Miracle-dz/UniFAR-FTUs huggingface dataset:
The smartphoners: consumer segmentation by smartphone usage

Smartphone usage is becoming an integral part of consumers’ lifestyle. Over 50% of the worldwide population own at least one smartphone and the adoption of mobile technologies have reshaped the boundaries between online and offline. This study aims to segment consumers by means of activities they perform on personal mobile phones. By analysing 264 online questionnaires and using ten smartphones’ functionalities, we identify five main Smartphoners’ profiles: Utility Users, Gamers, Unfriendly Users, Moderator Users and Supersmartphoners. Differences between smartphone users in terms of age, gender and area of residence, as well as brand of the smartphone owned, hours of usage and reasons to use have been investigated. Managerial and academic implications have been discussed.
Simple Technique Reducing Leakage Current for H-Bridge Converter in Transformerless Photovoltaic Generation

Given their structural arrangement, photovoltaic (PV) modules exhibit parasitic capacitance, which creates a path for high-frequency current during zero-state switching of the converter in transformerless systems. This current has to be limited to ensure safety and electromagnetic compatibility. Many solutions that can minimize or completely avoid this phenomenon, are available. However, most of these solutions are patented because they rely on specific and often complex converter topologies. This study aims to solve this problem by introducing a solution based on a classic converter topology with an appropriate modulation technique and passive filtering. A 5.5 kW single-phase residential PV system that consists of DC-DC boost stage and DC-AC H-bridge converter is considered. Control schemes for both converter stages are presented. An overview of existing modulation techniques for H-bridge converter is provided, and a modification of hybrid modulation is proposed. A system prototype is built for the experimental verification. As shown in the study, with simple filtering and proper selection of switching states, achieving low leakage current level is possible while maintaining high converter efficiency and required energy quality.
AN EFFICIENT SCHEDULING MECHANISM FOR DATA TRANSMISSIONS IN HEALTH CARE NETWORKS

- In health care networks, Internet of Things connects the patients with doctors and nurses through various devices effectively. The Wireless Body Area Networks play a vital role in the health care networks unlike most existing methods. WBAN communication is the method of transmitting information between WBAN-gateways and the medical centers. In this method, a gateway is assigned for a single patient and various medical packets are aggregated at each gateway. Their medical conditions are immediately reported to the base station with different priority levels based on their emergency. The base station forms the uplink WBAN transmissions by forming a queuing system which specifies the medical-grade Quality of Service requirements depending upon the priority of medical importance. The natural device intelligence of smart gateways in IoT-based networks designs an efficient and truthful mechanism to prevent gateways from misreporting the priority levels of medical packets. By incentivizing the base station, it manages the transmission scheduling in the desired manner by guaranteeing all gateways to honestly report the actual priority levels of the packets. Both theoretical and simulation results show that the proposed mechanism can meet all the requirements in terms of packet transmission.
Analysis of the Impact of a GPS Spoofing Attack on a UAV

The paper discusses scenarios of GPS spoofing attacks on UAVs. Three scenarios are proposed: when the attack is not carried out, when a low-intensity attack is carried out, and when an intense attack is carried out. After that, logs from the UAV are collected and the result of the attack is analyzed in relation to its impact on the cyber-physical parameters of the UAV. This analysis is carried out with the aim of further developing an intrusion detection and response system. It is necessary to understand which parameters change to what extent and under the influence of which attack scenario.
The intellectual system of movies recommendations based on the collaborative filtering

The investigation deals with designing and developing of intellectual system of movies recommendations based on the collaborative filtering using the Python software environment. In particular, the approaches (Content-based approach, Collaborative filtering, Hybrid models) in recommendatory system construction with the help of neural networks have been analyzed. It has been established that it is difficult to implement and learn the Content-based approach and it strongly depends on
Microsoft Word-6969532-file00

