bluuebunny/crossref_metadata_2025 huggingface dataset:
When Should a Black Box Be Transparent?
Authors: Neville-Neil George V.
Published: June 2022

The right answer in these cases is to ask the vendor for as much information as possible to reduce the risk in accepting this so-called replacement. First, ask for the test plans and test output so you can understand whether they tested the component in a way that relates to your use case. Just because they tested the thing doesn't mean they tested all the parts your product cares about. In fact, it's unlikely they did. They may have tested just the parts that connect back to the API, rather than the edge cases that would come up when a component is changed in your system.
The Cold Interstellar Medium of Galaxies in the Local Universe
Authors: Saintonge Amélie , Catinella Barbara
Published: June 2022

The cold interstellar medium (ISM) plays a central role in the galaxy evolution process. It is the reservoir that fuels galaxy growth via star formation, the repository of material formed by these stars, and a sensitive tracer of internal and external processes that affect entire galaxies. Consequently, significant efforts have gone into systematic surveys of the cold ISM of the galaxies in the local Universe. This review discusses the resulting network of scaling relations connecting the atomic and molecular gas masses of galaxies with their other global properties (stellar masses, morphologies, metallicities, star-formation activity…) and their implications for our understanding of galaxy evolution. Key take-home messages are as follows: ▪ From a gas perspective, there are three main factors that determine the star-formation rate of a galaxy: the total mass of its cold ISM, how much of that gas is molecular, and the rate at which any molecular gas is converted into stars. All three of these factors vary systematically across the local galaxy population. ▪ The shape and scatter of both the star-formation main sequence and the mass–metallicity relation are deeply linked to the availability of atomic and molecular gas. ▪ Future progress will come from expanding our exploration of scaling relations into new parameter space (in particular, the regime of dwarf galaxies), better connecting the cold ISM of large samples of galaxies with the environment that feeds them (the circumgalactic medium, in particular), and understanding the impact of these large scales on the efficiency of the star-formation process on molecular cloud scales.
Photometric Redshifts for Next-Generation Surveys
Authors: Newman Jeffrey A. , Gruen Daniel
Published: June 2022

Photometric redshifts are essential in studies of both galaxy evolution and cosmology, as they enable analyses of objects too numerous or faint for spectroscopy. The Rubin Observatory, Euclid, and Roman Space Telescope will soon provide a new generation of imaging surveys with unprecedented area coverage, wavelength range, and depth. To take full advantage of these data sets, further progress in photometric redshift methods is needed. In this review, we focus on the greatest common challenges and prospects for improvement in applications of photometric redshifts to the next generation of surveys: ▪ Gains in performance (i.e., the precision of redshift estimates for individual galaxies) could greatly enhance studies of galaxy evolution and some probes of cosmology. ▪ Improvements in characterization (i.e., the accurate recovery of redshift distributions of galaxies in the presence of uncertainty on individual redshifts) are urgently needed for cosmological measurements with next-generation surveys.

To achieve both of these goals, improvements in the scope and treatment of the samples of spectroscopic redshifts that make high-fidelity photometric redshifts possible will also be needed. For the full potential of the next generation of surveys to be reached, the characterization of redshift distributions must improve by roughly an order of magnitude compared with the current state of the art, requiring progress on a wide variety of fronts. We conclude by presenting a speculative evaluation of how photometric redshift methods and the collection of the necessary spectroscopic samples may improve by the time near-future surveys are completed.
Accelerated Evolution by Diversity-Generating Retroelements
Authors: Macadangdang Benjamin R. , Makanani Sara K. , Miller Jeff F.
Published: June 2022

Diversity-generating retroelements (DGRs) create vast amounts of targeted, functional diversity by facilitating the rapid evolution of ligand-binding protein domains. Thousands of DGRs have been identified in bacteria, archaea, and their respective viruses. They are broadly distributed throughout the microbial world, with enrichment observed in certain taxa and environments. The diversification machinery works through a novel mechanism termed mutagenic retrohoming, whereby nucleotide sequence information is copied from an invariant DNA template repeat (TR) into an RNA intermediate, selectively mutagenized at TR adenines during cDNA synthesis by a DGR-encoded reverse transcriptase, and transferred to a variable repeat (VR) region within a variable-protein gene ( 54 ). This unidirectional flow of information leaves TR-DNA sequences unmodified, allowing for repeated rounds of mutagenic retrohoming to optimize variable-protein function. DGR target genes are often modular and can encode one or more of a wide variety of discrete functional domains appended to a diversifiable ligand-binding motif. Bacterial variable proteins often localize to cellsurfaces, although a subset appear to be cytoplasmic, while phage-encoded DGRs commonly diversify tail fiber–associated receptor-binding proteins. Here, we provide a comprehensive review of the mechanism and consequences of accelerated protein evolution by these unique and beneficial genetic elements.
Function of the Omp85 Superfamily of Outer Membrane Protein Assembly Factors and Polypeptide Transporters
Authors: Doyle Matthew Thomas , Bernstein Harris D.
Published: June 2022

