bluuebunny/crossref_metadata_2025 huggingface dataset:
On the alleged explanatory impotence/conceptual vacuity of substance dualism
Authors: Moreland James
Published: April 2023

In the last decade, there has been a notable upsurge in property (PD) and generic substance dualism (SD). By SD I mean the view that there is a spiritual substantial soul that is different from but variously related to its body. SD includes Cartesian, certain forms of late Medieval hylomorphic (e.g., Aquinas'), and Haskerian emergent SD. Nevertheless, some form of physicalism remains the majority view in philosophy of mind. Several fairly standard objections have been raised against SD, and SDists have been preoccupied with these objections. As a result, a potent objection has not been given the attention it deserves. The purpose of this article is to fill that lacuna by raising the visibility of this objection and providing plausible responses to it. First, I shall clarify the explanatory–impotence challenge and, second, provide defeaters against it. Note that several of the issues to follow apply both to PD and SD. I will focus mostly on SD, but sometimes PD is a part of the discussion in that certain arguments for and against PD indirectly affect SD. When it is important for me to note that either SD or PD is specifically being addressed, I will notify the reader.
Assessing the potential of restoration measures and management techniques in a post‐pastured Azorean peatland: two years tendencies
Authors: Mendes Cândida , Dias Eduardo , Rochefort Line
Published: April 2023

During more than five centuries of human colonization, 50% of original peatlands in Azores have been destroyed or degraded, mainly due to pasture use, resulting in landscape changes and a loss of ecosystem biodiversity and services. This study aims to identify the most effective measures in the recovery and to detect initial responses (2 years). These are the first restoration experiments, carried out in a background of complete absence of strategies adapted for Azores pastured peatlands. In a post‐pastured peatland, 24 experiments were implemented, repeated in more degraded (northern) and more natural (southern) areas. The experiments were combinations of restoration measures, with the introduction ofJuniperus brevifolia,Calluna vulgaris, andSphagnum palustreand the use of management techniques to control herbaceous cover (alien‐rich herbaceous cover competing withSphagnumor peatland natural shrubs): intensive and extensive grazing and grass cutting. Principal response curves and redundancy analyses were used to assess changes in the flora and the physicochemical parameters. Globally there was an increase inSphagnumcover and a decrease in herbaceous species. This was accompanied by an increase in organic matter and a decrease in nitrogen. In more natural parcels (large artificially divided areas where different experiments were implemented), the most positive tendencies were associated with the combination ofJ. brevifoliaplanting and grass cutting. In more degraded areas, treatments had a lower impact, as the results tended to be similar to the control, pointing to an important natural regenerative succession dynamic that overlapped the response to the implemented treatments.
Incorporating learning into direct policy search for flood risk management
Authors: Wang Jingya , Johnson David R.
Published: April 2023

Direct policy search (DPS) is a method for identifying optimal policies (i.e., rules) for managing a system in response to changing conditions. In this article, we introduce a new adaptive way to incorporate learning into DPS. The standard DPS approach identifies “robust” policies by optimizing their average performance over a large ensemble of future states of the world (SOW). Our approach exploits information gained over time, updating prior beliefs about the kind of SOW being experienced. We first run the standard DPS approach multiple times, but with varying sets of weights applied to the SOWs when calculating average performance. Adaptive “metapolicies” then further improve performance by specifying how control of the system should switch between policies identified using different weight sets, depending on our updated beliefs about the relative likelihood of being in certain SOWs. We outline the general method and illustrate it using a case study of efficient dike heightening that simultaneously minimizes protection system costs and flood damage resulting from rising sea levels and storm surge. The solutions identified by our adaptive algorithm dominate the standard DPS on these two objectives, with an average marginal damage reduction of 35.1% for policies with similar costs; improvements are largest in SOWs with relatively lower sea level rise. We also evaluate how performance varies under different ways of implementing the algorithm, such as changing the frequency with which beliefs are updated.
Problems experienced when swallowing solid oral dosage forms in older Japanese patients with dysphagia: A cross‐sectional study
Authors: Tanaka Kumi , Kikutani Takeshi , Tamura Fumiyo , Sato Shiho , Komagata Yuka , Shibasaki Ikumi , Tomioka Kosei , Ichikawa Yoko , Shiobara Yuichiro , Sato Takanobu , Tohara Takashi
Published: April 2023

Aims

We aimed to assess the difficulty in taking solid oral dosage forms (SODFs) among older people with dysphagia and clarify the relationship between difficulty in swallowing SODFs and swallowing function.

Methods and results

Outpatients from a dysphagia clinic aged ≥65 years were asked yes‐or‐no questions about the applicability of eight items regarding difficulty in taking SODFs. Additionally, a videofluorographic swallowing study (VFSS) was performed to assess their swallowing function. The Kruskal–Wallis test and Spearman's rank correlation coefficient were used to analyze the relationship between difficulty in taking SODFs and swallowing function.

