cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25036364
title: Treating pain in sickle cell disease by means of focused ultrasound neuromodulation (Ultrasound Characterizations: Computer Simulations)

description: We developed a novel transcranial focused ultrasound transducer for treating pain in humanized sickle cell mice. The project promises to provide non-pharmacologic chronic pain treatment for patients associated with underlying conditions such as cancer or sickle cell disease (SCD).This dataset includes 5 .mat files with formatted transcranial focused ultrasound simulation pressure magnitude data (variable: <b><i>us_mag</i></b>). Each file name is marked with the transcranial brain targets, e.g., S1HL, insula, thalamus, that are responsible for pain signal processing. Other two .mat files have the formatted ultrasound pressure field when the ultrasound targets at a sham location or when the transducer is working in the coherent mode, i.e., all elements transmitting ultrasound simultaneously. When the tFUS targeted at S1HL, insula, thalamus and sham locations, the H276 was steering its focus by certain distances. These distances were listed in our preprinted work shown below. The spatial step sizes of the 3D matrix (<b><i>us_mag</i></b>) are included in each of these files (variable: <b><i>delta_x</i></b>, <b><i>delta_y</i></b>, <b><i>delta_z</i></b>).The simulations were implemented in Sim4Life V7.0 in the presence of a mouse skull model (CT image based). This work was supported in part by NIH EB029354, NS124564, and NS131069. More information can be found in the corresponding manuscript:Kim MG*, Yu K*, Yeh C-Y, Fouda R, Argueta D, Kiven S, Ni Y, Niu X, Chen Q, Kim K, Gupta K, He B. Low-intensity transcranial focused ultrasound changes pain-associated behaviors by modulating pain processing brain circuits. bioRxiv: https://doi.org/10.1101/2022.12.07.519518 (*Equal contribution, first author)If anyone uses the whole or part of the dataset provided here, we kindly ask you to cite the above publication in any of your publications or presentations:
DOI: 10.7910/dvn/btrefa
title: Replication Data for: "Russian Invasion of Ukraine and Chinese Public Support for War"

description: Replication Files: "Russian Invasion of Ukraine and Chinese Public Support for War" Authors: Deniz Aksoy, Ted Enamorado, and Tony Zirui Yang
DOI: 10.6084/m9.figshare.25036925
title: Treating pain in sickle cell disease by means of focused ultrasound neuromodulation (Ultrasound Characterizations: <i>Ex-vivo</i> Scanning)

description: We developed a novel transcranial focused ultrasound transducer for treating pain in humanized sickle cell mice. The project promises to provide non-pharmacologic chronic pain treatment for patients associated with underlying conditions such as cancer or sickle cell disease (SCD).This dataset includes 4 original ex-vivo scans formatted in MATLAB workspace. Their long file names include the scanning senarios, power source levels, fundamental frequency, sampling number, pulse repetition frequency, cycle per pulse number, x and y distances with step size, z distance with slice size, and z focal distance.For convenience, we also attached other 4 .mat files with formatted transcranial focused ultrasound pressure magnitude data scanned through hydrophone in a water tank (3-dimensional variable: <b><i>I</i></b><b><i>ntensity_locations</i></b>). Each file name is labeled with the scanning scenarios, i.e., free water vs. mouse skull, and with voltage levels of the Vantage system, i.e., 2.4 V or 20 V. 2.4 V power source is the major voltage used to test the efficacy of tFUS stimulation in modulating pain, and the 20 V power source is the scaled-up scenario used in positive control condition to test the safety of tFUS stimulation in mice. The spatial step sizes of the 3D matrix (<b><i>Intensity_locations</i></b>) are included in each of these files (variables: <b><i>step </i></b>for x and y dimensions, <b><i>slice </i></b>for z dimension, physical unit: mm). The pulse duration (<b><i>PD</i></b>) is 200 micro-second. The variables <b><i>xaxis_locations</i></b>, <b><i>y</i></b><b><i>axis_locations</i></b>, and <b><i>z</i></b><b><i>axis_locations </i></b>described the total step/slice numbers along those three directions.The ex-vivo scannings were implemented in the presence of a freshly excised mouse skull sample. This work was supported in part by NIH EB029354, NS124564, and NS131069. More information can be found in the corresponding manuscript:Kim MG*, Yu K*, Yeh C-Y, Fouda R, Argueta D, Kiven S, Ni Y, Niu X, Chen Q, Kim K, Gupta K, He B. Low-intensity transcranial focused ultrasound changes pain-associated behaviors by modulating pain processing brain circuits. bioRxiv: https://doi.org/10.1101/2022.12.07.519518 (*Equal contribution, first author)If anyone uses the whole or part of the dataset provided here, we kindly ask you to cite the above publication in any of your publications or presentations:
DOI: 10.5281/zenodo.10553794
title: Zambia Uber H3 level 6 database

description: Database for characterization of sub national units for Zambia using Uber H3 level 6 hexagons. Data includes crop, livestock, as well as climate data. H3 hexagons have unique identifiers that can be used to sum or average underlying data covered by area. As compared to square pixels, hexagons are better to fully cover a countries area. The lower the level used the better the fit.

