Miracle-dz/UniFAR-FTUs huggingface dataset:
Municipal Failure, Unequal Access and Conflicts Over Water: A Hydrosocial Perspective on Water Insecurity of Rural Households in KwaZulu-Natal, South Africa

Despite South Africa’s modern water legislation and commitment to the Sustainable Development Goals, over three million South Africans, most of whom live in rural areas, still lack access to a basic supply of safe drinking water. This case study examines the implications of unequal levels of household water insecurity (HWI) among rural households and communities; it considers the effects on their health and productivity and on their power relations with other households. We first ask whether municipal water services have succeeded in improving water access and reducing HWI for served households in the study area; we then investigate misuse and vandalism of municipal water infrastructure – the reason it occurs and how it interrelates with unequal access and HWI. We understand HWI in both a physical and a relational sense and employ the hydrosocial cycle as a lens to explore its relational dimension. Our research indicates that the District Municipality responsible for water services has largely failed to improve water access and reduce HWI for users of standpipes and users of unimproved sources/surface water, with adverse effects on health and productivity; only users of illegal yard taps benefit from water services. Partial coverage, incremental infrastructure development, neglect of infrastructure maintenance and corruption have produced uneven power relations that result in conflicts over water, vandalism and misuse of water infrastructure.
An Improved Synthesis of Tetraarylporphyrins

An improved synthesis for 5,10,15,20-tetrakis(pentafluorophenyl)porphyrin, 5,10,15,20–tetrakis(2,4,6-trimethylphenyl)porphyrin and 5,10,15,20-tetrakis(2,6-dichlorophenyl)porphyrin by an acid-catalysed condensation of pyrrole and properly substituted aldehyde, followed by oxidation, is reported, with yields of up to 30% being obtained.
On the Stochastic Theory of Chromatography

Chromatography has been represented as a Poisson process and expressions have been derived for the elution curves of various types of chromatographic systems, such as a column with several kinds of sites, and a column with one kind of site but with various realistic input distributions. The previous stochastic treatments of chromatography have solved exactly only the case of a column with one kind of site with a delta‐function input distribution. These various cases have been solved by means of the complex‐variable theory of Laplace transforms. The exact expressions are usually complicated and of not much numerical utility. A technique is described by means of which any case can be well approximated by a consideration of only the first few central moments. This has proved to be of great practical use since there exists a theorem of mathematical statistics which allows one to determine moments of complex problems when those of simpler problems are known. This makes it possible to derive easily used expressions for the various elution curves.
SMU Data Science Review SMU Data

Networks are always under the threat of malicious intrusions. Deep learning models are used to help identify and mitigate intrusions before damage can occur. Various types of deep learning models have been researched, built, and tested with the goal of improving intrusion detection and efficiencies. In this paper, a two-phase deep learning approach called a Hybrid Intrusion Detection System (HIDS) is proposed that uses Bi-Directional Long Short-Term Memory Neural Network (BLSTM) to assess both flow-based network data and packet-based data. This approach is unique because BLSTM is employed rather than a traditional Deep Neural Network (DNN) and two models are used to assess both flow-based and packet-based data, whereas typically only one type of data is assessed. The two models were tested using the UNSW-NB15 dataset and performance was evaluated using accuracy, precision, recall, and F1-measure. Accuracy of the models was compared to results generated using DNN models. The BLSTM flow-based model achieved an accuracy of 96% compared to 93% using DNN. However, the BLSTM packet-based model achieved 76% accuracy, which is slightly lower than 81% using DNN. The results suggest that BLSTM is more effective in predicting flow-based data, but DNN is more effective in predicting packet-based data. Future work will be to improve the BLSTM packet-based model so that it is better than or comparable to DNN. Once this is achieved, analyzing both flow-based and packet-based data in a hybrid fashion using BLSTM could provide an extra layer of reliable protection if built in a cascaded scenario.
Adaptive Active Control of Combustion Instabilities

