High Number Research Articles

Tamanhos de parcelas e amostras para variáveis biométricas em mudas de alface

ABSTRACT: In order to ensure reliable inferences in scientific experiments, sampling criteria should be determined and defined during the experimental design phase. Determining plot and sample sizes without scientific criteria could result in resource and labor inefficiencies with no gain in experimental precision. In this work we estimate plot and sample sizes for biometric variable analyses in lettuce seedlings. The seedlings were sown in four expanded polystyrene foam transplant trays with 128 and 200 cells. Foliar area, stem diameter, shoot height, root length, root volume, root area, fresh and dry shoot and root masses. The methods described by Paranaiba (PARANAIBA et al., 2009) and Cochran (COCHRAN, 1977) were used for plot size and sample size estimations, respectively. Sample size varied according to the variables analysed and transplant tray cell number. Root variables required the highest number of samples. For a 10% margin of error, 12 seedlings were necessary for evaluations in a 128 cell tray, while 11 seedlings were required for analysis in 200 cell trays.

Ligand- and Structure-based Approaches for Transmembrane Transporter Modeling.

The study of transporter proteins is key to understanding the mechanism behind multi-drug resistance and drug-drug interactions causing severe side effects. While ATP-binding transporters are well-studied, solute carriers illustrate an understudied family with a high number of orphan proteins. To study these transporters, in silico methods can be used to shed light on the basic molecular machinery by studying protein-ligand interactions. Nowadays, computational methods are an integral part of the drug discovery and development process. In this short review, computational approaches, such as machine learning, are discussed, which try to tackle interactions between transport proteins and certain compounds to locate target proteins. Furthermore, a few cases of selected members of the ATP binding transporter and solute carrier family are covered, which are of high interest in clinical drug interaction studies, especially for regulatory agencies. The strengths and limitations of ligand-based and structure-based methods are discussed to highlight their applicability for different studies. Furthermore, the combination of multiple approaches can improve the information obtained to find crucial amino acids that explain important interactions of protein-ligand complexes in more detail. This allows the design of drug candidates with increased activity towards a target protein, which further helps to support future synthetic efforts.

Plain Language Summary of principles for improving the care of people with eosinophil-associated diseases.

Eosinophil-associated diseases (EADs) are a group of conditions in which eosinophils (a type of white blood cell) are thought to play a key role in the disease and how it develops. Some EADs are common, such as atopic dermatitis (also called eczema) and a subtype of asthma called eosinophilic asthma, while others are rare, such as hypereosinophilic syndrome (a condition in which a person has a very high number of eosinophils in both the blood and one or more organs). People with EADs face many problems related to their conditions. Symptoms such as severe abdominal pain, itch, or shortness of breath impact both the patient as well as their friends and family. Patients with EADs also experience delays to diagnosis and treatment as well as financial barriers. Healthcare professionals sometimes fail to recognize the complex set of symptoms that characterize an EAD, and this may cause delays in reaching a correct diagnosis. As a result, it may take longer for a patient to get the best care and the most effective treatments, which may contribute to poor health. The goal of this charter is to describe the key elements of good quality care, which all people with EADs deserve, as well as to present an action plan to improve health and overall well-being for people with EADs. Proposed use of this patient charter: The principles described in this charter (a written guide to achieve an outcome) show the core elements of quality care that people with EADs must receive. They also describe clear steps to reduce the burden on patients and their caregivers and to improve patient health outcomes. We urge healthcare professionals, hospitals, and policymakers around the world to adopt these principles quickly. By doing this, people with EADs will be more likely to receive an accurate and timely diagnosis and have access to quality care and treatment in the right setting.

Weak Electrostatic Force on K+ in Gel Polymer Electrolyte Realizes High Ion Transference Number for Quasi Solid-State Potassium Ion Batteries.