Data sources used:

Livestock: FAO GLW (Cattle, Goats, Sheep, Chicken, Buffaloes) year 2015

Crops: IFPRI SPAM 2010 for Countries in SS Africa SPAM 2017

Climate: Worldclim 2.1

Elevation: SRTM CSI CGIAR

Field    Dataindex    H3 indexzabuffalo2    buffalozacattle20    Cattlezaducks201    Duckszachicken2    Chickenzasheep201    Sheepzagoats201    Goatszashoats20    Shoatszaacofarea    coffee area hazabanaarea    banana area hazabarlarea    barley area hazabeanarea    bean area hazacassarea    cassava areazacnutarea    colanut areazacottarea    cotton areazacowparea    cowpea area hazagrouarea    groundnut area hazalentarea    lentil area hazamaizarea    maize area hazaocerarea    other cereal area hazaofibarea    other fiber crops area hazaooilarea    other oilcrops area hazaopularea    other pulses area hazaortsarea    other rtbs area hazaplntarea    plantain area hazapmilarea    pearl milletarea hazapotaarea    potato area hazarapearea    Rape area hazarestarea    Rest of cops  area hazaricearea    rice area hazasesaarea    sesame area hazasmilarea    millet area hazasorgarea    sorghum area hazasoybarea    soybean area hazasugcarea    sugarcane area hazasunfarea    sunflower area hazaswpoarea    sweet potato area hazateasarea    tea  area hazatemfarea    temperate fruit area hazatobaarea    tobacco area hazatrofarea    tropical fruit area hazavegearea    vegetables area hazawheaarea    wheat area hazayamsarea    yams area hazaprecann_    annual rainfallzatmax_ann    longterm annual tmax (1970-2000)zatmin_ann    longterm annual tmin (1970-2000)zaworld250    Elevation m a.b.s.l.

Caveats:

Hexagon size can be smaller than actual pixel size like SPAM, values can be lower or higher depending on location and pixel below. Use as indicator of importance not absolute value.
DOI: 10.5281/zenodo.10553795
title: Zambia Uber H3 level 6 database

description: Database for characterization of sub national units for Zambia using Uber H3 level 6 hexagons. Data includes crop, livestock, as well as climate data. H3 hexagons have unique identifiers that can be used to sum or average underlying data covered by area. As compared to square pixels, hexagons are better to fully cover a countries area. The lower the level used the better the fit.

Data sources used:

Livestock: FAO GLW (Cattle, Goats, Sheep, Chicken, Buffaloes) year 2015

Crops: IFPRI SPAM 2010 for Countries in SS Africa SPAM 2017

Climate: Worldclim 2.1

Elevation: SRTM CSI CGIAR

Field    Dataindex    H3 indexzabuffalo2    buffalozacattle20    Cattlezaducks201    Duckszachicken2    Chickenzasheep201    Sheepzagoats201    Goatszashoats20    Shoatszaacofarea    coffee area hazabanaarea    banana area hazabarlarea    barley area hazabeanarea    bean area hazacassarea    cassava areazacnutarea    colanut areazacottarea    cotton areazacowparea    cowpea area hazagrouarea    groundnut area hazalentarea    lentil area hazamaizarea    maize area hazaocerarea    other cereal area hazaofibarea    other fiber crops area hazaooilarea    other oilcrops area hazaopularea    other pulses area hazaortsarea    other rtbs area hazaplntarea    plantain area hazapmilarea    pearl milletarea hazapotaarea    potato area hazarapearea    Rape area hazarestarea    Rest of cops  area hazaricearea    rice area hazasesaarea    sesame area hazasmilarea    millet area hazasorgarea    sorghum area hazasoybarea    soybean area hazasugcarea    sugarcane area hazasunfarea    sunflower area hazaswpoarea    sweet potato area hazateasarea    tea  area hazatemfarea    temperate fruit area hazatobaarea    tobacco area hazatrofarea    tropical fruit area hazavegearea    vegetables area hazawheaarea    wheat area hazayamsarea    yams area hazaprecann_    annual rainfallzatmax_ann    longterm annual tmax (1970-2000)zatmin_ann    longterm annual tmin (1970-2000)zaworld250    Elevation m a.b.s.l.