Abstract It is shown in this article that adaptive control algorithms may be used to suppress combustion instabilities in turbulent combustors. In a typical configuration a signal delivered by a sensor monitoring the flame serves as input to a numerical adaptive filter which sends a control signal through an actuator into the combustion chamber. The controller coefficients are updated at the sampling rate using a global response signal. The controller automatically finds optimal coefficients to control the different unstable modes of oscillation. In addition it adapts to evolutions in operating conditions such as a continuous sweep of air flow rate and a shift in the global equivalence ratio. Under certain conditions a secondary mode appears when the control system is operating. While this oscillation occurs as a result of a destabilizing effect of the control loop its amplitude remains limited. The theoretical background is developed and used to explain typical implementation problems such as the filter .
Evaluation of Modified CC Stabilization Using LARS Artificial Ligament in Unstable Distal Clavicle Fracture

Background: Unstable distal clavicle fracture is common, and there is no consensus regarding the gold standard treatment. The purpose of this study was to report a new surgical technique for the treatment of unstable distal clavicle fracture with modified coracoclavicular (CC) stabilization using a ligament augmentation and reconstruction system (LARS) artificial ligament, and to evaluate the clinical and radiographic outcomes.Patients and methods: We retrospectively reviewed 18 patients with acute unstable distal clavicle fractures (type Ⅱb) treated between January 2009 and June 2018 with modified CC stabilization using LARS artificial ligament. Indexes for evaluation included fracture healing, quality of reduction, and presence of complications (e.g., infections, nerve injuries, iatrogenic clavicle or coracoid fracture, the fixation loop failure, or loss of reduction). Shoulder function was evaluated using the Constant-Murley score.Results: Patients were assessed at a mean time of 31.8 months follow-up. All 18 patients experienced radiographic union. Follow-up radiographs showed anatomical reduction in 15 patients and slight loss of reduction in 3 patients. There were 2 cases of calcification of the CC ligament, 1 case of degenerative change around the acromioclavicular (AC) joint, and 1 case of clavicular osteolysis around screws noted during the follow-up. At the final follow-up, Constant scores were 91.2 ± 6.9. Conclusions: Treating unstable distal clavicle fractures (type Ⅱb) with modified CC stabilization using LARS artificial ligament resulted in a high union rate, satisfactory fracture reduction, a low complication rate, and excellent shoulder function. We consider this simple surgical technique that naturally restores stability to the distal clavicle fracture is an efficient method for treating the fracture.
Finite Time LTI System Identification

We address the problem of learning the parameters of a stable linear time invariant (LTI) system with unknown latent space dimension, or order, from a single time–series of noisy input-output data. We focus on learning the best lower order approximation allowed by finite data. Motivated by subspace algorithms in systems theory, where the doubly infinite system Hankel matrix captures both order and good lower order approximations, we construct a Hankel-like matrix from noisy finite data using ordinary least squares. This circumvents the non-convexities that arise in system identification, and allows accurate estimation of the underlying LTI system. Our results rely on careful analysis of self-normalized martingale difference terms that helps bound identification error up to logarithmic factors of the lower bound. We provide a data-dependent scheme for order selection and find an accurate realization of system parameters, corresponding to that order, by an approach that is closely related to the Ho-Kalman subspace algorithm. We demonstrate that the proposed model order selection procedure is not overly conservative, i.e., for the given data length it is not possible to estimate higher order models or find higher order approximations with reasonable accuracy.
The Impact of Foreign Direct Investment and Official Development Assistance on Tax Burden: An Analytical Study on Jordan

