Miracle-dz/UniFAR-FTUs huggingface dataset:
International Association for Management of Technology Iamot 2015 Conference Proceedings Ict Adoption in Smes for the Alleviation of Poverty

In developing countries information and communication technology (ICT) can be used as a tool for driving socio‐economic development such as poverty reduction. Small and medium enterprises (SMEs) are an engine for growth and they play an important role in poverty reduction by providing employment and driving economic development. In this research we followed an integrated approach whereby existing theories and government policy documents were analysed. Furthermore, the empirical data of other studies were used for comparison purposes. This research presents a theoretical analysis on how ICTs can be used to alleviate poverty by SMEs in South Africa. It describes the contribution of SMEs and the impact of ICTs on economic development and alleviation of poverty. ICT usage and a discussion of the various barriers faced by South African SMEs when adopting ICT are covered. The Word Bank strategy for attacking poverty is explored from a South African perspective. A theoretical framework has been constructed using the building blocks proposed by the theory of Schwarz et al. (2010), as well as the insights discovered from the current literature and empirical data. The framework provides a better understanding of how poverty can be attacked through the interaction of various stakeholders involved in the process, as well as the use of ICT in the SME environment. The results of this study will benefit the government and non‐government agencies that focus on the development of the SME sector, guiding them on how best to implement ICT initiatives to achieve poverty alleviation and accelerate usage. This will contribute to informing and enabling policy formulation, regulatory practice and business operations to produce positive growth and development outcomes.
Prevalence of depression in women diagnosed with breast cancer in Georgia

Abstract Background: Depression commonly occurs in patients with breast cancer (BC), significantly affecting their quality of life. We screened Georgian women diagnosed with BC for depressive symptoms to determine their prevalence and examine associations with various sociodemographic and clinical characteristics. This is the first study focusing on mental well-being in patients with cancer in Georgia. Methods: In a multicenter observational study, 177 women receiving BC treatment were examined at three tertiary oncology hospitals in Georgia. Patient Health Questionnaire 9 (PHQ-9) was used for the identification of depressive symptoms. Patients were stratified using basic information on age, marital status, educational level, social and financial support, employment status, and clinical characteristics. Results: The average age was 52.9 years (34–77); 117 (66%) were married; 79 (45%) were working, but only 30 (17%) reported having adequate financial status; 128 (72%) had stage I-III disease; and 64 (36%) reported some degree of pain. Using pro-rated PHQ-9 scores, 46 patients (44%; 95% CI, 37–51) reported some level of depressive symptoms while 25 women (14%; 95% CI, 9–19) met the criteria for probable depressive disorder. A higher proportion of patients reporting pain also reported depressive symptoms (37/66, 56%) compared with those reporting no pain (41/111, 34%) (P = .013); women with stage IV disease were more likely to report depressive symptoms (26/44, 57%) compared with those with stages I-III (53/133, 40%) (P = .049); and single/previously married women (42/60, 70%) were more likely to report depressive symptoms than married women (51/117, 44%) (P = .001). Depressive symptom reporting did not differ by age or reported support. Conclusion: One in six of this sample of Georgian patients with BC had depressive symptom levels consistent with a depressive disorder. Depressive symptoms covaried by marital status, staging, and reported pain. These results can inform practitioner oncologists in Georgia of the needs for psychological support for patients with cancer and assist in building such support services.
Did indigenous conservation ethics exist

Despite the common assertion that some indigenous peoples were conservationists, a number of authors have claimed that persuasive evidence for this is lacking. They have, apparently, overlooked such evidence. It is well documented, for example, that centuries ago Pacific Islanders invented and employed all the basic marine conservation measures that Europeans began to use only in the early 1900s. For islanders to have devised and employed deliberate conservation measures, they first had to learn that their natural resources were limited. They could only have done so by depleting them. Evidence that a culture overharvested or otherwise damaged its natural resources at some period in its history is no proof that it was, for all times, non-conservationist. Some Pacific Island cultures learned that their marine resources were limited and introduced marine conservation measures accordingly. Others never learned this lesson because their marine resources always exceeded harvesting pressure. I suggest that a worldwide survey of relevant literature would show that societies that developed conscious conservation practices were usually small and relied on natural resources that were circumscribed and thus easily depleted. Today, in an era of shrinking natural resource frontiers, establishing whether a conservation ethic exists in an indigenous culture is a vital first step in determining how to help its people live within their natural resource limits.
An improved graph convolutional networks for fault diagnosis of rolling bearing with limited labeled data