The Omp85 protein superfamily is found in the outer membrane (OM) of all gram-negative bacteria and eukaryotic organelles of bacterial origin. Members of the family catalyze both the membrane insertion of β-barrel proteins and the translocation of proteins across the OM. Although the mechanism(s) by which these proteins function is unclear, striking new insights have emerged from recent biochemical and structural studies. In this review we discuss the entire Omp85 superfamily but focus on the function of the best-studied member, BamA, which is an essential and highly conserved component of the bacterial barrel assembly machinery (BAM). Because BamA has multiple functions that overlap with those of other Omp85 proteins, it is likely the prototypical member of the Omp85 superfamily. Furthermore, BamA has become a protein of great interest because of the recent discovery of small-molecule inhibitors that potentially represent an important new class of antibiotics.
Mining Fatty Acid Biosynthesis for New Antimicrobials
Authors: Radka Christopher D. , Rock Charles O.
Published: June 2022

Antibiotic resistance is a serious public health concern, and new drugs are needed to ensure effective treatment of many bacterial infections. Bacterial type II fatty acid synthesis (FASII) is a vital aspect of bacterial physiology, not only for the formation of membranes but also to produce intermediates used in vitamin production. Nature has evolved a repertoire of antibiotics inhibiting different aspects of FASII, validating these enzymes as potential targets for new antibiotic discovery and development. However, significant obstacles have been encountered in the development of FASII antibiotics, and few FASII drugs have advanced beyond the discovery stage. Most bacteria are capable of assimilating exogenous fatty acids. In some cases they can dispense with FASII if fatty acids are present in the environment, making the prospects for identifying broad-spectrum drugs against FASII targets unlikely. Single-target, pathogen-specific FASII drugs appear the best option, but a major drawback to this approach is the rapid acquisition of resistance via target missense mutations. This complication can be mitigated during drug development by optimizing the compound design to reduce the potential impact of on-target missense mutations at an early stage in antibiotic discovery. The lessons learned from the difficulties in FASII drug discovery that have come to light over the last decade suggest that a refocused approach to designing FASII inhibitors has the potential to add to our arsenal of weapons to combat resistance to existing antibiotics.
Climate Change Effects on Pathogen Emergence: Artificial Intelligence to Translate Big Data for Mitigation
Authors: Garrett K.A. , Bebber D.P. , Etherton B.A. , Gold K.M. , Plex Sulá A.I. , Selvaraj M.G.
Published: June 2022

Plant pathology has developed a wide range of concepts and tools for improving plant disease management, including models for understanding and responding to new risks from climate change. Most of these tools can be improved using new advances in artificial intelligence (AI), such as machine learning to integrate massive data sets in predictive models. There is the potential to develop automated analyses of risk that alert decision-makers, from farm managers to national plant protection organizations, to the likely need for action and provide decision support for targeting responses. We review machine-learning applications in plant pathology and synthesize ideas for the next steps to make the most of these tools in digital agriculture. Global projects, such as the proposed global surveillance system for plant disease, will be strengthened by the integration of the wide range of new data, including data from tools like remote sensors, that are used to evaluate the risk ofplant disease. There is exciting potential for the use of AI to strengthen global capacity building as well, from image analysis for disease diagnostics and associated management recommendations on farmers’ phones to future training methodologies for plant pathologists that are customized in real-time for management needs in response to the current risks. International cooperation in integrating data and models will help develop the most effective responses to new challenges from climate change.
Economics of the US National Park System: Values, Funding, and Resource Management Challenges
Authors: Walls Margaret
Published: June 2022

The US national park system includes 423 sites covering more than 85 million acres of land and some of the most iconic landscapes in the country. The parks host approximately 320 million visitors a year. In this review, I survey the economics literature on national parks, focusing on four main topics: values and economic impacts of the parks, funding challenges, congestion and overcrowding, and resource management issues related mainly to climate change. In each area, I discuss gaps in the literature, new data and methods that could be applied to national parks, and important topics for future research. The most pressing needs are for more empirical research on use values, using new data sources and modern econometric methods, and relatedly, studies of the responsiveness of demand to pricing, which would be helpful for addressing both congestion and funding challenges.
How velocity impacts eccentric force generation of fully activated skinned skeletal muscle fibers in long stretches
Authors: Weidner Sven , Tomalka André , Rode Christian , Siebert Tobias
Published: June 2022

Eccentric muscle contractions are part of our daily lives. We found that force increased monotonically during slow stretches of fully activated muscle fibers, whereas higher stretch velocities resulted in an increasing drop in force after an initial increase and a final steeper rise in force. Cross-bridges cannot explain the observed force traces. This requires a viscoelastic non-cross-bridge contribution. Considering these results can improve muscle models and predictions of multibody simulations.
Multiple Positive Solutions and Estimates of Extremal Values for a Nonlocal Problem with Critical Sobolev Exponent and Concave-Convex Nonlinearities
Authors: Shi Zhigao , Qian Xiaotao
Published: June 2022

We are concerned with the following nonlocal problem involving critical Sobolev exponent