The purpose of this study is to investigate the effect of foreign direct investment and official development assistance on tax burden in Jordan employing the AutoRegressive Distributed Lags Bounds Testing (ARDL BT) co-integration approach to the data ranging from 1991 to 2018. The results indicated that there is a long-run relationship among variables. The results showed that there is a positive and statistically significant effect of the ratio of foreign direct investment to GDP (FDI) on tax burden (TB) in the long run, and a positive and statistically significant effect of the ratio of official development assistance to GDP (ODA) on tax burden (TB) in the long run. The estimation results indicate that a 1% increase in (FDI) increases (TB) by 0.53%, and a 1% increase in (ODA) increases (TB) by 1.45%. This study is the first of its kind in examining the impact of foreign direct investment and official development assistance together on the tax burden in Jordan.
A Pyrolysis Furnace with Reactor Tubes of Elliptical Cross Section

Circular tubes suspended in pyrolysis furnaces suffer from significant nonuniformities in heat flux, tube skin temperature, and coking rate profiles around the tube perimeter, due to the presence of front sides and shadow sides on the tubes. Simulation results for an ethane cracker with cracking tubes of elliptical cross section reveal that smoother circumferential heat flux, tube skin temperature, and coking rate profiles are obtained as the eccentricity of the elliptical tubes increases. The circumferential maximal values in coking rates are reduced by 30%. The more uniform tube skin temperature distributions and coke layers in tubes of elliptical cross section favor the run length of the furnace and the tube metal life.
Critical Success Factors on the Implementation of ERP Systems: Building a Theoretical Framework

Existing pressure for the confrontation of a radically changing external environment has led many companies to invest in various Information Systems, such as Enterprise Resource Planning (ERP), in order to optimize their production processes and strategies. Despite the fact that ERP system is an important strategic tool, many companies fail to take advantage of its benefits due to their default in many aspects of management and implementation. This study aims to investigate the critical success factors of enterprise resource planning system implementation and build a categorization framework so as to create a theoretical base that enhances any further research approaches in various sectors of the economy. Therefore, 37 ERP critical success factors were identified by using Content Analysis method and classified into relative categories to the ERP orientations of implementation and the ERP life cycle phases. Finally, these two types of categorization were merged in order to examine the critical success factors’ behavior during the ERP implementation. This paper and the multilateral theoretical framework it creates, sets out how critical success factors must be taken into account by companies and marks a beginning point that promises a sequence of further research approaches in particular economic sectors or in a set of them. By fulfilling the purpose of this study, a significant contribution to computer science literature and especially to the ERP field is offered. Keywords—Enterprise resource planning (ERP); ERP implementation; critical success factors (CSFs); content analysis (CA); categorization; theoretical framework
Different strokes for different folks: group variation in employee outcomes to human resource management Cafferkey,

Purpose Existing research on the relationship between human resources management (HRM) and employee outcomes rarely explores differences between employee groups and their receptiveness to HRM initiatives. Design/methodology/approach Using data from a single case organisation, the authors examine whether HRM practices applied uniformly across strategically distinct employee groups have differing influence on commitment, motivation and satisfaction of these groups. Findings Using occupational identity, the results indicate that different groups of employees have varied perceptions of, and reactions to, the same HRM practices. Originality/value The paper argues that existing theory and practice advocating universal or high potential HRM as a route to positive employee outcomes is potentially flawed. HRM ought rather to be tailored to the different specific utility needs of diverse occupational categories.
UV-9, UV-A, and Blue Light Signal Transduction Pathways lnteract Synergistically to Regulate Chalcone Synthase Gene Expression in Arabidopsis

UV and blue light stimulate transcription of key flavonoid biosynthesis genes in a range of higher plants. Here, we provide evidence that several distinct "inductive" and ''synergistic" UV/blue phototransduction pathways regulate chalcone synthase (CHS) gene transcription and transcript accumulation in Arabidopsis leaf tissue. Experiments with the long-hypocotyl hy4-2.23N mutant showed that separate inductive pathways mediate responses to UV-B and UV-Alblue light. Only the UV-Alblue light induction of CHS expression involved the CRYl photoreceptor. In addition, UV-A and blue light each act synergistically with UV-8 to stimulate CHS transcript accumulation and b-glucuronidase activity driven by a CHS promoter in transgenic leaf tissue. The UV-A and blue phototransduction pathways responsible for synergism are distinct because they produce transient and relatively stable signals, respectively, and can function additively to stimulate CHS promoter function. The hy4-2.23N mutant retains the synergistic interactions between UV-B and both UV-A and blue light, indicating that neither synergism pathway involves the CRYl photoreceptor. Our findings reveal considerable complexity in both photoreception and signal transduction in regulating CHS gene expression by UV and blue light.
Change in soft magnetic properties of Fe-based metallic glasses during hydrogen absorption and desorption