Rolling bearings are essential parts of rotating equipment. Due to their unique operating environment, bearings are vulnerable to failure. Graph neural network (GNN) provides an effective way of mining relationships between data samples. However, various existing GNN models suffer from issues like poor graph-structured data quality and high computational consumption. Moreover, the available fault samples are typically insufficient in real practice. Therefore, an improved graph convolutional network (GCN) is proposed for bearing fault diagnosis with limited labeled data. This method consists of two steps: graph structure data acquisition and improved graph convolution network building. Defining edge failure thresholds simplifies the generated weighted graph-structured data, thereby enhancing data quality and reducing training computation costs. Improvements to standard GCNs can effectively aggregate data features of different receptive field sizes without noticeably raising the computational complexity of the model. Experiments with limited labeled data are conducted on two public datasets and an actual experimental platform dataset to verify the superiority of the proposed method. In addition, experiments on imbalanced datasets also fully demonstrate the robustness of the proposed method.
Spherical Array-Based Joint Beamforming and UAV Positioning in Massive MIMO Systems

This work considers a spherical array (SA)-based dual-hop massive multiple-input multiple-output (mMIMO) system using an unmanned aerial vehicle (UAV) as an amplify-and-forward (AF) relay between the base station (BS) and Internet of Things (IoT) gateway. We propose a particle swarm optimization (PSO)-based UAV deployment technique to maximize the total achievable rate by considering joint optimization of UAV location, hybrid beamforming (HBF) at two terminal nodes, and analog beamforming/combining at the UAV relay. Additionally, we employ singular value decomposition (SVD) of the channel matrices to form the transmit and receive radio frequency (RF) stages of the UAV relay, and an orthogonal matching pursuit (OMP)-based algorithmic approach to the HBF for the BS and the gateway. The illustrative results show that our proposed joint beamforming scheme for two distinct SA configurations significantly improves spectral and energy efficiencies, and outperforms uniform rectangular arrays (URAs).
The Projection of Temperature and Precipitation over China under RCP Scenarios using a CMIP5 Multi-Model Ensemble

Abstract Climate changes in 21st century China are described based on the projections of 11 climate models under Representative Concentration Pathway (RCP) scenarios. The results show that warming is expected in all regions of China under the RCP scenarios, with the northern regions showing greater warming than the southern regions. The warming tendency from 2011 to 2100 is 0.06°C/10 a for RCP2.6, 0.24°C/10 a for RCP4.5, and 0.63°C/10 a for RCP8.5. The projected time series of annual temperature have similar variation tendencies as the new greenhouse gas (GHG) emission scenario pathways, and the warming under the lower emission scenarios is less than under the higher emission scenarios. The regional averaged precipitation will increase, and the increasing precipitation in the northern regions is significant and greater than in the southern regions in China. It is noted that precipitation will tend to decrease in the southern parts of China during the period of 2011–2040, especially under RCP8.5. Compared with the changes over the globe and some previous projections, the increased warming and precipitation over China is more remarkable under the higher emission scenarios. The uncertainties in the projection are unavoidable, and further analyses are necessary to develop a better understanding of the future changes over the region.
Cell-Free Massive MIMO with Protective Partial Zero-Forcing and Active Eavesdropping

We consider a cell-free massive MIMO (CF-mMIMO) system with multi-antenna access points (APs) and distributed protective partial zero-forcing (PPZF) precoding, which is prone to an active eavesdropping attack during uplink training. We develop a tractable analytical framework to derive a novel closed-form expression for the spectral efficiency (SE) at the users and eavesdropper (Eve), and, hence, the secrecy SE. These closed-form expressions are of particular importance for enabling further system design. Our findings show that PPZF can substantially outperform the conventional maximum-ratio transmission (MRT) scheme especially when the ratio of number of AP antennas to the number of users is high. Moreover, the secrecy enhancement obtained by using a higher number of AP antennas is more pronounced when Eve is located farther away from the legitimate user. Finally, simulation results validate the accuracy of the derived theoretical analysis.
Audio-Visual Praise Estimation for Conversational Video based on Synchronization-Guided Multimodal Transformer

This study investigates praise estimation, the task of estimating the existence of preferable behaviors of a speaker in a conversational video. To estimate praises from multimodal information, considering synchronized behavior across modalities is important. Such cross-modal synchronization can be modeled by the conventional multimodal Transformer in a time-axis concatenation architecture because it models relevance between all time steps of all input modalities using attention matrices. However, the attention matrices are so high-dimensional that the model training can be difﬁcult with a limited amount of training data. To alleviate this problem, we propose introducing a loss function representing the prior knowledge that the attention should link around the synchronized time steps across the input modalities. Our experiments on a business negotiation conversation corpus showed that the proposed method could improve the praise estimation’s macro F1.
Accentor: An Explicit Lexical Stress Model for TTS Systems