Dept. of Anesthesiology (RBM, EL, AO, RS, VJT, SMT), Neuroscience (VJT, SMT), Neuroscience Graduate Program (SMT, VJT) at the University of Virginia Health System, Charlottesville, VA; Dept. of Anesthesiology, InJe University Ilsan Paik Hospital & College of Medicine, Seoul, Korea (WJC); Department of Anesthesiology and Intensive Care Medicine, Tuebingen University Hospital, Eberhard-Karls University, Tuebingen, Germany (V-SE) Molecular Pharmacology Fast Forward. Published on August 5, 2011 as doi:10.1124/mol.111. 073205
Bacterial Vaginosis in Recent Abortion: An Observational Study in the Department of Obstetrics & Gynaecology, SMS Medical College, Jaipur

Background: Bacterial Vaginosis (BV) is the most common cause of abnormal vaginal discharge among women of reproductive age, accounting for 40 to 50 per cent of all cases of vaginal discharge.Bacterial Vaginosis (BV)is a special public health concern in India because of the high burden of reproductive and pregnancy-related morbidity.The purpose of the study is to lookfor the cost-effective, less time-consuming method that can be added to the routine screening for the women who are pregnant and having persistent vaginal discharge to help in reducing adverse pregnancy outcome. Also, screening of BV in fertile women is necessary to prevent spontaneous abortion. Material & Methods: This is a hospital based observational study done on women between the age of 1839 years, attending Gynaecological Out-Patient Department, with a history of spontaneous abortion 2 to 6 weeks back in SMS Medical College, Jaipur, Rajasthan.For sample collection, a nonlubricated bivalve speculum was inserted into the vagina, and vaginal swabs were taken from the vaginal walls and posterior fornix with four sterile cotton swabs for pH examination, whiff test, pap’s smear, Gram’s staining and culture. Results: Our study showed that no significant association was found between age, religion, residence & socio-economic status and BV. Maximum proportion (36%) of BV observed among women who had history of 2 nd trimester pregnancy loss.While classifying Bacterial vaginosis positive cases of recent spontaneous abortion according to Nugent score (Gram staining), 52.17% cases were positive on both scores and remaining all 47.82% cases showed intermediate results. Conclusion: We concluded that the screening of Bacterial Vaginosis in pregnant women may be used for evaluating women who are predisposed for abortion. However, to be able to use BV screening for routine purpose in determining the poor reproductive outcome, further work and research are needed.
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(General comments) At first, I felt some difficulties to understand the manuscript as “Research article” which should “report substantial new results and conclusions from scientific investigation. ” as expressed in the Manuscript types written on ACP Home Page. The manuscript is rather “Review” or “Overview article” for the special issue. Actually, it is indicated as the articles for the special issue, “Pan-Eurasian Experiment (PEEX)”, and the manuscript most fits as “Special issue overview article”.
Gongronema latifolium Benth . Leaves ( Uteze ) Ameliorate Malaria Infection in Plasmodium berghei-Infected Mice

Herbs are vital sources of bioactive compounds. This study evaluates the antimalarial, antioxidant, phytochemical and nutritional properties of Gongronema latifolium Benth. (Uteze) leaves. Pulverized dry leaves sample were macerated in hexane, methanol, ethanol and distilled water to obtain their respective extracts. The antimalarial efficacy of these extracts was assessed in male Swiss albino mice infected intraperitoneally with chloroquine-sensitive Plasmodium berghei NK65, using the chemo-suppressive, prophylactic and mean survival time (MST) assays. Phytochemical and proximate analyses were assessed by standard protocols. The antioxidant capacity of the extracts was analyzed using DPPH radical scavenging and ferrous ion chelating assays. From the results, the plant had significant (p < 0.05) antimalarial activity compared to the infected untreated control. The chemo-suppressive activity of the extracts declined accordingly; ethanol (46.34%) > methanol (43.16%) > aqueous (32.24%), while their prophylactic activity declined in the order of aqueous (40.25%) > ethanol (38.99%) > methanol (26.94%). Only MST in the four-day chemo-suppressive assay was significant (p < 0.05) compared to the infected untreated control. Tannins, alkaloids, flavonoids, saponins, phenolics, cardiac glycosides and proanthocyanidins were detected in reasonable quantities in the plant. The plant also had antioxidant activity as the aqueous extract (IC50 48.50 ± 0.42) scavenged DPPH radicals better, while methanol extract (IC50 21.15 ± 0.33) chelated ferrous ion radicals more compared to other extracts. Meanwhile, the percentage nutritional composition of the plant was moisture (6.23 ± 0.01), total ash (2.22 ± 0.02), crude fat (16.32 ± 0.04), crude fibre (1.04 ± 0.01), crude protein (9.33 ± 0.58) and nitrogen free extract (64.85 ± 0.63). In conclusion, the antimalarial activity of Gongronema latifolium Benth. (Uteze) leaves could be due to its rich phytochemical and nutritional properties. DOI: https://dx.doi. org/10.4314/jasem.v26i3. 7 Copyright: Copyright © 2022 Orumwensodia and Uadia. This is an open access article (https://pkp.sfu.ca/ojs/) distributed under the Creative Commons Attribution License (CCL), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Dates: Received: 23 August 2021; Revised: 21 December 2021; Accepted: 06 January 2022
Self-supervised learning for Formosan speech representation and linguistic phylogeny

