Existing empirical literature provides converging evidence that selective emigration enhances human capital accumulation in the world's poorest countries. However, the within-country distribution of such brain gain effects has received limited attention. Focusing on Senegal, we provide evidence that the brain gain mechanism primarily benefits the wealthiest regions that are internationally connected and have better access to education. Conversely, human capital responses are negligible in regions lacking international connectivity, and even negative in better connected regions with inadequate educational opportunities. These results extend to internal migration, implying that highly vulnerable populations are trapped in the least developed areas.

Earlier research largely ignored the effects of climate change on the growth of agricultural total factor productivity (TFP) in Africa. This study shows how climate inputs impact TFP growth in addition to other productivity growth indicators and metrics, as well as how they can impact overall input efficiency as productivity drivers. We use a panel of 42 African nations from 1999 to 2019 and a nonparametric data envelopment analysis-Malmquist technique. The non-parametric analysis revealed that the average growth rate of the non-climate-induced TFP estimates was 1.9%, while the average growth rate of the climate-induced TFP estimates was 2.4%. Accounting for temperature and precipitation separately, TFP grew by 2.3% on average. This growth rate (2.3%) is slightly less than the combined effect of temperature and precipitation (2.4%) but higher than the typical TFP growth rate (1.9%) that ignores climate variables, indicating that TFP growth in African agriculture risks being underestimated when climate inputs are ignored. We also find the distribution of the climate effects to vary across regions. In northern Africa, for example, the temperature-induced TFP growth rates were negative due to rising temperature in the region. Evidence from the decomposed TFP estimates indicates that climate variables also influence productivity determinants. However, technology improvement is fundamental to mitigating the effects of extreme weather inputs on TFP growth in Africa's agriculture. As a result, a few policy suggestions are provided to help policymakers deal with the effects of climate change on TFP growth in Africa's agriculture and ensure food security. The study advocated for a reevaluation of the climate–agriculture effect in order to fully comprehend the role of climate factors and their contributions to agricultural TFP growth in Africa.

Let $\mathcal {M}$ be a semifinite von Nemann algebra equipped with an increasing filtration $(\mathcal {M}_n)_{n\geq 1}$ of (semifinite) von Neumann subalgebras of $\mathcal {M}$ . For $0<p <\infty $ , let $\mathsf {h}_p^c(\mathcal {M})$ denote the noncommutative column conditioned martingale Hardy space and $\mathsf {bmo}^c(\mathcal {M})$ denote the column “little” martingale BMO space associated with the filtration $(\mathcal {M}_n)_{n\geq 1}$ .

We prove the following real interpolation identity: if $0<p <\infty $ and $0<\theta <1$ , then for $1/r=(1-\theta )/p$ ,

$$ \begin{align*} \big(\mathsf{h}_p^c(\mathcal{M}), \mathsf{bmo}^c(\mathcal{M})\big)_{\theta, r}=\mathsf{h}_{r}^c(\mathcal{M}), \end{align*} $$

For the case of complex interpolation, we obtain that if $0<p<q<\infty $ and $0<\theta <1$ , then for $1/r =(1-\theta )/p +\theta /q$ ,

$$ \begin{align*} \big[\mathsf{h}_p^c(\mathcal{M}), \mathsf{h}_q^c(\mathcal{M})\big]_{\theta}=\mathsf{h}_{r}^c(\mathcal{M}) \end{align*} $$

These extend previously known results from $p\geq 1$ to the full range $0<p<\infty $ . Other related spaces such as spaces of adapted sequences and Junge’s noncommutative conditioned $L_p$ -spaces are also shown to form interpolation scale for the full range $0<p<\infty $ when either the real method or the complex method is used. Our method of proof is based on a new algebraic atomic decomposition for Orlicz space version of Junge’s noncommutative conditioned $L_p$ -spaces.

We apply these results to derive various inequalities for martingales in noncommutative symmetric quasi-Banach spaces.

The blue shark Prionace glauca is the most abundant species in the artisanal driftnet fishery off the coastal waters of Ivory Coast. The reproductive parameters were investigated with the aim of providing basic information on the reproductive biology for fisheries management. A total of 424 specimens (256 males and 168 females) ranging from 170–330 cm in total length (TL) were sampled between August 2014 and November 2016. Sample for embryonic sex ratio was obtained from 18 litters of 503 individuals (255 males and 248 females). The embryonic sex ratio was not significantly different from 1:1 (χ2 = 0.10, P > 0.05, N = 503). The size at 50% maturity (L50) was 218.1 cm TL for males and 223.3 cm TL for females. The litter size based on the number of embryos varied from 6 to 62, with an average of 30 embryos. Mating started in July whereas ovulation, fertilization and uterine eggs occurred in late October–November. Smallest embryos of 3–5 cm in stretch total length (STL) appeared in uterus from November to January. The embryo size varied widely among months, and well-pigmented embryos were already present in April–May samples, although most of them occurred in August–September, suggesting a gestation period of around 11 months. The absence of neonates in catches, as well as parturition females, does not support a hypothesis that parturition takes place in the Gulf of Guinea.

