Households’ Non-leisure Time Allocation for Children and Determinants of Child Labour in Punjab, Pakistan

Pakistan is one of those countries in Asia where incidence of child labour is very high. Children should not have to work, but the estimates of the Child Labour Survey 1996 show that there are 3.3 million working children between the ages of 5–14 years in Pakistan. Due to political, social and economic pressures, developing countries like Pakistan tend to react by enacting legislation which bans child labour. Countries which are now developed did the same thing when they successfully completed their industrialisation. Child labour is often harmful for the children, but there are situations where the alternatives to child labour may offer only deeper poverty both for the children and their families. Therefore, mishandling of this issue can make matters from bad to worse, for example, if legislation pushes children into even worse situations. The Government of Pakistan has enacted the Employment of Children Act of 1991 which has banned employment of children below the age of 14 years and their employment is now a cognisable offence under the Act punishable by imprisonment and fine.1 Such interventions can lead to reductions in the already limited choices available to the child. For example, this legislation may mean that the child can neither work nor go to school. To put it differently, this ban does not address market failures, for example, in the education market. Hence, to tackle this complex problem different policy instruments are required which address not only the aspects of market failures, but also distributional and efficiency considerations of such services. In handling the issue of child labour, the supply side factors which motivate households to allocate non-leisure time of their children can provide useful insights to address this complex problem.

Households’ Non-leisure Time Allocation for Children and Determinants of Child Labour in Punjab, Pakistan

Pakistan is one of those countries in Asia where incidence of child labour is very high. Children should not have to work, but the estimates of the Child Labour Survey 1996 show that there are 3.3 million working children between the ages of 5-14 years in Pakistan. Due to political, social and economic pressures, developing countries like Pakistan tend to react by enacting legislation which bans child labour. Countries which are now developed did the same thing when they successfully completed their industrialisation. Child labour is often harmful for the children, but there are situations where the alternatives to child labour may offer only deeper poverty both for the children and their families. Therefore, mishandling of this issue can make matters from bad to worse, for example, if legislation pushes children into even worse situations. The Government of Pakistan has enacted the Employment of Children Act of 1991 which has banned employment of children below the age of 14 years and their employment is now a cognisable offence under the Act punishable by imprisonment and fine.1 Such interventions can lead to reductions in the already limited choices available to the child. For example, this legislation may mean that the child can neither work nor go to school. To put it differently, this ban does not address market failures, for example, in the education market

Initial B Cell Activation Induces Metabolic Reprogramming and Mitochondrial Remodeling.

B lymphocytes provide adaptive immunity by generating antigen-specific antibodies and supporting the activation of T cells. Little is known about how global metabolism supports naive B cell activation to enable an effective immune response. By coupling RNA sequencing (RNA-seq) data with glucose isotopomer tracing, we show that stimulated B cells increase programs for oxidative phosphorylation (OXPHOS), the tricarboxylic acid (TCA) cycle, and nucleotide biosynthesis, but not glycolysis. Isotopomer tracing uncovered increases in TCA cycle intermediates with almost no contribution from glucose. Instead, glucose mainly supported the biosynthesis of ribonucleotides. Glucose restriction did not affect B cell functions, yet the inhibition of OXPHOS or glutamine restriction markedly impaired B cell growth and differentiation. Increased OXPHOS prompted studies of mitochondrial dynamics, which revealed extensive mitochondria remodeling during activation. Our results show how B cell metabolism adapts with stimulation and reveals unexpected details for carbon utilization and mitochondrial dynamics at the start of a humoral immune response

The Socio-Economics Dynamics at Distribution of Small Scale Bananas Comodity in West Java

The pattern of the commercial banana farm rise the socio-economic dynamics in the value chain banana distribution. In West Java, the exposure to market information make banana farmers get access to the market directly but they have to encounter a domination of big seller (Bandar). This study aimed to analize the types of value chain and the relationships among the actors. This research was conducted in Cugenang, Cianjur, West Java by using qualitative methods of case approach. The results showed seven types of value chain in the banana distribution among the farmers to the consumer which realization the cooperation relationship of information flow, production inputs, and finance. The chain was build based on kinship, relationship farmer groups, relationship capital, and direct access to the market. Farmers related to middlemen for sorting and packing bananas, while relations with Bandar done by middlemen in capital bond. Farmer groups member had relationship with marketers group (BPK) which do grading the quality of bananas. Relations with capital loans bonding between farmer-middleman-Bandar made value chain grew longer and farmers increasingly passive in determining the price. Competition occured between sections of middlemen at the local level because of the dominance Bandar who controlled the market access. BPK independently sell commodities had compete with Bandar who has a network of cooperation in the middleman

Ampk regulates IgD expression but not energy stress with B cell activation.

