Miracle-dz/UniFAR-FTUs huggingface dataset:
UTICAJ SOCIODEMOGRAFSKIH FAKTORA NA RAZVOJ ANKSIOZNOSTI U TOKU

Uvod/Cilj: Pandemija Kovid-19 predstavlja ozbiljnu pretnju globalnom mentalnom zdravlju. Strah od smrti, socijalno distanciranje, ekonomski problemi, promene u obrazovanom sistemu i prestanak uobičajenog svakodnevnog funkcionisanja indukuju psihijatrijske poremećaje, u prvom redu anksioznost. Cilj istraživanja je bio da se utvrditi uticaj sociodemografskih faktora na razvoj anksioznosti u toku pandemije Kovid-19. Metode: Studijom preseka, tokom dva meseca, bilo je obuhvaćeno 200 osoba bez simptoma Kovida-19, 60,0% žena i 40,0% muškaraca, prosečne starosti 51,0 ± 9,2 godina. Sto osoba se javilo u ambulantu porodične medicine Doma zdravlja Krupa na Uni zbog pregleda ili administrativnih razloga, a drugih sto je bilo u njihovoj pratnji. Pored opšteg upitnika za prikupljanje podataka, korišćen je Upitnik za samoprocenu intenziteta simptoma generalizovanog anksioznog poremećaja (engl. Generalized Anxiety Disorder-7, GAD-7). U statističkoj analizi podataka korišćeni su χ2-test i Fisher-ov test. Rezultati: Simptome anksioznosti imalo je 52,5% ispitanika uključenih u ovu studiju preseka, i to 35,0% blage, 15,5% umerene i 2,0% ozbiljne. Anksioznost je nešto češće bila kod muškarca (56,2%) nego žena (50,0%), kao i kod starijih (60-79 godina) (92,6%) nego mlađih ispitanika (12,5% za uzrast 20-39 i 44,7% za uzrast 40-59 godina). Osobe sa nižim stepenom obrazovanja (44,5% ispitanika sa osnovnom i 46,6% sa srednjom školom) su češće bile sa simptomima anksioznosti, nego osobe sa višim stepenom obrazovanja (33,3%), zaposleni (69,5%) u odnosu na nezaposlene (43,0%), i osobe koje žive u urbanoj (80,8%) nego ruralnoj sredini (42,6%). Simptomi anksioznosti zabeleženi su kod 51,3% ispitanika koji su bili u braku ili vanbračnoj zajednici i kod 56,8% ispitanika koji nisu bili u braku ili vanbračnoj zajednici. Osobe sa simptomima anksioznosti su značajno češće bile uzrasta 60-79 godina nego osobe bez anksioznosti. Između ovih grupa nije bilo značajne razlike u odnosu na pol, stepen obrazovanja, zaposlenost, mesto stanovanja i bračni status ispitanika. Zaključak: Svaka druga osoba u ovom istraživanju imala je neki vid anksioznosti. Neophodna su dalja istraživanja u ovoj oblasti i predlaganje adekvatnih preventivnih programa.
1 PASTORALISM AND CONSERVATION – WHO BENEFITS ?

Conservation business is booming in East Africa, but is threatened by major long term wildlife declines. Pastoralist rangelands are among the highest-earning and fastest-growing tourism destinations, but their populations have mean incomes and development indices consistently below national averages. Governments and conservation organisations see green development, often through community-based conservation (CBC), as building sustainable livelihoods and biodiversity conservation in EA rangelands. We look at the contribution conservation makes to Maasai pastoralist livelihoods, based on studies in two Tanzanian and three Kenyan sites differing in proximity to protected areas, urban settlements, markets and infrastructure, and in wildlife-related revenues, as well as in national economic and political context. Conservation brings little to household income in most sites compared to returns from livestock, cultivation, and off-farm work. Special circumstances mean conservation business brings local benefits in the Mara, but are rarely achieved elsewhere. Pace and scale of conservation-driven loss of access to resources has serious implications for livelihoods security, while negative tradeoffs from CBC and “conservation with development” initiatives may drive both impoverishment and wildlife declines. Background Conservation is big business in East Africa. Tourism is regularly among the top three contributors to GDP and to foreign exchange earnings in Kenya, accounting for USD 884 million in 2010 (KShs 73.7 billion). Despite the global financial crisis, Tanzania earned 1.16 billion USD from tourism in 2009. In both countries, tourists are largely drawn by the appeal of wildlife alongside other attractions. Conservationists see tourists’ dollars as one of the principal means to generate meaningful income for the rural poor. Government policies (URT 2005; UNDP/UNEP/IIED/IUCN/WRI 2005), conservation NGO projects (AWF 2005), entrepreneurial initiatives (Nelson 2004; www.Lewa.org) and research publications (Pearce and Moran 1994, Hutton et al 2005) all promote wildlife-based tourism. Maasailand, the region of Kenya and Tanzania dominated by Maa-speaking pastoralists, is a hotspot of conservation, poverty and new initiatives to redistribute tourist income, and a good place to explore dynamics and distribution of revenues. In Kenya, Maasailand and other pastoral areas represent among the fastest growing tourism destinations (33% growth in bed-nights 2004-5: Ministry of Tourism and Wildlife 2006). In Tanzania in 2009, 16 National Parks earned 43.8 million USD, Ngorongoro Conservation Area 1 http://www.tourism. go.ke/ministry.nsf/pages/facts_figures; Kenya National Bureau of Statistics (economic survey; leading economic indicators) http://www.knbs. or.ke/ 2 http://www.tanzania. go.tz/economicsurveyf.html:
Can you explain AI to me? Teachers’ pre-concepts about Artificial Intelligence