The stress level can be altered in soft magnetic amorphous alloys by hydrogen absorption. The resulting changes in the soft magnetic parameters are reversible or irreversible, depending on the chemical composition. Some of these effects are demonstrated in Fe–B, Fe–W–B, and Fe–V–B glassy ribbons, in which various magnetic parameters are measured mainly during hydrogen desorption. The rate of hydrogen desorption is also monitored by measuring the pressure change in a hermetically closed bomb. The observed phenomena are interpreted on the basis of induced stresses and chemical interactions between the solute metal and hydrogen.
A new emydine species from the Medial Miocene ( Barstovian ) of Nebraska , USA with a new generic arrangement for the species of Clemmys sensu MCDOWELL ( 1964 ) ( Reptilia : Testudines

K u r z f a s s u n g . Eine neue Emydinen-Art aus dem Mittel-Miozän (Barstovian) von Nebraska, USA, mit einer neuen Gattungseinteilung für die Arten von Clemmys sensu MCDOWELL (1964) (Reptilia: Testudines: Emydidae). – Aufgrund der eindeutigen Paraphylie der Gattung Clemmys sensu MCDOWELL (1964) wird vorgeschlagen, das Genus Clemmys RITGEN, 1828 auf die Typusart Clemmys guttata (SCHNEIDER, 1792) zu beschränken. Clemmys marmorata (BAIRD & GIRARD, 1852), die Emydinen mit Plastralscharnier nähersteht als den bisher mit marmorata in der Gattung Clemmys zusammengefassten Arten mit starrem Plastron, wird als Vertreter der monotypischen Gattung Actinemys AGASSIZ, 1857 betrachtet. Clemmys insculpta (LE CONTE, 1830 [1829]) und Clemmys muhlenbergii (SCHOEPFF, 1801) werden als Angehörige einer weiteren distinkten Gattung eingestuft, für die der Name Glyptemys AGASSIZ, 1857 (Species typica: Testudo insculpta LE CONTE, 1830 [1829] = Glyptemys insculpta) gewählt wird. Dadurch erhält dieser Name Vorrang vor dem für Testudo muhlenbergii SCHOEPFF, 1801 errichteten Gattungsnamen Calemys AGASSIZ, 1857. – Glyptemys valentinensis n. sp. wird anhand von umfangreichem Fundmaterial aus Nebraska (USA) beschrieben. Mit dieser neuen Art ist die Gattung Glyptemys seit dem Mittel-Miozän bekannt (mittleres bis oberes Barstovian: ca. 14,5-11,5 Mio. Jahre vor heute). Morphologisch ähnelt Glyptemys valentinensis der rezenten Glyptemys insculpta mehr als G. muhlenbergii. Es wird vermutet, dass sich G. insculpta aus G. valentinensis zwischen dem oberen Barstovian und dem oberen Hemphillian (11,5-5,5 Mio. Jahre vor heute) entwickelt hat. G. valentinensis könnte der letzte gemeinsame Vorfahre von G. insculpta und G. muhlenbergii sein, da Sequenzdaten des mitochondrialen Cytochrom b-Gens für eine Differenzierung beider Taxa genau im mittleren Barstovian (vor ca. 14,5 Millionen Jahren) sprechen.
Dielectric studies of PVDF crystallization. Application to in-situ monitoring in injection molding