Ampk is an energy gatekeeper that responds to decreases in ATP by inhibiting energy-consuming anabolic processes and promoting energy-generating catabolic processes. Recently, we showed that Lkb1, an understudied kinase in B lymphocytes and a major upstream kinase for Ampk, had critical and unexpected roles in activating naïve B cells and in germinal center formation. Therefore, we examined whether Lkb1 activities during B cell activation depend on Ampk and report surprising Ampk activation with in vitro B cell stimulation in the absence of energy stress, coupled to rapid biomass accumulation. Despite Ampk activation and a controlling role for Lkb1 in B cell activation, Ampk knockout did not significantly affect B cell activation, differentiation, nutrient dynamics, gene expression, or humoral immune responses. Instead, Ampk loss specifically repressed the transcriptional expression of IgD and its regulator, Zfp318. Results also reveal that early activation of Ampk by phenformin treatment impairs germinal center formation but does not significantly alter antibody responses. Combined, the data show an unexpectedly specific role for Ampk in the regulation of IgD expression during B cell activation

Enhancing volleyball training:empowering athletes and coaches through advanced sensing and analysis

Modern sensing technologies and data analysis methods usher in a new era for sports training and practice. Hidden insights can be uncovered and interactive training environments can be created by means of data analysis. We present a system to support volleyball training which makes use of Inertial Measurement Units, a pressure sensitive display floor, and machine learning techniques to automatically detect relevant behaviours and provides the user with the appropriate information. While working with trainers and amateur athletes, we also explore potential applications that are driven by automatic action recognition, that contribute various requirements to the platform. The first application is an automatic video-tagging protocol that marks key events (captured on video) based on the automatic recognition of volleyball-specific actions with an unweighted average recall of 78.71% in the 10-fold cross-validation setting with convolution neural network and 73.84% in leave-one-subject-out cross-validation setting with active data representation method using wearable sensors, as an exemplification of how dashboard and retrieval systems would work with the platform. In the context of action recognition, we have evaluated statistical functions and their transformation using active data representation besides raw signal of IMUs sensor. The second application is the “bump-set-spike” trainer, which uses automatic action recognition to provide real-time feedback about performance to steer player behaviour in volleyball, as an example of rich learning environments enabled by live action detection. In addition to describing these applications, we detail the system components and architecture and discuss the implications that our system might have for sports in general and for volleyball in particular.</p

Towards Automatic Modelling of Volleyball Players' Behavior for Analysis, Feedback and Hybrid Training

Automatic tagging of video recordings of sports matches and training sessions can be helpful to coaches and players and provide access to structured data at a scale that would be unfeasible if one were to rely on manual tagging. Recognition of different actions forms an essential part of sports video tagging. In this paper, the authors employ machine learning techniques to automatically recognize specific types of volleyball actions (i.e., underhand serve, overhead pass, serve, forearm pass, one hand pass, smash, and block which are manually annotated) during matches and training sessions (uncontrolled, in the wild data) based on motion data captured by inertial measurement unit sensors strapped on the wrists of eight female volleyball players. Analysis of the results suggests that all sensors in the inertial measurement unit (i.e., magnetometer, accelerometer, barometer, and gyroscope) contribute unique information in the classification of volleyball actions types. The authors demonstrate that while the accelerometer feature set provides better results than other sensors, overall (i.e., gyroscope, magnetometer, and barometer) feature fusion of the accelerometer, magnetometer, and gyroscope provides the bests results (unweighted average recall = 67.87%, unweighted average precision = 68.68%, and κ = .727), well above the chance level of 14.28%. Interestingly, it is also demonstrated that the dominant hand (unweighted average recall = 61.45%, unweighted average precision = 65.41%, and κ = .652) provides better results than the nondominant (unweighted average recall = 45.56%, unweighted average precision = 55.45, and κ = .553) hand. Apart from machine learning models, this paper also discusses a modular architecture for a system to automatically supplement video recording by detecting events of interests in volleyball matches and training sessions and to provide tailored and interactive multimodal feedback by utilizing an HTML5/JavaScript application. A proof of concept prototype developed based on this architecture is also described