bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of superhydrophobic sand mulching on evapotranspiration and phenotypic responses in tomato (Solanum lycopersicum) plants under normal and reduced irrigation
Authors: Odokonyero Kennedy , Gallo Adair , Dos Santos Vinicius , Mishra Himanshu
Published: April 2022

Irrigated agriculture in arid and semi‐arid regions is a vital contributor to the global food supply. However, these regions endure massive evaporative losses that are compensated by exploiting limited freshwater resources. To increase water‐use efficiency in these giga‐scale operations, plastic mulches are utilized; however, their non‐biodegradability and eventual land‐filling renders them unsustainable. In response, we have developed superhydrophobic sand (SHS) mulching technology that is comprised of sand grains or sandy soils with a nanoscale coating of paraffin wax. Here, we investigate the effects of 1 cm‐thick SHS mulching on the evapotranspiration and phenotypic responses of tomato (Solanum lycopersicum) plants as a model system under normal and reduced irrigation inside controlled growth chambers. Experimental results reveal that under either irrigation scenario, SHS mulching suppresses evaporation and enhances transpiration by 78% and 17%, respectively relative to the unmulched soil. Comprehensive phenotyping revealed that SHS mulching enhanced root xylem vessel diameter, stomatal aperture, stomatal conductance, and chlorophyll content index by 21%, 25%, 28%, and 23%, respectively, in comparison with the unmulched soil. Consequently, total fruit yields, total dry mass, and harvest index increased in SHS‐mulched plants by 33%, 20%, and 16%, respectively compared with the unmulched soil. We also provide mechanistic insights into the effects of SHS mulching on plant physiological processes. These results underscore the potential of SHS for realizing food–water security and greening initiatives in arid regions.
Risk assessment and resistance inheritance of triflumezopyrim resistance in Laodelphax striatellus
Authors: Zhang Shuirong , Gu Fuchuan , Du Ying , Li Xuyang , Gong Changwei , Pu Jian , Liu Xuemei , Wang Xuegui
Published: April 2022

BACKGROUND

Laodelphax striatellus (Fallén) (Hemiptera: Delphacidae) is one of the most important insect pests of rice, and it has been able to develop strong resistance to many insecticides. Triflumezopyrim, a new type of mesoionic insecticide developed by Corteva Agriscience, showed high biological activity in controlling piercing‐sucking insect pests such as planthopper and leafhopper.

RESULTS

In this study, we continuously selected a susceptible laboratory stain (Unsel) of L. striatellus for 16 generations by exposing it to triflumezopyrim in the laboratory. A 45.1‐fold triflumezopyrim‐resistant strain (Tri‐sel) was established, in which cross‐resistance to nitenpyram and acetamiprid was not detected. The realized heritability (h2) of the Tri‐sel strain was estimated at 0.13. The mortalities of the testing F1 (the offspring of a cross between Unsel and Tri‐sel strains) suggested that the resistance of L. striatellus to triflumezopyrim was autosomal and incompletely dominant, as well as a polygenic inheritance. In addition, the results of synergist experiment showed that P450s potentially contributed to the triflumezopyrim resistance. The activities of detoxification enzymes in the Unsel and Tri‐sel strains indicated that the activity of P450s in the Tri‐sel strain was significantly increased, consistent with the results of synergist experiments. Furthermore, 12 P450 genes demonstrated significant up‐regulation.

CONCLUSIONS

L. striatellus has a certain risk of resistance to triflumezopyrim after continuous selection. Triflumezopyrim resistance did not result in cross‐resistance to neonicotinoid insecticides. The up‐regulation of multiple P450 genes may mediate triflumezopyrim resistance in L. striatellus. © 2022 Society of Chemical Industry.
Fluorescence of Single Rhodamine Molecules Near the Surface of Gold
Authors: Fang Liping , Li Haolin , Ma Xuhang , Song Qiuming , Zhu Xi , Chen Rui
Published: April 2022

Fluorescent properties of single Rhodamine molecules at different distances to the surface of a high‐quality polycrystalline gold film are investigated by the time‐correlated single‐photon counting technique. The fluorescence lifetime and the fluorescence intensity of the dye molecules as a function of their distance to the gold surface are modeled quantitatively by a classical model for a horizontal electric dipole. The analysis shown herein represents a useful tool to model and further to control molecular fluorescence near complex plasmonic structures, where delicate manipulation of fluorescence emission intensity is of paramount importance.
Moving towards sustainable environmental development for BRICS: Investigating the asymmetric effect of natural resources on CO2
Authors: Caglar Abdullah Emre , Guloglu Bulent , Gedikli Ayfer
Published: April 2022