Formosan languages, spoken by the indigenous peoples of Taiwan, have unique roles in the reconstruction of Proto-Austronesian Languages. This paper presents a real-world Formosan language speech dataset, including 144 h of news footage for 16 Formosan languages, and uses self-supervised models to obtain and analyze their speech representations. Among the news footage, 13 h of the validated speech data of Formosan languages are selected, and a language classifier, based on XLSR-53, is trained to classify the 16 Formosan languages with an accuracy of 86%. We extracted and analyzed the speech vector representations learned from the model and compared them with 152 manually coded linguistic typological features. The comparison shows that the speech vectors reflect Formosan languages' phonological and morphological aspects. Furthermore, the speech vectors and linguistic features are used to construct a linguistic phylogeny, and the resulting genealogical grouping corresponds with previous literature. These results suggest that we can investigate the current real-world language usages through the speech model, and the dataset opens a window to look into the Formosan languages in vivo.
Appendix: Spherical Motion Dynamics

Effective learning rate Since Batch Normalization (Ioffe & Szegedy, 2015) becomes an indispensable module of popular network structures, the scale of the weight norm does not affect the output of unit at all, Euclidean distance defined in weight space completely fails to measure the evolving of DNN during learning process. As a result, learning rate η cannot properly measure update efficiency of normalized DNN. To deal with such issue, van Laarhoven (2017); Hoffer et al. (2018); Zhang et al. (2019b) propose “effective learning rate” as a substitute for learning rate to measure update efficiency of normalized neural network using stochastic gradient descent (SGD), defined as
Contagion Prevention of COVID-19 by means of Touch Detection for Retail Stores

The recent Covid-19 pandemic has changed many aspects of people's life. One of the principal preoccupations regards how easily the virus spreads through infected items. Of special concern are physical stores, where the same items can be touched by a lot of people throughout the day. In this paper a system to efficiently detect the human interaction with clothes in clothing stores is presented. The system recognizes the elements that have been touched, allowing a selective sanitization of potentially infected items. In this work two approaches are presented and compared: the pixel approach and the bounding box approach. The former has better detection performances while the latter is slightly more efficient. Copyright for this paper by its authors. Use permitted under Creative.
Search Query Extension Semantics

The problems of extracting the most complete information from the semantic library by accounting for related documents are considered. Expert knowledge encrypted in the subject area can be made available when the user obtains additional information from linked documents. A feature of the approach is the use of a shallow neural network algorithm to expand the search query in mathematical subject areas, where expert knowledge is available with a significant scientific background of users. The solution to this problem can be achieved by means of semantic analysis in the knowledge space using machine learning algorithms. The paper investigates the construction of a vector representation of documents based on paragraphs in relation to the data array of the digital semantic library LibMeta. Each piece of text is labelled. Both the whole document and its separate parts can be marked. Since the problem of enriching user queries with synonyms was solved, when building a search model in conjunction with word2vec algorithms, an approach of “indexing first, then train-ing” was used to cover more information and give more accurate results.
Microsoft Word-32491666-file00