Results

Among the 93 participants, the average number of SODFs consumed was 5.8 ± 3.1. In the questionnaire, the average number of “yes” answers was 2.2 ± 2.2, and 65 patients (71.0%) answered “yes” to at least one question. Additionally, no significant relationship was observed between the perceived difficulty in swallowing SODFs and VFSS findings.

Conclusion

Approximately 70% of participants reported subjective difficulty in taking SODFs, showing that patients uniformly reported perceived difficulty in taking SODFs regardless of actual swallowing function. The results of this study suggest that patients must be questioned thoroughly about their SODFs use, regardless of the objective severity of their dysphagia.
Bilateral palpebral reduction and concurrent mycoplasmosis in a wild Agassiz's desert tortoise (Gopherus agassizii)
Authors: Jacobson Elliott R. , Berry Kristin H. , Brooks Dennis E. , Roberts John F.
Published: April 2023

A wild Agassiz's desert tortoise, Gopherus agassizii, with bilateral eyelid reduction and plaques of tissue covering the superior surface of both corneas was examined in the field and subsequently submitted to the University of Florida for diagnostics. Polymerase chain reaction (PCR), from a swab of both corneas, was positive for Mycoplasma agassizii. Two months later, the tortoise was euthanatized and necropsied. There was increased bulbar exposure associated with dermal excoriation of periocular scales in both superior and inferior palpebra resulting in an increased palpebral fissure opening. Concurrently, there was bilateral conjunctivitis of the nictitating membranes and squamous metaplasia of the bulbar conjunctiva. Using PCR, Mycoplasma testudineum, another pathogen of tortoises, was identified in both nasal cavities, and the upper respiratory tract histopathological findings were consistent with those described for M. testudineum in Agassiz's desert tortoises. Although eye disease has been reported in desert and gopher (Gopherus polyphemus) tortoises with mycoplasmosis, widespread loss of palpebral tissue, conjunctivitis of the nictitans, and squamous metaplasia of the bulbar conjunctiva have not been reported in tortoises.
Well‐being in acute care nurse managers: A risk analysis of physical and mental health factors
Authors: Martin Shirley D. , Urban Regina W. , Foglia Dorothy C. , Henson Jo Sheree , George Viji , McCaslin Tricia
Published: April 2023

Background

Nurse managers have experienced tremendous stress during the COVID‐19 pandemic, contributing to negative psychological outcomes. Positive professional well‐being is a construct that can be promoted to mitigate poor psychological outcomes and burnout in nurses. Little is known about the health, healthy behaviors, effects of stress on homelife, and well‐being of nurse managers in the United States (U.S.).

Aims

The aims of the study were to explore nurse managers’ well‐being related to self‐reported stress and health perceptions and habits.

Methods

A sample of 80 (41% response rate) nurse managers responded to a cross‐sectional web‐based survey sent via email in a southwestern U.S. 13‐hospital system. Nurses answered 39 quantitative questions about demographics, well‐being (9‐item Well‐Being Index [WBI]), perceptions of stress affecting homelife, and perceptions of health and health‐related behaviors.

Results

Mean WBI (2.9 [2.7]) indicated risk for poor psychological outcomes. Managers (75%) reported stress from work affected their personal lives and a decline in overall health during the pandemic. Most (80%) reported burnout and emotional problems. Nurse managers had 8.1 times increased risk of poor WBI scores if stress from work affected their personal life than if they reported no spillover stress into their personal life (OR = 8.1, 95% CI [2.6, 25.0]).

Linking Evidence to Action

Findings from this study add a nuanced understanding of nurse managers’ well‐being. The strongest risk factor for poor WBI scores was stress levels affecting personal life. Interventions to improve well‐being in nurse managers are needed. Limitations are the convenience sampling, limited geographic location, and response rate of <50%. Further research is needed to support nurse managers in stress reduction and development of boundaries that prohibit the spillover effect of workplace stress. Organizations may consider a combination of administrative support and changes as well as provision of on‐the‐job training of interventions that support individual well‐being.
Sensorimotor control in the congenital absence of functional muscle spindles
Authors: Macefield Vaughan G. , Smith Lyndon J. , Norcliffe‐Kaufmann Lucy , Palma Jose‐Alberto , Kaufmann Horacio
Published: April 2023

Hereditary sensory and autonomic neuropathy type III (HSAN III), also known as familial dysautonomia or Riley–Day syndrome, results from an autosomal recessive genetic mutation that causes a selective loss of specific sensory neurones, leading to greatly elevated pain and temperature thresholds, poor proprioception, marked ataxia and disturbances in blood pressure control. Stretch reflexes are absent throughout the body, which can be explained by the absence of functional muscle spindle afferents – assessed by intraneural microelectrodes inserted into peripheral nerves in the upper and lower limbs. This also explains the greatly compromised proprioception at the knee joint, as assessed by passive joint‐angle matching. Moreover, there is a tight correlation between loss of proprioceptive acuity at the knee and the severity of gait impairment. Surprisingly, proprioception is normal at the elbow, suggesting that participants are relying more on sensory cues from the overlying skin; microelectrode recordings have shown that myelinated tactile afferents in the upper and lower limbs appear to be normal. Nevertheless, the lack of muscle spindles does affect sensorimotor control in the upper limb: in addition to poor performance in the finger‐to‐nose test, manual performance in the Purdue pegboard task is much worse than in age‐matched healthy controls. Unlike those rare individuals with large‐fibre sensory neuropathy, in which both muscle spindle and cutaneous afferents are absent, those with HSAN III present as a means of assessing sensorimotor control following the selective loss of muscle spindle afferents.
Beyond an inflammatory mediator: Interleukin‐1 in neurophysiology
Authors: Lima Tatiane S.
Published: April 2023