Environmental sustainability has become the most critical global agenda of the 21st century. The Paris Agreement goals to keep the global temperature rise below 2 compared to the pre‐industrial period. BRICS, which use intensive natural resources, hold regular meetings, and announce policies to comply with the Paris Agreement. This article aims to help BRICS achieve their sustainable development goals. In order to achieve this aim, the relationship between renewable energy consumption, natural resources, and CO2 emissions is explored in depth using the non‐linear panel autoregressive distributed lag method controlling for economic growth and foreign direct investments. Robust results are obtained by allowing for heterogeneity and cross‐section dependence in econometric analysis. Contrary to the previous literature, it has been shown in the empirical analysis that the impact of natural resources on CO2 emissions is not the same in both the long and short‐run. In the long‐run, negative and positive changes in natural resources increase environmental degradation, while foreign direct investments improve environmental quality. In addition, it seems that renewable energy sources have not reached the level to enhance environmental quality. The empirical results indicated that natural resource and renewable energy consumption findings are novel and bring a different perspective to the existing literature. BRICS should take measures to ensure sustainable use of natural resources in order to minimize dependence on fossil fuels. China, Russia, India, and South Africa should increase the share of RSE in the total energy mix and support renewable energy infrastructure investments for moving towards sustainable environmental development.
Chiral Diuranyl(VI) Complexes and Their Catecholase Activities: Experimental and Theoretical Insights
Authors: Ghosh Sabari , Srivastava Ankit K. , Sharma Manju , Pal Samudranil
Published: April 2022

Two enantiomeric pairs of complexes, [(UO2)2(R/S‐L1)2(H2O)2] ⋅ 2MeCN and [(UO2)2(R/S‐L2)2(Me2NCHO)2] (H2R/S‐L1=R/S‐N‐(salicylidene)‐2‐amino‐1‐propanol and H2R/S‐L2=R/S‐N‐(2‐hydroxy‐1‐naphthylidene)‐2‐amino‐1‐propanol) and their characterization by elemental analysis, mass spectrometry, various spectroscopy and X‐ray crystallography are reported. In each complex, trans‐UO22+ units are in edge‐shared NO4 pentagonal planes formed by the two alkoxide end bridging ONO‐donor (R/S‐L1/2)2− and the two solvent molecules. The first pair is inactive, while the second pair is active towards catecholase activity. The mass spectra suggest formation of the adduct {complex−Me2NCHO+substrate} and EPR spectra indicate a radical pathway for the catalytic reaction. Computational studies indicate that primarily the binding strength of the solvent molecule dictates the adduct formation and hence the catalytic inactivity/activity. Based on experimental observations and theoretical calculations a four step mechanism has been proposed for the catalytic activities of the second pair of complexes.
Imidazolium‐Based Energetic Materials
Authors: Sevilia Sagi , Parvari Galit , Bernstein Jonathan , Fridman Natalia , Grinstein Dan , Gottlieb Levi , Eichen Yoav , Szpilman Alex M.
Published: April 2022

We show that 1‐(2‐hydroxyethyl)‐1H‐imidazol‐3‐ium and 1‐(2‐hydroxyethyl)‐3‐methyl‐1H‐imidazol‐3‐ium salts, as well as the salts of their nitrite esters, that include oxidizing anions (so‐called explosphores) such as nitrate, picrate and perchlorate„ are endowed with high enthalpies of decomposition, high decomposition temperatures, and high densities. This combined with detonation velocities and pressures calculated using Explo5, indicates that especially the perchlorate salts have potential as energetic materials. All the studied salts are easily preparable in up to gram scale through two or three synthetic steps from simple imidazole. Many of these salts are ionic liquids, which may render them useful as energetic plasticizers or gel filled materials.
Elucidating Design Principles for Engineering Cell‐Derived Vesicles to Inhibit SARS‐CoV‐2 Infection
Authors: Gunnels Taylor F. , Stranford Devin M. , Mitrut Roxana E. , Kamat Neha P. , Leonard Joshua N.
Published: April 2022

The ability of pathogens to develop drug resistance is a global health challenge. Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) presents an urgent need wherein several variants of concern resist neutralization by monoclonal antibody (mAb) therapies and vaccine‐induced sera. Decoy nanoparticles—cell‐mimicking particles that bind and inhibit virions—are an emerging class of therapeutics that may overcome such drug resistance challenges. To date, quantitative understanding as to how design features impact performance of these therapeutics is lacking. To address this gap, this study presents a systematic, comparative evaluation of various biologically derived nanoscale vesicles, which may be particularly well suited to sustained or repeated administration in the clinic due to low toxicity, and investigates their potential to inhibit multiple classes of model SARS‐CoV‐2 virions. A key finding is that such particles exhibit potent antiviral efficacy across multiple manufacturing methods, vesicle subclasses, and virus‐decoy binding affinities. In addition, these cell‐mimicking vesicles effectively inhibit model SARS‐CoV‐2 variants that evade mAbs and recombinant protein‐based decoy inhibitors. This study provides a foundation of knowledge that may guide the design of decoy nanoparticle inhibitors for SARS‐CoV‐2 and other viral infections.
Online multitarget tracking system for autonomous vehicles using discriminative dictionary learning with embedded auto‐encoder algorithm
Authors: Gu Xiaoqing , Jiang Yizhang
Published: April 2022