Quasi-solid-state potassium-ion batteries (SSPIBs) are of great potential for commercial use due to the abundant reserves and cost-effectiveness of resources, as well as high safety. Gel polymer electrolytes (GPEs) with high ionic conductivity and fast interfacial charge transport are necessary for SSPIBs. Here, the weak electrostatic force between K+ and electronegative functional groups in the ethoxylated trimethylolpropane triacrylate (ETPTA) polymer chains, which can promote fast migration of free K+, is revealed. To further enhance the interfacial reaction kinetics, a multilayered GPE by in situ growth of poly(vinylidenefluoride-co-hexafluoropropylene) (PVDF-HFP) on ETPTA (PVDF-HFP|ETPTA|PVDF-HFP) is constructed to improve the interface contact and provide sufficient K+ concentration in PVDF-HFP. A high ion transference number (0.92) and a superior ionic conductivity (5.15 × 10-3 S cm-1) are achieved. Consequently, the SSPIBs with both intercalation-type (PB) and conversion-type (PTCDA) cathodes show the best battery performance among all reported SSPIBs of the same cathode. These findings demonstrate that potassium-ion batteries have the potential to surpass Li/Na ion batteries in solid-state systems.

Central Countries' and Brazil's Contributions to Nanotechnology

Abstract: Nanotechnology is a cornerstone of the scientific advances witnessed over the past few years. Nanotechnology applications are extensively broad, and an overview of the main trends worldwide can give an insight into the most researched areas and gaps to be covered. This document presents an overview of the trend topics of the three leading countries studying in this area, as well as Brazil for comparison. The data mining was made from the Scopus database and analyzed using the VOSviewer and Voyant Tools software. More than 44.000 indexed articles published from 2010 to 2020 revealed that the countries responsible for the highest number of published articles are The United States, China, and India, while Brazil is in the fifteenth position. Thematic global networks revealed that the standing-out research topics are health science, energy, wastewater treatment, and electronics. In a temporal observation, the primary topics of research are: India (2020), which was devoted to facing SARS-COV 2; Brazil (2019), which is developing promising strategies to combat cancer; China (2018), whit research on nanomedicine and triboelectric nanogenerators; the United States (2017) and the Global tendencies (2018) are also related to the development of triboelectric nanogenerators. The collected data are available on GitHub. This study demonstrates the innovative use of data-mining technologies to gain a comprehensive understanding of nanotechnology's contributions and trends and highlights the diverse priorities of nations in this cutting-edge field.

Synthesis and In Silico Studies of Quinazolinones as PARP-1 Inhibitors.

Cancer is a leading threat to humankind, accounting for nearly one million deaths in 2018, and the expected number of cancer-related deaths in 2040 is more than 16 million. The most common causes of cancer deaths are lung, colorectal, stomach, liver and breast cancer, while the highest number of new cancer cases belong to lung, breast, colorectal, prostate, stomach and liver cancer. PARP-1 is an enzyme that plays an important role in DNA repair, cell propagation/survival and death due to its influence on numerous biological processes. Quinazolinones represent an important scaffold in medicinal chemistry and have a broad spectrum of biological activities. In this study, we have synthesized quinazolinones by reaction of 2-aminobenzamide and substituted aldehydes. Molecular docking studies of synthesized compounds were performed for their PARP-1 binding affinities using Schrodinger 2016 software. In silico ADME studies were also performed for the synthesized compounds using the QikProp tool of Schrodinger software. Results of molecular docking studies indicated that synthesized quinazolinones had a good affinity towards active site of PARP-1 and compound 4 had the best docking score (-10.343). Results of ADME studies indicated the drug-like properties of synthesized compounds, which make them suitable drug candidates. All the synthesized compounds have a better docking score than niraparib (-9.05). Further, the synthesized compounds have a favorable ADME profile. Therefore, they may serve as important leads in discovering PARP-1 inhibitors.

Mycobacterium tuberculosis: A New Hitchhiker in the Etiopathogenesis of Periodontitis.