−

a
−
b

∫

Ω

∇
u

2

d
x

Δ
u
=
λ

u

q
−
2

u
+
δ

u

2

u
,

x
∈
Ω
,

u
=
0
,

x
∈
∂
Ω
,

where

Ω

is a smooth bounded domain in

ℝ

4

,

a
,
b
>
0

,

1
<
q
<
2

,

δ

, and

λ

are positive parameters. We prove the existence of two positive solutions and obtain uniform estimates of extremal values for the problem. Moreover, the blow-up and the asymptotic behavior of these solutions are also discussed when

b
↘
0

and

δ
↘
0

. In the proofs, we apply variational methods.
Alternate Distributed Beamforming with Power Allocation for Decode-and-Forward Multirelay Systems Using Buffers
Authors: Zhou Jiayu , Qiao Deli , Qian Haifeng
Published: June 2022

In this paper, a novel transmission policy referred as alternate distributed beamforming (ADB) for buffer-aided half-duplex (HD) multirelay systems is proposed, in which the relays are divided into two groups and activated alternately in their transmitter and receiver modes, with one group receiving the same information broadcast from the source while the other group simultaneously transmitting the common messages to the destination via distributed beamforming in each time slot. It is worth noting that the relays used for reception and transmission are determined without the instantaneous channel state information (CSI). Theoretical analysis of the achievable throughput of the proposed scheme in Rayleigh fading channels is provided, and the approximate closed-form expressions are derived for multiantenna relay scenario, with single-antenna relay scenario as a special case. Moreover, the asymptotic expressions for the maximum achievable throughput of the proposed scheme and corresponding optimal power allocation in the high- and low-SNR regimes are derived as well. Numerical results in accordance with theoretical analysis demonstrate that the proposed policy achieves a significant improvement in the maximum achievable throughput compared with benchmark schemes. It is shown that for the ADB scheme, the almost or exact symmetric relay grouping may achieve the best performance in the high-SNR regime. It is also shown that increasing the number of antennas equipped at each relay is better than increasing the number of relays equipped with a single antenna when the total number of antennas at the relays is fixed.
Feature Matching Optimization of Multimedia Remote Sensing Images Based on Multiscale Edge Extraction
Authors: Wang Yani , Dong Jinfang , Wang Bo
Published: June 2022

In order to solve the problem of low efficiency of image feature matching in traditional remote sensing image database, this paper proposes the feature matching optimization of multimedia remote sensing images based on multiscale edge extraction, expounds the basic theory of multiscale edge, and then registers multimedia remote sensing images based on the selection of optimal control points. In this paper, 100 remote sensing images with a size of 3619

∗

825 with a resolution of 30 m are selected as experimental data. The computer is configured with 2.9 ghz CPU, 16 g memory, and i7 processor. The research mainly includes two parts: image matching efficiency analysis of multiscale model; matching accuracy analysis of multiscale model and formulation of model parameters. The results show that when the amount of image data is large, feature matching takes more time. With the increase of sampling rate, the amount of image data decreases rapidly, and the feature matching time also shortens rapidly, which provides a theoretical basis for the multiscale model to improve the matching efficiency. The data size is the same, 3619 × 1825, which makes the matching time between images have little difference. Therefore, the matching time increases linearly with the increase of the number of images in the database. When the amount of image data in the database is large, a higher number of layers should be used; when the amount of image data in the database is small, the number of layers of the model should be reduced to ensure the accuracy of matching. The availability of the proposed method is proved.
The Quest for Outpatient Mastectomy in COVID-19 Era: Barriers and Facilitators
Authors: van Zeelst L. J. , Derksen R. , Wijers C. H. W. , Hegeman J. , Berry R. , de Wilt J. H. W. , Strobbe L. J. A.
Published: June 2022

Background. The rate of inpatient mastectomies remains high despite multiple studies reporting favourably on outpatient mastectomies. Outpatient mastectomies do not compromise quality of patient care and are more efficient than inpatient care. The objective of this study was to evaluate the feasibility of outpatient mastectomy. Materials and Methods. Implementation of an outpatient mastectomy program was evaluated in a retrospective study. All patients who underwent mastectomy between January 2019 and September 2021 were included. Results. 213 patients were enrolled in the study: 62.4% (n = 133) outpatient mastectomies versus 37.6% (n = 80) inpatient mastectomies. A steady rise in outpatient mastectomies was observed over time. The second quarter of 2020, coinciding with the first COVID-19 wave, showed a peak in outpatient mastectomies. The only significant barrier to outpatient mastectomy proved to be bilateral mastectomy. Unplanned return to care was observed in 27.8% of the outpatient versus 36.3% of the inpatient mastectomies (

P
=
0.198

); the reason for unplanned return of care was similar in both groups. Conclusions. Outpatient mastectomy is shown to be feasible and safe with a steady increase during the study period. A barrier to outpatient mastectomy was bilateral mastectomy. Incidence of unplanned return to care or complications did not differ significantly between the outpatient and inpatient cohorts.
Physicochemical Stability Study of Oral Suspension Containing Ruxolitinib in Children with Steroid-Refractory Acute Graft-Versus-Host Disease
Authors: Hinterlang Mélanie , Sebti Maria , Cotteret Camille , Vidal Fabrice , Neven Bénédicte , Cisternino Salvatore , Schlatter Joël
Published: June 2022