With the advancements in 5G network and mobile edge computing technology, autonomous vehicle technology has gained new development opportunities. Multitarget tracking becomes the research hotspots in autonomous vehicles. Since many factors such as motion blur, partial occlusion, and illumination changes affect the performance of target tracking, the problem of target tracking is still an open topic. In this article, inspired by the strong discriminative ability of dictionary learning, the discriminative dictionary learning with embedded auto‐encoder (DDLEA) algorithm is developed for the multitarget tracking system. The DDLEA algorithm integrates the auto‐encoder into the dictionary learning framework and learns sparse representations while preserving the local structure and discriminative information of data. The learned dictionary model has the strong recognition ability. Further, a multitarget tracking system is developed based on the proposed DDLEA algorithm and the hierarchical data association scheme. Based on the target confidence in the STKSVD model, the hierarchical data association method first uses the Hungarian algorithm to complete the preliminary matching of high confidence targets, and then further tracks the low confidence targets to improve the tracking ability. Experiments are carried out the public MOT 2015 dataset. Compared with several popular multitarget tracking algorithms, the tracking performance of our system is satisfactory.
Joint Gaussian graphical model estimation: A survey
Authors: Tsai Katherine , Koyejo Oluwasanmi , Kolar Mladen
Published: April 2022

Graphs representing complex systems often share a partial underlying structure across domains while retaining individual features. Thus, identifying common structures can shed light on the underlying signal, for instance, when applied to scientific discovery or clinical diagnoses. Furthermore, growing evidence shows that the shared structure across domains boosts the estimation power of graphs, particularly for high‐dimensional data. However, building a joint estimator to extract the common structure may be more complicated than it seems, most often due to data heterogeneity across sources. This manuscript surveys recent work on statistical inference of joint Gaussian graphical models, identifying model structures that fit various data generation processes.

This article is categorized under:

Data: Types and Structure > Graph and Network Data

Statistical Models > Graphical Models
Use of a Steerable Sheath for Completely Femoral Access in Branched Endovascular Aortic Repair Compared to Upper Extremity Access
Authors: Hauck Sven R. , Eilenberg Wolf , Kupferthaler Alexander , Kern Maximilian , Dachs Theresa-Marie , Wressnegger Alexander , Neumayer Christoph , Loewe Christian , Funovics Martin A.
Published: April 2022

Purpose

To compare bridging stent graft (BSG) implantation in downward oriented branches in branched endovascular aortic repair (bEVAR), using a commercially available steerable sheath from an exclusively femoral access (TFA) with traditional upper extremity access (UEA).

Methods

In a retrospective cohort study, 7 patients with 19 branches in the TFA cohort received BSG insertion using the Medtronic Heli FX steerable sheath from a femoral access, and 10 patients with 32 branches in the UEA cohort from a brachial approach. Technical success, total intervention time, fluoroscopy time, branch cannulation time, and complication rate were recorded.

Results

Technical success was 19/19 branches in the TFA and 31/32 in the UEA cohort. The mean branch cannulation time was considerably shorter in the TFA group (17 vs. 29 min, p = 0.003), and total intervention time tended to be shorter (169 vs. 217 min, p = 0.176).

Conclusion

Using a commercially available steerable sheath allowed successful cannulation of all branches in this cohort and was associated with significantly shorter branch cannulation times. Potentially, this technique can lower the stroke and brachial puncture site complication risk as well as reduce total intervention time and radiation dose.

Level of Evidence

2b, retrospective cohort study.
CT-monitored minimal ablative margin control in single-session microwave ablation of liver tumors: an effective strategy for local tumor control
Authors: Joo Ijin , Morrow Kenneth W. , Raman Steven S. , McWilliams Justin P. , Sayre James W. , Lu David S.
Published: April 2022

Objectives

To investigate the usefulness of minimal ablative margin (MAM) control by intra-procedural contrast-enhanced CT (CECT) in microwave ablation (MWA) of liver tumors.

Methods

A total of 334 consecutive liver tumors (240 hepatocellular carcinomas [HCCs] and 94 colorectal liver metastases [CRLMs]) in 172 patients treated with percutaneous MWA were retrospectively included. MAM of each tumor was assessed after expected ablation completion using intra-procedural CECT, allowing within-session additional ablation to any potentially insufficient margin. On immediate post-MWA MRI, complete ablation coverage of tumor and final MAM status were determined. The cumulative local tumor progression (LTP) rate was estimated by using the Kaplan-Meier method. To identify predictors of LTP, Cox regression analysis with a shared frailty model was performed.

Results

Intra-procedural CECT findings prompted additional ablation in 18.9% (63/334) of tumors. Final complete ablation coverage of tumor and sufficient MAM were determined by MRI to be achieved in 99.4% (332/334) and 77.5% (259/334), and their estimated 6-month, 1-year, and 2-year LTP rates were 3.2%, 7.5%, and 12.9%; and 1.0%, 2.1%, and 6.9%, respectively. Insufficient MAM on post-MWA MRI, perivascular tumor location, and tumor size (cm) were independent risk factors for LTP (hazard ratio = 14.4, 6.0, and 1.1, p < 0.001, p = 0.003, and p = 0.011, respectively), while subcapsular location and histology (HCC vs CRLM) were not.

Conclusions

In MWA of liver tumors, intra-procedural CECT monitoring of minimal ablative margin facilitates identification of potentially suboptimal margins and guides immediate additional intra-session ablation to maximize rates of margin-sufficient ablations, the latter being a highly predictive marker for excellent long-term local tumor control.