Since its discovery in the early 1940s, the interleukin‐1 (IL‐1) cytokine family has been associated primarily with acute and chronic inflammation. The family member IL‐1β is produced by different leucocytes, endothelial cells and epithelial cells. This cytokine has been characterized as a key modulator of inflammation and innate immunity because it induces the transcription of several downstream inflammatory genes. More recently, several groups have demonstrated that IL‐1β production is also required to maintain homeostasis in several organ systems. This review focuses on providing an overview of the more recently characterized role of IL‐1β in the physiology of the CNS. So far, IL‐1β signalling has been implicated in neuronal survival, neurite growth, synaptic pruning, synaptic transmission, neuroplasticity and neuroendocrine functions.
A Novel Neural Machine Translation Approach for low-resource Sanskrit-Hindi Language pair
Authors: Sethi Nandini , Dev Amita , Bansal Poonam
Published: April 2023

Sanskrit is one of the earliest native languages and is correctly described as "the gods' language" because of its wide use in Indian religious literature from the past. However, it is becoming less popular in modern India. Due in significant part to the need for more materials for translation both in and out of Sanskrit, it is no longer commonly utilized. This study explores the feasibility of using machine translation (MT) to provide a link between Sanskrit and, one of the earliest native languages, and its contemporary descendant Hindi. A study was conducted between existing modelling methodologies, notably Statistical machine translation (SMT), and the proposed novel deep learning-based Machine translation strategy using a manually created parallel corpus for the Sanskrit-Hindi language pair. While SMT creates interpretations by mapping phrases from the languages of the source and destination, statistical models, and bilingual text corpora for learning parameters, neural machine translation (NMT) frequently models entire phrases in a single integrated model, using a convolutional neural network to calculate the probability of a word sequence. The proposed NMT model is implemented using an encoder-decoder with an attention mechanism paradigm and the inclusion of gated recurrent units. Our approach involved development of a novel model for Sanskrit-Hindi machine translation using deep learning and the creation of parallel corpora for the Sanskrit-Hindi language pair. The proposed model is evaluated on automated and human-based metrics, and results show that our proposed deep learning-based model outperforms statistical modelling techniques on Moses, surpassing them both with a BLEU score of 53.8% compared to 34.56%. This article examines the undiscovered area of machine translation from Sanskrit to Hindi and discusses the main benefits and drawbacks of statistical and neural machine translation while providing a fresh viewpoint on the subject.
The Influence of Chinese Characters on Chinese Sign Language
Authors: Ren Tianyu , Yao Dengfeng , Yang Chaoran , Kang Xinchen
Published: April 2023

Chinese Sign Language (CSL)
and Chinese are languages used in the Chinese mainland. As a dominant language, Chinese has great influence on all levels of CSL. CSL, as a visual sign language, is fundamentally different from Chinese in linguistic structure. Unlike English, Chinese, as a pictograph, has influence on Chinese and CSL. This study explains in detail the influence of Chinese characters on CSL at the lexical level, including many elements from Chinese, such as “仿字 fangzi” (form imitating Chinese characters), “书空 shukong” (writing in the air with the index finger), loan translation, finger spelling, and mouthing patterns. This influence is not a simple borrowing of Chinese characters, but a creative imitation and adaptation according to the needs of sign language to express meaning. After a long period of evolution, the characteristics of Chinese characters are naturally integrated into CSL loanwords, which makes the relationship between sign language and Chinese characters closer. CSL borrows a large number of Chinese words, most of which are signs to express non-core concepts. These borrowed signs are an indispensable part of the CSL sign language family, enrich sign language vocabulary, improve the accuracy of sign language expression, and play a positive role in promoting the learning, work, and lives of deaf people.
Computing Graph Descriptors on Edge Streams
Authors: Hassan Zohair Raza , Ali Sarwan , Khan Imdadullah , Shabbir Mudassir , Abbas Waseem
Published: April 2023

Feature extraction is an essential task in graph analytics. These feature vectors, called graph descriptors, are used in downstream vector-space-based graph analysis models. This idea has proved fruitful in the past, with spectral-based graph descriptors providing state-of-the-art classification accuracy. However, known algorithms to compute meaningful descriptors do not scale to large graphs since: (1) they require storing the entire graph in memory, and (2) the end-user has no control over the algorithm’s runtime. In this article, we present streaming algorithms to approximately compute three different graph descriptors capturing the essential structure of graphs. Operating on edge streams allows us to avoid storing the entire graph in memory, and controlling the sample size enables us to keep the runtime of our algorithms within desired bounds. We demonstrate the efficacy of the proposed descriptors by analyzing the approximation error and classification accuracy. Our scalable algorithms compute descriptors of graphs with millions of edges within minutes. Moreover, these descriptors yield predictive accuracy comparable to the state-of-the-art methods but can be computed using only 25% as much memory.
Mexican Sign Language Corpus: Towards an Automatic Translator
Authors: Trujillo-Romero Felipe , García-Bautista Gibran
Published: April 2023