The accurate placement of word stress is a critical component of the correct pronunciation of words. Contemporary publicly available text-to-speech (TTS) datasets have a relatively narrow coverage of unique words, which causes modern neural TTS systems to synthesize speech that often suffers from lexical stress errors. In this work, we propose an efﬁcient approach for explicitly modeling lexical stress knowledge with a dedicated Accentor neural network. The Accentor is trained separately on a large lexically diverse stress-annotated text corpus that is automatically compiled using an automatic speech recognition system. We demonstrate that the Accentor can be combined with a TTS acoustic model to reliably control the word stress encoded in the generated acoustic features. Experiments show that our approach increases the stress prediction accuracy by a factor of 12 in comparison to other modern TTS systems and improves the naturalness and comprehensibility of the synthesized speech. 1
Porous Natural Diamond with Embedded Metal (Pt0.50–Co0.50)

Natural diamond crystals with a highly porous surface were used as substrates for synthesizing single-phase bimetallic Pt–Co nanoparticles at temperatures of 500 °C and 800 °C. The metal nanoparticles inside the pores were determined to take the form of single-phase Pt0.50Co0. 50 solid solutions with different degrees of superstructure ordering. A detailed characterization of both nanoalloys revealed a tetragonal symmetry with a space group, P4/mmm. For the sample obtained at 500 °C, the lattice parameters were a = 2.673(2), c = 3.735(3) Å, and c/a = 1.397(1); for the samples obtained at 800 °C, the parameters were—a = 2.688(2), c = 3.697(3) Å, and c/a = 1.375(1). Within the experimental parameters, no significant chemical interaction of the diamond with the Pt–Co particles was identified. The results demonstrate a strong anchoring effect of the metallic material within the etching pores. The successful synthesis of bimetallic Pt–Co particles embedded inside the caverns can facilitate a study of their magnetic properties. The presence of Pt–Co in specific diamond compositions can also be used for marking diamond crystals as a means for their subtle identification, as well as confirming the possibility of capturing significant amounts of metal along with diamonds during their dissolution in the deep Earth.
An Analysis of Glottal Features of Chronic Kidney Disease Speech and Its Application to CKD Detection

Chronic kidney disease (CKD) causes a continuous decline in kidney function and structural damage to the kidneys. The speech characteristics of CKD speakers will be different from those of non-CKD speakers because the typical characteristics of CKD, which are impairment of respiratory and laryngeal muscles, can affect respiration, the primary source of speech. In this paper, we identify the glottal characteristics of CKD speech and then investigate whether CKD can be automatically detected using the glottal features. Statistical analysis shows significant differences between groups in glottal source features, representing the breathy characteristic of CKD speech. Through the classification experiment, we compare the performance of solely using voice quality features (baseline) against additional glottal and spectral features. When glottal source features and voice quality features are used together, an F1-score of 0.88 with a 76% relative increase compared to the baseline is obtained.
Geochemistry and Mineralogy of Peridotites and Chromitites from Zhaheba Ophiolite Complex, Eastern Junggar, NW China: Implications for the Tectonic Environment and Genesis