Key Points

• In MWA of liver tumors, intra-procedural CECT can identify potentially suboptimal minimal ablative margin, leading to immediate additional ablation in a single treatment session.

• Achieving a finally sufficient ablative margin through the MWA with intra-procedural CECT monitoring of minimal ablative margin results in excellent local tumor control.
Feasibility of an accelerated 2D-multi-contrast knee MRI protocol using deep-learning image reconstruction: a prospective intraindividual comparison with a standard MRI protocol
Authors: Herrmann Judith , Keller Gabriel , Gassenmaier Sebastian , Nickel Dominik , Koerzdoerfer Gregor , Mostapha Mahmoud , Almansour Haidara , Afat Saif , Othman Ahmed E.
Published: April 2022

Objectives

The aim of this study was to evaluate the image quality and diagnostic performance of a deep-learning (DL)–accelerated two–dimensional (2D) turbo spin echo (TSE) MRI of the knee at 1.5 and 3 T in clinical routine in comparison to standard MRI.

Material and methods

Sixty participants, who underwent knee MRI at 1.5 and 3 T between October/2020 and March/2021 with a protocol using standard 2D–TSE (TSES) and DL–accelerated 2D–TSE sequences (TSEDL), were enrolled in this prospective institutional review board–approved study. Three radiologists assessed the sequences regarding structural abnormalities and evaluated the images concerning overall image quality, artifacts, noise, sharpness, subjective signal-to-noise ratio, and diagnostic confidence using a Likert scale (1–5, 5 = best).

Results

Overall image quality for TSEDL was rated to be excellent (median 5, IQR 4–5), significantly higher compared to TSES (median 5, IQR 4 – 5, p < 0.05), showing significantly lower extents of noise and improved sharpness (p < 0.001). Inter- and intra-reader agreement was almost perfect (κ = 0.92–1.00) for the detection of internal derangement and substantial to almost perfect (κ = 0.58–0.98) for the assessment of cartilage defects. No difference was found concerning the detection of bone marrow edema and fractures. The diagnostic confidence of TSEDL was rated to be comparable to that of TSES (median 5, IQR 5–5, p > 0.05). Time of acquisition could be reduced to 6:11 min using TSEDL compared to 11:56 min for a protocol using TSES.

Conclusion

TSEDL of the knee is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared to TSES, reducing the acquisition time about 50%.

Key Points

• Deep-learning reconstructed TSE imaging is able to almost halve the acquisition time of a three-plane knee MRI with proton density and T1-weighted images, from 11:56 min to 6:11 min at 3 T.

• Deep-learning reconstructed TSE imaging of the knee provided significant improvement of noise levels (p < 0.001), providing higher image quality (p < 0.05) compared to conventional TSE imaging.

• Deep-learning reconstructed TSE imaging of the knee had similar diagnostic performance for internal derangement of the knee compared to standard TSE.
Short- and long-term effect of high versus low-to-moderate intensity exercise to optimise health-related quality of life after oncological treatment—results from the Phys-Can project
Authors: Ax Anna-Karin , Johansson Birgitta , Lyth Johan , Nordin Karin , Börjeson Sussanne
Published: April 2022

Purpose

This study aimed to evaluate the effect of high intensity (HI) vs low-to-moderate intensity (LMI) exercise on health-related quality of life (HRQoL) up to 18 months after commencement of oncological treatment in patients with breast, colorectal or prostate cancer. In addition, we conducted a comparison with usual care (UC).

Methods

Patients scheduled for (neo)adjuvant oncological treatment (n = 577) were randomly assigned to 6 months of combined resistance and endurance training of HI or LMI. A longitudinal descriptive study (UC) included participants (n = 89) immediately before the RCT started. HRQoL was assessed by EORTC QLQ-C30 at baseline, 3, 6 and 18 months (1 year after completed exercise intervention) follow-up. Linear mixed models were used to study the groups over time.

Results

Directly after the intervention, HI scored significant (P = 0.02), but not clinically relevant, higher pain compared with LMI. No other significant difference in HRQoL was found between the exercise intensities over time. Clinically meaningful improvements in HRQoL over time were detected within both exercise intensities. We found favourable significant differences in HRQoL in both exercise intensities compared with UC over time.

Conclusion

This study adds to the strong evidence of positive effect of exercise and shows that exercise, regardless of intensity, can have beneficial effects on HRQoL during oncological treatment and also for a substantial time after completion of an exercise intervention. In this study, for one year after.