Unidad de Hepatología Experimental, Centro de Investigación, Hospital La Fe, Valencia, Spain (M.T.D., J.V.C., M.J.G., A.L.); CIBERehd, Centro de Investigación Biomédica en Red en el Área Temática de Enfermedades Hepáticas y Digestivas, Fondo de Investigación Sanitaria, Spain (M.T.D., J.V.C., M.J.G.); Departamento de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad de Valencia, Spain (M.T.D., J.V.C.); Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, United Kingdom (D.H., J.B.H.); Unidad Mixta Hospital La Fe-Advancell, Fundación para la Investigación Hospital La Fe, Valencia, Spain (L.P.) DMD Fast Forward. Published on May 25, 2010 as doi:10.1124/dmd.110. 033605
Addition of cellulolytic bacteria in complete feed block based on agro-industrial by- products for Kacang goats

Copyright resides with the authors in terms of the Creative Commons Attribution 4.0 South African Licence. See: http://creativecommons.org/licenses/by/4.0/za Condition of use: The user may copy, distribute, transmit and adapt the work, but must recognise the authors and the South African Journal of Animal Science. ______________________________________________________________________________________ Abstract The research aimed at assessing the effects on nutrient digestion and ruminal fermentation by goats of a complete feed block (CFB) that incorporated agro-industrial by-products that were high in fibre and cellulolytic bacteria. Three Kacang goats, a native Indonesian breed, were used in a 3 × 3 Latin square experimental design with i) CFB without microbes (control), ii) CFB containing 1% Pseudomonas aeruginosa and 1% Acinetobacter baumannii, and iii) CFB containing 2% P. aeruginosa and 2% A. baumannii. Microbes in the CFBs consisted of lactic acid bacteria, yeast and cellulolytic bacteria that ranged from 10 6 to 10 8 cfu/g. The goats were fed each day at 08h00 and 16h00. The inclusion of P. aeruginosa and A. baumannii at 2% level reduced both neutral detergent fibre (NDF) and acid detergent fibre compared with other treatments. Goats fed on CFB with microbes had higher (P <0.01) digestibility of organic matter (OM) and NDF compared with control. The addition of P. aeruginosa and A. baumannii at 2% level increased (P <0.05) ruminal ammonia nitrogen (N-NH3), acetate, and total VFA. However, goats fed on CFB with microbes had lower (P <0.05) urinary N excretion, which improved (P <0.05) N retention compared with the control. It was concluded that a combination of lactic acid bacteria, yeast and cellulolytic bacteria in the CFB could modify fermentation in the rumen and increase the use of nitrogen in goats. ______________________________________________________________________________________
Cheyne-Stokes Respiration Perception via Machine Learning Algorithms

With the development of science and technology, transparent, non-invasive general computing is gradually applied to disease diagnosis and medical detection. Universal software radio peripherals (USRP) enable non-contact awareness based on radio frequency signals. Cheyne-Stokes respiration has been reported as a common symptom in patients with heart failure. Compared with the disadvantages of traditional detection equipment, a microwave sensing method based on channel state information (CSI) is proposed to qualitatively detect the normal breathing and Cheyne-Stokes breathing of patients with heart failure in a non-contact manner. Firstly, USRP is used to collect subjects’ respiratory signals in real time. Then the CSI waveform is filtered, smoothed and normalized, and the relevant features are defined and extracted from the signal. Finally, the machine learning classification algorithm is used to establish a recognition model to detect the Cheyne-Stokes respiration of patients with heart failure. The results show that the system accuracy of support vector machine (SVM) is 97%, which can assist medical workers to identify Cheyne-Stokes respiration symptoms of patients with heart failure.
A Training Configurations

Training hyper-parameters. For both fully and semi-supervised node classification tasks on the citation networks, Cora, Citeseer and Pubmed, we train our DGC following the hyper-parameters in SGC [5]. Specifically, we train DGC for 100 epochs using Adam [2] with learning rate 0.2. For weight decay, as in SGC, we tune this hyperparameter on each dataset using hyperopt [1] for 10,000 trails. For the large-scale inductive learning task on the Reddit network, we also follow the protocols of SGC [5], where we use L-BFGS [3] optimizer for 2 epochs with no weight decay.
TUNNEL WIDENING OF ACL RECONSTRUCTION AUGMENTED BY AN PLATELET RICH OSTEOCONDUCTIVE-OSTEOINDUCTIVE ALLOGRAFT COMPOUND: A RANDOMIZED BLIND-ANALYSIS PILOT STUDY