Periodontitis, a chronic inflammatory disease of the gums affects both the ligament and alveolar bone. Severe form of periodontal disease affects a strikingly high number of one billion adults globally. The disease permutes both the soft and hard tissues of the oral cavity leading to localized and systemic diseases. Periodontitis has a deleterious impact on systemic health causing diabetes, cardiovascular diseases, and other disease. The cause of enhanced inflammatory process is due to dysbiosis and an unregulated immune response. Innate immune response and T cells trigger uninhibited cytokine release causing an unwarranted inflammatory response. The RANK- RANKL interaction between osteoblasts, immune cells and progenitor osteoclasts results in maturation of osteoclasts which promote bone resorption. It is well established that dysbiosis of the oral cavity has been implicated in periodontitis. But emerging reports suggest that pulmonary pathogen, Mycobacterium tuberculosis (Mtb), causes extra-pulmonary diseases such as periodontitis. Many clinical case reports advocate the involvement of Mtb in periodontitis which poses a threat with the surge of tuberculosis in HIV and other immunocompromised individuals. Fostering a better understanding of the mechanism, causative agents and control on inflammatory response is imperative in prevention and treatment of periodontitis.

Contaminated Gibbs-Type Priors

Gibbs-type priors are combinatorial processes widely used as key components in several Bayesian nonparametric models. By virtue of their flexibility and mathematical tractability, they turn out to be predominant priors in species sampling problems and mixture modeling. We introduce a new family of processes which extends the Gibbs-type one, by including a contaminant component in the model to account for an excess of observations with frequency one. We first investigate the induced random partition, the associated predictive distribution, the asymptotic behavior of the total number of blocks and the number of blocks with a given frequency: all the results we obtain are in closed form and easily interpretable. A remarkable aspect of contaminated Gibbs-type priors relies on their predictive structure, compared to the one of the standard Gibbs-type family: it depends on the additional sampling information on the number of observations with frequency one out of the observed sample. As a noteworthy example we focus on the contaminated version of the Pitman-Yor process, which turns out to be analytically tractable and computationally feasible. Finally we pinpoint the advantage of our construction in different applications: we show how it helps to improve predictive inference in a species-related dataset exhibiting a high number of species with frequency one; we also discuss the use of the proposed construction in mixture models to perform density estimation and outlier detection.

Diversity, utility and communities of weed in wheat of Nowshera, Pakistan

Weeds are disregarded for their competitive nature and difficulties during harvesting and threshing. Categorizing them by economic use classes enables effective management. Weed ecological studies in wheat crop fields were conducted to evaluate the floristic diversity, ecological characteristics, community structures and economic uses of weeds in District Nowshera, Pakistan. Different wheat crop fields were surveyed for the collection and identification of plant species growing as weed. Total 50 plant species from 47 genera and 20 families were recorded in the study area. Asteraceae had the highest number of species (10), followed by Poaceae (9). Therophytes were more with 42 species, followed by geophytes and Hemicryptophytes each with 3 species. Most species had mesophyllous leaf size (15), while nanophyllous (12) and microphyllous (11). Simple leaves were more common (28) than dissected leaves (22). Nonspiny species were (44) while only 6 had spines. Maximum plant species were fodder (35) and medicinal (10). In the study, four distinct weed communities were identified using quadrate method i.e. Cynodon-Anagallis-Melilotus, Arenaria-Anagallis-Cannabis, Cynodon-Parthenium-Coronopus and Rumex-Arenaria-Oxalis. These findings provide a valuable starting point for future in-depth investigations on the entire flora and vegetation of Nowshera, Pakistan.