Implications for cancer survivors

Patients can be advised to exercise at either intensity level according to their personal preferences, and still benefit from both short-term and long-term improvements in HRQoL.
Immersive machine learning for social attitude detection in virtual reality narrative games
Authors: Dobre Georgiana Cristina , Gillies Marco , Pan Xueni
Published: April 2022

People can understand how human interaction unfolds and can pinpoint social attitudes such as showing interest or social engagement with a conversational partner. However, summarising this with a set of rules is difficult, as our judgement is sometimes subtle and subconscious. Hence, it is challenging to program Non-Player Characters (NPCs) to react towards social signals appropriately, which is important for immersive narrative games in Virtual Reality (VR). We collaborated with two game studios to develop an immersive machine learning (ML) pipeline for detecting social engagement. We collected data from participants-NPC interaction in VR, which was then annotated in the same immersive environment. Game design is a creative process and it is vital to respect designer’s creative vision and judgement. We therefore view annotation as a key part of the creative process. We trained a reinforcement learning algorithm (PPO) with imitation learning rewards using raw data (e.g. head position) and socially meaningful derived data (e.g. proxemics); we compared different ML configurations including pre-training and a temporal memory (LSTM). The pre-training and LSTM configuration using derived data performed the best (84% F1-score, 83% accuracy). The models using raw data did not generalise. Overall, this work introduces an immersive ML pipeline for detecting social engagement and demonstrates how creatives could use ML and VR to expand their ability to design more engaging experiences. Given the pipeline’s results for social engagement detection, we generalise it for detecting human-defined social attitudes.
Antimicrobial susceptibility testing is crucial when treating Finegoldia magna infections
Authors: Walser Fabienne , Prinz Julia , Rahm Stefan , Zingg Patrick O. , Mancini Stefano , Imkamp Frank , Zbinden Reinhard , Achermann Yvonne
Published: April 2022

Finegoldia magna is an anaerobic gram-positive bacterium that can cause invasive human infections. Recently, a 52-year-old patient suffering from a periprosthetic joint infection (PJI) due to F. magna was treated with cefepime on hemodialysis; however, treatment failed due to relapse caused by antibiotic-resistant strains. Reports on the antimicrobial susceptibility of F. magna clinical isolates are rare. We collected 57 clinical F. magna isolates from Zurich, Switzerland, between September 2019 and July 2020 and tested their antimicrobial susceptibility to investigate the local resistance pattern. Antimicrobial susceptibility testing (AST) was evaluated for nine antibiotics (benzylpenicillin, amoxicillin/clavulanic acid, cefuroxime, cefepime, levofloxacin, rifampicin, metronidazole, doxycycline, and clindamycin) by E-test according to CLSI guidelines. All F. magna strains were susceptible to benzylpenicillin, amoxicillin/clavulanic acid, and metronidazole, while 75% to clindamycin. F. magna isolates showed MIC values lower than species-unrelated breakpoints for cefuroxime, levofloxacin, and cefepime in 93%, 56%, and 32% of the cases, respectively. MIC values for rifampicin and doxycycline were lower than locally determined ECOFFs in 98% and 72% of the cases, respectively. In summary, we recommend the use of benzylpenicillin, amoxicillin/clavulanic acid, or metronidazole without prior AST as first-line treatment option against F. magna PJI infections. If cefuroxime, cefepime, levofloxacin, rifampicin, doxycycline, or clindamycin are used, AST is mandatory.
Climate change impacts on future driving and walking conditions in Finland, Norway and Sweden
Authors: Freistetter Nadine-Cyra , Médus Erika , Hippi Marjo , Kangas Markku , Dobler Andreas , Belušić Danijel , Käyhkö Jukka , Partanen Antti-Ilari
Published: April 2022

Road weather is a major concern for the public safety and health, industries and transport sectors. Half of the yearly 27,000 road and 50,000 pedestrian injuries in Finland, Norway and Sweden can be traced back to slippery road and walkway conditions. We simulated the climate change impacts on future roads and walkways for mid- and end-century in Finland, Norway and Sweden with the road weather model RoadSurf, driven by the regional climate model HCLIM38 with boundary data from two global climate models following the RCP8.5 scenario.

Our simulations for mid-century suggest strong road surface temperature increases, especially in southern Finland (+ 5.1 °C) and Sweden (+ 7.1 °C). Snowy and icy road surface conditions decreased by 23 percentage points, causing 18.5 percentage points less difficult driving conditions during the cold season. Zero-degree-crossing days mostly decreased in autumn and spring by up to 7 days and increased in winter by up to 5 days. Sidewalks mostly showed a decrease in slipperiness, but a five percentage point increase of water above ice layers on the sidewalks in winter, suggesting the slip-season might become shorter, but more slippery.

Our results are upper extreme estimates but can serve as a reference to help local decision-makers plan mitigation and adaptation measures ahead of time.
Survey on image encryption techniques using chaotic maps in spatial, transform and spatiotemporal domains
Authors: Zia Unsub , McCartney Mark , Scotney Bryan , Martinez Jorge , AbuTair Mamun , Memon Jamshed , Sajjad Ali
Published: April 2022

Chaos-based cryptosystems have been an active area of research in recent years. Although these algorithms are not standardized like AES, DES, RSA, etc., chaos-based cryptosystems like Chebyshev polynomials can provide additional security when used with standard public key cryptosystems like RSA and El-gamal. Standard encryption algorithms such as AES have always been the primary choice, but when it comes to image or video encryption, many researchers recommend chaos-based encryption techniques due to their computational efficiency. This paper presents a survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatiotemporal domains for better understanding. The significant improvements in the field of image encryption are discussed. In addition, comparative analysis is performed to validate the evaluation matrices for quantifying the encryption algorithms’ security and performance in recent papers.
Attitudes Toward Payment for Research Participation: Results from a U.S. Survey of People Living with HIV
Authors: Polonijo Andrea N. , Dubé Karine , Galea Jerome T. , Greene Karah Yeona , Taylor Jeff , Christensen Christopher , Brown Brandon
Published: April 2022

