Miracle-dz/UniFAR-FTUs huggingface dataset:
Trial results for the production of the improved 5LP linter

A pilot-industrial copy of an improved mixer has been developed to implement an effective process of seed raising. The manufactured pilot copy was installed on the 5LP linter in the cotton spinning workshop of the cotton spinning enterprise SANGZOR TEKSTIL LLC, Dostlik district, Jizzakh region, and the linter was improved, comparative research work was carried out with the 5LP linter with a simple construction mixer in the workshop. The studies were carried out at a distance of 8-12 mm between the saw cylinder and the mixer, selected on the basis of theoretical and practical results. During the experimental period, the quality of seeds obtained from the lint of seeds of the Bukhoro-6 variety of selection I improved by an average of 0.37 (abs)% to 0.85 (abs)%, and the quality of down improved by 0.62 (abs) % to 0.78 (abs.)%. Improving the quality of down one class higher, UzDST 645:2016 “Cotton lint. Technical conditions” type I corresponded to type B “Middle” class. Linter performance averaged 47 kg/h to 35 kg/h of seed and 2.8 kg/h to 3.4 kg/h of fluff compared to the existing 5LP linter. The quality of seeds obtained by linting seeds of the III variety of Bukhara-6 selection in the proposed 5LP linter by an average of 0.46 (abs)% to 0.38 (abs)%, the quality of fluff by 0.37 (abs)% improved by 0.25 (abs) %. Produced down is a class higher, UzDst 645:2016 “Cotton lint. Technical conditions”, type II type B was the “Middle” class. It was found that the productivity of the linter is 46-49 kg/h higher for seeds and 3.1-4.0 kg/h for linter than that of the 5LP linter with a simple mixer design. As a result of research work using an improved mixer in a 5LP linter working chamber, installing 6 mm thick rubber on metal sheets in the mixer, while pushing rubber from metal sheets to a distance of 6 mm, so as not to adversely affect the amount of oil extracted from seeds when lintering technical seeds, the distance between the rubber sheets and the saw cylinder was determined to be set at 8-10 mm, and when linting seeds, 12 mm should be left so as not to exceed the specified rate.
Sustainable coastal management in supporting blue economy: an Indonesian experience

The coastal regions had a great ecosystem and potential for the sustainability of life. At the same time, growing human and environmental pressures in coastal areas significantly impact coastal systems. Various problems arise in the development and utilisation of the coastal regions. The issues have prompted the importance of studying coastal area management policies. Specifically, legal uncertainty in the management of utilisation has initiated the formulation of the RZWP3K policy. This study uses stakeholder analysis to map the actors involved and their influence on coastal area management policies. This study was conducted using a qualitative method and stakeholder analysis to explore and classify the actors shaping coastal area management policies. The stakeholder analysis method classified constituents into important actors, contextual fixers, users, and audiences using variables of interest and impact. Developing policies for coastal management is hampered by the conflicting agendas of many parties and their multiple goals and worries. This study recommends that the government maintain stakeholders by keeping them informed, actively groomed, monitored and managed, or satisfied. This paper contributes to conceptual stakeholder analysis literature to analyse coastal area management policies.
Sustainable Livelihood of Fishers in Palangpang Beach, Sukabumi, Indonesia

Ciletuh is an areas in Sukabumi which was inaugurated as Global Geopark by UNESCO in 2017, and has many potential natural resources. The high number of visits at Palangpang Beach, Ciwaru Village, is an opportunity for fishermen in Ciwaru Village to participate in activities involving fishermen in the marine tourism sector but this is inversely proportional to the infrastructure development at the Ciletuh Geopark. So, it is important to analyze sustainable livelihood of fishermen before and after the development of the Ciletuh Geopark. The research methods used are descriptive analysis, and sustainable livelihood analysis. The results show that sustainable livelihood assets of fishermen who increasing were human capital, social capital, physical capital, and economic and financial capital, while natural capital experienced a decline in assets due to the accumulation of garbage on the shore and in the sea that interferes with fishing activities. Finally, The local government and the management of Auction Place of Fish of Ciwaru have made improvements to fishery support facilities, in the form of parking lots for fishing boats and more adequate fish landings for fishermen, but the government needs to manage the garbage on the beach area.
Resistance functions for spherical particles, droplets and bubbles in cylindrical tubes