Clinical Data Analysis of 10,152 Patients Treated with Acupuncture during Perioperative Period

Objective: To analyze applications of acupuncture treatments during perioperative period and foresee the development of acupuncture in general hospitals by analyzing the clinical data of 10,152 patients treated with acupuncture during perioperative period. Methods: Extracted the perioperative acupuncture treatment records from surgical departments from January 2015 to December 2020 through the Information Management Center of Qilu Hospital. Diagnosis, primary disease, and the department applying for perioperative acupuncture treatments were extracted from their medical records. Frequency of perioperative acupuncture treatments from each department, diseases treated by acupuncture, and primary diseases were counted. The number of acupuncture treatments were counted though the Lianzhong Digital Medical Record Retrieval System of the hospital and effectiveness was evaluated according to the course of disease. Results: There were 10,152 perioperative acupuncture treatments from 17 surgical departments with 43 wards. Each ward had at least one request for acupuncture treatments every month, and the utilization rate of acupuncture increased year over year. The top five departments with the highest number of requests for perioperative acupuncture treatments were the gynecology department, orthopedics department, neurosurgery department, general surgery department and urology department. Acupuncture was mainly used to promote gastrointestinal function (50%) and nerve function (39%), followed by promoting recovery of bladder function (6%) and other diseases existing in the perioperative period (5%). The effectiveness is recognized by patients and surgeons. Conclusion: Acupuncture has been widely used in postoperative rehabilitation and can go further. The treatment of perioperative conditions is an opportunity for the development of acupuncture in general hospitals.

Recovered supernova Ia rate from simulated LSST images

Aims. The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) will revolutionize time-domain astronomy by detecting millions of different transients. In particular, it is expected to increase the number of known type Ia supernovae (SN Ia) by a factor of 100 compared to existing samples up to redshift ∼1.2. Such a high number of events will dramatically reduce statistical uncertainties in the analysis of the properties and rates of these objects. However, the impact of all other sources of uncertainty on the measurement of the SN Ia rate must still be evaluated. The comprehension and reduction of such uncertainties will be fundamental both for cosmology and stellar evolution studies, as measuring the SN Ia rate can put constraints on the evolutionary scenarios of different SN Ia progenitors. Methods. We used simulated data from the Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) and LSST Data Preview 0 to measure the SN Ia rate on a 15 deg2 region of the “wide-fast-deep” area. We selected a sample of SN candidates detected in difference images, associated them to the host galaxy with a specially developed algorithm, and retrieved their photometric redshifts. We then tested different light-curve classification methods, with and without redshift priors (albeit ignoring contamination from other transients, as DC2 contains only SN Ia). We discuss how the distribution in redshift measured for the SN candidates changes according to the selected host galaxy and redshift estimate. Results. We measured the SN Ia rate, analyzing the impact of uncertainties due to photometric redshift, host-galaxy association and classification on the distribution in redshift of the starting sample. We find that we are missing 17% of the SN Ia, on average, with respect to the simulated sample. As 10% of the mismatch is due to the uncertainty on the photometric redshift alone (which also affects classification when used as a prior), we conclude that this parameter is the major source of uncertainty. We discuss possible reduction of the errors in the measurement of the SN Ia rate, including synergies with other surveys, which may help us to use the rate to discriminate different progenitor models.

Musculoskeletal injury in military specialists: a 2-year retrospective study

BackgroundMilitary specialists are elite personnel who are trained to work across diverse operational environments where a high level of physical conditioning is a prerequisite for their role. Anecdotally, personnel are...

Design of siRNAs Against Immune-Implicated Atherosclerosis Genes: Computational Study

Atherosclerosis is a chronic, immune-implicated, disease with high numbers of mortality globally. The aim of the current study is to target these genes by specific siRNA utilizing bioinformatics tools. Eight siRNAs were designed via RNAxs from C1QA and ITBG2 gene sequences retrieved from NCBI database. GC% and Tm of siRNAs were calculated through OligoCalc web interface. In addition, hybridization energy of siRNAs with the corresponding target sequences as well as docking to argonaute 2 protein were performed using DuplexFold and HDock. The designed siRNAs exhibited acceptable GC content and Tm values. Besides, the hybridization energy and docking scores were highly significant to block the expression of the mentioned genes. In conclusion, the designed siRNAs are superior candidates for silencing immune-mediated atherosclerotic genes which deserve further consideration.