Ruxolitinib, used in children with steroid-refractory acute graft-versus-host (GVH) disease, is currently commercially available only as a tablet adult dosage. For the paediatric population, an oral liquid would be an adapted dosage formulation. The aim of this study was to develop ruxolitinib compounded oral suspensions at 2 mg/mL by using commercial tablets in available aqueous vehicle (Inorpha) and to measure its stability at both room temperature and under refrigeration. Chemical stability of suspensions containing ruxolitinib was evaluated for 60 days based on pH, degradation, and drug content. Physical stability of the drug suspension was evaluated by visual aspect and odour. The remaining ruxolitinib concentration of the suspension was at least 95% of the initial concentration after 60 days at both temperatures. The pH, colour, and odour of the suspensions throughout the study remained unchanged with respect to the initial time point.
Cytotoxic Activity, Cell Cycle Inhibition, and Apoptosis-Inducing Potential of Athyrium hohenackerianum (Lady Fern) with Its Phytochemical Profiling
Authors: Elasbali Abdelbaset Mohamed , Al-Soud Waleed Abu , Al-Oanzi Ziad H. , Qanash Husam , Alharbi Bandar , Binsaleh Naif K. , Alreshidi Mousa , Patel Mitesh , Adnan Mohd
Published: June 2022

In the present study, we investigated the cytotoxic effects of Athyrium hohenackerianum ethanolic extract (AHEE) on the proliferation of breast, lung, and colon cancer cells. The AHEE was tested for its effect on the progression of the cell cycle, followed by induction of apoptosis determination by flow cytometry. Real-time qRT-PCR was also utilized to observe the initiation of apoptosis. In addition, GC-MS was performed in order to identify the active phytochemicals present in the AHEE. A cytotoxic activity with an IC50 value of 123.90 μg/mL against HCT-116 colon cancer cells was exhibited by AHEE. Following propidium iodide staining, annexin-V/PI, and clonogenic assays, AHEE treatment results in cell arrest in the S phase, causing an increase in the early and late phases of apoptosis and displaying antiproliferative potential, respectively. The morphological alterations were further monitored using acridine orange/ethidium bromide (AO/EB) staining. When compared with the control cells, features of apoptotic cell death, including nuclear fragmentation, in the AHEE-treated cells were noticed. The apoptosis was also confirmed by detecting the increased expression of p53 and caspase-3 along with the downregulation of Bcl-2. GC-MS analysis revealed that trans-linalool oxide, loliolide, phytol, 4,8,12,16-tetramethylheptadecan-4-olide, and gamma-sitosterol were the major phytochemical constituents. Based on these findings, it can be suggested that AHEE causes cellular death via apoptosis, which should be further explored for the identification of active compounds responsible for these observed effects. Therefore, AHEE can be used in the pharmaceutical development of anticancer agents for cancer therapeutics.
Characterization of the Prognostic Values of CXCL Family in Epstein–Barr Virus Associated Gastric Cancer
Authors: Mu Li , Hu Shun , Li Guoping , Wu Ping , Ren Caihong , Lin Taiyu , Zhang Sheng
Published: June 2022

Background. CXCL family is a class of secreted growth factors signaling through G-protein-coupled receptors, and abnormal expression is associated with the growth and progression of many tumors. However, their prognostic value has been poorly studied in Epstein–Barr virus- (EBV-) associated gastric cancer (EBVaGC). Therefore, it is of great significance to explore the prognostic value of the CXCL family in EBVaGC. Methods. CXCL family mRNA expression was analyzed in STAD data from The Cancer Genome Atlas (TCGA). Kaplan-Meier Plotter was used to assess the prognostic value of the CXCL family. Transcription factors (TFs) and miRNAs associated with the CXCL family were identified by TFCheckpoint, miRWalk, and ViRBase databases. The prognostic model was evaluated using the EBVaGC patient cohort GSE51575. Results. The mRNA expression of CXCL1/3/5/6/8/9/10/11/16 was significantly upregulated, while the expression of CXCL12/14 was downregulated in EBVaGC compared with normal tissues from TCGA-STAD. The mRNA expressions of CXCL9, CXCL10, CXCL11, and CXCL17 in EBVaGCs were higher than those in EBVnGCs, but the mRNA expressions of CXCL6, CXCL12, and CXCL17 were lower than those in EBVnGCs. The mRNA expression levels of CXCL9, CXCL10, and CXCL11 in EBVaGCs were higher than those in EBVnGCs regardless of the tumor stage. High mRNA expression of CXCL8 was associated with better OS in patients with EBVaGC, while high expression of CXCL9 was associated with better OS in patients with EBVnGC. We obtained 10 candidate potential transcription factors (TFs) associated with CXCLs: OTOP3, NKX6-2, NKX2-2, FEV, SMYD1, TRIMSO, TBX10, CDX1, SLC26A3, and ARC. 576 miRNA-mRNA interactions were obtained. Among them, 65 miRNAs were predicted to be correlated with CXCL6, CXCL9, CXCL10, and CXCL11. Similar to the results of TCGA-STAD, the GSE51575 dataset also showed that the mRNA expression levels of CXCL1/3/9/10/11/16 were markedly enhanced in EBVaGC tissues compared with corresponding normal gastric mucosa tissues, while the mRNA expression levels of CXCL12/14 were significantly reduced. The mRNA expression levels of CXCL3/9/10/11/13/17 were increased in EBVaGC compared with EBVnGC tissues. Conclusions. The expression differences of CXCL family members are closely associated with the progression of EBVaGC. Expression of CXCL9/10/11/17 mRNA may be a promising prognostic indicator for EBVaGC patients.
Global Well-Posedness and Analyticity for the Three-Dimensional Incompressible Nematic Liquid Crystal Flows in Scaling Invariant Spaces
Authors: Liu Xuanjiang , Xu Fuyi , Fu Peng
Published: June 2022