The development of the Sign Language Corpus has been motivated by its great utility and application to various purposes and research areas. However, some countries do not have their own Sign Language Corpus. Developing a corpus thereby benefits the community of people with speech disabilities in diverse areas such as education. Thus, the motivation to develop this work is to present an advance toward constructing an RGB-D corpus of Mexican Sign Language captured by a Kinect sensor. A total of 90,000 samples of 570 words and 30 phrases interpreted by 150 people who commonly use Mexican Sign Language were collected. Of the participants, 86 were women and 64 were men, aged between 12 and 60 years old. The Mexican Sign Language Corpus was recorded by signers from three different regions of the south of Mexico. The constructed corpus contains depth, color, point clouds, and human skeleton positions. Six hundred of the most used words were selected from 17 semantic fields, considering the variability in the movement of both hands. After training a neural network, the performance developed by the recognition system was 98.62%.
A Derivative-based Parser Generator for Visibly Pushdown Grammars
Authors: Jia Xiaodong , Kumar Ashish , Tan Gang
Published: April 2023

In this article, we present a derivative-based, functional recognizer and parser generator for visibly pushdown grammars. The generated parser accepts ambiguous grammars and produces a parse forest containing all valid parse trees for an input string in linear time. Each parse tree in the forest can then be extracted also in linear time. Besides the parser generator, to allow more flexible forms of the visibly pushdown grammars, we also present a translator that converts a tagged CFG to a visibly pushdown grammar in a sound way, and the parse trees of the tagged CFG are further produced by running the semantic actions embedded in the parse trees of the translated visibly pushdown grammar. The performance of the parser is compared with popular parsing tools, including ANTLR, GNU Bison, and other popular hand-crafted parsers. The correctness and the time complexity of the core parsing algorithm are formally verified in the proof assistant Coq.
Smurf1 Facilitates Oxidative Stress and Fibrosis of Ligamentum Flavum by Promoting Nrf2 Ubiquitination and Degradation
Authors: Gu Yifei , Hu Jinquan , Wang Chen , Qi Min , Chen Yu , Yu Wenchao , Wang Zhanchao , Wang Xinwei , Yuan Wen
Published: April 2023

Lumbar spinal stenosis (LSS), which can lead to irreversible neurologic damage and functional disability, is characterized by hypertrophy and fibrosis in the ligamentum flavum (LF). However, the underlying mechanism is still unclear. In the current study, the effect of Smurf1, a kind of E3 ubiquitin ligase, in promoting the fibrosis and oxidative stress of LF was investigated, and its underlying mechanism was explored. The expression of oxidative stress and fibrosis-related markers was assessed in the tissue of lumbar spinal stenosis (LSS) and lumbar disc herniation (LDH). Next, the expression of the top 10 E3 ubiquitin ligases, obtained from Gene Expression Omnibus (GEO) dataset GSE113212, was assessed in LDH and LSS, and confirmed that Smurf1 expression was markedly upregulated in the LSS group. Furthermore, Smurf1 overexpression promotes the fibrosis and oxidative stress of LF cells. Subsequently, NRF2, an important transcription factor for oxidative stress and fibrosis, was predicted to be a target of Smurf1. Mechanistically, Smurf1 directly interacts with Nrf2 and accelerates Nrf2 ubiquitination and degradation. In conclusion, the current study suggests that Smurf1 facilitated the fibrosis and oxidative stress of LF and induced the development of LSS by promoting Nrf2 ubiquitination and degradation.
The Importance of Natural Indigo Dye and Its Revitalization and Ethiopian Potential for Indigo Growing
Authors: Kabish Abera Kechi , Abate Molla Tadesse , Alemar Zelalem Adane , Girmay Solomon
Published: April 2023

