The linearly decreasing convergence factor a. by Junhao Wei (6816803)

Table_2_Maternal oral probiotic use is associated with decreased breastmilk inflammatory markers, infant fecal microbiome variation, and altered recognition memory responses in inf... by Sara Gonia (14132166)

“…In this observational study, we explore if early life exposure to probiotics via the mother during pregnancy and lactation, is associated with decreased inflammation in breastmilk, maternal and infant microbiome variation, and altered infant neurodevelopmental features.…”

Table_1_Maternal oral probiotic use is associated with decreased breastmilk inflammatory markers, infant fecal microbiome variation, and altered recognition memory responses in inf... by Sara Gonia (14132166)

“…In this observational study, we explore if early life exposure to probiotics via the mother during pregnancy and lactation, is associated with decreased inflammation in breastmilk, maternal and infant microbiome variation, and altered infant neurodevelopmental features.…”

The injectable contraceptives depot medroxyprogesterone acetate and norethisterone enanthate substantially and differentially decrease testosterone and sex hormone binding globulin... by Chanel Avenant (409756)

“…Both contraceptives substantially decreased, from D0 to 25W, the total testosterone [DMPA-IM D0 0.560, 25W 0.423 nmol/L, -24.3% (p < 0.0001); NET-EN D0 0.551, 25W 0.253 nmol/L, -54.1%, (p < 0.0001)], SHBG [DMPA-IM D0 45.0, 25W 32.7 nmol/L, -29.8% (p < 0.0001); NET-EN D0 50.2, 25W 17.6 nmol/L, -65.1% (p < 0.0001)], and calculated free testosterone levels [DMPA-IM D0 6.87, 25W 5.38 pmol/L, -17.2% (p = 0.0371); NET-EN D0 6.00, 25W 3.70, -40.0% (p < 0.0001)]. …”

Changes in baseline T-cell activation markers through week 12 and week 24 according to the linear regression model. a. by Tosi M. Mwakyandile (16408705)

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Changes in baseline T-cell exhaustion, monocyte activation and platelet activation markers through week 12 and week 24 according to the linear regression model. a. by Tosi M. Mwakyandile (16408705)

Subjects:

Algorithm operation steps. by Junyan Wang (4738518)

“…Experimental results demonstrate that SCI-YOLO11 achieves a 3.2% improvement over baseline models in terms of MAP@0.5 metric; precision and recall rates increase by 2.6% and 3.7%, respectively. Additionally, its parameter count and floating-point operations decrease by 6% and 7.9%, respectively. …”

Study-related adverse events. by Benjamin R. Lewis (22279166)

Subjects:

Study flow chart. by Benjamin R. Lewis (22279166)

Subjects:

Study CONSORT diagram. by Benjamin R. Lewis (22279166)

Subjects:

Larger example of stimuli with cue relevant for Task 3. by Marcel F. Hinss (14675457)

Changes in baseline CD4 count through week 12 and week 24 according to the linear regression model. by Tosi M. Mwakyandile (16408705)

Subjects:

A Locally Linear Dynamic Strategy for Manifold Learning. by Weifan Wang (4669081)

“…For 10-30% noise, where the Hebbian network employs a local linear transform, learning selectively increases signal direction alignment (blue) while simultaneously decreasing noise direction alignment (orange). …”

Raw data 6–9 and 15. by Fateme Khorramroo (18086501)

nsP4-C483Y or Q192L mutations decrease sensitivity to 4′-FlU. by Peiqi Yin (6533747)

Biases in larger populations. by Sander W. Keemink (21253563)

“…(<b>B</b>) Minimum and maximum bias in a long 1D array with rectified cosine tuning. Bias expressed in terms of the distance between neurons in a linear population of equally spaced neurons. …”

Comparison of diffusion simulations: implicit scheme of the GDE with a 30-second time step (blue line), implicit scheme of the PNGM with α = 0.6 and a 15-second time step (green li... by Mouad Klai (20818364)

Estimation of the coefficients of a generalised linear model of posttraumatic stress symptomatology. by Beatriz Arregui-Gallego (21553735)

Why does task performance decrease with burst length? by Swathi Anil (17382903)

Uganda 2023 NCD risk factor STEPS survey data. by Ronald Kusolo (13200268)

“…The risk factor prevalences that increased significantly were: high blood glucose from 1.5% in 2014 to 3.3% in 2023 (p< 0.001); overweight and obesity from 19.3% in 2014 to 24.1% in 2023 (p< 0.001); current alcohol consumption from 28.5% in 2014 to 31.1% in 2023 (p=0.013); and sedentariness from 26.6% in 2014 to 31.9% in 2023 (p< 0.001). The risk factor prevalences that decreased significantly were: inadequate physical activity from 5.0% in 2014 to 3.6% in 2023 (p=0.003), and current smoke tobacco use from 9.6% in 2014, to 8.3% in 2023 (p= 0.046). …”