The Cauchy problem for the three-dimensional incompressible flows of liquid crystals in scaling invariant spaces is considered. In this work, we exhibit three results. First, we prove the global well-posedness of mild solution for the system without the supercritical nonlinearity∇d2dwhen the norms of the initial data are bounded exactly by the minimal value of the viscosity coefficients. Our second result is a proof of the global existence of mild solution in the time dependent spaces for the system including the term∇d2dfor small initial data. Lastly, we also get analyticity of the solution.
University Network Education and School-Based Platform Based on Smart Campus Data Platform Architecture
Authors: Xia Liping , Guo Dun
Published: June 2022

With the vigorous development of college informatization construction, many colleges and universities have established and applied digital campus platforms. The main research of this paper is the construction and application of the school-based platform of university network education based on smart campus data platform architecture. This article conducts interviews and classroom observations with teachers of different teaching ages. The construction of school-based curriculum system is reflected in the text as the school’s curriculum plan. The average test score of the experimental class is 7.94 points higher than the average score of the control class, which shows that the test score of the experimental class is higher than that of the control class. The experimental data show that the school-based platform of college network education based on the smart campus data platform architecture can effectively improve the learning effect of students, and popularizing it in the construction of the existing school-based network education platform can promote the in-depth development of smart education.
Optimizing Object Storage System by the Object Multi-Tiered Balanced Organization
Authors: Zhang Lei , Feng Dongyu , Lei Chengxi
Published: June 2022

The era of big data has been constantly producing a huge amount of small files that will cause problems such as uneven distribution of copies and massive random readings and writings, resulting in delays in data accessions and degrading performances. By aiming at resolving the problems of an object storage system concerning the organization of small file objects such as layout imbalance, uneven loading, and adaptability of poor data migration, this article introduces a new strategy for object organization called object multi-tiered balanced organization strategy (OMBOS) with improved performance on massive small files in a real object storage system. Apart from the conventional strategy, the OMBOS achieves a multi-level balanced object by establishing weight indicators that reflect the comprehensive performance of nodes, including the balanced distribution of objects between replica sets and the balanced distribution of I/O requests in the replica sets as well as adapting to the equilibrium of the scale changes of the system dynamics. The OMBOS establishes a comprehensive performance evaluation model based on the fuzzy analytic hierarchy process and calculates the performance weights of the nodes of the object storages and replica sets. Then, the consistent hash-based object placement between the replica sets algorithm (BROP) and the I/O-loading balance in the replica set algorithm (IRIB) are utilized to implement performance-weighted objects in the object storage system through a tiered organization when the performance weights are taken into account. When the system scale changes flexibly, data migration is the only performed process in the nodes by adding or removing nodes, so data will not be migrated between existing nodes. Hence, the amount of data migration reaches the theoretical setting. Experiments show that the OMBOS achieves a balanced layout of objects based on performance weights, which meets the balancing and adaptability requirements of data organization. When compared to the original layout strategy through the balanced layout of objects, it performs nearly double the random access method.
Effectiveness and Safety of Levothyroxine Tablets Combined with Iodine-131 in the Treatment of Thyroid Cancer
Authors: Bai Yang , Jin Jian , Liu Yonghong , Zhang Buyong , Zhang Bo , Li Jie
Published: June 2022

Objective. To explore the effectiveness of levothyroxine tablets combined with iodine-131 in thyroid cancer patients after radical thyroidectomy and the effect on their serum thyroglobulin (Tg) and thyroglobulin antibody (TgAb) levels. Methods. A total of 70 thyroid cancer patients receiving radical thyroidectomy in our hospital from July 2015 to April 2016 were recruited and were assigned via different treatment methods (1 : 1) to receive either levothyroxine tablets (observation group) or levothyroxine tablets plus iodine-131 (control group). Outcome measures included treatment efficiency, 1, 3, and 5-year recurrence and metastasis, serum Tg and TgAb levels, postoperative survival, and adverse reactions. Results. The total effective rate of treatment in the control group was significantly higher than that in the observation group (

P
<
0.05

). There was no significant difference in cancer recurrence and metastasis rate between the two groups one year postoperatively (

P
>
0.05

). The rate of cancer recurrence and metastasis in the control group was significantly lower than that in the observation group 3 and 5 years after surgery (

P
<
0.05

). Before treatment, there was no significant difference in serum Tg and TgAb levels between the two groups (

P
>
0.05

). After treatment, serum Tg and TgAb levels decreased in both groups, with lower results in the control group (

P
<
0.05

). There was no significant difference in the 1 and 3-year survival rates between the two groups (

P
>
0.05

). The 5-year survival rate in the control group was significantly higher than that in the observation group (

P
<
0.05

). There was no significant difference in adverse reactions between the two groups (