The recent increasing consciousness for environment sustainability and health hazards is the motive for looking for alternative environment-friendly materials and manufacturing processes. Therefore, environmental compatibility and safety to the health manufacturing process are a worldwide concern. The use of excessive and toxic synthetic dyes in textile and apparel manufacturing processes lineages environment pollution and health hazards to the surroundings where they are sited. Consequently, penetrating for alternative eco-friendly dyes has been initiated in recent times by researchers and development motivators in order to reduce the excessive use of synthetic dyes. In this regard, natural indigo dye from the indigo plant is getting attention, and thus, it is preferred as good as synthetic indigo dye, owing to its inherited dyeing property. With natural indigo dye, it can be achieved eco-friendly dyeing without the application of mordant attaining commercially acceptable fastness properties. Owing to the popularity of blue jeans around the world, especially those that are naturally dyed indigo blue, indigo dye consumption is now rising. Furthermore, currently, natural indigo dye is demanding for functional textile finishing, cosmetics and food colouration, UV protection and deodorizing agents, and other applications. In general, because of its increasing demand and wide applications, natural indigo has become an important cash crop and is traded in the international market with a price range of 35 to 40 USD per kilogram as per its purity level. Indigo dye has therefore been revived with more applications than it had before the advent of man-made colourants. The revival of indigo presents a chance for underdeveloped nations with incorporated economic and social benefits. Ethiopia as a developing country and situated in tropical Africa will benefit from indigo revival because of its potentials with having a suitable climate, a young workforce, enough land resource, and its booming textile and apparel industries.
3D Printing of Bone Substitutes Based on Vat Photopolymerization Processes: A Systematic Review
Authors: Enbergs Simon , Spinnen Jacob , Dehne Tilo , Sittinger Michael
Published: April 2023

Treatment options for critically sized bone defects are currently limited to metal osteosynthesis, autologous bone grafting, or calcium-based implants to bridge the gap. Additive manufacturing techniques pose a possible alternative. The light-basedthree-dimensional printing process of vat photopolymerization (VP) is of particular interest since it enables the printing of complex scaffold architectures at high resolution. This review compares multiple vat photopolymerization processes as well as the employed resin components’ interactions with musculoskeletal cells and tissue. The results show an outstanding printing capability, exceeding the potential of other printing methods. However, despite the availability of various biocompatible materials, neither the mechanical strength of bone nor the scale necessary for clinical application has been achieved so far when relying on single material constructs. One possible solution is the development of adaptive hybrid constructs produced with multimaterial VP.
A Physical Layer Key Generation Scheme Based on Deep Learning Compensation and Balanced Vector Quantization
Authors: Chen Liquan , Chen Zhaofa , Lu Tianyu , Hu Aiqun
Published: April 2023

Channel reciprocity is the foundation for physical layer key generation, which is influenced by noise, hardware impairments, and synchronization offsets. Weak channel reciprocity will result in a high key disagreement rate (KDR). The existing solutions for improving channel reciprocity cannot achieve satisfactory performance improvements. Furthermore, the existing quantization algorithms generally use one-dimensional channel features to quantize and generate secret keys, which cannot fully utilize channel information. The multidimensional vector quantization technique also needs to improve in terms of randomness and time complexity. This paper proposes a physical layer key generation scheme based on deep learning and balanced vector quantization. Specifically, we build a channel reciprocity compensation network (CRCNet) to learn the mapping relationship between Alice and Bob’s channel measurements. Alice compensates for channel measurements via a trained CRCNet to reduce channel measurement errors between legitimate users and enhance channel reciprocity. We also propose a balanced vector quantization algorithm based on integer linear programming (ILP-BVQ). ILP-BVQ reduces the time complexity of quantization on the basis of ensuring key randomness and a low KDR. Simulation results showed that the proposed CRCNet performs better in terms of channel reciprocity and KDR, while the proposed ILP-BVQ algorithm improves time consumption and key randomness.
ImageDroid: Using Deep Learning to Efficiently Detect Android Malware and Automatically Mark Malicious Features
Authors: Liu Pengfei , Wang Weiping , Zhang Shigeng , Song Hong
Published: April 2023

The popularity of the Android platform has led to an explosion in malware. The current research on Android malware mainly focuses on malware detection or malware family classification. These studies need to extract a large number of features, which consumes a lot of manpower and material resources. Moreover, some malware use obfuscation to evade decompiler tools extracting features. To address these problems, we propose ImageDroid, a method based on the image format of Android applications that can not only detect and classify malware without prior knowledge but also detect the obfuscated malware. Furthermore, we utilize the Grad-CAM interpretable mechanism of the deep learning model to automatically label the image that play a key role in determining maliciousness in a visual way. We evaluate ImageDroid over 10,000 Android applications. Experimental results show that the accuracy of malicious detection and multifamily classification achieve 97.2% and 95.1%, respectively, and the detection accuracy of obfuscated malware achieves 94.6%.
Degradation Status and Local Community Perception towards Kadar-Basaso Wetland in Sinana District of Bale Zone, South Eastern Ethiopia
Authors: Abdela Umer , Oumer Abdurazak , Ukule Abdulkedir
Published: April 2023

