Miracle-dz/UniFAR-FTUs huggingface dataset:
VU Research Portal Out of Sync?

This article questions existing findings and provides new evidence about the consequences of nonstandard work schedules on partnership quality. Using quantitative couple data from the Netherlands Kinship Panel Study (NKPS) (N = 3,016) and semi-structured qualitative interviews (N = 34), we found that, for women, schedules with varying hours resulted in greater relationship dissatisfaction than for men. Men with young children who worked varying hours had less relationship conflict and spent more time with children. Parents used nonstandard schedules for tag-team parenting or to maintain perceptions of full-time motherhood. The lack of negative effects, particularly for night shifts, suggests that previous findings – largely U.S. ones – are not universal and may be attributed to wider cultural, industrial relations, and economic contexts.
A cost efﬁciency analysis of boro rice production in Dinajpur district of Bangladesh

The size of the farm is an important factor that reﬂects the efﬁcient utilization of resources in farming. Therefore, this paper aims to investigate how the farm size affects the cost efﬁciency of rice production during the Boro season in Bangladesh. In particular, the analysis aims to estimate the concentration of cost efﬁciency among the 240 small, medium, and large Boro rice growers sampled in the Dinajpur district. Descriptive statistics were used to evaluate the socioeconomic characteristics of rice farmers. A Cobb-Douglas type stochastic cost frontier model was employed to ﬁgure out how the rice farmers are cost-efﬁcient. The sociodemographic factors that affect efﬁcient investment in rice production also have been identiﬁed. The results of the study show a broad range of cost efﬁciency scores between 56.65 to 96.40% for the worse to the best rice-growing farmer, respectively with an average efﬁciency of 84.01%. The ﬁndings also show that the mean cost efﬁciency level of small, medium, and large farmers was 83.30, 85.58, and 94.43%, respectively. The land rental fees, human labor wages, irrigation prices, and pesticide prices are the key factors that contribute to the productivity of rice cultivation. The relatively higher level of cost efﬁciency among large farmers obviously demonstrates the notion that only large farmers in the study region are investing efﬁciently in rice growing. Irrespective of the farm size, the cost efﬁciency drivers found out that more efﬁcient were the farmers who had more experience in farming, obtained training on rice production techniques, and better access to institutional credit. It is therefore recommended that rice farmers should be well trained, provided credit access along with developing rural set-up, and also provide extension services in order to increase the cost efﬁciency levels in Boro season.
Equivalent Diﬀerentiable optimization Problems and Descent Methods for Asymmetric Variational Inequality Problems

Whether or not the general asymmetric variational inequality problem can be formulated as a diﬀerentiable optimization problem has been an open question. This paper gives an aﬃrmative answer to this question. We provide a new optimization problem formulation of the variational inequality problem and show that its objective function is continuously diﬀerentiable whenever the mapping involved in the latter problem is continuously diﬀerentiable. We also show that under appropriate assumptions on the latter mapping, any stationary point of the optimization problem is a global optimal solution, and hence solves the variational inequality problem. We discuss descent methods for solving the equivalent optimization problem and comment on systems of nonlinear equations and nonlinear complementarity problems
Five years of Sentinel-5p TROPOMI operational ozone proﬁling and geophysical validation using ozonesonde and lidar ground-based networks

The Sentinel-5 Precursor (S5P) satellite operated by the European Space Agency (ESA) carries the TROPOspheric Monitoring Instrument (TROPOMI) on a Sun-synchronous low-Earth orbit since October 13, 2017. The S5P mission has acquired more than ﬁve years of TROPOMI nadir ozone proﬁle data retrieved from the Level-0-to-1B processor version 2.0 and the Level-1B-to-2 Optimal Estimation based processor version 2.4. 0. The latter is described in detail in this work, followed by the geophysical validation of the resulting ozone proﬁles for the period May 2018 to April 2023. Comparison of TROPOMI 5 ozone proﬁle data to co-located ozonesonde and lidar measurements used as references, concludes to a median agreement better than 5 to 10 % in the troposphere. The bias goes up to -15 % in the upper stratosphere (35-45 km) where it can exhibit vertical oscillations. The comparisons show a dispersion of about 30 % in the troposphere and 10 to 20 % in the upper troposphere to lower stratosphere (UTLS) and in the middle stratosphere, which is close to mission requirements. Chi-square tests of the observed differences conﬁrm on average the validity of the ex-ante (prognostic) satellite and ground-based data 10 uncertainty estimates in the middle stratosphere, above about 20 km. Around the tropopause and below, the mean chi-square
UvA-DARE (Digital Academic Repository) Occupancy disorder in the magnetic topological insulator candidate Mn 1-x Sb 2+x Te 4