In recent years, experimental techniques based on microdielectrometry have presented an attractive and increasing interest for continuous monitoring in a nondestructive way of the advancement of thermoset resin reactions under cure. A new application of this technique has been carried out also for in situ monitoring of thermoplastic crystallization. Therefore, a dynamic rheometer equipped with a dielectric cell, as well as an instrumented slit die, were designed. The crystallization process is depicted by a conductivity drop as well as by the occurrence of a maximum in the real permittivity. The decrease of the specific conductivity results from a modification of the conductive paths whereas the increase in permittivity is due to an interfacial polarization phenomenon between the amorphous phase and the growing crystalline entities. As a second step of development, microdielectrometry has been applied for in situ monitoring of the crystallization of thermoplastics during an injection molding process. The electric sensors were located at the walls of the mold cavity so that an analysis of bulk dielectric properties during the filling, post-filling and the cooling phases could be performed. The dielectric method detailed herein provides a new non-invasive technique and could be applied to a closed-loop control of the injection molding process.
A Typology of Young Cocoa Farmers in Ghana-Attitudes , Motivation and Aspirations

The average age of cocoa farmers over the decades suggest that most people tend to venture cocoa farming career at a latter age of their lives. While older farmers are less likely to well adopt good agricultural practices and are more risk averse in farm investments, young cocoa farmers are more likely to well adopt good agricultural practices to enhance yields. This rationale is partly behind the drive to bring more young people into cocoa farming with the government, donor agencies and civil society organizations making great investments into the young people with the aim to increase national production as well as secure the future of the Ghanaian cocoa industry. However, the young people tend to be considered as a relatively homogenous group when the reality is great heterogeneity in young people’s characteristics, past experiences, and future aspirations. We argue in this paper that it is important to know the typology of youth within the farming communities in order to make judicious investments. This paper introduces the concept of young cocoa farmer typology as a means for targeting prudent investment and extension delivery. The paper is based on a survey that was conducted in Offinso, Wassa Akropong and Asumura in the Ashanti, Western and Brong-Ahafo regions of Ghana respectively with a total of 120 young cocoa farmers. Using the two-step clustering approach, three types of young cocoa farmers were derived: positive young cocoa farmers (34.2%), pessimistic young farmers (36.7%) and stuck young farmers (29.1%). Results suggest that these young farmers’ exposure and previous experiences, in particular their familiarity with successful cocoa farmers in their immediate environment significantly motivated their attitudes towards cocoa farming. Further, the future aspirations of young farmers could significantly affect their attitudes. It is thus recommended that government policies and programmes or interventions to increase youth in cocoa farming for cocoa sustainability be more targeted, with customized approaches that addresses heterogeneity among cocoa farmers in order that interventions may achieve the desired impact. Introduction Many authors (e.g., Boahene et al., 1999; Anim-Kwapong et al., 2005; Baffoe-Asare et al., 2013) have noted that older farmers have risk averse attitudes towards cocoa farming and are less likely to well adopt good agricultural practices that enhance yields. In Ghana majority of cocoa farmers are aged (above 50 years old) and this raises concerns of sustainability in the cocoa industry. Meanwhile, analyses of the average age of cocoa farmers from some studies suggest that the narrative of ageing cocoa farmers may not be accurate since their average age has remained fairly constant for over two decades (Figure 1). Figure 1: Average age of cocoa farmers over the years based on previous research Source: Authors’ construct 53 50 50 49 52
Deep learning for classification of sleep EEG data during the epidemic of Coronavirus Disease

Sleep is an important part of the body's recuperation and energy accumulation, and the quality of sleep also has a significant impact on people's physical and mental state during the epidemic of Coronavirus Disease. It has attracted increasing attention how to improve the quality of sleep and reduce the impact of sleep related diseases on health. The electroencephalogram (EEG) signals collected during sleep belong to spontaneous EEG signals. Spontaneous sleep EEG signals can reflect the body own changes, which is also an important basis for diagnosis and treatment of related diseases. Therefore, the establishment of an effective model for classifying sleep EEG signals is an important auxiliary tool for evaluating sleep.