospitalization, and outcomes of 29 infants born at 22 weeks of gestation who were actively resuscitated and admitted to our center during 2013–2020.
RESULTS: The survival rate was 82.8% (24/29). Tracheal intubation was performed in all patients, and surfactant was given for 27 (93.1%). Conventional mechanical ventilation was introduced in 27 (93.1%), and this was changed to high-frequency oscillatory ventilation in more than half by day 4. Surgical treatments of patent ductus arteriosus, necrotizing enterocolitis, and retinopathy of prematurity were required in 4 (13.7%), 3 (10.3%), and 15 (51.7%), respectively. No patient required a tracheostomy or ventriculoperitoneal shunt.
CONCLUSIONS:Among infants born at 22 weeks of gestation, the overall survival rate and survival rate without morbidities were relatively high.
Early LGM environments accelerated the MSA/LSA transition in southern African highlands: the Robberg’s emergence at Melikane (Lesotho)
Authors: Pazan Kyra , Stewart Brian A. , Dewar Genevieve 
Published: February 2023

Abstract
Melikane, a large sandstone rockshelter in the Maloti-Drakensberg Mountains of highland Lesotho, preserves an 80,000 year-old archaeological sequence including two layers (4 & 5) dated to the onset of the Last Glacial Maximum (LGM), ~ 24 kcal BP. Paleoenvironmental proxies indicate that these layers were associated with increasing aridification and changes in resource distribution. An analysis of > 17,000 lithic artifacts combining attribute and morphometric approaches reveals that these environmental changes occurred alongside the adoption of Later Stone Age (LSA) Robberg bladelet technology at the site (Layer 4), which developed out of an early microlithic industry we classify as “incipient Robberg” (Layer 5). We argue that the accelerated implementation and standardization of bladelet technology in Layer 4 was the consequence of modifying and expanding existing technologies to function in a high-stakes LGM environment. While intrasite continuities and gradual changes in flaking systems at Melikane are inconsistent with the Robberg’s arrival via population replacement or migration (cf. Bousman and Brink, 2018), shared flaking systems with penecontemporary sites also implicate a role for cultural transmission in the Robberg’s development and demand an alternate explanation for its use in nonmarginal environments. We attribute its adoption in southern Africa more broadly to the extraordinary flexibility of bladelet technology and an ongoing cycle of connectivity and isolation throughout the LGM, encouraging the development of new flaking systems and their subsequent coalescence and diffusion.