: MnSb 2 Te 4 is a candidate magnetic topological insulator exhibiting more pronounced cation intermixing than its predecessor MnBi 2 Te 4 . Investigating the cation intermixing and its possible implications on the magnetic order in MnSb 2 Te 4 are currently hot topics in research on quantum materials for spintronics and energy-saving applications. Two single-crystal X-ray diffraction measurements of Mn 1 − x Sb 2 + x Te 4 ( x = 0.06 and x = − 0.1) are presented alongside a detailed discussion of its crystal structure with a spotlight on the apparent occupancy disorder between the two cations. This disorder has been noted by other groups as well, yet never been analyzed in-depth with single-crystal X-ray diffraction. The latter is the tool of choice to receive a meaningful quanti ﬁ cation of antisite disorder. Between the two synthesis procedures we ﬁ nd subtle differences in phases and/or alternation of the cation content which has implications on the magnetic order, as illustrated by bulk magnetometry. Understanding and assessing this disorder in magnetic topological insulators of the MnX 2 Te 4 (X = Bi, Sb) type is crucial to gauge their applicability for modern spintronics. Furthermore, it opens new ways to tune the “ chemical composition – physical property ” relationship in these compounds, creating an alluring aspect also for fundamental science.
Miocene Volcaniclastic Sequence Within the Xiyu Formation from Source to Sink: Implications for Drainage Development and Tectonic Evolution in Eastern Pamir, NW Tibetan Plateau

The formation of the Pamir salient and the Tashkorgan‐Yarkand River is highly debated with the ages ranging from pre‐Cenozoic to late Miocene. One approach to resolve these issues is to draw support from the sedimentary record in the surrounding basins. A volcaniclastic sequence, which divides into Lower and Upper Members, was identified in the southwestern Tarim Basin. The Lower Member was transported by dilute streamflows, which likely flowed during or soon after eruptions, while the Upper Member was formed by a syneruptive volcanic debris flow. Chronological, petrologic, and geochemical data consistently indicate that the sequence was derived from the Central Pamir at ~11 Ma. The ~11 Ma emplacement of the volcaniclastic sequence provides unique constraints for the evolution of the Tashkorgan‐Yarkand River and the Pamir salient. Provenance data indicate a multistage evolutionary history of the Tashkorgan‐Yarkand River. The paleo‐Tashkorgan River was initially formed in the piedmont of the Pamir marginal range before ~15 Ma. This river cut back into the Tashkorgan region at ~15 Ma, after which it has eroded the Central Pamir by ~11 Ma. The N‐S trending upper reaches of the Tashkorgan River and the Yarkand River were established after ~11 Ma. The emplacement of the volcanic debris flow, together with regional deformation evidence, indicates limited strike‐slip motion between Pamir and the Tarim at least since ~11 Ma, which refutes hundreds of kilometers offset between the Pamir and the Tarim after this time and supports an earlier indention of the Pamir salient.
Nitrification Potential of Achromobacter xylosoxidans Isolated from Fresh Water Finfish Farms of Kerala, India

Over the decades, Aquaculture as a traditional practice has evolved to science based activity to meet the demands of food security as well as national economy. During 2016, world aquaculture production has projected to 73.8 mt with US$160.2 billion as an estimated first-sale value (FA0.2016). Total world aquaculture production accounted for 44.1% during 2014 and 31.1 % as compared in 2004. Feed is a crucial input for Semi –intensive and intensive aquaculture and usually contributes over 40-50% production costs but nearly 36% of the feed is excreted in the form of organic waste (Brune et al., 2003). The protein requirement of fish is about two to three times higher than that of mammals. Ammonium is one of the end products of protein metabolism (Walsh and Wright, 1995). In water, ammonia occurs in two forms which together are called total ammonia International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 08 (2018) Journal homepage: http://www.ijcmas. com
Vitamin C Intake and Serum Uric Acid Concentration in Men 1