Modeling and sensitivity analysis of a supersonic inductive Magnetohydrodynamic (MHD) generator

This study presents the supersonic inductive Magnetohydrodynamic (SIMHD) generator and simulates its model through the use of COSMOL Multiphysics. This generator, as an inductive MHD generator, is suggested to address the problems associated with the conventional MHD generator. Since the proposed generator does not require a moving part to convert thermal energy to electrical energy, it is categorized as a direct energy convertor. The SIMHD generator consists of a converging-diverging duct and is divided into two sections at the diverging part by means of a diaphragm. Both of these sections are diverging, which makes it possible to obtain a high Mach number. In this regard, the performance of the SIMHD generator is studied by its mathematical modeling and numerical simulation using the finite element method. In addition, a sensitivity analysis is carried out on the design parameters. The results indicate that the proposed SIMHD duct design will increase the speed from 160 to 1300 m⁄s, and decrease the temperature from 2100 to 1300 K. Moreover, considering a charge generation equation, the produced power for the resistive load 50 Ω equals 25.3 kW. This generator also has the potential to be used in scramjets and ramjets.

Multi-Label Noise Robust Collaborative Learning for Remote Sensing Image Classification.

The development of accurate methods for multi-label classification (MLC) of remote sensing (RS) images is one of the most important research topics in RS. The MLC methods based on convolutional neural networks (CNNs) have shown strong performance gains in RS. However, they usually require a high number of reliable training images annotated with multiple land-cover class labels. Collecting such data is time-consuming and costly. To address this problem, the publicly available thematic products, which can include noisy labels, can be used to annotate RS images with zero-labeling cost. However, multi-label noise (which can be associated with wrong and missing label annotations) can distort the learning process of the MLC methods. To address this problem, we propose a novel multi-label noise robust collaborative learning (RCML) method to alleviate the negative effects of multi-label noise during the training phase of a CNN model. RCML identifies, ranks, and excludes noisy multi-labels in RS images based on three main modules: 1) the discrepancy module; 2) the group lasso module; and 3) the swap module. The discrepancy module ensures that the two networks learn diverse features, while producing the same predictions. The task of the group lasso module is to detect the potentially noisy labels assigned to multi-labeled training images, while the swap module is devoted to exchange the ranking information between two networks. Unlike the existing methods that make assumptions about noise distribution, our proposed RCML does not make any prior assumption about the type of noise in the training set. The experiments conducted on two multi-label RS image archives confirm the robustness of the proposed RCML under extreme multi-label noise rates. Our code is publicly available at: https://www.noisy-labels-in-rs.org.

Bi-DexHands: Towards Human-Level Bimanual Dexterous Manipulation.

Achieving human-level dexterity in robotics remains a critical open problem. Even simple dexterous manipulation tasks pose significant difficulties due to the high number of degrees of freedom and the need for cooperation among heterogeneous agents (e.g., finger joints). While some researchers have utilized reinforcement learning (RL) to control a single hand in manipulating objects, tasks that require coordinated bimanual cooperation are still under-explored due to the fewer suitable environments, which can result in difficulties and sub-optimal performance. To address these challenges, we introduce Bi-DexHands, a simulator with two dexterous hands featuring 20 bimanual manipulation tasks and thousands of target objects, designed to match various levels of human motor skills based on cognitive science research. We developed Bi-DexHands in Issac Gym, enabling highly efficient RL training at over 30,000 frames per second using a single NVIDIA RTX 3090. Based on Bi-DexHands, we present a comprehensive evaluation of popular RL algorithms in different settings, including single-agent/multi-agent RL, offline RL, multi-task RL, and meta RL. Our findings show that on-policy algorithms, such as PPO, can master simple manipulation tasks that correspond to those of 48-month-old babies, such as catching a flying object or opening a bottle. Furthermore, multi-agent RL can improve the ability to perform manipulations that require skilled bimanual cooperation, such as lifting a pot or stacking blocks. Despite achieving success in individual tasks, current RL algorithms struggle to learn multiple manipulation skills in most multi-task and few-shot learning scenarios. This highlights the need for further research and development within the RL community.

Evasive Spike Variants Elucidate the Preservation of T Cell Immune Response to the SARS-CoV-2 Omicron Variant.