Wetlands are valuable resources that provide a variety of functions for local populations, including environmental, hydrological, and socioeconomic benefits. Despite the importance of wetlands to humanity, they have been largely degraded and even lost in many countries including Ethiopia because they are wrongly regarded as wastelands. Some wetland conservation policies were designed not based on the perceptions of the people residing around the wetlands and lack of attention to communal areas. It is because of this gap that a quantitative analysis of physicochemical soil quality analysis and the local community’s perceptions was carried out with the overall goal of analyzing the degradation status of Kadar-Basaso wetland and community perceptions. A cross-sectional research approach was used with a purposeful soil sampling from/in 6 plots sized 50 m × 50 m and >100 m apart along two transect lines, and 200 household heads chosen randomly from three villages(Basaso, Shallo, and Nano Robe) bordering the wetland. Soil sampling, questionnaires, focus group discussion, and key informant interviews were used to collect data and then examined quantitatively and qualitatively. The result shows that the Kadar-Basaso wetland was moderately degraded. The physicochemical analysis of the soil reveals that the pH was acidic, indicating the presence of acidic waste effluents. In addition, the electric conductivity was salt-free, cation exchange capacity were found to be low, the organic matter was relatively low, potassium levels vary very little, and Phosphorous variation was minimal. Expansion of farmland and Overgrazing were the most damaging elements affecting wetland biodiversity. From the analysis, it was noted that communities’ attitudes influence human activities on the wetland. The study recommends that the government and wetland management authorities must establish strategies to minimize deterioration in the area and offer better infrastructure for both livestock keepers and farmers to improve the long-term usage of wetlands. The best management strategies should be devised for all sizes, types, and all site wetlands.
Application Analysis of Intelligent Particle Swarm Algorithm in the Development of Modern Tourism Intelligence
Authors: Jin Huihui
Published: April 2023

Information technology has been increasingly vital in the rapid expansion of the tourism industry economy. The new information technology has become a significant driving force and factor in the tourism industry’s economic development. The application of new information technology to the advancement of modern tourist intelligence has emerged as an essential study area. Smart tourism, aided by informatization, can frequently provide more attractive economic benefits to tourism businesses. Tourism is being positioned as a new economic growth point and core business in an increasing number of cities. Various measures have been taken among the main body of the city to improve the tourism competitiveness of the city, so as to be in an advantageous position in the fierce market competition. Under this background, the research on urban tourism competitiveness has become a research hotspot in the development of modern tourism intelligence. This study used a combined PSO and neural network to assess the competitiveness of urban tourism. First, this paper offers a method that makes use of an improved IPSO. It changes the inertia weight dynamically and nonlinearly based on the particle fitness value. Simultaneously, the particle swarm technique is enhanced by combining the particle iterative cycle to boost position disturbance. Second, in order to build an IPSO-BP network, this work optimizes the initial weights and thresholds of the BP network based on IPSO. This work uses this network to evaluate the competitiveness of urban tourism, which can overcome the defects of traditional BP network. Third, this work conducts systematic experiments on the IPSO-BP method, and the experimental results confirm the superiority of this method in the evaluation of urban tourism competitiveness.
Lightweight Field Insect Recognition and Classification Model Based on Improved Deep Learning under Complex Background
Authors: Wu Feng , Li Yueying
Published: April 2023

Insect monitoring in the field is an extremely important part of the agricultural production system. Recent advances in computer technology have provided the technical foundation for automatic field insect monitoring. In insect automatic monitoring, insect recognition and classification based on images is one of the most active research areas. Rapid advancements in computer vision technology based on deep learning have provided new ideas for implementing automatic field insect monitoring. Firstly, the field insect images are preprocessed and input to the lightweight algorithm for feature extraction, and the prediction networks of different sizes are output by multiscale feature fusion; then, the joint cross-merge ratio is introduced for automatic identification and classification of field insects. Compared with other algorithms, the simulation results show that the proposed algorithm has higher accuracy, less time consumption, and stronger robustness. It effectively solves the insect accumulation and background interference problems and can identify field insects online in real time.
Thyrotoxicosis after COVID-19 Infection with a Delay in Graves’ Disease Antibody Positivity
Authors: Boyle Dennis C. , Mullally Jamie A.
Published: April 2023

Background and Objective. Mounting evidence implicates COVID-19 as a cause of thyroid dysfunction, including thyrotoxicosis due to both thyroiditis and Graves’ disease (GD). In this report, we present a case of thyrotoxicosis following COVID-19 infection that was ultimately found to represent GD with significantly delayed diagnostic serum antibody positivity. Case Report. A 65-year-old woman with a history of uncomplicated COVID-19 infection one month prior, presented to the Emergency Department with exertional dyspnea and palpitations, and was found to be in atrial fibrillation with rapid ventricular response (AF with RVR). Labs showed subclinical hyperthyroidism and the patient was started on a beta-blocker and methimazole. One month later, thyroid-stimulating immunoglobulin (TSI) resulted negative and thyroid function tests had normalized. The clinical picture suggested thyroiditis, and methimazole was stopped. One month later, the patient again presented in AF with RVR, with labs showing overt biochemical thyrotoxicosis. Antibodies were re-tested, and the thyrotropin receptor antibody (TRAb) and TSI resulted positive, confirming GD. Discussion. Most notable in this case is the feature of delayed GD antibody positivity: the diagnostic immunoassay for GD resulted negative one and two months after infection, but was ultimately positive three months after infection. To the authors’ knowledge, this represents the longest delayed antibody positivity reported to date, amongst cases of new-onset GD following COVID. Conclusion. The clinical course of GD following COVID-19 infection is highly variable. This case underscores the need for vigilance in monitoring for delayed GD antibody positivity due to the important therapeutic implications of distinguishing thyroiditis from GD.
Cancer-Specific Survival after Limb Salvage versus Amputation in Children and Adolescents with Osteosarcoma: A Population-Based Analysis with Propensity Score Matching
Authors: Li Zhenwei , Xu Bo , Cai Jingjing , Zha Zhengang
Published: April 2023