Little is known about how payment affects individuals' decisions to participate in HIV research. Using data from a U.S. survey of people living with HIV (N = 292), we examined potential research participants’ attitudes toward payment, perceived study risk based on payment amount, and preferred payment forms, and how these factors vary by sociodemographic characteristics. Most respondents agreed people should be paid for HIV research participation (96%) and said payment would shape their research participation decisions (80%). Men, less formally educated individuals, and members of some minoritized racial-ethnic groups were less likely to be willing to participate in research without payment. Higher payment was associated with higher perceived study risks, while preferences for form of payment varied by age, gender, education, race-ethnicity, and census region of residence. Findings suggest payment may influence prospective research participants’ risk–benefit calculus and participation, and that a one-size-fits-all approach to payment could differentially influence participation among distinct sociodemographic groups.
Distance approximation to support customer selection in vehicle routing problems
Authors: Akkerman Fabian , Mes Martijn
Published: April 2022

Estimating the solution value of transportation problems can be useful to assign customers to days for multi-period vehicle routing problems, or to make customer selection decisions very fast (e.g., within an online environment). In this paper, we apply several regression methods to predict the total distance of the traveling salesman problem (TSP) and vehicle routing problem (VRP). We show that distance can be estimated fairly accurate using simple regression models and only a limited number of features. Besides using features found in the scientific literature, we also introduce new classes of spatial features. The model is validated on a fictional case with different spatial instances considering both a backordering and lost sales configuration, and on a realistic case that involves dynamic waste collection in the city of Amsterdam, The Netherlands. For the fictional case, we show differences in performance per instance type and configuration, and we show that our model can save up to $$25.3\%$$

25.3
%

in distance compared with a heuristic approximation. For the waste collection case, we introduce a cost function that combines the travel distance and service level, and show that our model can reduce distances up to 17% compared to a well-known heuristic approximation while maintaining the same service level. Furthermore, we show the benefits of using approximations for combining offline learning with online or frequent optimization.
A socio-legal analysis of the Belgian protective legislation towards victims of aggravated forms of migrant smuggling
Authors: de Massol de Rebetz Roxane , van der Woude Maartje
Published: April 2022

As many scholars have shown, and other than what is suggested by their legal definition, migrant smuggling and human trafficking are not always easily distinguishable in reality. Acknowledging this grey area between the two phenomena, the Belgian legislature has introduced an alternative approach (referred to as ‘third-way approach’) which would offer migrants who have experienced ‘aggravated forms’ of migrant smuggling the same protective status that is usually strictly reserved for victims of human trafficking. Interestingly enough, migrants don’t seem inclined to make use of this procedure. Through a series of expert interviews, this article shines light on the perspective of key actors within the Belgian criminal justice system and migration control apparatus with regard to this third-way approach and its functioning in practice. In so doing, the article not only reveals how the proper functioning of this third-way approach is hindered by a series of organizational and institutional factors, but it also shows how the different actors are struggling with the inherent tension between the objectives of protecting state security and the protection of the needs of vulnerable groups in precarious life situations.
Initial and supplementary indication approval of new targeted cancer drugs by the FDA, EMA, Health Canada, and TGA
Authors: Michaeli Daniel Tobias , Mills Mackenzie , Michaeli Thomas , Miracolo Aurelio , Kanavos Panos
Published: April 2022

Background. Previous research focused on the clinical evidence supporting new cancer drugs’ initial US Food and Drug Administration (FDA) approval. However, targeted drugs are increasingly approved for supplementary indications of unknown evidence and benefit. Objectives. To examine the clinical trial evidence supporting new targeted cancer drugs’ initial and supplementary indication approval in the US, EU, Canada, and Australia. Data and Methods. 25 cancer drugs across 100 indications were identified with FDA approval between 2009–2019. Data on regulatory approval and clinical trials were extracted from the FDA, European Medicines Agency (EMA), Health Canada (HC), Australian Therapeutic Goods Administration (TGA), and clinicaltrials.gov. Regional variations were compared with χ2-tests. Multivariate logistic regressions compared characteristics of initial and supplementary indication approvals, reporting adjusted odds ratios (AOR) with 95% confidence intervals (CI). Results. Out of 100 considered cancer indications, the FDA approved 96, the EMA 92, HC 86, and the TGA 83 (83%, p < 0.05). The FDA more frequently granted priority review, conditional approval, and orphan designations than other agencies. Initial approvals were more likely to receive conditional / accelerated approval (AOR: 2.69, 95%CI [1.07–6.77], p < 0.05), an orphan designation (AOR: 3.32, 95%CI [1.38–8.00], p < 0.01), be under priority review (AOR: 2.60, 95%CI [1.17–5.78], p < 0.05), and be monotherapies (AOR: 5.91, 95%CI [1.14–30.65], p < 0.05) than supplementary indications. Initial indications’ pivotal trials tended to be shorter (AOR per month: 0.96, 95%CI [0.93–0.99], p < 0.05), of lower phase design (AOR per clinical phase: 0.28, 95%CI [0.09–0.85], p < 0.05), and enroll more patients (AOR per 100 patients: 1.19, 95%CI [1.01–1.39], p < 0.05). Conclusions. Targeted cancer drugs are increasingly approved for multiple indications of varying clinical benefit. Drugs are first approved as monotherapies in rare diseases with a high unmet need. Whilst expedited regulatory review incentivizes this prioritization, indication-specific safety, efficacy, and pricing policies are necessary to reflect each indication’s differential clinical and economic value.
From scenario to mounting risks: COVID-19’s perils for development and supply security in the Sahel
Authors: Al-Saidi Mohammad , Saad Suhair A. Gayoum , Elagib Nadir Ahmed
Published: April 2022