Caveats:

Hexagon size can be smaller than actual pixel size like SPAM, values can be lower or higher depending on location and pixel below. Use as indicator of importance not absolute value.
DOI: 10.5281/zenodo.10553800
title: Zimbabwe Uber H3 level 6 database

description: Database for characterization of sub national units for Zimbabwe using Uber H3 level 6 hexagons. Data includes crop, livestock, as well as climate data. H3 hexagons have unique identifiers that can be used to sum or average underlying data covered by area. As compared to square pixels, hexagons are better to fully cover a countries area. The lower the level used the better the fit.

Data sources used:

Livestock: FAO GLW (Cattle, Goats, Sheep, Chicken, Buffaloes) year 2015

Crops: IFPRI SPAM 2010 for Countries in SS Africa SPAM 2017

Climate: Worldclim 2.1

Elevation: SRTM CSI CGIAR

Field    Dataindex    H3 indexzibuffalo2    buffalozicattle20    Cattleziducks201    Duckszichicken2    Chickenzisheep201    Sheepzigoats201    Goatszishoats20    Shoatsziacofarea    coffee area hazibanaarea    banana area hazibarlarea    barley area hazibeanarea    bean area hazicassarea    cassava areazicnutarea    colanut areazicottarea    cotton areazicowparea    cowpea area hazigrouarea    groundnut area hazilentarea    lentil area hazimaizarea    maize area haziocerarea    other cereal area haziofibarea    other fiber crops area haziooilarea    other oilcrops area haziopularea    other pulses area haziortsarea    other rtbs area haziplntarea    plantain area hazipmilarea    pearl milletarea hazipotaarea    potato area hazirapearea    Rape area hazirestarea    Rest of cops  area haziricearea    rice area hazisesaarea    sesame area hazismilarea    millet area hazisorgarea    sorghum area hazisoybarea    soybean area hazisugcarea    sugarcane area hazisunfarea    sunflower area haziswpoarea    sweet potato area haziteasarea    tea  area hazitemfarea    temperate fruit area hazitobaarea    tobacco area hazitrofarea    tropical fruit area hazivegearea    vegetables area haziwheaarea    wheat area haziyamsarea    yams area haziprecann_    annual rainfallzitmax_ann    longterm annual tmax (1970-2000)zitmin_ann    longterm annual tmin (1970-2000)ziworld250    Elevation m a.b.s.l.

 

Caveats:

Hexagon size can be smaller than actual pixel size like SPAM, values can be lower or higher depending on location and pixel below. Use as indicator of importance not absolute value.
DOI: 10.5281/zenodo.10553801
title: Zimbabwe Uber H3 level 6 database

description: Database for characterization of sub national units for Zimbabwe using Uber H3 level 6 hexagons. Data includes crop, livestock, as well as climate data. H3 hexagons have unique identifiers that can be used to sum or average underlying data covered by area. As compared to square pixels, hexagons are better to fully cover a countries area. The lower the level used the better the fit.

Data sources used:

Livestock: FAO GLW (Cattle, Goats, Sheep, Chicken, Buffaloes) year 2015

Crops: IFPRI SPAM 2010 for Countries in SS Africa SPAM 2017

Climate: Worldclim 2.1

Elevation: SRTM CSI CGIAR

Field    Dataindex    H3 indexzibuffalo2    buffalozicattle20    Cattleziducks201    Duckszichicken2    Chickenzisheep201    Sheepzigoats201    Goatszishoats20    Shoatsziacofarea    coffee area hazibanaarea    banana area hazibarlarea    barley area hazibeanarea    bean area hazicassarea    cassava areazicnutarea    colanut areazicottarea    cotton areazicowparea    cowpea area hazigrouarea    groundnut area hazilentarea    lentil area hazimaizarea    maize area haziocerarea    other cereal area haziofibarea    other fiber crops area haziooilarea    other oilcrops area haziopularea    other pulses area haziortsarea    other rtbs area haziplntarea    plantain area hazipmilarea    pearl milletarea hazipotaarea    potato area hazirapearea    Rape area hazirestarea    Rest of cops  area haziricearea    rice area hazisesaarea    sesame area hazismilarea    millet area hazisorgarea    sorghum area hazisoybarea    soybean area hazisugcarea    sugarcane area hazisunfarea    sunflower area haziswpoarea    sweet potato area haziteasarea    tea  area hazitemfarea    temperate fruit area hazitobaarea    tobacco area hazitrofarea    tropical fruit area hazivegearea    vegetables area haziwheaarea    wheat area haziyamsarea    yams area haziprecann_    annual rainfallzitmax_ann    longterm annual tmax (1970-2000)zitmin_ann    longterm annual tmin (1970-2000)ziworld250    Elevation m a.b.s.l.