Objective— We examined associations between vitamin C intake and serum uric acid in a population-based study. Methods— We included 1,387 men without hypertension, and Body Mass Index <30 kg/m 2 in the Health Professional Follow-up Study. Dietary intake was assessed with a semi-quantitative food frequency questionnaire validated for use in this population. Serum uric acid concentrations were measured. Results— Greater intakes of total vitamin C were significantly associated with lower serum uric acid concentrations, after adjustment for smoking, BMI, ethnicity, blood pressure, presence of gout, use of aspirin, and intake of energy, alcohol, dairy protein, fructose, meat, seafood, and coffee. An inverse dose-response association was observed through vitamin C intake of 400–500 mg/d, and then reached a plateau. Adjusted mean uric acid concentrations across total vitamin C intake categories (<90, 90–249, 250–499, 500–999, or ≥ 1000 mg/d) were 6.4, 6.1, 6.0, 5.7, and 5.7 mg/dl, respectively (P for trend<0.001). Greater vitamin C intake was associated with lower prevalence of hyperuricemia (serum uric acid > 6 mg/dl). The multivariate ORs for blood collection, as predictors, we observed similar inverse associations between vitamin C intake and uric acid. Conclusions— These population-based data indicate that vitamin C intake is inversely associated with serum uric acid concentrations. These findings support a potential role of vitamin C in the prevention of hyperuricemia and gout. the cross-sectional relationship between vitamin C intake and serum uric acid concentrations. In secondary analyses, we used average of diets collected in 1986 and 1990 as exposures to reflect long-term dietary intake patterns. All P-values are two sided.
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states

Assessing aerosol mixing states, which mainly depend on aerosol chemical compositions is indispensable to estimate aerosol direct and indirect effects. While the limitations in the measurements of aerosol chemical composition and mixing states persist globally, the Optical Properties of Aerosols and Clouds (OPAC) model has been widely used to construct optically equivalent aerosol chemical compositions from measured aerosol optical properties using Mie inversion. However, the representation of real atmospheric aerosol mixing scenarios in OPAC has perennially been challenged by the exclusive 15 assumption of external mixing. A Python successor to the aerosol module of the OPAC model is developed, named 'AeroMix,' with novel capabilities to 1) model externally and core-shell mixed aerosols, 2) simulate optical properties of aerosol mixtures constituted by any number of aerosol components, 3) and define aerosol composition and relative humidity in up to 6 vertical layers. Designed as a versatile open-source aerosol optical model framework, AeroMix is tailored for sophisticated inversion algorithms aimed at modeling aerosol mixing states and also their physical and chemical properties. AeroMix's performance 20 is demonstrated by modeling the probable aerosol mixing states over Kanpur (urban), India, and the Bay of Bengal (marine). The modeled mixing states are consistent with independent measurements using single-particle soot photometer (SP2) and transmission electron microscopy (TEM), substantiating the potential capability of AeroMix to model complex aerosol mixing scenarios involving multiple internally mixed components in diverse environments. This work contributes a valuable tool for modeling aerosol mixing states to assess their impact on cloud nucleating properties and radiation budget
S.Taylor ‘A new mystique? Working for yourself in the neoliberal economy’ in B.Conor, R.Gill and S.Taylor (eds) Gender and Creative Labour Sociological Review Monographs A new mystique? Working for yourself in the neoliberal economy

This article discusses the growing UK trend of people working for themselves. Beginning with the example of a media representation, it explores the wider implications of a discursive drift by which discourses of entrepreneurialism and contemporary creative work converge on the new figure of the worker who leaves paid employment for the supposed satisfactions of working from home. The article argues that, in contrast to the heroic masculine figures of the entrepreneur and artist, this is a feminised low-status worker. Its celebration is part of a ‘new mystique’ resembling the ‘housewife trap’ described by Friedan (1963) half a century ago, because for increasing numbers of people, both male and female, working for yourself amounts to exclusion to an almost subsistence level of economic activity on the margins of the neoliberal economy.
PrivObfNet: A Weakly Supervised Semantic Segmentation Model for Data Protection