Numerical computations are performed to evaluate the resistance functions for low Reynolds number flow past spherical particles, droplets and bubbles in cylindrical domains. Spheres of arbitrary radius a and radial position b move with arbitrary velocity U within a cylinder of radius R. The undisturbed fluid may be at rest, or subject to a pressure-driven flow with maximum velocity U0. The spectral boundary element method is employed to compute the resistance force for torque-free bodies in three cases: rigid solids, fluid droplets with viscosity ratio λ = 1, and bubbles with viscosity ratio λ = 0. A lubrication theory is developed to predict the limiting resistance of bodies near contact with the cylinder walls. Compact algebraic expressions are developed which accurately represent the numerical data over the entire range of particle positions 0 < b/(R − a) < 1 for all particle sizes in the range 0 < a/R < 0.9. The resistance functions are consistent with known analytical results and are presented in a form suitable for further studies of particle migration in cylindrical vessels.
Study on the effective use of solar and hydro energy for powering agriculture and water management

This article highlights the combined use of solar and hydropower based on a rational combination of traditional and renewable energy sources for powering agriculture and water management. At the same time, a combined integrated power supply system was formed. Provided, the energy is required from renewable sources, it fully provides the consumer, and the excess energy is transferred to the centralized network (N″), if the energy received from the network is less than the energy entering the network, the recommended system is efficient (N′″).
Novel heuristic-based hybrid ResNeXt with recurrent neural network to handle multi class classification of sentiment analysis

Present-day, interdisciplinary research is increasing in social network-related applications, and it is a daily routine activity in every human life. So, sentiment analysis (SA) based on opinion mining is the most sophisticated concept in the well-known social network environment. Different machine learning methods were implemented to extract different text label features in SA, and all of those methods can detect whether a given text is positive or negative based on the text features. Analysis of sentiment has been suffering from inaccuracies while using machine learning and sentiment-based lexical methods dependent on domain-specific problems. Multi-class SA is an expensive task where memory, label samples, and other parameters are insufficient. So, we propose and implement a novel hybrid model which is a combination of ResNeXt and recurrent neural framework (NH-ResNeXt-RNF) to explore multi-class sentiment from textual features. This framework investigates the polarity of words connected to a specific domain across the entire dataset and eliminates noisy data in an unsupervised manner using pre-processing. Optimization is required to perform efficient multi-class classification to reduce the effort associated with annotation for multi-class SA via unsupervised learning. The proposed model performance is evaluated on two data sets namely: Amazon and Twitter. We increase the accuracy of the sentiment of polarity on each sentence present in the data set. Experimental results of the proposed approach give better and more efficient multi-class (positive, negative, very positive, neutral and highly negative) domain-specific sentiment than traditional approaches related to supervised, semi-supervised, and unsupervised domains. The proposed hybrid model accuracy is 96.5% and 95.37% for Amazon and Twitter datasets respectively.
High-flow nasal oxygen as an adjunct for the safe removal of impacted metallic upper airway foreign bodies

Abstract Foreign body airway obstruction is considered an airway emergency and is a challenging clinical scenario for both the otolaryngologist and the anaesthetist. We present three cases of impacted upper airway metallic foreign bodies. Supra-glottic airways were obstructed and precarious. Apnoeic oxygenation utilizing high-flow nasal oxygen (HFNO), a form of tubeless anaesthetic, was used in all three cases, leading to the safe removal of the foreign bodies. Increased training, awareness and equipment availability to provide HFNO apnoeic oxygenation in the emergency setting for otolaryngology airway procedures will lead to better outcomes for patients and decreases the risk of a potential surgical airway.
Novel Scheme for Defining the Clinical Implications of TP53 Mutations in Myeloid Neoplasia

Background: TP53 mutations (TP53MT) occur in diverse genomic configurations. Particularly, biallelic inactivation is associated with poor overall survival in cancer. Lesions affecting only one allele might not be directly leukemogenic, questioning the presence of cryptic biallelic subclones in cases with dismal prognosis. Methods: We have collected clinical and molecular data of 7400 patients with myeloid neoplasms and applied a novel model to properly resolve the allelic configuration of TP53MT and assess prognosis more precisely. Results: Overall, TP53MT were found in 1010 patients. Following the traditional criteria, 36% of cases were classified as single hits while 64% exhibited double hits genomic configuration. Using a newly developed molecular algorithm, we found that 579 (57%) patients had unequivocally biallelic, 239 (24%) likely contained biallelic, and 192 (19%) had most likely monoallelic TP53MT. Such classification was further substantiated by a survival-based model built after re-categorization. Among cases traditionally considered monoallelic, the overall survival of those with probable monoallelic mutations was similar to the one of wild-type patients and was better than that of patients with a biallelic configuration. As a result, patients with certain biallelic hits, regardless of the disease subtype (AML or MDS), had a similar prognosis. Similar results were observed when the model was applied to an external cohort. These results were recapitulated by single-cell DNA studies, which unveiled the biallelic nature of previously considered monoallelic cases. Conclusion: Our novel approach more accurately resolves TP53 genomic configuration and uncovers genetic mosaicism for the use in the clinical setting to improve prognostic evaluation.
PROTOCOL: Interventions to increase youth employment: An evidence and gap map