 

Caveats:

Hexagon size can be smaller than actual pixel size like SPAM, values can be lower or higher depending on location and pixel below. Use as indicator of importance not absolute value.
DOI: 10.5281/zenodo.10553710
title: Ethiopia Uber H3 level 6 database

description: Database for characterization of sub national units for Ethiopia using Uber H3 level 6 hexagons. Data includes crop, livestock, as well as climate data. H3 hexagons have unique identifiers that can be used to sum or average underlying data covered by area. As compared to square pixels, hexagons are better to fully cover a countries area. The lower the level used the better the fit.

Data sources used:

Livestock: FAO GLW (Cattle, Goats, Sheep, Chicken, Buffaloes) year 2015

Crops: IFPRI SPAM 2010 for Countries in SS Africa SPAM 2017

Climate: Worldclim 2.1

Elevation: SRTM CSI CGIAR

 

 




Field
Data


index
H3 index


etbuffalo2
Buffalo


etcattle20
Cattle


etducks201
Ducks


etchicken2
Chicken


etsheep201
Sheep


etgoats201
Goats


etshoats20
Shoats


etacofarea
coffee area ha


etbanaarea
banana area ha


etbarlarea
barley area ha


etbeanarea
bean area ha


etcassarea
cassava area


etcnutarea
colanut area


etcottarea
cotton area


etcowparea
cowpea area ha


etgrouarea
groundnut area ha


etlentarea
lentil area ha


etmaizarea
maize area ha


etocerarea
other cereal area ha


etofibarea
other fiber crops area ha


etooilarea
other oilcrops area ha


etopularea
other pulses area ha


etortsarea
other rtbs area ha


etplntarea
plantain area ha


etpmilarea
pearl milletarea ha


etpotaarea
potato area ha


etrapearea
Rape area ha


etrestarea
Rest of cops  area ha


etricearea
rice area ha


etsesaarea
sesame area ha


etsmilarea
millet area ha


etsorgarea
sorghum area ha


etsoybarea
soybean area ha


etsugcarea
sugarcane area ha


etsunfarea
sunflower area ha


etswpoarea
sweet potato area ha


etteasarea
tea  area ha


ettemfarea
temperate fruit area ha


ettobaarea
tobacco area ha


ettrofarea
tropical fruit area ha


etvegearea
vegetables area ha


etwheaarea
wheat area ha


etyamsarea
yams area ha


etprecann_
annual rainfall


ettmax_ann
longterm annual tmax (1970-2000)


ettmin_ann
longterm annual tmin (1970-2000)


etworld250
Elevation m a.b.s.l.




 

Caveats:

Hexagon size can be smaller than actual pixel size like SPAM, values can be lower or higher depending on location and pixel below. Use as indicator of importance not absolute value.
DOI: 10.5281/zenodo.10553711
title: Ethiopia Uber H3 level 6 database

description: Database for characterization of sub national units for Ethiopia using Uber H3 level 6 hexagons. Data includes crop, livestock, as well as climate data. H3 hexagons have unique identifiers that can be used to sum or average underlying data covered by area. As compared to square pixels, hexagons are better to fully cover a countries area. The lower the level used the better the fit.

Data sources used:

Livestock: FAO GLW (Cattle, Goats, Sheep, Chicken, Buffaloes) year 2015

Crops: IFPRI SPAM 2010 for Countries in SS Africa SPAM 2017

Climate: Worldclim 2.1

Elevation: SRTM CSI CGIAR

 

 