The Omicron variants boast the highest infectivity rates among all SARS-CoV-2 variants. Despite their lower disease severity, they can reinfect COVID-19 patients and infect vaccinated individuals as well. The high number of mutations in these variants render them resistant to antibodies that otherwise neutralize the spike protein of the original SARS-CoV-2 spike protein. Recent research has shown that despite its strong immune evasion, Omicron still induces strong T Cell responses similar to the original variant. This work investigates the molecular basis for this observation using the neural network tools NetMHCpan-4.1 and NetMHCiipan-4.0. The antigens presented through the MHC Class I and Class II pathways from all the notable SARS-CoV-2 variants were compared across numerous high frequency HLAs. All variants were observed to have equivalent T cell antigenicity. A novel positive control system was engineered in the form of spike variants that did evade T Cell responses, unlike Omicron. These evasive spike proteins were used to statistically confirm that the Omicron variants did not exhibit lower antigenicity in the MHC pathways. These results suggest that T Cell immunity mounts a strong defense against COVID-19 which is difficult for SARS-CoV-2 to overcome through mere evolution.

A mono-layer matrix for pelleting marigold (Tagetes erecta) seeds

Marigold growers in Thailand face challenges in the cultivation from seeds of marigold owing to the elongated, slender and sometimes fragile shape of the seeds. These characteristics often result in a high number of seedlings with abnormal traits, making them susceptible to diseases and insects. The objective of this study was to develop a pellet formulation for marigold seeds to increase their size and facilitate cultivation from seeds. Seven pellet matrices, including a commercial product (pre-pelleted seeds), were assessed for integrity, including friability, dissolution period germination, shoot length, and root length under both laboratory and greenhouse conditions. Methylhydroxyethyl cellulose (MHEC) was used as the binding agent for each pellet matrix. Seeds pelleted with MHEC-bentonite and MHEC-zeolite resulted in irregularly shaped pellets, whereas the other matrices appeared smoother and more similar to commercially-pelleted seeds. CaCO3 and talc-pelleted seeds had a high friability, whereas CaSO4 -, pumice- and bentonite-pelleted seeds had friability values similar to those of the commercially- pelleted seeds. CaSO4 -pelleted seeds exhibited germination rates that were the closest to those of non-pelleted and commercially-pelleted seeds under both laboratory and greenhouse conditions. In conclusion, the MHEC- CaSO4 matrix is the most suitable choice for pelleting marigold seeds.

First Report of Tobacco Streak Virus in Cannabis sativa in New York.