Background. The study aims to identify whether osteosarcoma patients of children and young adults will benefit from a survival profit from the choice of the operation method. Methods. The National Cancer Institute SEER database from 2000 to 2018 was selected for a retrospective analysis of 1630 children and young adults with a primary diagnosis of osteosarcoma, 1222 who underwent limb-preserving surgery, and 408 who underwent amputation. Confounders were controlled for by propensity score matching (PSM), cancer-specific survival (CSS) was analyzed using the Kaplan–Meier method, and univariate and multivariate Cox regression was used to analyze the factors influencing the prognosis of children and young osteosarcoma patients after surgery. A nomogram plot predicted 1-, 3-, and 5- survival rate in osteosarcoma. The model’s accuracy was validated by the area under the ROC and calibration curves. Results. After PSM, multifactor Cox regression analysis found AJCC Stage III-IV (CSS : HR = 5.26, 95% CI 1.95–14.18,

p
=
0.
 
001

; HR = 5.54, 95% CI 2.56–12.01,

p
<
0.
 
001

. Limb salvage surgery (CSS : HR = 0.58, 95% CI 0.44–0.77,

p
<
0.
 
001

) has independent impact factors for CSS prognosis. The survival curve before and after PSM showed that patients with osteosarcoma of children and young adults who underwent limb salvage surgery had a survival benefit compared with those who underwent amputation surgery. Gender, chemotherapy, histology, primary tumor site, stage, and surgical modality were modeled in a total of six variables in the nomogram. The model exhibited good predictive performance. The AUC were 0.823, 0.74, and 0.757 for training set at 1, 3, and 5 years, respectively. The AUC of validation set 0.666, 0.722, and 0.699 at 1, 3, and 5 years, respectively. The model also predicted CSS with good fidelity for both datasets. This model was significantly superior to the 8th edition of the AJCC TNM staging system, with a better net benefit in predicting CSS in children and young adults with osteosarcoma. Conclusion. Limb salvage surgery is an option for children and young adults with osteosarcoma and cancer-specific survival rates can be improved by receiving limb salvage surgery.
Molecular Prevalence and Risk Factors of Campylobacter Infection in Puppies in the Nairobi Metropolitan Region, Kenya
Authors: Mbindyo Sharon N. , Kitaa Jafred M. A. , Abuom Tequiero O. , Aboge Gabriel O. , Muasya Daniel W. , Muchira Beatrice W. , Gitahi Nduhiu , Mulei Charles M.
Published: April 2023

Campylobacter species are widely distributed pathogens; however, data on its epidemiology in puppies remain scanty, especially in Kenya. A cross‐sectional study was conducted in the Nairobi Metropolitan Region to determine molecular prevalence and associated risk factors of Campylobacter species infection in puppies. A total of 260 rectal swabs were collected from puppies from breeding kennels, shelters, and the University of Nairobi Veterinary Teaching and Referral Hospital. The samples were subjected to polymerase chain reaction (PCR) assays for identification of Campylobacter species. Data on potential risk factors associated with puppy exposure were collected using a semistructured questionnaire. Multivariable mixed effects logistic regression analyses were performed with kennels as random effects. Campylobacter species were detected in 64 of the 260 sampled puppies yielding an overall prevalence of 24.6%. Multivariable results showed that puppies from shelters, puppies from kennels that are washed daily, puppies with a recent history of vomiting, and those treated with antibiotics in the past month were significantly associated with the presence of Campylobacter species. Being a kenneled puppy and having had concurrent bacterial infections were identified as protective factors. This study provides molecular evidence of puppy exposure to Campylobacter species which could have impact on puppy health and highlights the need to develop awareness and management strategies to potentially reduce the risk of transmitting this pathogen among puppies, to humans, and other animals.
A Modified Dai–Liao Conjugate Gradient Method Based on a Scalar Matrix Approximation of Hessian and Its Application
Authors: Ivanov Branislav , Milovanović Gradimir V. , Stanimirović Predrag S. , Awwal Aliyu Muhammed , Kazakovtsev Lev A. , Krutikov Vladimir N.
Published: April 2023

We introduce and investigate proper accelerations of the Dai–Liao (DL) conjugate gradient (CG) family of iterations for solving large-scale unconstrained optimization problems. The improvements are based on appropriate modifications of the CG update parameter in DL conjugate gradient methods. The leading idea is to combine search directions in accelerated gradient descent methods, defined based on the Hessian approximation by an appropriate diagonal matrix in quasi-Newton methods, with search directions in DL-type CG methods. The global convergence of the modified Dai–Liao conjugate gradient method has been proved on the set of uniformly convex functions. The efficiency and robustness of the newly presented methods are confirmed in comparison with similar methods, analyzing numerical results concerning the CPU time, a number of function evaluations, and the number of iterative steps. The proposed method is successfully applied to deal with an optimization problem arising in 2D robotic motion control.
Therapeutic Landscape of AXL Receptor Kinase in Triple-Negative Breast Cancer
Authors: Ozyurt Rumeysa , Ozpolat Bulent
Published: April 2023