P
>
0.05

). Conclusion. Levothyroxine tablets combined with iodine-131 for thyroid cancer patients undergoing radical thyroidectomy effectively could improve the treatment efficiency, reduce the risk of cancer recurrence and metastasis after surgery, lower the serum Tg and TgAb levels of patients, and prolong the survival of patients, with a high safety profile. Further trials are, however, required prior to clinical promotion.
Iodine Deficiency in Patients with Hypothyroidism: A Pilot Study
Authors: van Veggel Kristin Mariëlla , Ivarson Dina Mehus , Rondeel Jan Maria Martinus , Mijnhout Gerritje Sophie
Published: June 2022

Objective. Worldwide, 21 countries have insufficient iodine in their diets. Persistent iodine deficiency may result in hypothyroidism. The aim of this study is to determine whether iodine measurements can be used to determine the prevalence of iodine deficiency in patients with (subclinical) hypothyroidism compared to a control group. Design. A prospective cohort pilot study was performed at the Internal Medicine Outpatient Clinic of Isala, a large teaching hospital in Zwolle, the Netherlands. Patients. This study consisted of two groups of 24 adult patients each: a group of consecutive patients presenting with overt or subclinical hypothyroidism and a control group of euthyroid patients with type 1 diabetes mellitus. Measurements. All patients collected 24-hour urine. Iodine status was determined using urinary iodine concentration (UIC), urinary iodine excretion (UIE), and iodine creatinine ratio (I : Cr). Iodine deficiency was defined as an iodine concentration <100 µg/L for UIC, iodine level <125 µg for UIE, and <0.13 µmol/mmol for I : Cr. Results. According to UIE and UIC measurements, 54.2% of hypothyroid patients were iodine-deficient compared to 41.7–45.8% in the control group. According to the I : Cr measurement 91.7% of hypothyroid patients were iodine-deficient compared to 87.5% in the control group. No significant difference was seen between the two groups. No correlation was found between thyroid-stimulating hormone (TSH) level and iodine deficiency. Conclusions. Iodine deficiency is prevalent in both hypothyroid patients and euthyroid patients. Because there is no significant difference between the groups, a single 24-hour urine or spot urine sample to determine UIC, UIE, and I : Cr, seems not suitable to determine iodine status in an individual participant.
ZNF165 Is Involved in the Regulation of Immune Microenvironment and Promoting the Proliferation and Migration of Hepatocellular Carcinoma by AhR/CYP1A1
Authors: Liu Peng , Zhou Yan , Dong Xin , Zheng Biao , Liang Bo , Liang Rui , Liu Zhong , Li Li , Gong Peng
Published: June 2022

The strong tumorigenic capacity and treatment resistance made hepatocellular carcinoma (HCC) a huge threat to public health. ZNF165, the kruppel family of zinc-finger-containing transcription factors, is expressed in HCC; however, its specific role in HCC and the molecular mechanism are yet to be elucidated. In this study, we observed that ZNF165 was overexpressed in liver cancer tissues and the immune microenvironment; higher ZNF165 expression was correlated with lower overall survival in liver cancer patients. The ZNF165 knockdown in Bel7402 cells revealed the impairment of the tryptophan/kynurenine/AhR/CYP1A1 axis. Moreover, the knockdown of CYP1A1 significantly inhibited the proliferation and migration of HCC cells, and ZNF165 promoted the transcriptional activity of AhR by facilitating the nuclear translocation of CYP1A1. In conclusion, the present study argued that ZNF165 was highly expressed in liver tissues and the immune microenvironment. ZNF165 promoted the proliferation and migration of HCC cells by activating the tryptophan/kynurenine/AhR/CYP1A1 axis and promoting the expression of CYP1A1.
Prediction of Photovoltaic Power by ANN Based on Various Environmental Factors in India
Authors: Suresh Kumar B. , Mahilraj Jenifer , Chaurasia R. K. , Dalai Chitaranjan , Seikh A. H. , Mohammed S. M. A. K. , Subbiah Ram , Diriba Abdi
Published: June 2022

Extreme weather conditions, which affect photovoltaic output power, can have a major impact on electricity generated by PV systems. In India, an annual PV power density of 2000kWh/m-2 may be used. Renewable energy (RE) is expected to play a rising part in the nations in coming years. The sun’s radiation is the primary source of renewable energy (RE). With the objective of predicting PV output power with the least amount of error in mind, it is vital to analyse the impact of major environmental parameters on it. The researchers looked at a variety of environmental factors in this study, including irradiance, humidity levels, meteorological conditions, wind velocity, PV global temperature and dust deposition. Countries such as India would gain immensely from this since it will increase the quantity of PV power generated in their national networks. ANN-based prediction models and multiple regression models were used to predict PV system hourly power output. There were three ANN models that predicted PV output power with RMSEs of 2.1436, 6.1555, and 5.3551, respectively, utilising all features using the correlation feature selection (CFS) or relief feature selection (ReliefF) approaches. It is possible to reduce bias to enhance accuracy by employing two distinct bias calculation methodologies, which were applied in this study. For example, the ANN model outperforms linear regression, M5P decision trees and GAUSSIAN process regression (GPR) models in terms of performance.
Transmission Line Distance Protection Algorithm Based on Bayesian Inference
Authors: Tiferes Rodrigo Rozenblit , Manassero Junior Giovanni
Published: June 2022