The use of social media has made it easy to communicate and share information over the internet. However, it also brings issues such as data privacy leakage, which can be exploited by recipients with malicious intentions to harm the sender. In this paper, we propose a deep neural network that analyzes user’s image for privacy sensitive content and automatically locates sensitive regions for obfus-cation. Our approach relies solely on image level annotations and learns to (a) predict an overall privacy score, (b) detect sensitive attributes and (c) demarcate the sensitive regions for obfuscation, in a given input image. We validated the performance of our proposed method on three large datasets, VISPR, PASCAL VOC 2012 and MS COCO 2014, in terms of privacy score, attribute prediction and obfuscation performance. On the VISPR dataset, we achieved a Pearson correlation of 0.88 and a Spearman correlation of 0.86, outperforming previous methods. On PASCAL VOC 2012 and MS COCO 2014, our model achieved a mean IOU of 71.5% and 43.9% respectively, and is among the state-of-the-art techniques using weakly supervised semantic segmentation learning.
expression of HIV-1 MPER extended epitope on the surface of the recombinant probiotic

Background Mucosal vaccines have the potential to induce protective immune responses at the sites of infection. Applying CRISPR/Cas9 editing, we aimed to develop a probiotic-based vaccine candidate expressing the HIV-1 envelope membrane-proximal external region (MPER) on the surface of E. coli Nissle 1917. Results The HIV-1 MPER epitope was successfully introduced in the porin OmpF of the E. coli Nissle 1917 (EcN-MPER) and the modification was stable over 30 passages of the recombinant bacteria on the DNA and protein level. Furthermore, the introduced epitope was recognized by a human anti-HIV-1 gp41 (2F5) antibody using both live and heat-killed EcN-MPER, and this antigenicity was also retained over 30 passages. Whole-cell dot blot suggested a stronger binding of anti-HIV-1 gp41 (2F5) to heat-killed EcN-MPER than their live counterpart. An outer membrane vesicle (OMV) – rich extract from EcN-MPER culture supernatant was equally antigenic to anti-HIV-1 gp41 antibody which suggests that the MPER antigen could be harboured in EcN-MPER OMVs. Using quantitative ELISA, we determined the amount of MPER produced by the modified EcN to be 14.3 µg/10 8 cfu. Conclusions The CRISPR/Cas9 technology was an effective method for establishment of recombinant EcN-MPER bacteria that was stable over many passages. The developed EcN-MPER clone was devoid of extraneous plasmids and antibiotic resistance genes which eliminates the risk of plasmid transfer to animal hosts, should this clone be used as a vaccine. Also, the EcN-MPER clone was recognised by anti-HIV-1 gp41 (2F5) both as live and heat-killed bacteria making it suitable for pre-clinical evaluation. Expression of OmpF on bacterial surfaces and released OMVs identifies it as a compelling candidate for recombinant epitope modification, enabling surface epitope presentation on both bacteria and OMVs. By applying the methods described in this study, we present a potential platform for cost-effective and rational vaccine antigen expression and administration, offering promising prospects for further research in the field of vaccine development.
Family structure and adolescents’ binge drinking: the role of parental monitoring

Despite the general decline in alcohol use among adolescents, binge drinking in this age group remains a serious public health problem. The overarching aim of this study was to examine the association between family structure and adolescents' binge drinking and to what extent this association is accounted for by differences in parental monitoring. The study utilised data from the Stockholm School Survey 2014, involving 12,540 students in 9th and 11th grade in the Stockholm Municipality, Sweden. The analytical sample was restricted to 10,279 students. Descriptive statistics, cross tabulations with chi-square tests, and binary logistic regression were applied in the analyses. Controlling for sociodemographic characteristics including gender, grade, and parental education, family structure was significantly associated with adolescents' binge drinking, where binge drinking was higher among students in the non-nuclear family structure compared with those in the nuclear family structure. However, the association between family structure and adolescents' binge drinking was not accounted for by differences in parental monitoring. In conclusion, the non-nuclear family structure is a risk factor, but also high parental monitoring is a protective factor in relation to adolescents' binge drinking. Accordingly, the findings of the study may be used as a basis for preventive work.
Using structural controllability in detecting eﬀective immune system elements against cancer cells