Abstract The research question guiding the production of the youth employment evidence and gap map (EGM) is stated as follows: What is the nature and extent of the evidence base of impact evaluations and systematic reviews on youth employment programmes in the world? The primary objective of is to catalogue impact evaluations and systematic reviews on youth employment interventions to enhance discoverability of evidence by decision makers, development patterners and researchers, so as to promote evidence‐based decision making in programming and delivery of youth employment initiatives. This evidence gap map is also a primary input into the implementation of Mastercard Foundation's strategy titled “Africa Works: Mastercard Foundation Strategy 2018–2030”, which points out sharing of evidence‐based knowledge and innovation with stakeholders as a key strategy to be used (Mastercard Foundation). The time frame for the development of the youth EGM will run from the last quarter of 2019 to December 2020. The five secondary objectives are: (i) To construct a framework for the classification of youth employment effectiveness studies. The objective will be achieved through the development of an intervention and outcome framework using an engaged consultative process involving the review team, Mastercard Foundation and other stakeholders. (ii) To identify available evidence, and clusters of evidence, including its quality rating. This will involve activities such as identification of studies using a standardised study search strategy, screening and coding of studies in EPPI Reviewer 4, which is a web‐based software program for production of reviews. (iii) To create a map of youth employment effectiveness studies equipped with an appealing user‐friendly web‐based search content visualisation using interactive mapping software. To achieve this object, data coded in EPPI Reviewer 4 will be exported to another software (EPPI mapper) which is designed for generating EGMs. (iv) To produce a narrative report of the youth employment EGM. This will be achieved through analysis of data in EPPI Reviewer 4 and report writing. To disseminate the EGM to users to increase awareness to support evidence‐informed decision‐making across countries. We will achieve this objective by organising dissemination workshops, participating in conferences and hosting the evidence and gap on our websites.
Filopodia-like protrusions of adjacent somatic cells shape the developmental potential of oocytes

Filopodia-like protrusions sent by the somatic cells to the oocyte play a role in the structural integrity of the germline–somatic complex, and regulate gene expression in the oocyte and thus its developmental potential and chances to produce a viable embryo. The oocyte must grow and mature before fertilization, thanks to a close dialogue with the somatic cells that surround it. Part of this communication is through filopodia-like protrusions, called transzonal projections (TZPs), sent by the somatic cells to the oocyte membrane. To investigate the contribution of TZPs to oocyte quality, we impaired their structure by generating a full knockout mouse of the TZP structural component myosin-X (MYO10). Using spinning disk and super-resolution microscopy combined with a machine-learning approach to phenotype oocyte morphology, we show that the lack of Myo10 decreases TZP density during oocyte growth. Reduction in TZPs does not prevent oocyte growth but impairs oocyte-matrix integrity. Importantly, we reveal by transcriptomic analysis that gene expression is altered in TZP-deprived oocytes and that oocyte maturation and subsequent early embryonic development are partially affected, effectively reducing mouse fertility. We propose that TZPs play a role in the structural integrity of the germline–somatic complex, which is essential for regulating gene expression in the oocyte and thus its developmental potential.
Challenges and opportunities in remote sensing-based crop monitoring: a review

Abstract Building a more resilient food system for sustainable development and reducing uncertainty in global food markets both require concurrent and near-real-time and reliable crop information for decision making. Satellite-driven crop monitoring has become a main method to derive crop information at local, regional, and global scales by revealing the spatial and temporal dimensions of crop growth status and production. However, there is a lack of quantitative, objective, and robust methods to ensure the reliability of crop information, which reduces the applicability of crop monitoring and leads to uncertain and undesirable consequences. In this paper, we review recent progress in crop monitoring and identify the challenges and opportunities in future efforts. We find that satellite-derived metrics do not fully capture determinants of crop production and do not quantitatively interpret crop growth status; the latter can be advanced by integrating effective satellite-derived metrics and new onboard sensors. We have identified that ground data accessibility and the negative effects of knowledge-based analyses are two essential issues in crop monitoring that reduce the applicability of crop monitoring for decisions on food security. Crowdsourcing is one solution to overcome the restrictions of ground-truth data accessibility. We argue that user participation in the complete process of crop monitoring could improve the reliability of crop information. Encouraging users to obtain crop information from multiple sources could prevent unconscious biases. Finally, there is a need to avoid conflicts of interest in publishing publicly available crop information.
High-power and highly reliable operation of Al-Free InGaAs-InGaAsP 0.98-/spl mu/m lasers with a window structure fabricated by Si ion implantation