This paper presents a distance protection method based on estimating the resistances and inductances seen by the relay using a least-squares (LS) approach combined with the application of Bayesian inference (BI) to determine fault probabilities in the protected zone over time. The use of BI in the presented algorithm increases the security and reliability of the LS-based line protection approach, which, although fast, may yield impedance estimates with numerical inaccuracies and therefore configures a solution capable of detecting faults internal to the protected zone rapidly and dependably. The authors tested the proposed algorithm using data sets obtained from transmission line fault simulations performed in Alternative Transients Program (ATP), which considered noisy measurements, current transformer (CT) saturation, capacitive-coupling voltage transformer (CCVT) transients, switching onto fault, close-in faults, frequency variations, uncertainties in the line’s parameters, and power swings. Furthermore, the authors tested the presented method against measurements recorded by field protection equipment during seventy-nine actual fault events on four existing 500 [kV] lines. The results indicate that the proposed algorithm is a fast, secure, and reliable distance protection solution and that using BI to the LS-based distance protection approach increases security while maintaining fast fault detection.
Oncological and Functional Outcomes after Hemicortical Resection and Biological Reconstruction Using Allograft for Parosteal Osteosarcoma of the Distal Femur
Authors: Savvidou Olga D , Goumenos Stavros , Trikoupis Ioannis , Kaspiris Angelos , Melissaridou Dimitra , Gavriil Panagiotis , Georgoulis Jimmy , Papagelopoulos Panayiotis J
Published: June 2022

Background. Parosteal osteosarcoma (PAOS) is a surface osteosarcoma. Treatment options include wide excision and endoprosthetic or allograft. However, due to the low local recurrence and metastasis rate, when it appears in the posterior surface of the distal femur, the lesion can be managed with hemicortical wide resection and biological reconstruction with hemicortical allograft. The purpose of this study is to evaluate the oncological and functional outcomes of patients with parosteal osteosarcoma (PAOS) of the posterior cortex of the distal femur who underwent biological reconstruction after hemicortical resection. Methods. Eleven patients who underwent wide tumor resection and defect reconstruction of the posterior surface of the distal femur using hemicortical allograft were retrospectively studied. Local recurrence, metastasis, complications, and the functional outcome using the Musculoskeletal Tumor Society (MSTS) scoring system were evaluated. Results. The average postoperative follow-up period was 53.64 months (range, 30 to 84 months). At the latest follow-up, all patients had no evidence of disease without metastases. One patient with local recurrence underwent revision surgery with fibula autograft reconstruction. The mean MSTS score was 93.45 ± 3.56. Conclusions. Treatment of patients with PAOS of the posterior aspect of the distal femur with hemicortical resection and allograft reconstruction has satisfactory oncological and functional outcome and low complication rates.
Phytochemical Characterization and Pharmacological Properties of Lichen Extracts from Cetrarioid Clade by Multivariate Analysis and Molecular Docking
Authors: Ureña-Vacas Isabel , González-Burgos Elena , De Vita Simona , Divakar Padreep K. , Bifulco Giuseppe , Gómez-Serranillos M. Pilar
Published: June 2022

Introduction. Lichens, due to the presence of own secondary metabolites such as depsidones and depsides, became a promising source of health-promoting organisms with pharmacological activities. However, lichens and their active compounds have been much less studied. Therefore, the present study aims to evaluate for the first time the antioxidant capacity and enzyme inhibitory activities of 14 lichen extracts belonging to cetrarioid clade in order to identify new natural products with potential pharmacological activity. Materials and Methods. In this study, an integrated strategy was applied combining multivariate statistical analysis (principal component analysis and hierarchical cluster analysis), phytochemical identification, activity evaluation (in vitro battery of antioxidant assays FRAP, DPPH, and ORAC), and enzyme inhibitory activity against acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) and molecular profiling with in silico docking studies of the most promising secondary metabolites. Results. Among fourteen lichen samples, Dactylina arctica stands out for its higher antioxidant capacities, followed by Nephromopsis stracheyi, Tuckermannopsis americana, Vulpicida pinastri, and Asahinea scholanderi. Moreover, Asahinea scholanderi and Cetraria cucullata extracts were the best inhibitors of AChE and BuChE. The major secondary metabolites identified by HPLC were alectoronic acid and α-collatolic acid for Asahinea scholanderi and usnic acid and protolichesterinic acid for Cetraria cucullata. Molecular docking studies revealed that alectoronic acid exhibited the strongest binding affinity with both AChE and BuChE with and without water molecules. Conclusions. Our results concluded that these species could be effective in the treatment of neurodegenerative diseases, being mandatory further investigation in cell culture and in vivo models.
Sub-Lorentzian Geometry of Curves and Surfaces in a Lorentzian Lie Group
Authors: Liu Haiming , Guan Jianyun
Published: June 2022

We consider the sub-Lorentzian geometry of curves and surfaces in the Lie group

E

1
,
1

.

Firstly, as an application of Riemannian approximants scheme, we give the definition of Lorentzian approximants scheme for

E

1
,
1

which is a sequence of Lorentzian manifolds denoted by

E

λ

1

,

λ

2

L

. By using the Koszul formula, we calculate the expressions of Levi-Civita connection and curvature tensor in the Lorentzian approximants of

E

λ

1

,

λ

2

L

in terms of the basis

E

1

,

E

2

,

E

3

.