The Zhaheba ophiolite is an ocean relic of the Zhaheba-Aermantai oceanic slab, a branch of the early Paleozoic Paleo-Asian Ocean. The peridotites consist mainly of harzburgite, lherzolite and minor dunite, chromitite. This study describes the whole-rock geochemistry and mineral chemistry of the Zhaheba peridotite and chromitite for the purpose of constraining their tectonic environment and genesis. The major oxides and the trace element concentrations of the peridotites are comparable with abyssal peridotite, but fall outside the field of SSZ (suprasubduction zone) peridotite and the fore-arc peridotite. The massive chromites belong to the high-Cr group, with an average Cr# (Cr/(Cr + Al)) atomic ratio) value of chromian spinel of 0.77, whereas the average Mg# value is 0.60. The disseminated chromites give a lower concentration of Cr2O3 (38.96–42.15 wt.%, average 40.35 wt.%) and lower Cr# values (0.50–0.56, average 0.53), but slightly higher contents of MgO (13.23 wt.%) and Mg# (0.61) than the massive chromites. In the diagrams of Cr#-Mg#, NiO-Cr# and TiO2-Cr#, the massive chromites fall in the field of boninite, and the disseminated chromite in the peridotite plot fall in the field of abyssal peridotite and mid-oceanic ridge basalt (MORB). The massive chromitites, with high-Cr, display a boninite affinity, whereas the disseminated chromite plot in the high-Al and abyssal peridotite type field may be generated by the extension of the Zhaheba ocean in the MOR environment then experienced deep subduction and exhumation. The calculated degrees of partial melting for the massive chromites are 21%−22%, and for the disseminated chromites in peridotites the degrees are 17%−18%. The calculated values of fO2 for the massive chromites range from −1.44 to +0.20, and the values for the disseminated chromites range from −0.32 to +0.18. The inferred parental melt composition for massive chromitite falls in the field of boninite in an arc setting, whereas the disseminated chromite in peridotites are in the field of a MORB setting. This indicates that the parental magmas of the former were more refractory than the latter. A two-stage evolution model for the chromites was proposed, in which disseminated chromites were first formed in an MOR environment and then modified by later-stage melts and fluids, and formed massive chromites were formed in an SSZ setting during intra-oceanic subduction.
Psychometric Properties of the Peruvian Version of the MOS Scale for Social Support in Cancer Patients and Convergent Network with Quality of Life

Introduction One of the key psychosocial factors that impact mental and emotional health is social support. While much research has been conducted on the role of social support in the lives of cancer patients, there is a lack of studies that consider populations who need specific tools to assess this concept. Purpose The aim of this study was to evaluate the psychometric properties of the MOS Social Support Scale (1991) in 499 Peruvian cancer patients between the ages of 18 and 87 (M= 46.30, SD = 15.747). Methods In this study, three models of the MOS were analyzed based on 19-item versions (four factor, second order and bifactor model). Results The results showed a better psychometric fit in the 19-item bifactor model with optimal fit indices through the structural equation method (SB-χ2/df = 1.94, CFI = 0.966, TLI= 0.955, SRMR = 0.038 and RMSEA = 0.058). Additionally, there was evidence of configural, metric and scalar invariance with this instrument according to the gender of the surveyed cancer patients. Convergent validity using a network analysis approach revealed positive associations between social support dimensions and quality of life. Conclusion Emotional support and positive interactions dimensions were found to be important interconnections in the overall network, as indicated by their greater centralities. Therefore, this instrument could be suggested as a reliable way to evaluate cancer patients and their perceived support.
Exploiting the DD-Cell as an Ultra-Compact Entropy Source for an FPGA-Based Re-Configurable PUF-TRNG Architecture

Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) are both needed in the Privacy Preserving Mutual Autentication (PPMA) protocol, often used in IoT Applications to generate and secure cryptographic keys. Since to guarantee security of IoT nodes in an untrusted setting, the PPMA key and encrypted data must be located on the same chip, the concept of integrating both a PUF and a TRNG on the same device has emerged as a new security paradigm. Up to now only a few designs for achieving PUF and TRNG simultaneously on field programmable gate array (FPGA) platforms have been presented in the technical literature, and most of them show sub-optimal performance for one of the two cryptographic primitives. This paper presents a re-configurable design that is able to operate as an FPGA-compatible PUF+TRNG primitive, and relies on the Delay-Difference-Cell (DD-Cell) as the basic entropy source. A theoretical model of the DD-Cell explaining the PUF and the TRNG behaviour of the DD-Cell which highlights the effects of the routing connections on the FPGA on the performances is presented. The proposed solution has been implemented on the Artix-7 FPGA platform, and an extensive measurement campaign involving 32 FPGA boards has been carried out. Measured performances of the proposed PUF and TRNG primitives have been compared against state of the art PUFs and TRNGs, showing performances in line with the state of the art. The comparison against the PUF+TRNG designs available in the literature has shown that the proposed solution exhibits the best trade-off among PUF and TRNG performance, providing the most compact PUF and the highest throughput TRNG.
PRODUCTIVITY OF INTERCROPPING SYSTEM IN SUGARCANE WITH SUGARBEET AND WHEAT

Results of two years field experiments conducted to explore the possibilities of remunerative autumn planting of cane by intercropping and by changing the method of planting showed that autumn planting sugarcane intercropped with sugarbeet or wheat significantly increased the cane production and gives Rs.19427- and Rs. 9681-additional income, respectivley, when compared with standard practice of spring planting giving monetary return of Rs 10646 per ha. Further it was observed that paired planting of sugarcane at 45 cm and using the 135 cm inter-paired space for growing intercrops was superior to uniform raw spacing.