Motivation: Cancer, a leading cause of death worldwide, is intertwined with immune system. Changing the state of immune system, as a complex network of cells and molecules interacting in a hierarchical mode, holds considerable fascination to ﬁght cancer. This alteration can involve debilitating pro-tumorigenic and reinvigorating anti-tumorigenic functions by the help of driver vertices. The utilization of network controllability and control centrality-based analysis will aid in the identiﬁcation of driver vertices to control target proteins that play signiﬁcant roles in the anti-tumorigenic and pro-tumorigenic functions of immune cells. In this study, a weighted generalization of the control centrality was constructed, in which the control power of each vertex in the network is obtained based on the importance of a set of under control vertices. Results: Screening all homo sapiens-related pathways in KEGG database, we ﬁnd that “Immune and cancer pathways” subnetwork showed the greatest number of edges and nodes in relation to positive and negative target proteins. The ﬁrst ﬁve driver vertices obtained for positive targets are ICAM2, TLR2, MAP2K4, ELK1, SIRT1 and for negative targets are ELK4, RBX1, NFATC1, NFATC2, NFATC3. Our results suggest that exposing the external signal to reinvigorate driver vertices of positive targets and debilitate driver vertices of negative target will result in changing the immune system state to ﬁght cancer.
Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

a Wind Farm in Central Sweden DTU Orbit (29/12/2018) Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden For any energy system relying on wind power, accurate forecasts of wind fluctuations are essential for efficient utilisation in the power grid. Statistical wind power prediction tools [1] use numerical weather prediction (NWP) model data along with measurements and can correct magnitude errors operationally. It is, however, entirely up to the NWP input to describe the timing of fluctuations correctly.
Learning-based Spotlight Position Optimization for Non-Line-of-Sight Human Localization and Posture Classification

Non-line-of-sight imaging (NLOS) is the process of estimating information about a scene that is hidden from the direct line of sight of the camera. NLOS imaging typically requires time-resolved detectors and a laser source for illumination, which are both expensive and computationally intensive to handle. In this paper, we propose an NLOS-based localization and posture classification technique that uses an off-the-shelf projector and camera system. We leverage a message-passing neural network to learn a visible scene geometry and predict the best position to be spotlighted by the projector that can maximize the NLOS signal. The neural network is trained end-to-end and the network parameters are optimized to maximize the NLOS performance. Unlike prior deep-learning-based NLOS techniques that assume planar relay walls, our system allows us to handle line-of-sight scenes where scene geometries are more arbitrary. Our method demonstrates state-of-the-art performance in object localization and position classification us-ing both synthetic and real scenes.
Ordinal Classification with Distance Regularization for Robust Brain Age Prediction

Age is one of the major known risk factors for Alzheimer's Disease (AD). Detecting AD early is crucial for effective treatment and preventing irreversible brain damage. Brain age, a measure derived from brain imaging reflecting structural changes due to aging, may have the potential to identify AD onset, assess disease risk, and plan targeted interventions. Deep learning-based regression techniques to predict brain age from magnetic resonance imaging (MRI) scans have shown great accuracy recently. However, these methods are subject to an inherent regression to the mean effect, which causes a systematic bias resulting in an overestimation of brain age in young subjects and underestimation in old subjects. This weakens the reliability of predicted brain age as a valid biomarker for downstream clinical applications. Here, we reformulate the brain age prediction task from regression to classification to address the issue of systematic bias. Recognizing the importance of preserving ordinal information from ages to understand aging trajectory and monitor aging longitudinally, we propose a novel ORdinal Distance Encoded Regularization (ORDER) loss that incorporates the order of age labels, enhancing the model's ability to capture age-related patterns. Extensive experiments and ablation studies demonstrate that this framework reduces systematic bias, outperforms state-of-art methods by statistically significant margins, and can better capture subtle differences between clinical groups in an independent AD dataset. Our implementation is publicly available at ***.