As a starting point for a professional development (PD) program for teachers, this Research Full Paper investigates which ideas and pre-concepts teachers have about artificial intelligence (AI). Along with artificial intelligence’s increasing relevance in society, it is also finding its way into curricula for K-12. However, in this context, it is not only the students who are confronted with a new topic, but also their teachers. The vast majority of CS teachers have not dealt with AI during their studies and are, therefore, facing a stiff challenge when it comes to teaching it. Consequently, there is an unquestionable need for professional development for teachers in the field of artificial intelligence.Following the strategy of the Professional Development for CS Principles (PD4CS) initiative, a broad characterization of the content knowledge related to the respective topic is necessary as a first step. For this reason, semi-structured interviews were conducted with teachers with different levels of experience and varying previous knowledge of Computer Science to find out what pre-concepts about AI teachers would bring into a PD program. Based on this, together with a body of knowledge gathered from experts and reference books in artificial intelligence, the necessary AI content knowledge of the teachers is defined.The semi-structured interviews were analyzed using a qualitative approach based on the text analysis of Mayring. To respond to low intercoder-agreement, we used an approach described by Campbell and Quincy.Investigations of previous knowledge in programming show that this knowledge has a significant impact on misconceptions found with the participants. Bonar and Soloway identified gaps in previous knowledge as one reason for this. Our findings point to a similar effect of previous knowledge in the field of AI. This poses a problem as our participants are teachers who will be AI instructors themselves and who might pass on certain misconceptions to their students. Consequently, the accurate identification and description of the teachers’ knowledge gaps is an important starting point for providing a suitable and successful professional development program.
Content-Based Music Recommendation using Deep Learning

Music streaming services use recommendation systems to improve the customer experience by generating favorable playlists and by fostering the discovery of new music. State of the art recommendation systems use both collaborative filtering and content-based recommendation methods. Collaborative filtering suffers from the cold start problem; it can only make recommendations for music for which it has enough user data, so content-based methods are preferred. Most current content-based recommendation systems use convolutional neural networks on the spectrograms of track audio. The architectures are commonly borrowed directly from the field of computer vision. It is shown in this study that musically-motivated convolutional neural network architectures outperform architectures that are highly-optimized for image-related tasks. A content-based recommendation model is built using musically-motivated deep learning architectures. The model is shown to be able to map an artist onto an artist embedding space where its nearest neighbors by cosine similarity are related artists and make good recommendations. It is also shown that metadata, such as lyrics, artist origin, and year, significantly improve these mappings when combined with raw audio data.
Re-sampling in instrumental variables regression

Instrumental variables regression in the context of a re-sampling is considered. In the work one builds a framework identifying a target of inference. It tries to generalize an idea of a non-parametric regression and motivate instrumental variables regression from a new perspective. The framework assumes a target of estimation to be formed by two factors an environment and internal model specific structure. Aside from the framework, the work develops a re-sampling method suited to test linear hypothesis on the target. Particular technical environment and procedure are given and explained cohesively in the introduction and in the body of the work that follows. Specifically, following the work of Spokoiny, Zilova 2015 [20], the writing justifies and applies numerically multiplier bootstrap procedure to construct non-asymptotic confidence intervals for the testing problem. The procedure and underlying statistical toolbox were chosen to account for an issue appearing in the model and overlooked by asymptotic analysis. That is weakness of instrumental variables. The issue, however, is addressed by design of the finite sample approach by Spokoiny 2014 [18] and in that sense the study contributes to econometric theory. Moreover, in the work a set of mathematical tools crucial for the discussion were developed or in case was needed build. Among others the work covers the topics: classification of instrumental variables, general justification of finite sample approach, namely Wilks expansion, matrix concentration inequalities and a general way to regularize a probability function.
Information content of radiance climatologies for advanced infra-red sounders