Continuous, detailed isotope (δD and δ18O) profiles were obtained from eight snow pits dug in the vicinity of Vostok station, Antarctica, during the period 1984– 2000. In addition, snow samples taken along the 1km long accumulation-stake profile were measured to determine spatial variability in isotope composition of recent snow. the stacked δD time series spanning the last 55 years shows only weak correlation with the mean annual air temperature recorded at Vostok station. Significant oscillations of both snow accumulation and snow isotope composition with the periods 2.5, 5, 20 and, possibly, ~102 years observed at single points are interpreted in terms of drift of snow-accumulation waves of various scales on the surface of the ice sheet.

Rapid changes in agricultural systems call for profound changes in agricultural research and extension practices. The Diagnosis, Design, Assessment, Training and Extension (DATE) approach was developed and applied to co-design Conservation Agriculture-based cropping systems in contrasted situations. DATE is a multi-scale, multi-stakeholder participatory approach that integrates scientific and local knowledge. It emerged in response to questions raised by and issues encountered in the design of innovative systems. A key feature of this approach is the high input of innovative systems which are often although not exclusively based on conservation agricultural practices. Prototyping of innovative cropping systems (ICSs) largely relies on a conceptual model of soil–plant–macrofauna–microorganism system functioning. By comparing the implementation of the DATE approach and conservation agriculture-based cropping systems in Madagascar, Lao PDR, and Cambodia, we show that: (i) the DATE approach is flexible enough to be adapted to local conditions; (ii) market conditions need to be taken into account in designing agricultural development scenarios; and (iii) the learning process during the transition to conservation agriculture requires time. The DATE approach not only enables the co-design of ICSs with farmers, but also incorporates training and extension dimensions. It feeds back practitioners’ questions to researchers, and provides a renewed and extended source of innovation to farmers.

We provide an analogue of Gundy's decomposition for $L_1$-bounded non-commutative martingales. An important difference from the classical case is that for any $L_1$-bounded non-commutative martingale, the decomposition consists of four martingales. This is strongly related with the row/column nature of non-commutative Hardy spaces of martingales. As applications, we obtain simpler proofs of the weak type $(1,1)$ boundedness for non-commutative martingale transforms and the non-commutative analogue of Burkholder's weak type inequality for square functions. A sequence $(x_n)_{n \ge 1}$ in a normed space $\mathrm{X}$ is called 2-co-lacunary if there exists a bounded linear map from the closed linear span of $(x_n)_{n \ge 1}$ to $l_2$ taking each $x_n$ to the $n$th vector basis of $l_2$. We prove (using our decomposition) that any relatively weakly compact martingale difference sequence in $L_1 (\mathcal{M}, \tau)$ whose sequence of norms is bounded away from zero is 2-co-lacunary, generalizing a result of Aldous and Fremlin to non-commutative $L_1$-spaces.

We prove a weak-type (1,1) inequality for square functions of non-commutative martingales that are simultaneously bounded in $L^2$ and $L^1$. More precisely, the following non-commutative analogue of a classical result of Burkholder holds: there exists an absolute constant $K > 0$ such that if $\mathcal{M}$ is a semi-finite von Neumann algebra and $( \mathcal{M}_n )^{ \infty }_{n = 1}$ is an increasing filtration of von Neumann subalgebras of $\mathcal{M}$ then for any given martingale $x = ( x_n )^{\infty}_{n = 1}$ that is bounded in $L^2 ( \mathcal{M} ) \cap L^1 ( \mathcal{M} )$, adapted to $( \mathcal{M}_n )^{\infty}_{n = 1}$, there exist two martingale difference sequences, $a = ( a_n )_{n = 1}^\infty$ and $b = ( b_n )_{n = 1}^\infty$, with $dx_n = a_n + b_n$ for every $n \geq 1$,

\| ( \sum^\infty_{n = 1} a_n^* a_n )^{1/2} \|_{2} + \| ( \sum^\infty_{n = 1} b_n b_n^* )^{1/2} \|_{2} \leq 2 \| x \|_2,

and

\| ( \sum^\infty_{n = 1} a_n^* a_n )^{1/2} \|_{1, \infty} + \| ( \sum^\infty_{n = 1} b_n b_n^* )^{1/2} \|_{1, \infty} \leq K \| x \|_1.

As an application, we obtain the optimal orders of growth for the constants involved in the Pisier–Xu non-commutative analogue of the classical Burkholder–Gundy inequalities.