In 2022, virus-like symptoms were observed in a field of diverse hemp (Cannabis sativa L.) germplasm in Ontario County, New York. Less than 1% of plants exhibited stunting and curled leaves (Figure S1), consistent with tobacco streak virus (TSV) symptoms on other plants (Liu et al. 2022). Most typically, the plants were considerably reduced in overall size, with upwards, adaxial curling along the leaf margin with newer leaves appearing to be the most affected. Fifteen symptomatic plants representing nine accessions were tested for 12 viruses and viroids through Agdia Testing Services (Elkhart, IN). Of these, eight plants representing five accessions including: G 33204 21UO SD ('Cherry Wine S1'), G 33211 21UO SD ('Wife'), G 33225 22CL01 CL ('Candida #2'), G 33270 22UO SD ('Falkowski CBD Mix'), and G 33365 22UO SD ('Queen Dream'), were positive for TSV, a type of Ilarvirus in the Bromoviridae family. Presence of TSV was confirmed through enzyme-linked immunosorbent assay testing. TSV is a positive-sense, single-stranded RNA virus with a wide host range that can be transmitted by thrips, mechanical injury, seed, and pollen (Zambrana-Echevarría et al. 2021). To confirm the presence of TSV, two putatively TSV-infected samples were subjected to RNA-Seq analysis. RNA was extracted using the RNeasy Plant Mini Kit (Qiagen, Aarhus, Denmark) per manufacturer's direction. Stranded RNA libraries were prepared using the Illumina TruSeq Stranded Total RNA with Ribo-Zero Plant kit (San Diego, California, USA). Paired-end 2x150bp sequencing was performed on an Illumina NovaSeq6000 sequencer. RNA-Seq data was trimmed using the fastp program (Chen et al. 2018) with default parameters to remove adapter sequences and low-quality bases. After filtering, 49,696,041 and 56,126,804 paired-end reads were retained from 'Wife' and 'Falkowski CBD Mix' samples, respectively. Filtered RNA-seq reads were mapped to TSV genome accession GCF_000865505.1 using the bowtie2 (Langmead & Salzberg 2012) aligner with default parameters. From 'Wife' and 'Falkowski CBD Mix' samples, 153 and 139 reads mapped to the TSV reference genome. To further validate the presence of TSV reads, RNA-Seq data was analyzed using the Kraken2 pipeline (Wood et al. 2019). Using the Kraken2 virus database, reads associated with TSV (NCBI taxonomy ID: 12317) were identified. This analysis identified 172 and 151 TSV reads from 'Wife' and 'Falkowski CBD Mix,' respectively. Higher numbers of reads identified using the Kraken2 analysis is due to the more permissive k-mer matching approach implemented in Kraken2. Furthermore, we identified several other virus taxa in the samples. Of note, both samples had a high number of reads associated with Amazon lily mild mottle virus with 254,493 and 116,150 reads from 'Wife' and 'Falkowski CBD Mix,' respectively. Among other virus species belonging to Ilarviruses, Cassava Ivorian bacilliform virus and Cowpea chlorotic mottle viruses were detected from both samples. To further validate infection by TSV, samples from both ELISA-positive and ELISA-negative plants were subjected to PCR using the primers and protocol described in Zambrana-Echevarría et al. 2021. Amplification of an approximately 700 base-pair product was observed in the putatively ELISA-positive samples, but not in the ELISA-negative samples. The amplicons were further cloned into the pGEM-T Easy vector (Promega, Madison, WI, U.S.A) using the manufacturer's protocol and sequenced using M13 forward and M13 reverse primers (Functional Biosciences, Madison, WI, U.S.A). Sequencing results indicated considerable similarity to TSV genomes available in GenBank, between 88% and 99%. Raw sequence data generated from this study was deposited in NCBI under the bioproject ID PRJNA1009441. Though it cannot be ruled out that the observed symptoms were caused exclusively by TSV infection due to the high number of other viral reads, the results contribute to the literature that indicates hemp can host TSV and should be considered a potential source of TSV inoculum (Chiginsky et al. 2021). This new inoculum source could cause significant crop damage and economic loss when grown with TSV susceptible row and specialty crops.

Mapping the literature of social network ties in business and management field: A bibliometric study

In recent years, academics have focused increasingly on social network connections across different organisations. Social networking for businesses is a topic that crosses many disciplines, including social sciences, computer science, engineering, management, education, sociology, and psychology, so it's no surprise that definitions, methods, and approaches to social networks are constantly debated. Based on a data set of 3466 publications from the Scopus database, the goal of this study is to map the previous literature on social network ties of organisations to the business and management area. The data set was taken from the Scopus database to investigate the main authors, the number of publications, the most influential journals, the most used keywords and the top productive institutions and countries. The goal of this study is to map the previous literature on the social network ties of organisations to the business and management area. The most influential publications, authors, journals, and keywords are thus identified using four methods of bibliographic analysis, as follows: bibliographic coupling, analysis of co-occurrence of authors' keywords, and analysis of co-authorship (a) countries and (b) authors. According to the study’s findings, the USA is the most prolific country, having over 900 publications in the past five years, followed by China and the UK. The publication trend has increased over the last 5 years in the business and management field and will keep increasing because of the growing interest of researchers and practitioners in the given field. Knowledge-based systems are found to be the top productive journal and Hong Kong Polytechnic University is the most influential institution with the highest number of publications.