Background: The anterior cruciate ligament (ACL) is a commonly injured ligament in the knee. Bone tunnel widening is a known phenomenon after soft-tissue ACL reconstruction and etiology and clinical relevance have not been fully elucidated. Osteoconductive compounds are biomaterials providing an appropriate scaffold for bone formation such as demineralized bone matrix. Osteoinductive materials contain growth factors stimulating bone lineage cells and bone growth. A possible application of osteoinductive/osteoconductive (OIC) material is in ACL surgery. Questions/Purposes: We hypothesized that OIC placed in ACL bone tunnels: 1) reduces tunnel widening, 2) improves graft maturation and 3) reduces tunnel ganglion cyst formation. To test this hypothesis, this study evaluated the osteogenic effects of demineralized bone matrix (DBM) and platelet rich plasma (PRP) on tunnel widening, graft maturation, and ganglion cyst formation. Study Design: Randomized controlled clinical trial pilot study. Methods: A total of 26 patients electing ACL reconstruction surgery were randomized between OIC and control group. Measurements of tunnel expansion and graft-tunnel incorporation were conducted via quantitative image analysis of MRI scans performed at six months after surgery for both groups. Results: No patients had adverse post-operative reactions or infections. The use of OIC significantly reduced tunnel widening (p < 0.05) and improved graft maturation (p < 0.05). Patients treated with OIC presented with a significantly lower prevalence of ganglion cyst compared to the control group (p < 0.05). Conclusion: The use of OIC has measurable effects on the reduction of tunnel widening, improved graft maturation and decreased size of ganglion cyst after ACL reconstruction. Clinical Relevance: This study explored the utilization of biologics to minimize bone tunnel widening in ACL reconstruction surgery. Study Design: Randomized controlled clinical trial.
A meta‐analytic investigation of grey matter differences in anorexia nervosa and autism spectrum disorder

Recent research reports Anorexia Nervosa (AN) to be highly dependent upon neurobiological function. Some behaviours, particularly concerning food selectivity are found in populations with both Autism Spectrum Disorder (ASD) and AN, and there is a proportionally elevated number of anorexic patients exhibiting symptoms of ASD. We performed a systematic review of structural MRI literature with the aim of identifying common structural neural correlates common to both AN and ASD. Across 46 ASD publications, a meta-analysis of volumetric differences between ASD and healthy controls revealed no consistently affected brain regions. Meta-analysis of 23 AN publications revealed increased volume within the orbitofrontal cortex and medial temporal lobe, and adult-only AN literature revealed differences within the genu of the anterior cingulate cortex. The changes are consistent with alterations in flexible reward-related learning and episodic memory reported in neuropsychological studies. There was no structural overlap between ASD and AN. Findings suggest no consistent neuroanatomical abnormality associated with ASD, and evidence is lacking to suggest that reported behavioural similarities between those with AN and ASD are due to neuroanatomical structural similarities.
Cheetah: Lean and Fast Secure Two-Party Deep Neural Network Inference

Secure two-party neural network inference (2PC-NN) can offer privacy protection for both the client and the server and is a promising technique in the machine-learning-as-a-service setting. However, the large overhead of the current 2PC-NN inference systems is still being a headache, especially when applied to deep neural networks such as ResNet50. In this work, we present Cheetah , a new 2PC-NN inference system that is faster and more communication-efﬁcient than state-of-the-arts. The main contributions of Cheetah are two-fold: the ﬁrst part includes carefully designed homomorphic encryption-based protocols that can evaluate the linear layers (namely convolution, batch normalization, and fully-connection) without any expensive rotation operation. The second part includes several lean and communication-efﬁcient primitives for the non-linear functions (e.g., ReLU and truncation). Using Cheetah , we present intensive benchmarks over several large-scale deep neural networks. Take ResNet50 for an example, an end-to-end execution of Cheetah under a WAN setting costs less than 2.5 minutes and 2.3 gigabytes of communication, which outperforms CrypTFlow2 (ACM CCS 2020) by about 5 . 6 × and 12 . 9 × , respectively.