When assimilating observations into numerical weather prediction (NWP) models, it is usually assumed that there are two sources of information: the observations and the NWP background field. Current research to improve the exploitation of advanced infra-red sounder data is making use of “radiance climatologies”, i.e. large ensembles of “historical” radiances from the same instruments. The leading principal components (PCs) of the covariances of such ensembles are being used to make the processing and assimilation of these data more efficient in both the forward (radiative transfer) computation and the inverse (retrieval/assimilation) component and to reduce the noise in the measured spectra. These radiance climatologies therefore constitute a potential third source of information for retrieval/assimilation processes. We consider here, from a theoretical perspective, the status of this third source of information and its implications for retrieval/analysis accuracy. We compare two methods of applying PCs to the processing of IASI spectra: simple PC truncation and optimal radiance estimation. We show why it is possible to reduce the noise in IASI Level 1C data considerably (by a factor ~3), yet this does not lead to comparable reductions in retrieval/analysis error. We also present the theory required to consider whether it is possible, with information from the radiance climatology, to reduce the retrieval error at all.
Supply Chain Quality and Organizational Performance: Moderating Role of Competitive Advantages

Efficient Supply Chain Management (SCM) has become an extremely flexible means of obtainingmarket advantages and improving company productivity as there is no longer rivalry within firms but supplychains. Such investigations conceptualize and address five facets of SCM practices (supplier strategic alliance,customer relationships, information exchange, efficiency exchange, and postponement) and examine thecorrelation with SCM operations, competitive gains, and organizational outcomes. Data was collected from 232Jordanian individuals, and structural equation analysis was used to assess the connections involved in theresearch. The results indicate that competitive advantages have a small effect on supply chain efficiency andorganizational performance. The comparative edge would therefore specifically and valuably impact corporateperformance. This work provides theoretical evidence to support methodological and prescriptive conclusions onthe consequences of SCM practices in the literature.
Simulation and Experiment Reveal a Complex Scenario for the Adsorption of an Antifungal Drug in Ordered Mesoporous Silica

Ordered mesoporous silicas have been widely investigated as drug carriers in several fields, from tissue engineering to cancer therapy. The knowledge of the specific interactions between the surface of mesoporous silicas and drugs is necessary to guide development of new and improved drug delivery systems. However, such knowledge is still scarce, due to the arduous interpretation of experimental results. In this work, we characterize the incorporation of clotrimazole, a common antifungal drug, inside ordered mesoporous silica by means of a joint computational and experimental approach. Experimentally the drug was loaded through supercritical CO2 and its adsorption investigated through infrared spectroscopy, N2 adsorption isotherms, and thermogravimetric analysis. Modeling involved static and dynamic Density Functional Theory simulations of clotrimazole adsorbed on realistic models of amorphous silica surfaces. A good agreement between the computational and the experimental results was obtained, concerning.
SEMEN FREEZING AND SUBSEQUENT INSEMINATION RESULTS IN SOUTH AFRICAN ANGORA GOATS

INTRODUCTION Genetic improvement in a breed is dependent on the rate of genetic change achieved in stud animals and the rate and efficiency of distribution of this superior genetics to the lower levels of the breed structure. The Angora Ram Breeders wanted to expedite this process by making superior genetics available to the entire industry through frozen semen. However, the low historic conception rates achieved with laparoscopic insemination with frozen semen in Angora goats were unacceptable and would inhibit the widespread use of this technology in the industry. Therefore, various trials were conducted over a 10-year period with the aim to develop a frozen semen protocol for South African Angora goats.
A Comparison of Communication Tone and Responding Across Users and Developers in Two R Mailing Lists

—The R programming language has an active community of both users and developers, which maintain mailing lists to communicate. Given their differences in training and stability, the effects of communication tone on responding may differ across these two groups. We thus compared the prevalence and characteristics of different tones in the R-help user and R-devel developer mailing lists over a ten-year period as well as their relation to replies. Our analyses indicate that developers displayed marginally more positive and negative tones than users. Moreover, developers seemed less inﬂuenced by tone when choosing to reply to messages. Overall, our results suggest that different tones may produce small differences in responding across users and developers.
A cross-sectional study on prevalence of cryptosporidiosis and its associated risk factors in calves in Gondar town and its suburbs, NW Ethiopia. Online J. Anim. Feed Res., 9(4): 162-168. www.ojafr.ir;