These expressions will be used to define the notions of the intrinsic curvature for curves, the intrinsic geodesic curvature of curves on surfaces, and the intrinsic Gaussian curvature of surfaces away from characteristic points. Furthermore, we derive the expressions of those curvatures and prove two generalized Gauss-Bonnet theorems in

E

λ

1

,

λ

2

L

.
Classification of Diabetic Retinopathy Based on Multiscale Hybrid Attention Mechanism and Residual Algorithm
Authors: Miao Yue , Tang Siyuan
Published: June 2022

The key of classification diagnosis of diabetic retinopathy lies in the recognition of the features of small lesions, and it is difficult to extract the features of too small lesions by general extraction methods. In order to solve the problem that it is difficult to extract small focus, a hybrid attention mechanism combined with residual convolutional neural network model algorithm is proposed to improve the classification accuracy of diabetic retinopathy. Firstly, a multiscale deep learning network model with hybrid attention is designed, and then, the high-level features of images are extracted by using the network model; finally, after balancing different types of samples by sampling algorithm, the spatial attention and channel attention of the extracted features are enhanced; small-step learning strategy, loss function, and initial parameters are used to optimize the performance of the network model. The classifier based on multiscale hybrid attention network is used to judge the five classifications. Experimental results show that the proposed algorithm can learn more features of small targets and can effectively improve the classification performance of diabetic retina. An experimental test was performed on Kaggle’s publicly available dataset of diabetic retinas, and the classification accuracy was 93.8%, compared to some existing classification models; the method proposed in this paper can achieve better classification results for diabetic retinopathy.
Qualitative Analysis of a Spatiotemporal Prey‐Predator Model with Additive Allee Effect and Fear Effect
Authors: Ke Changcheng , Yi Ming , Guo Yanfeng
Published: June 2022

A diffusive predator‐prey system with both the additive Allee effect and the fear effect in the prey subject to Neumann boundary conditions is considered in this paper. Firstly, non‐negative and non‐trivial solution a priori estimations are shown. Furthermore, for specific parameter ranges, the absence of non‐constant positive solutions is demonstrated. Secondly, we use the linearized theory to investigate the stability of non‐negative constant solutions. The spatially homogeneous and non‐homogeneous periodic solutions, as well as non‐constant steady state solutions, are next investigated by using Allee effect parameters as the bifurcation parameter. Finally, numerical simulation is used to illustrate some theoretical results.
Cloud Data Access Prevention Method in Face Recognition Technology Based on Computer Vision
Authors: Qian Mingzhu , Wang Xiaobao
Published: June 2022

With the development of cloud technology and the innovation of information network technology, people’s dependence on the network has gradually increased, and there are some loopholes in cloud data access. The traditional account permission model can no longer meet the conditions of cloud data access alone. If the visitor temporarily leaves the computer or goes out in an emergency, the data are likely to be leaked. Based on the importance and concern of this issue, some scholars have proposed an authentication system combined with biometric face recognition, but the traditional face recognition system has certain security risks. Such as using face pictures and videos to deceive the system, tampering with face templates, etc. Based on this, this paper proposes an encrypted face authentication system based on CNN neural network. Through the authentication of face data, the content transmission of each part is carried out in the form of ciphertext to ensure the security of information. The experimental results in this paper show that the authentication accuracy rate of DeepID is 94% when it is not encrypted, and the authentication accuracy rate decreases slightly after encryption, which is 93.3%. It is similar in other cases. When the network structure and data set remain unchanged, encryption reduces the authentication accuracy rate by 0.3%–2.4%. It can be seen that the scheme proposed in this chapter improves the system security at the cost of a smaller accuracy rate.
Microglia in Alzheimer’s Disease: A Favorable Cellular Target to Ameliorate Alzheimer’s Pathogenesis
Authors: Sumsuzzman Dewan Md. , Uddin Md. Sahab , Kabir Md. Tanvir , Hasana Sharifa , Perveen Asma , Alanazi Ibtesam S. , Albadrani Ghadeer M. , Abdel-Daim Mohamed M. , Ashraf Ghulam Md
Published: June 2022

Microglial cells serve as molecular sensors of the brain that play a role in physiological and pathological conditions. Under normal physiology, microglia are primarily responsible for regulating central nervous system homeostasis through the phagocytic clearance of redundant protein aggregates, apoptotic cells, damaged neurons, and synapses. Furthermore, microglial cells can promote and mitigate amyloid β phagocytosis and tau phosphorylation. Dysregulation of the microglial programming alters cellular morphology, molecular signaling, and secretory inflammatory molecules that contribute to various neurodegenerative disorders especially Alzheimer’s disease (AD). Furthermore, microglia are considered primary sources of inflammatory molecules and can induce or regulate a broad spectrum of cellular responses. Interestingly, in AD, microglia play a double-edged role in disease progression; for instance, the detrimental microglial effects increase in AD while microglial beneficiary mechanisms are jeopardized. Depending on the disease stages, microglial cells are expressed differently, which may open new avenues for AD therapy. However, the disease-related role of microglial cells and their receptors in the AD brain remain unclear. Therefore, this review represents the role of microglial cells and their involvement in AD pathogenesis.