The African Sahel countries are inherently fragile, environmentally insecure and economically weak. This paper underscores the compounded impacts brought about by the COVID-19 pandemic on resource supply security and, hence, the long-term development of the region. It outlines the Sahel-specific COVID-19 scenario by firstly highlighting the underlying vulnerabilities and later linking the health sector outcomes to increased political instability and environmental insecurity, particularly the deterioration of food security. In this sense, this paper shows from a region-wide perspective how COVID-19 in the Sahel is associated with enlarged sociopolitical developmental perils. Lower remittance sent by expatriates, violent conflicts, increased cross-border terrorism and migration, discriminant mobility restrictions of people and goods, weak national healthcare infrastructures, bottlenecks in international aid, pressures on the education system and recent climate extremes are some revealing examples of aggravators of the impacts on the supply of vital resources, such as food. This paper also shows the importance of considering the close interlinks between health, food and political stability in the Sahel. There is a paramount need for more comprehensive approaches linking human health to other sectors, and for re-considering local sustainable agriculture. To avoid prolonged or recurrent humanitarian crises, the Sahel countries need to strengthen response capacities through public sector-led responses. Examples of these responses include reinforced national disaster programs for the vulnerable, support to sustainable agriculture and food markets, improved performance and communication of public sector relief, state-based cooperation, building of regional alliances and peacemaking efforts.
A machine-learning approach to discerning prevalence and causes of myopia among elementary students in Hubei
Authors: Tu Yuyang , Hu Xuemin , Zeng Caiqiong , Ye Meihong , Zhang Peng , Jin Xiaoqin , Zhang Jianwei , Zhou Lianhong
Published: April 2022

Objective

Our aim is to establish a machine-learning model that will enable us to investigate the key factors influencing the prevalence of myopia in students.

Methods

We performed a cross-sectional study that included 16,653 students from grades 1–3 across 17 cities in Hubei Province. We used questionnaires to discern levels of participation in potential factors contributing to the development of myopia. The relative importance of potential contributors was ranked using machine-learning methods. The students’ visual acuity (VA) was measured and those with logMAR VA of > 0.0 underwent a autorefraction test to determine students’ refraction status.

Results

The prevalence of myopia in grades 1, 2, and 3 was 14.70%, 20.54% and 28.93%, respectively. Myopia rates among primary school students in provincial capital city (32.35%) were higher than those in other urban (23.03%) and rural (14.82%) areas. Children with non-myopic parents, only one myopic parent, or both parents having myopia exhibited myopic rates of 16.36%, 25.18%, and 41.37%, respectively. Myopia prevalence was higher in the students who continued to use their eyes at close range for a long time and lower in those engaged longer in outdoor activities. The machine-learning model determined that the top three contributing factors were the students’ age (0.36), followed by place of residence (0.34), starting age of education (0.21).

Conclusion

The overall prevalence of myopia was 21.52%. Children’s age and place of residence were the important influencing factors, but genetics and environmental were also played key roles in myopia development.
The economics of missionary expansion: evidence from Africa and implications for development
Authors: Jedwab Remi , Meier zu Selhausen Felix , Moradi Alexander
Published: April 2022

How did Christianity expand in Africa to become the continent’s dominant religion? Using annual panel census data on Christian missions from 1751 to 1932 in Ghana, and pre-1924 data on missions for 43 sub-Saharan African countries, we estimate causal effects of malaria, railroads and cash crops on mission location. We find that missions were established in healthier, more accessible, and richer places before expanding to economically less developed places. We argue that the endogeneity of missionary expansion may have been underestimated, thus questioning the link between missions and economic development for Africa. We find the endogeneity problem exacerbated when mission data is sourced from Christian missionary atlases that disproportionately report a selection of prominent missions that were also established early.
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework
Authors: Mitchener Ludovico , Tuckey David , Crosby Matthew , Russo Alessandra
Published: April 2022