Cryptosporidiosis is a common gastrointestinal disorder in humans and animals caused by various Cryptosporidium species. The present study was carried out to determine the prevalence of cryptosporidium oocyst and its potential risk factors in calves less than one year of age in and around Gondar town. For this purpose, 384 fecal samples (n=384 calves) from different dairy farms were collected and screened by using modified Ziehl-Neelsen staining technique. The overall prevalence of Cryptosporidium oocysts was 21.4 % (82/384). The association between different risk factors and prevalence of Cryptosporidium oocysts was assessed. There were significant associations (P<0.05) between prevalence of Cryptosporidium oocysts and age of calves, fecal consistencies, daily cleaning of the farm and water source. On the other hand, there was no significant association between prevalence of Cryptosporidium oocysts and sex, breed, and body condition of the calves and also provision of colostrums to the calves (P>0.05). In conclusion, this study demonstrated host factors and management factors greatly affect the prevalence of Cryptosporididosis in calves. Therefore, the current study reported the role of host factors (age and sex) and management factors (water source and daily cleaning of the farm) needed to be clearly recognized by all stakeholders in order to understand their effects on the disease occurrences as well as in control and prevention of in calves.
A Review on High Performance Cloud Computing in Big Data

Cloud computing is the product of the traditional computer technology and network technology development integration. Such as grid computing, distributed computing, parallel computing, utility computing, network storage, virtualization, and load balancing. To perform integrating multiple relative low-cost computing entities into one perfect system with powerful computing ability via the network and with the help of the SaaS, PaaS, IaaS, MSP and other advanced business models distributing this powerful computing ability to the hands of the end user. Cloud computing system mainly uses MapReduce model. The core design idea of MapReduce is to divide and conquer the problem and calculate on data rather than push data to calculate which effectively avoids many communication costs generated during data transmission.
Biopeaks: a Graphical User Interface for Feature Extraction from Heart- and Breathing Biosignals

Heartand breathing biosignals increasingly gain popularity in academia and industry, sparked by the availability of easy-to-use, low-cost biosignal sensors along with a growing ecosystem of free, open-source software for the analysis of biosignals (Carreiras et al., n.d.; Makowski et al., 2020). However, an open-source, freely available graphical user interface (GUI) for biosignal analysis is currenly lacking. biopeaks addresses this need. Compared to application programming interfaces (Carreiras et al., n.d.; Makowski et al., 2020), its GUI allows for more intuitive and immediate visual interaction with the biosignal, which is especially valuable during data preprocessing and exploration. At the time of writing, biopeaks is used in multiple projects at the Gemhlab.
Rickettsia aeschlimannii and Wolbachia endosymbiont in Ctenocephalides canis from Eurasian lynx (Lynx lynx) Near the China-Kazakhstan Border

Twenty-five dog fleas (Ctenocephalides canis) and five ticks identified as Hyalomma asiaticum were collected from a Eurasian lynx (Lynx lynx) pup in northwestern China. Molecular analyses of four genetic markers showed the presence of Rickettsia aeschlimannii DNA in 5 out of 20 fleas. Only rickettsial 17-kDa gene was detected in the blood sample of the lynx. In addition, 2 out of 20 fleas were positive to Wolbachia endosymbiont by targeting 16S rDNA while there was no Bartonella DNA found both in 5 ticks and 20 fleas by using gltA and 16S-23S ITS. Our findings suggest that i) C. canis parasitizing wild Eurasian lynx harbors R. aeschlimannii and Wolbachia endosymbiont in the China-Kazakhstan border, and ii) Wolbachia endosymbiont in present study is closer to that in C. canis infesting sheltered dogs in Turkey.
DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings

Word embeddings are a core component of modern natural language processing systems, making the ability to thoroughly evaluate them a vital task. We describe DiaLex, a benchmark for intrinsic evaluation of dialectal Arabic word embeddings. DiaLex covers five important Arabic dialects: Algerian, Egyptian, Lebanese, Syrian, and Tunisian. Across these dialects, DiaLex provides a testbank for six syntactic and semantic relations, namely male to female, singular to dual, singular to plural, antonym, comparative, and genitive to past tense. DiaLex thus consists of a collection of word pairs representing each of the six relations in each of the five dialects. To demonstrate the utility of DiaLex, we use it to evaluate a set of existing and new Arabic word embeddings that we developed. Beyond evaluation of word embeddings, DiaLex supports efforts to integrate dialects into the Arabic language curriculum. It can be easily translated into Modern Standard Arabic and English, which can be useful for evaluating word translation. Our benchmark, evaluation code, and new word embedding models will be publicly available.
Increased systemic HSP70B levels in spinal muscular atrophy infants

Despite newly available treatments for spinal muscular atrophy (SMA), novel circulating biomarkers are still critically necessary to track SMA progression and therapeutic response. To identify potential biomarkers, we performed whole‐blood RNA sequencing analysis in SMA type 1 subjects under 1 year old and age‐matched healthy controls. Our analysis revealed the Heat Shock Protein Family A Member 7 (HSPA7)/heat shock 70kDa protein 7 (HSP70B) as a novel candidate biomarker to track SMA progression early in life. Changes in circulating HSP70B protein levels were associated with changes in circulating neurofilament levels in SMA newborns and infants. Future studies will determine whether HSP70B levels respond to molecular therapies.