Field
Data


index
H3 index


etbuffalo2
Buffalo


etcattle20
Cattle


etducks201
Ducks


etchicken2
Chicken


etsheep201
Sheep


etgoats201
Goats


etshoats20
Shoats


etacofarea
coffee area ha


etbanaarea
banana area ha


etbarlarea
barley area ha


etbeanarea
bean area ha


etcassarea
cassava area


etcnutarea
colanut area


etcottarea
cotton area


etcowparea
cowpea area ha


etgrouarea
groundnut area ha


etlentarea
lentil area ha


etmaizarea
maize area ha


etocerarea
other cereal area ha


etofibarea
other fiber crops area ha


etooilarea
other oilcrops area ha


etopularea
other pulses area ha


etortsarea
other rtbs area ha


etplntarea
plantain area ha


etpmilarea
pearl milletarea ha


etpotaarea
potato area ha


etrapearea
Rape area ha


etrestarea
Rest of cops  area ha


etricearea
rice area ha


etsesaarea
sesame area ha


etsmilarea
millet area ha


etsorgarea
sorghum area ha


etsoybarea
soybean area ha


etsugcarea
sugarcane area ha


etsunfarea
sunflower area ha


etswpoarea
sweet potato area ha


etteasarea
tea  area ha


ettemfarea
temperate fruit area ha


ettobaarea
tobacco area ha


ettrofarea
tropical fruit area ha


etvegearea
vegetables area ha


etwheaarea
wheat area ha


etyamsarea
yams area ha


etprecann_
annual rainfall


ettmax_ann
longterm annual tmax (1970-2000)


ettmin_ann
longterm annual tmin (1970-2000)


etworld250
Elevation m a.b.s.l.




 

Caveats:

Hexagon size can be smaller than actual pixel size like SPAM, values can be lower or higher depending on location and pixel below. Use as indicator of importance not absolute value.
DOI: 10.5517/ccdc.csd.cc2952vf
title: CCDC 2120054: Experimental Crystal Structure Determination

description: Related Article: Pelin Köse Yaman, Sevde Demir, Serpil Denizaltı, Hakan Erer, Okan Zafer Yeşilel|2024|New J.Chem.|48|1850|doi:10.1039/D3NJ04256A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25952/ra6s-ff89
title: Impacts of Ascaridia galli infection on health, immunity, productivity and egg quality of free-range laying hens

description: Two experiments were conducted at Laureldale research farms. Hens were artificially infected with different doses of Ascaridia galli eggs. Impacts on health, immune response, productions were measured. Subsequently, hens were ranged on the contaminated ranges. The impacts of such naturally acquired infections were measured.
description: Two experiments were conducted at Laureldale research farms. Hens were artificially infected with different doses of Ascaridia galli eggs. Impacts on health, immune response, productions were measured. Subsequently, hens were ranged on the contaminated ranges. The impacts of such naturally acquired infections were measured.
DOI: 10.6084/m9.figshare.25045322
title: Viral Encephalitis Dataset for Ghana

description: Encephalitis is an inflammation of the functional tissues of the brain and is characterised by an acute onset of fever, altered mental status and the onset of seizures. Viruses constitute the major aetiology for encephalitis and molecular diagnostic techniques such as Polymerase Chain Reaction (PCR) and genome sequencing are the preferred diagnostic techniques for confirmation of viral aetiology. In this study, we determined the viruses associated with encephalitis among patients presenting to a major referral hospital in Ghana. We also assessed the clinical epidemiology, risk factors/determinants and outcome of individuals who presented with signs and symptoms of encephalitis in a tertiary hospital setting in Ghana.
DOI: 10.6084/m9.figshare.25045370
title: Supplementary Material for: Effects of liquid and bar soaps on the skin of Brazilian newborns: a randomized controlled trial

description: Introduction: Compared to adults, newborns’ skin has thinner epidermis and stratum corneum with decreased hydration level, higher transepidermal water loss, and pH variation between 5.5 and 7.5. These characteristics can predispose the occurrence of dryness, infections, and dermatological conditions. Water and liquid soap with adequate formulation have shown to be beneficial and safe for newborns’ skin. However, studies evaluating the effect of bar soap, products widely used in Brazil and Latin America, are unknown. Therefore, the objective of this study was to compare the effects of liquid and bar soaps on the term newborns’ skin.
Methods: This randomized controlled, parallel, single-blind clinical trial was conducted at a public university hospital in São Paulo, Brazil. 100 healthy term newborns with no congenital anomalies, acute diseases, or dermatological conditions were randomized to use a liquid soap (experimental group) or bar soap (control group). Skin pH, transepidermal water loss, stratum corneum hydration, sebum content, and skin condition were assessed before and after the first bath, at 48 hours, 14 days, and 28 days after birth. These evaluations were performed on the forearm, abdomen, buttocks, and thigh. In addition, the mother's perception of soap use was also evaluated. 
Results: Data of 100 newborns were analyzed by intention to treat. The rate of retention was 53%. Newborns exposed to the liquid soap presented significantly better skin acidification (p&lt;0.001) and significantly better stratum corneum hydration (p&lt;0.001) than the skin of newborns exposed to the bar soap, regardless of the area evaluated. There were no significant differences in transepidermal water loss, sebum content, dryness, erythema, or skin breakdown and the mother's perceptions of use of the soaps. 
Conclusion: newborns in the experimental group presented better skin acidification and stratum corneum hydration when compared to newborns in the control group.