In this paper we introduce Detect, Understand, Act (DUA), a neuro-symbolic reinforcement learning framework. The Detect component is composed of a traditional computer vision object detector and tracker. The Act component houses a set of options, high-level actions enacted by pre-trained deep reinforcement learning (DRL) policies. The Understand component provides a novel answer set programming (ASP) paradigm for symbolically implementing a meta-policy over options and effectively learning it using inductive logic programming (ILP). We evaluate our framework on the Animal-AI (AAI) competition testbed, a set of physical cognitive reasoning problems. Given a set of pre-trained DRL policies, DUA requires only a few examples to learn a meta-policy that allows it to improve the state-of-the-art on multiple of the most challenging categories from the testbed. DUA constitutes the first holistic hybrid integration of computer vision, ILP and DRL applied to an AAI-like environment and sets the foundations for further use of ILP in complex DRL challenges.
Rate-type models of dissipative compressible fluids
Authors: Giorgi Claudio , Morro Angelo
Published: April 2022

Two models of dissipative compressible fluids are established within the general setting of Rational Thermodynamics. It is a common feature underlying the analysis of the thermodynamic consistency that the entropy production and the free energy potential are viewed as constitutive functions of the same set of physical variables and no internal variable is involved. Also in light of late experimental observations, hysteretic models are established for the dependence of pressure on the mass density. Next relaxation properties are modelled via rate equations with an objective derivative which combines the corotational rate with the divergence of the velocity.
On the Gittins index for multistage jobs
Authors: Aalto Samuli , Scully Ziv
Published: April 2022

Optimal scheduling in single-server queueing systems is a classic problem in queueing theory. The Gittins index policy is known to be the optimal nonanticipating policy minimizing the mean delay in the M/G/1 queue. While the Gittins index is thoroughly characterized for ordinary jobs whose state is described by the attained service, it is not at all the case with jobs that have more complex structure. Recently, a class of such jobs, multistage jobs, were introduced, and it was shown that the computation of Gittins index of a multistage job decomposes into separable computations for the individual stages. The characterization is, however, indirect in the sense that it relies on the recursion for an auxiliary function (the so-called SJP—single-job profit—function) and not for the Gittins index itself. In this paper, we focus on sequential multistage jobs, which have a fixed sequence of stages, and prove that, for them, it is possible to compute the Gittins index directly by recursively combining the Gittins indices of its individual stages. In addition, we give sufficient conditions for the optimality of the FCFS and SERPT disciplines for scheduling sequential multistage jobs. On the other hand, we demonstrate that, for nonsequential multistage jobs, it is better to compute the Gittins index by utilizing the SJP functions.
Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations
Authors: Gerster Moritz , Waterstraat Gunnar , Litvak Vladimir , Lehnertz Klaus , Schnitzler Alfons , Florin Esther , Curio Gabriel , Nikulin Vadim
Published: April 2022

Electrophysiological power spectra typically consist of two components: An aperiodic part usually following an 1/f power law $$P\propto 1/{f}^{\beta }$$

P
∝
1
/

f

β

and periodic components appearing as spectral peaks. While the investigation of the periodic parts, commonly referred to as neural oscillations, has received considerable attention, the study of the aperiodic part has only recently gained more interest. The periodic part is usually quantified by center frequencies, powers, and bandwidths, while the aperiodic part is parameterized by the y-intercept and the 1/f exponent $$\beta$$
β
. For investigation of either part, however, it is essential to separate the two components. In this article, we scrutinize two frequently used methods, FOOOF (Fitting Oscillations & One-Over-F) and IRASA (Irregular Resampling Auto-Spectral Analysis), that are commonly used to separate the periodic from the aperiodic component. We evaluate these methods using diverse spectra obtained with electroencephalography (EEG), magnetoencephalography (MEG), and local field potential (LFP) recordings relating to three independent research datasets. Each method and each dataset poses distinct challenges for the extraction of both spectral parts. The specific spectral features hindering the periodic and aperiodic separation are highlighted by simulations of power spectra emphasizing these features. Through comparison with the simulation parameters defined a priori, the parameterization error of each method is quantified. Based on the real and simulated power spectra, we evaluate the advantages of both methods, discuss common challenges, note which spectral features impede the separation, assess the computational costs, and propose recommendations on how to use them.
Throwing Injury Prevention Strategies with a Whole Kinetic Chain-Focused Approach
Authors: Mayes Michael , Salesky Madeleine , Lansdown Drew A.
Published: April 2022

Purpose of Review

This review examines the relationship between the baseball pitching motion and the kinetic chain. The goal was to determine the underlying causes of a deficiency in throwing mechanics throughout a throwing motion, and to provide an evidence-based approach on how to prevent injuries caused by a lack of proper mechanics. In doing so, we sought to provide a warm-up strategy that can be added to every baseball player’s daily on-field routine that is tailored to each phase of the throwing motion.

Recent Findings

To help minimize the risk of injury to overhead throwing athletes, a thorough understanding of the throwing motion is critical. Throwing a ball places extreme stress on the body, notably the shoulder and elbow joints. With a clear understanding of the biomechanics of throwing, we can develop an injury prevention routine to minimize unnecessary stresses throughout the kinetic chain.

The throwing cycle is a complex motion that places various stresses throughout the thrower’s body, from the ankle to the core, and from the back to the shoulder and elbow. A thorough understanding of the mechanics of this motion, along with specific exercises to target the specific actions of each phase, may allow for throwers, regardless of their age and experience, to minimize injury risk.