We have fabricated Al-free InGaAs-InGaAsP-GaAs strained quantum-well 0.98-/spl mu/m lasers with a window structure. The window structure was obtained by Si ion-implantation-induced QW intermixing. The photoluminescence and photocurrent measurements show that an implantation energy of 100 keV and a dose of 1E13 cm/sup -2/ are enough for the fabrication of the window structure in our laser structure. The threshold current of the fabricated 0.98-/spl mu/m lasers with a window structure is 20 mA and a stable lateral mode is obtained up to 300 mW, and these results suggest that there is no scattering loss or absorption due to the introduction of a window structure. The reliability of the lasers is greatly improved by the introduction of the window structure: they exhibited stable operation for more than 1000 h at 240-mW output power at 50/spl deg/C. And this results gives us an estimated lifetime of more than 200 000 h at 25/spl deg/C.
Discrete singular convolution method for buckling analysis of rectangular Mindlin plates

The discrete singular convolution (DSC) method is proposed for solving the elastic buckling problem of thick rectangular plates under a uniaxial compressive loading. To allow for the effect of transverse shear deformation in thick plates, the Mindlin plate theory has been adopted. The numerical results are checked against available analytical and other numerical solutions. It is found that the convergence of the DSC approach is very good and the results agree well with those obtained by other researchers.
A Bayesian Estimate of the Pricing Kernel

The focus of this article is the Pricing Kernel (PK), the building-block of asset pricing theory. In the classical framework the shape of the PK is monotonically decreasing in the stock price, nevertheless empirical evidence suggests that the PK is locally increasing in the interval around the 0% return and has an irregular behaviour in the tails of the distribution. We argue that these deviations, known as pricing kernel puzzle, derive from a dis-homogeneity between the physical and the risk neutral (RN) measure and can be corrected by embedding some forward looking information into the physical measure. Our proposed methodology combines the information from historical returns with that coming from the RN measure through a non-parametric Poisson-Dirichlet process. As a result the irregular behaviour of the PK in the tails of the distribution is reduced and the monotonicity is ensured in almost all cases.
Mixed-Integer Quadratic Optimization and Iterative Clustering Techniques for Semi-Supervised Support Vector Machines

Among the most famous algorithms for solving classification problems are support vector machines (SVMs), which find a separating hyperplane for a set of labeled data points. In some applications, however, labels are only available for a subset of points. Furthermore, this subset can be non-representative, e.g., due to self-selection in a survey. Semi-supervised SVMs tackle the setting of labeled and unlabeled data and can often improve the reliability of the results. Moreover, additional information about the size of the classes can be available from undisclosed sources. We propose a mixed-integer quadratic optimization (MIQP) model that covers the setting of labeled and unlabeled data points as well as the overall number of points in each class. Since the MIQP's solution time rapidly grows as the number of variables increases, we introduce an iterative clustering approach to reduce the model's size. Moreover, we present an update rule for the required big-$M$ values, prove the correctness of the iterative clustering method as well as derive tailored dimension-reduction and warm-starting techniques. Our numerical results show that our approach leads to a similar accuracy and precision than the MIQP formulation but at much lower computational cost. Thus, we can solve solve larger problems. With respect to the original SVM formulation, we observe that our approach has even better accuracy and precision for biased samples.
On Finite-Step Convergence of the Non-Greedy Algorithm and Proximal Alternating Minimization Method with Extrapolation for $L_1$-Norm PCA

The classical non-greedy algorithm (NGA) and the recently proposed proximal alternating minimization method with extrapolation (PAMe) for $L_1$-norm PCA are revisited and their finite-step convergence are studied. It is first shown that NGA can be interpreted as a conditional subgradient or an alternating maximization method. By recognizing it as a conditional subgradient, we prove that the iterative points generated by the algorithm will be constant in finitely many steps under a certain full-rank assumption; such an assumption can be removed when the projection dimension is one. By treating the algorithm as an alternating maximization, we then prove that the objective value will be fixed after at most $\left\lceil\frac{F^{\max}}{\tau_0} \right\rceil$ steps, where the stopping point satisfies certain optimality conditions. Then, a slight modification of NGA with improved convergence properties is analyzed. It is shown that the iterative points generated by the modified algorithm will not change after at most $\left\lceil\frac{2F^{\max}}{\tau} \right\rceil$ steps; furthermore, the stopping point satisfies certain optimality conditions if the proximal parameter $\tau$ is small enough. For PAMe, it is proved that the sign variable will remain constant after finitely many steps and the algorithm can output a point satisfying certain optimality condition, if the parameters are small enough and a full rank assumption is satisfied. Moreover, if there is no proximal term on the projection matrix related subproblem, then the iterative points generated by this modified algorithm will not change after at most $\left\lceil \frac{4F^{\max}}{\tau(1-\gamma)} \right\rceil$ steps and the stopping point also satisfies certain optimality conditions, provided similar assumptions as those for PAMe. The full rank assumption can be removed when the projection dimension is one.