Early cancer recurrence, driven by resistance to therapeutics, is a major obstacle to overcome poor survival in triple-negative breast cancer (TNBC). Recently, overexpression of AXL has been identified as one of the key molecular determinants leading to the development of acquired resistance to chemotherapy and targeted anticancer treatments. AXL overactivation drives many hallmarks of cancer progression, including cell proliferation, survival, migration, metastasis, drug resistance, and is linked to poor patient survival and disease recurrence. Mechanistically, AXL represents a signaling hub that regulates a complex signaling pathways crosstalk. Therefore, emerging data highlight the clinical significance of AXL as an attractive therapeutic target. Currently, there is no FDA approved AXL inhibitor but several AXL small molecule inhibitors and antibodies are being tested in clinical settings. In this review we outline the functions and regulation of AXL, its role in resistance to therapy, and current strategies targeting AXL with emphasis on TNBC.
The Dynamics of Team Learning: Harmony and Rhythm in Teamwork Arrangements for Innovation
Authors: Harvey Jean-François , Cromwell Johnathan R. , Johnson Kevin J. , Edmondson Amy C.
Published: April 2023

Innovation teams must navigate inherent tensions between different learning activities to produce high levels of performance. Yet, we know little about how teams combine these activities—notably reflexive, experimental, vicarious, and contextual learning—most effectively over time. In this article, we integrate research on teamwork episodes with insights from music theory to develop a new theoretical perspective on team dynamics, which explains how team activities can produce harmony, dissonance, or rhythm in teamwork arrangements that lead to either positive or negative effects on overall performance. We first tested our theory in a field study using longitudinal data from 102 innovation teams at a Fortune Global 500 company; then, we replicated and elaborated our theory in a study of 61 MBA project teams at an elite North American university. Results show that some learning activities can occur within the same teamwork episode to have harmonious positive effects on team performance, while other activities combine to have dissonant negative effects when occurring in the same episode. We argue that dissonant activities must be spread across teamwork episodes to help teams achieve a positive rhythm of team learning over time. Our findings contribute to theory on team dynamics, team learning, and ambidexterity.
Small states shelter diplomacy: Balancing costs of entrapment and abandonment in the alliance dilemma
Authors: Pedersen Rasmus
Published: April 2023

Shelter theory has emerged as a promising but unrealized alternative to existing theories of bandwagon and hiding in the literature. It describes how small states can utilize the structural power of great powers to achieve political aims through the formation of asymmetric alliances. At present it is not clear exactly what shelter diplomacy aims to achieve, what type of costs it protects small states against and to what degree asymmetric shelters are useful when the preferences between the small state and the shelter partner widen. The article addresses these gaps. It develops a realist inspired model of shelter diplomacy that specifies when, how and with what effects small states can utilize the structural powers of great powers. It demonstrates how shelter diplomacy can help small states balance the costs of abandonment and entrapment in the alliance dilemma through construction of both asymmetric and symmetric shelters. The main contributions are to bring shelter diplomacy into the International Relations mainstream literature and develop a new theoretical middle position between the more well-described bandwagon and hiding strategies. The model is applied to a Danish case that demonstrates how small states have utilized and adopted dynamic shelter strategies in the European integration process.
I Trends in Theorizing Democratic Legitimacy
Authors: Rak Joanna
Published: April 2023

The current literature on democratic legitimacy is vital to addressing why assaults on democracy are effective. The theoretical frameworks of the construction of legitimacy by international organizations (IOs) help us comprehend how and why IOs seek support and when the results of these quests effectively curb democratic backsliding in their member states. Furthermore, the explanatory models of domestic democratic legitimacy allow us to understand how anti-democratic actors claim the right to rule and what makes their claims successful. They also explain what makes militant democracies fail. The theories differentiate between socially attributed legitimacy and the acquisition of social legitimacy through claims to the right to rule. Their conceptualizations differ depending on the audiences, claimants, and consequences of legitimacy.
Militant Splinter Groups and the Use of Violence
Authors: Robinson Kaitlyn , Malone Iris
Published: April 2023

Existing research portrays militant splinter groups as more violent than their parent organizations due to factors like more extreme preferences or capacity-building needs. Though widely held, the assumption that splinters are particularly violent has not been systematically tested. In this paper, we develop and test an alternative explanation for splinter behavior. We argue splinter groups often appear less violent than their parents due to an underlying selection effect. Splinters break away where there are large organizational barriers to internally address a faction’s grievances. These barriers tend to exist in well-organized parents that are also capable of high levels of violence. Splinter groups lack this established organizational infrastructure, resulting in lower levels of relative violence. We test this logic with an original dataset on parent and splinter groups and a pair of comparative case studies. We find that splinters are less violent than parent organizations, challenging conventional wisdom.